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	<title>CiteULike: davclark's library [95 articles]</title>
	<description>CiteULike: davclark's library [95 articles]</description>


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<item rdf:about="http://www.citeulike.org/user/davclark/article/1783734">
    <title>Multiple routes to memory: Distinct medial temporal lobe processes build item and source memories</title>
    <link>http://www.citeulike.org/user/davclark/article/1783734</link>
    <description>&lt;i&gt;Proceedings of the National Academy of Sciences, Vol. 100, No. 4. (18 February 2003), pp. 2157-2162.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;A central function of memory is to permit an organism to distinguish between stimuli that have been previously encountered and those that are novel. Although the medial temporal lobe (which includes the hippocampus and surrounding perirhinal, parahippocampal, and entorhinal cortices) is known to be crucial for recognition memory, controversy remains regarding how the specific subregions within the medial temporal lobe contribute to recognition. We used event-related functional MRI to examine the relation between activation in distinct medial temporal lobe subregions during memory formation and the ability (i) to later recognize an item as previously encountered (item recognition) and (ii) to later recollect specific contextual details about the prior encounter (source recollection). Encoding activation in hippocampus and in posterior parahippocampal cortex predicted later source recollection, but was uncorrelated with item recognition. In contrast, encoding activation in perirhinal cortex predicted later item recognition, but not subsequent source recollection. These outcomes suggest that the subregions within the medial temporal lobe subserve distinct, but complementary, learning mechanisms. 10.1073/pnas.0337195100</description>
    <dc:title>Multiple routes to memory: Distinct medial temporal lobe processes build item and source memories</dc:title>

    <dc:creator>Lila Davachi</dc:creator>
    <dc:creator>Jason Mitchell</dc:creator>
    <dc:creator>Anthony Wagner</dc:creator>
    <dc:identifier>doi:10.1073/pnas.0337195100</dc:identifier>
    <dc:source>Proceedings of the National Academy of Sciences, Vol. 100, No. 4. (18 February 2003), pp. 2157-2162.</dc:source>
    <dc:date>2007-10-18T09:18:28-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:publicationName>Proceedings of the National Academy of Sciences</prism:publicationName>
    <prism:volume>100</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>2157</prism:startingPage>
    <prism:endingPage>2162</prism:endingPage>
    <prism:category>fmri</prism:category>
    <prism:category>learning</prism:category>
    <prism:category>memory</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/171560">
    <title>Predicting the orientation of invisible stimuli from activity in human primary visual cortex</title>
    <link>http://www.citeulike.org/user/davclark/article/171560</link>
    <description>&lt;i&gt;Nature Neuroscience, Vol. 8, No. 5. (24 April 2005), pp. 686-691.&lt;/i&gt;</description>
    <dc:title>Predicting the orientation of invisible stimuli from activity in human primary visual cortex</dc:title>

    <dc:creator>John-Dylan Haynes</dc:creator>
    <dc:creator>Geraint Rees</dc:creator>
    <dc:identifier>doi:10.1038/nn1445</dc:identifier>
    <dc:source>Nature Neuroscience, Vol. 8, No. 5. (24 April 2005), pp. 686-691.</dc:source>
    <dc:date>2005-04-26T18:40:18-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Nature Neuroscience</prism:publicationName>
    <prism:issn>1097-6256</prism:issn>
    <prism:volume>8</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>686</prism:startingPage>
    <prism:endingPage>691</prism:endingPage>
    <prism:publisher>Nature Publishing Group</prism:publisher>
    <prism:category>fmri</prism:category>
    <prism:category>methods</prism:category>
    <prism:category>perception</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/819069">
    <title>Statistical parametric maps in functional imaging: A general linear approach</title>
    <link>http://www.citeulike.org/user/davclark/article/819069</link>
    <description>&lt;i&gt;Human Brain Mapping, Vol. 2, No. 4. (1994), pp. 189-210.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Statistical parametric maps are spatially extended statistical processes that are used to test hypotheses about regionally specific effects in neuroimaging data. The most established sorts of statistical parametric maps (e.g., Friston et al. [1991]: J Cereb Blood Flow Metab 11:690-699; Worsley et al. [1992]: J Cereb Blood Flow Metab 12:900-918) are based on linear models, for example ANCOVA, correlation coefficients and t tests. In the sense that these examples are all special cases of the general linear model it should be possible to implement them (and many others) within a unified framework. We present here a general approach that accomodates most forms of experimental layout and ensuing analysis (designed experiments with fixed effects for factors, covariates and interaction of factors). This approach brings together two well established bodies of theory (the general linear model and the theory of Gaussian fields) to provide a complete and simple framework for the analysis of imaging data.The importance of this framework is twofold: (i) Conceptual and mathematical simplicity, in that the same small number of operational equations is used irrespective of the complexity of the experiment or nature of the statistical model and (ii) the generality of the framework provides for great latitude in experimental design and analysis. © 1995 Wiley-Liss, Inc.</description>
    <dc:title>Statistical parametric maps in functional imaging: A general linear approach</dc:title>

    <dc:creator>KJ Friston</dc:creator>
    <dc:creator>AP Holmes</dc:creator>
    <dc:creator>KJ Worsley</dc:creator>
    <dc:creator>JP Poline</dc:creator>
    <dc:creator>CD Frith</dc:creator>
    <dc:creator>RSJ Frackowiak</dc:creator>
    <dc:identifier>doi:10.1002/hbm.460020402</dc:identifier>
    <dc:source>Human Brain Mapping, Vol. 2, No. 4. (1994), pp. 189-210.</dc:source>
    <dc:date>2006-08-27T09:06:29-00:00</dc:date>
    <prism:publicationYear>1994</prism:publicationYear>
    <prism:publicationName>Human Brain Mapping</prism:publicationName>
    <prism:volume>2</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>189</prism:startingPage>
    <prism:endingPage>210</prism:endingPage>
    <prism:category>fmri</prism:category>
    <prism:category>methods</prism:category>
    <prism:category>statistics</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1584042">
    <title>An Implicit Plan Overrides an Explicit Strategy during Visuomotor Adaptation</title>
    <link>http://www.citeulike.org/user/davclark/article/1584042</link>
    <description>&lt;i&gt;J. Neurosci., Vol. 26, No. 14. (5 April 2006), pp. 3642-3645.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The relationship between implicit and explicit processes during motor learning, and for visuomotor adaptation in particular, is poorly understood. We set up a conflict between implicit and explicit processes by instructing subjects to counter a visuomotor rotation using a cognitive strategy in a pointing task. Specifically, they were told the exact nature of the directional perturbation, a rotation that directed them 45degrees counterclockwise from the desired target, and they were instructed to counter it by aiming for the neighboring clockwise target, 45degrees away. Subjects were initially successful in completely negating the rotation with this strategy. Surprisingly, however, they were unable to sustain explicit control and made increasingly large errors to the desired target. The cognitive strategy failed because subjects simultaneously adapted unconsciously to the rotation to the neighboring target. Notably, the rate of implicit adaptation to the neighboring target was not significantly different from rotation adaptation in the absence of an opposing explicit strategy. These results indicate that explicit strategies cannot substitute for implicit adaptation to a visuomotor rotation and are in fact overridden by the motor planning system. This suggests that the motor system requires that planned and executed trajectories remain congruous in visual space, and enforces this correspondence even at the expense of an opposing explicit task goal. 10.1523/JNEUROSCI.5317-05.2006</description>
    <dc:title>An Implicit Plan Overrides an Explicit Strategy during Visuomotor Adaptation</dc:title>

    <dc:creator>Pietro Mazzoni</dc:creator>
    <dc:creator>John Krakauer</dc:creator>
    <dc:identifier>doi:10.1523/JNEUROSCI.5317-05.2006</dc:identifier>
    <dc:source>J. Neurosci., Vol. 26, No. 14. (5 April 2006), pp. 3642-3645.</dc:source>
    <dc:date>2007-08-22T19:15:58-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>J. Neurosci.</prism:publicationName>
    <prism:volume>26</prism:volume>
    <prism:number>14</prism:number>
    <prism:startingPage>3642</prism:startingPage>
    <prism:endingPage>3645</prism:endingPage>
    <prism:category>consciousness</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>movement</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2640187">
    <title>Enhanced Intersubject Correlations during Movie Viewing Correlate with Successful Episodic Encoding</title>
    <link>http://www.citeulike.org/user/davclark/article/2640187</link>
    <description>&lt;i&gt;Neuron, Vol. 57, No. 3. (7 February 2008), pp. 452-462.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Summary While much has been learned regarding the neural substrates supporting episodic encoding using highly controlled experimental protocols, relatively little is known regarding the neural bases of episodic encoding of real-world events. In an effort to examine this issue, we measured fMRI activity while observers viewed a novel TV sitcom. Three weeks later, subsequent memory (SM) for the narrative content of movie events was assessed. We analyzed the encoding data for intersubject correlations (ISC) based on subjects' subsequent memory (ISC-SM) performance to identify brain regions whose BOLD response is significantly more correlated across subjects during portions of the movie that are successfully as compared to unsuccessfully encoded. These regions include the parahippocampal gyrus, superior temporal gyrus, anterior temporal poles, and the temporal-parietal junction. Further analyses reveal (1) that these correlated regions can display distinct activation profiles and (2) that the results seen with the ISC-SM analysis are complementary to more traditional linear models and allow analysis of complex time course data. Thus, the ISC-SM analysis extends traditional subsequent memory findings to a rich, dynamic and more ecologically valid situation.</description>
    <dc:title>Enhanced Intersubject Correlations during Movie Viewing Correlate with Successful Episodic Encoding</dc:title>

    <dc:creator>Uri Hasson</dc:creator>
    <dc:creator>Orit Furman</dc:creator>
    <dc:creator>Dav Clark</dc:creator>
    <dc:creator>Yadin Dudai</dc:creator>
    <dc:creator>Lila Davachi</dc:creator>
    <dc:identifier>doi:10.1016/j.neuron.2007.12.009</dc:identifier>
    <dc:source>Neuron, Vol. 57, No. 3. (7 February 2008), pp. 452-462.</dc:source>
    <dc:date>2008-04-08T05:11:28-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Neuron</prism:publicationName>
    <prism:volume>57</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>452</prism:startingPage>
    <prism:endingPage>462</prism:endingPage>
    <prism:category>memory</prism:category>
    <prism:category>methods</prism:category>
    <prism:category>movies</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1590293">
    <title>Intersubject Synchronization of Cortical Activity During Natural Vision</title>
    <link>http://www.citeulike.org/user/davclark/article/1590293</link>
    <description>&lt;i&gt;Science, Vol. 303, No. 5664. (12 March 2004), pp. 1634-1640.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;To what extent do all brains work alike during natural conditions? We explored this question by letting five subjects freely view half an hour of a popular movie while undergoing functional brain imaging. Applying an unbiased analysis in which spatiotemporal activity patterns in one brain were used to &#34;model&#34; activity in another brain, we found a striking level of voxel-by-voxel synchronization between individuals, not only in primary and secondary visual and auditory areas but also in association cortices. The results reveal a surprising tendency of individual brains to &#34;tick collectively&#34; during natural vision. The intersubject synchronization consisted of a widespread cortical activation pattern correlated with emotionally arousing scenes and regionally selective components. The characteristics of these activations were revealed with the use of an open-ended &#34;reverse-correlation&#34; approach, which inverts the conventional analysis by letting the brain signals themselves &#34;pick up&#34; the optimal stimuli for each specialized cortical area. 10.1126/science.1089506</description>
    <dc:title>Intersubject Synchronization of Cortical Activity During Natural Vision</dc:title>

    <dc:creator>Uri Hasson</dc:creator>
    <dc:creator>Yuval Nir</dc:creator>
    <dc:creator>Ifat Levy</dc:creator>
    <dc:creator>Galit Fuhrmann</dc:creator>
    <dc:creator>Rafael Malach</dc:creator>
    <dc:identifier>doi:10.1126/science.1089506</dc:identifier>
    <dc:source>Science, Vol. 303, No. 5664. (12 March 2004), pp. 1634-1640.</dc:source>
    <dc:date>2007-08-24T16:13:05-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Science</prism:publicationName>
    <prism:volume>303</prism:volume>
    <prism:number>5664</prism:number>
    <prism:startingPage>1634</prism:startingPage>
    <prism:endingPage>1640</prism:endingPage>
    <prism:category>methods</prism:category>
    <prism:category>movies</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2911397">
    <title>Dedicated and intrinsic models of time perception</title>
    <link>http://www.citeulike.org/user/davclark/article/2911397</link>
    <description>&lt;i&gt;Trends in Cognitive Sciences, Vol. In Press, Corrected Proof&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Two general frameworks have been articulated to describe how the passage of time is perceived. One emphasizes that the judgment of the duration of a stimulus depends on the operation of dedicated neural mechanisms specialized for representing the temporal relationships between events. Alternatively, the representation of duration could be ubiquitous, arising from the intrinsic dynamics of nondedicated neural mechanisms. In such models, duration might be encoded directly through the amount of activation of sensory processes or as spatial patterns of activity in a network of neurons. Although intrinsic models are neurally plausible, we highlight several issues that must be addressed before we dispense with models of duration perception that are based on dedicated processes.</description>
    <dc:title>Dedicated and intrinsic models of time perception</dc:title>

    <dc:creator>Richard Ivry</dc:creator>
    <dc:creator>John Schlerf</dc:creator>
    <dc:identifier>doi:10.1016/j.tics.2008.04.002</dc:identifier>
    <dc:source>Trends in Cognitive Sciences, Vol. In Press, Corrected Proof</dc:source>
    <dc:date>2008-06-20T19:54:50-00:00</dc:date>
    <prism:publicationName>Trends in Cognitive Sciences</prism:publicationName>
    <prism:volume>In Press, Corrected Proof</prism:volume>
    <prism:category>overview</prism:category>
    <prism:category>time</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2883820">
    <title>What we can do and what we cannot do with fMRI</title>
    <link>http://www.citeulike.org/user/davclark/article/2883820</link>
    <description>&lt;i&gt;Nature, Vol. 453, No. 7197. (12 June 2008), pp. 869-878.&lt;/i&gt;</description>
    <dc:title>What we can do and what we cannot do with fMRI</dc:title>

    <dc:creator>Nikos Logothetis</dc:creator>
    <dc:identifier>doi:10.1038/nature06976</dc:identifier>
    <dc:source>Nature, Vol. 453, No. 7197. (12 June 2008), pp. 869-878.</dc:source>
    <dc:date>2008-06-11T21:05:36-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Nature</prism:publicationName>
    <prism:volume>453</prism:volume>
    <prism:number>7197</prism:number>
    <prism:startingPage>869</prism:startingPage>
    <prism:endingPage>878</prism:endingPage>
    <prism:publisher>Macmillan Publishers Limited. All rights reserved</prism:publisher>
    <prism:category>fmri</prism:category>
    <prism:category>methods</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/565989">
    <title>Brain activity before an event predicts later recollection</title>
    <link>http://www.citeulike.org/user/davclark/article/565989</link>
    <description>&lt;i&gt;Nature Neuroscience, Vol. 9, No. 4. (26 February 2006), pp. 489-491.&lt;/i&gt;</description>
    <dc:title>Brain activity before an event predicts later recollection</dc:title>

    <dc:creator>Leun Otten</dc:creator>
    <dc:creator>Angela Quayle</dc:creator>
    <dc:creator>Sarah Akram</dc:creator>
    <dc:creator>Thomas Ditewig</dc:creator>
    <dc:creator>Michael Rugg</dc:creator>
    <dc:identifier>doi:10.1038/nn1663</dc:identifier>
    <dc:source>Nature Neuroscience, Vol. 9, No. 4. (26 February 2006), pp. 489-491.</dc:source>
    <dc:date>2006-03-27T16:11:33-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Nature Neuroscience</prism:publicationName>
    <prism:issn>1097-6256</prism:issn>
    <prism:volume>9</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>489</prism:startingPage>
    <prism:endingPage>491</prism:endingPage>
    <prism:publisher>Nature Publishing Group</prism:publisher>
    <prism:category>eeg</prism:category>
    <prism:category>memory</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2890271">
    <title>Accuracy of spatial localizations near the time of saccadic eye movements.</title>
    <link>http://www.citeulike.org/user/davclark/article/2890271</link>
    <description>&lt;i&gt;Vision research, Vol. 25, No. 8. (1985), pp. 1077-1082.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Two-dimensional eye movements were recorded while subjects used a hammer to strike targets that were flashed-on briefly before, during or up to 750 msec after a horizontal saccade. Mean position of hammer blows was 20 min arc (SD = 67 min arc) from the target when the only cue to target location was eye position. Position of responses varied slightly with time of target exposure relative to the saccade. These results show that observers can closely monitor small changes in eye position during and near the time of saccadic eye movements.</description>
    <dc:title>Accuracy of spatial localizations near the time of saccadic eye movements.</dc:title>

    <dc:creator>RM Hansen</dc:creator>
    <dc:creator>AA Skavenski</dc:creator>
    <dc:source>Vision research, Vol. 25, No. 8. (1985), pp. 1077-1082.</dc:source>
    <dc:date>2008-06-13T01:00:02-00:00</dc:date>
    <prism:publicationYear>1985</prism:publicationYear>
    <prism:publicationName>Vision research</prism:publicationName>
    <prism:issn>0042-6989</prism:issn>
    <prism:volume>25</prism:volume>
    <prism:number>8</prism:number>
    <prism:startingPage>1077</prism:startingPage>
    <prism:endingPage>1082</prism:endingPage>
    <prism:category>motor</prism:category>
    <prism:category>movement</prism:category>
    <prism:category>perception</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/126655">
    <title>Measuring, estimating, and understanding the psychometric function: a commentary.</title>
    <link>http://www.citeulike.org/user/davclark/article/126655</link>
    <description>&lt;i&gt;Percept Psychophys, Vol. 63, No. 8. (November 2001), pp. 1421-1455.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The psychometric function, relating the subject's response to the physical stimulus, is fundamental to psychophysics. This paper examines various psychometric function topics, many inspired by this special symposium issue of Perception &#38; Psychophysics: What are the relative merits of objective yes/no versus forced choice tasks (including threshold variance)? What are the relative merits of adaptive versus constant stimuli methods? What are the relative merits of likelihood versus up-down staircase adaptive methods? Is 2AFC free of substantial bias? Is there no efficient adaptive method for objective yes/no tasks? Should adaptive methods aim for 90% correct? Can adding more responses to forced choice and objective yes/no tasks reduce the threshold variance? What is the best way to deal with lapses? How is the Weibull function intimately related to the d' function? What causes bias in the likelihood goodness-of-fit? What causes bias in slope estimates from adaptive methods? How good are nonparametric methods for estimating psychometric function parameters? Of what value is the psychometric function slope? How are various psychometric functions related to each other? The resolution of many of these issues is surprising.</description>
    <dc:title>Measuring, estimating, and understanding the psychometric function: a commentary.</dc:title>

    <dc:creator>SA Klein</dc:creator>
    <dc:source>Percept Psychophys, Vol. 63, No. 8. (November 2001), pp. 1421-1455.</dc:source>
    <dc:date>2005-03-14T14:41:37-00:00</dc:date>
    <prism:publicationYear>2001</prism:publicationYear>
    <prism:publicationName>Percept Psychophys</prism:publicationName>
    <prism:issn>0031-5117</prism:issn>
    <prism:volume>63</prism:volume>
    <prism:number>8</prism:number>
    <prism:startingPage>1421</prism:startingPage>
    <prism:endingPage>1455</prism:endingPage>
    <prism:category>methods</prism:category>
    <prism:category>perception</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2720323">
    <title>Reduction of stimulus visibility compresses apparent time intervals</title>
    <link>http://www.citeulike.org/user/davclark/article/2720323</link>
    <description>&lt;i&gt;Nature Neuroscience, Vol. 11, No. 5. (13 April 2008), pp. 541-542.&lt;/i&gt;</description>
    <dc:title>Reduction of stimulus visibility compresses apparent time intervals</dc:title>

    <dc:creator>Masahiko Terao</dc:creator>
    <dc:creator>Junji Watanabe</dc:creator>
    <dc:creator>Akihiro Yagi</dc:creator>
    <dc:creator>Shin'ya Nishida</dc:creator>
    <dc:identifier>doi:10.1038/nn.2111</dc:identifier>
    <dc:source>Nature Neuroscience, Vol. 11, No. 5. (13 April 2008), pp. 541-542.</dc:source>
    <dc:date>2008-04-26T06:19:25-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Nature Neuroscience</prism:publicationName>
    <prism:issn>1097-6256</prism:issn>
    <prism:volume>11</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>541</prism:startingPage>
    <prism:endingPage>542</prism:endingPage>
    <prism:publisher>Nature Publishing Group</prism:publisher>
    <prism:category>time</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2709722">
    <title>Receptive fields of single neurones in the cat's striate cortex.</title>
    <link>http://www.citeulike.org/user/davclark/article/2709722</link>
    <description>&lt;i&gt;The Journal of physiology, Vol. 148 (October 1959), pp. 574-591.&lt;/i&gt;</description>
    <dc:title>Receptive fields of single neurones in the cat's striate cortex.</dc:title>

    <dc:creator>DH HUBEL</dc:creator>
    <dc:creator>TN WIESEL</dc:creator>
    <dc:source>The Journal of physiology, Vol. 148 (October 1959), pp. 574-591.</dc:source>
    <dc:date>2008-04-23T18:22:28-00:00</dc:date>
    <prism:publicationYear>1959</prism:publicationYear>
    <prism:publicationName>The Journal of physiology</prism:publicationName>
    <prism:issn>0022-3751</prism:issn>
    <prism:volume>148</prism:volume>
    <prism:startingPage>574</prism:startingPage>
    <prism:endingPage>591</prism:endingPage>
    <prism:category>classic</prism:category>
    <prism:category>perception</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1218945">
    <title>Loss of recent memory after bilateral hippocampal lesions.</title>
    <link>http://www.citeulike.org/user/davclark/article/1218945</link>
    <description>&lt;i&gt;J Neurol Neurosurg Psychiatry, Vol. 20, No. 1. (February 1957), pp. 11-21.&lt;/i&gt;</description>
    <dc:title>Loss of recent memory after bilateral hippocampal lesions.</dc:title>

    <dc:creator>WB SCOVILLE</dc:creator>
    <dc:creator>B MILNER</dc:creator>
    <dc:source>J Neurol Neurosurg Psychiatry, Vol. 20, No. 1. (February 1957), pp. 11-21.</dc:source>
    <dc:date>2007-04-10T09:56:41-00:00</dc:date>
    <prism:publicationYear>1957</prism:publicationYear>
    <prism:publicationName>J Neurol Neurosurg Psychiatry</prism:publicationName>
    <prism:issn>0022-3050</prism:issn>
    <prism:volume>20</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>11</prism:startingPage>
    <prism:endingPage>21</prism:endingPage>
    <prism:category>no-tag</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/171561">
    <title>Decoding the visual and subjective contents of the human brain</title>
    <link>http://www.citeulike.org/user/davclark/article/171561</link>
    <description>&lt;i&gt;Nature Neuroscience, Vol. 8, No. 5. (24 April 2005), pp. 679-685.&lt;/i&gt;</description>
    <dc:title>Decoding the visual and subjective contents of the human brain</dc:title>

    <dc:creator>Yukiyasu Kamitani</dc:creator>
    <dc:creator>Frank Tong</dc:creator>
    <dc:identifier>doi:10.1038/nn1444</dc:identifier>
    <dc:source>Nature Neuroscience, Vol. 8, No. 5. (24 April 2005), pp. 679-685.</dc:source>
    <dc:date>2005-04-26T18:40:18-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Nature Neuroscience</prism:publicationName>
    <prism:issn>1097-6256</prism:issn>
    <prism:volume>8</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>679</prism:startingPage>
    <prism:endingPage>685</prism:endingPage>
    <prism:publisher>Nature Publishing Group</prism:publisher>
    <prism:category>methods</prism:category>
    <prism:category>perception</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2476639">
    <title>Identifying natural images from human brain activity</title>
    <link>http://www.citeulike.org/user/davclark/article/2476639</link>
    <description>&lt;i&gt;Nature (05 March 2008)&lt;/i&gt;</description>
    <dc:title>Identifying natural images from human brain activity</dc:title>

    <dc:creator>Kendrick Kay</dc:creator>
    <dc:creator>Thomas Naselaris</dc:creator>
    <dc:creator>Ryan Prenger</dc:creator>
    <dc:creator>Jack Gallant</dc:creator>
    <dc:identifier>doi:10.1038/nature06713</dc:identifier>
    <dc:source>Nature (05 March 2008)</dc:source>
    <dc:date>2008-03-06T04:09:09-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Nature</prism:publicationName>
    <prism:issn>0028-0836</prism:issn>
    <prism:publisher>Nature Publishing Group</prism:publisher>
    <prism:category>methods</prism:category>
    <prism:category>perception</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/556485">
    <title>Category-specific cortical activity precedes retrieval during memory search.</title>
    <link>http://www.citeulike.org/user/davclark/article/556485</link>
    <description>&lt;i&gt;Science, Vol. 310, No. 5756. (23 December 2005), pp. 1963-1966.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Here we describe a functional magnetic resonance imaging study of humans engaged in memory search during a free recall task. Patterns of cortical activity associated with the study of three categories of pictures (faces, locations, and objects) were identified by a pattern-classification algorithm. The algorithm was used to track the reappearance of these activity patterns during the recall period. The reappearance of a given category's activity pattern correlates with verbal recalls made from that category and precedes the recall event by several seconds. This result is consistent with the hypothesis that category-specific activity is cueing the memory system to retrieve studied items.</description>
    <dc:title>Category-specific cortical activity precedes retrieval during memory search.</dc:title>

    <dc:creator>SM Polyn</dc:creator>
    <dc:creator>VS Natu</dc:creator>
    <dc:creator>JD Cohen</dc:creator>
    <dc:creator>KA Norman</dc:creator>
    <dc:identifier>doi:10.1126/science.1117645</dc:identifier>
    <dc:source>Science, Vol. 310, No. 5756. (23 December 2005), pp. 1963-1966.</dc:source>
    <dc:date>2006-03-18T17:29:00-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Science</prism:publicationName>
    <prism:issn>1095-9203</prism:issn>
    <prism:volume>310</prism:volume>
    <prism:number>5756</prism:number>
    <prism:startingPage>1963</prism:startingPage>
    <prism:endingPage>1966</prism:endingPage>
    <prism:category>memory</prism:category>
    <prism:category>methods</prism:category>
    <prism:category>semantics</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1142227">
    <title>Cortical and Subcortical Contributions to Stop Signal Response Inhibition: Role of the Subthalamic Nucleus</title>
    <link>http://www.citeulike.org/user/davclark/article/1142227</link>
    <description>&lt;i&gt;J. Neurosci., Vol. 26, No. 9. (1 March 2006), pp. 2424-2433.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Suppressing an already initiated manual response depends critically on the right inferior frontal cortex (IFC), yet it is unclear how this inhibitory function is implemented in the motor system. It has been suggested that the subthalamic nucleus (STN), which is a part of the basal ganglia, may play a role because it is well placed to suppress the &#34;direct&#34; fronto-striatal pathway that is activated by response initiation. In two experiments, we investigated this hypothesis with functional magnetic resonance imaging and a Stop-signal task. Subjects responded to Go signals and attempted to inhibit the initiated response to occasional Stop signals. In experiment 1, Going significantly activated frontal, striatal, pallidal, and motor cortical regions, consistent with the direct pathway, whereas Stopping significantly activated right IFC and STN. In addition, Stopping-related activation was significantly greater for fast inhibitors than slow ones in both IFC and STN, and activity in these regions was correlated across subjects. In experiment 2, high-resolution functional and structural imaging confirmed the location of Stopping activation within the vicinity of the STN. We propose that the role of the STN is to suppress thalamocortical output, thereby blocking Go response execution. These results provide convergent data for a role for the STN in Stop-signal response inhibition. They also suggest that the speed of Go and Stop processes could relate to the relative activation of different neural pathways. Future research is required to establish whether Stop-signal inhibition could be implemented via a direct functional neuroanatomic projection between IFC and STN (a &#34;hyperdirect&#34; pathway). 10.1523/JNEUROSCI.4682-05.2006</description>
    <dc:title>Cortical and Subcortical Contributions to Stop Signal Response Inhibition: Role of the Subthalamic Nucleus</dc:title>

    <dc:creator>Adam Aron</dc:creator>
    <dc:creator>Russell Poldrack</dc:creator>
    <dc:identifier>doi:10.1523/JNEUROSCI.4682</dc:identifier>
    <dc:source>J. Neurosci., Vol. 26, No. 9. (1 March 2006), pp. 2424-2433.</dc:source>
    <dc:date>2007-03-05T20:24:20-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>J. Neurosci.</prism:publicationName>
    <prism:volume>26</prism:volume>
    <prism:number>9</prism:number>
    <prism:startingPage>2424</prism:startingPage>
    <prism:endingPage>2433</prism:endingPage>
    <prism:category>controller</prism:category>
    <prism:category>dopamine</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>stop-signal</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/331072">
    <title>Dissociable Controlled Retrieval and Generalized Selection Mechanisms in Ventrolateral Prefrontal Cortex</title>
    <link>http://www.citeulike.org/user/davclark/article/331072</link>
    <description>&lt;i&gt;Neuron, Vol. 47, No. 6. (15 September 2005), pp. 907-918.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;SummaryHow does ventrolateral prefrontal cortex (VLPFC) control mnemonic processing? Alternative models propose that VLPFC guides top-down (controlled) retrieval of knowledge from long-term stores or selects goal-relevant products of retrieval from among competitors. A paucity of evidence supports a retrieval/selection distinction, raising the possibility that these models reduce to a common mechanism. Here, four manipulations varied semantic control demands during fMRI: judgment specificity, cue-target-associative strength, competitor dominance, and number of competitors. Factor analysis revealed evidence for a metafactor that accounted for common behavioral variance across manipulations and for functional variance in left mid-VLPFC. These data support a generalized control process that selects relevant knowledge from among competitors. By contrast, left anterior VLPFC and middle temporal cortex were sensitive to cue-target-associative strength, but not competition, consistent with a control process that retrieves knowledge stored in lateral temporal cortex. Distinct PFC mechanisms mediate top-down retrieval and postretrieval selection.</description>
    <dc:title>Dissociable Controlled Retrieval and Generalized Selection Mechanisms in Ventrolateral Prefrontal Cortex</dc:title>

    <dc:creator>David Badre</dc:creator>
    <dc:creator>Russell Poldrack</dc:creator>
    <dc:creator>Juliana Par&#38;#x00e9;-Blagoev</dc:creator>
    <dc:creator>Rachel Insler</dc:creator>
    <dc:creator>Anthony Wagner</dc:creator>
    <dc:identifier>doi:10.1016/j.neuron.2005.07.023</dc:identifier>
    <dc:source>Neuron, Vol. 47, No. 6. (15 September 2005), pp. 907-918.</dc:source>
    <dc:date>2005-09-23T13:53:28-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Neuron</prism:publicationName>
    <prism:volume>47</prism:volume>
    <prism:number>6</prism:number>
    <prism:startingPage>907</prism:startingPage>
    <prism:endingPage>918</prism:endingPage>
    <prism:category>attention</prism:category>
    <prism:category>controller</prism:category>
    <prism:category>fmri</prism:category>
    <prism:category>frontal</prism:category>
    <prism:category>memory</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2635615">
    <title>Computational and neurobiological mechanisms underlying cognitive flexibility.</title>
    <link>http://www.citeulike.org/user/davclark/article/2635615</link>
    <description>&lt;i&gt;Proceedings of the National Academy of Sciences of the United States of America, Vol. 103, No. 18. (2 May 2006), pp. 7186-7191.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The ability to switch between multiple tasks is central to flexible behavior. Although switching between tasks is readily accomplished, a well established consequence of task switching (TS) is behavioral slowing. The source of this switch cost and the contribution of cognitive control to its resolution remain highly controversial. Here, we tested whether proactive interference arising from memory places fundamental constraints on flexible performance, and whether prefrontal control processes contribute to overcoming these constraints. Event-related functional MRI indexed neural responses during TS. The contributions of cognitive control and interference were made theoretically explicit in a computational model of task performance. Model estimates of two levels of proactive interference, &#34;conceptual conflict&#34; and &#34;response conflict,&#34; produced distinct preparation-related profiles. Left ventrolateral prefrontal cortical activation paralleled model estimates of conceptual conflict, dissociating from that in left inferior parietal cortex, which paralleled model estimates of response conflict. These computationally informed neural measures specify retrieved conceptual representations as a source of conflict during TS and suggest that left ventrolateral prefrontal cortex resolves this conflict to facilitate flexible performance.</description>
    <dc:title>Computational and neurobiological mechanisms underlying cognitive flexibility.</dc:title>

    <dc:creator>D Badre</dc:creator>
    <dc:creator>AD Wagner</dc:creator>
    <dc:identifier>doi:10.1073/pnas.0509550103</dc:identifier>
    <dc:source>Proceedings of the National Academy of Sciences of the United States of America, Vol. 103, No. 18. (2 May 2006), pp. 7186-7191.</dc:source>
    <dc:date>2008-04-06T22:41:05-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Proceedings of the National Academy of Sciences of the United States of America</prism:publicationName>
    <prism:issn>0027-8424</prism:issn>
    <prism:volume>103</prism:volume>
    <prism:number>18</prism:number>
    <prism:startingPage>7186</prism:startingPage>
    <prism:endingPage>7191</prism:endingPage>
    <prism:category>attention</prism:category>
    <prism:category>controller</prism:category>
    <prism:category>frontal</prism:category>
    <prism:category>task-switching</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2285186">
    <title>Left ventrolateral prefrontal cortex and the cognitive control of memory.</title>
    <link>http://www.citeulike.org/user/davclark/article/2285186</link>
    <description>&lt;i&gt;Neuropsychologia, Vol. 45, No. 13. (1 October 2007), pp. 2883-2901.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Cognitive control mechanisms permit memory to be accessed strategically, and so aid in bringing knowledge to mind that is relevant to current goals and actions. In this review, we consider the contribution of left ventrolateral prefrontal cortex (VLPFC) to the cognitive control of memory. Reviewed evidence supports a two-process model of mnemonic control, supported by a double dissociation among rostral regions of left VLPFC. Specifically, anterior VLPFC (approximately BA 47; inferior frontal gyrus pars orbitalis) supports controlled access to stored conceptual representations, whereas mid-VLPFC (approximately BA 45; inferior frontal gyrus pars triangularis) supports a domain-general selection process that operates post-retrieval to resolve competition among active representations. We discuss the contribution of these control mechanisms across a range of mnemonic domains, including semantic retrieval, recollection of contextual details about past events, resolution of proactive interference in working memory, and task switching. Finally, we consider open directions for future research into left VLPFC function and the cognitive control of memory.</description>
    <dc:title>Left ventrolateral prefrontal cortex and the cognitive control of memory.</dc:title>

    <dc:creator>D Badre</dc:creator>
    <dc:creator>AD Wagner</dc:creator>
    <dc:identifier>doi:10.1016/j.neuropsychologia.2007.06.015</dc:identifier>
    <dc:source>Neuropsychologia, Vol. 45, No. 13. (1 October 2007), pp. 2883-2901.</dc:source>
    <dc:date>2008-01-24T16:10:13-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Neuropsychologia</prism:publicationName>
    <prism:issn>0028-3932</prism:issn>
    <prism:volume>45</prism:volume>
    <prism:number>13</prism:number>
    <prism:startingPage>2883</prism:startingPage>
    <prism:endingPage>2901</prism:endingPage>
    <prism:category>attention</prism:category>
    <prism:category>controller</prism:category>
    <prism:category>fmri</prism:category>
    <prism:category>frontal</prism:category>
    <prism:category>memory</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1700291">
    <title>Functional Magnetic Resonance Imaging Evidence for a Hierarchical Organization of the Prefrontal Cortex.</title>
    <link>http://www.citeulike.org/user/davclark/article/1700291</link>
    <description>&lt;i&gt;J Cogn Neurosci (24 September 2007)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Abstract The prefrontal cortex (PFC) is central to flexible and organized action. Recent theoretical and empirical results suggest that the rostro-caudal axis of the frontal lobes may reflect a hierarchical organization of control. Here, we test whether the rostro-caudal axis of the PFC is organized hierarchically, based on the level of abstraction at which multiple representations compete to guide selection of action. Four functional magnetic resonance imaging (fMRI) experiments parametrically manipulated the set of task-relevant (a) responses, (b) features, (c) dimensions, and (d) overlapping cue-to-dimension mappings. A systematic posterior to anterior gradient was evident within the PFC depending on the manipulated level of representation. Furthermore, across four fMRI experiments, activation in PFC subregions was consistent with the sub- and superordinate relationships that define an abstract representational hierarchy. In addition to providing further support for a representational hierarchy account of the rostro-caudal gradient in the PFC, these data provide important empirical constraints on current theorizing about control hierarchies and the PFC.</description>
    <dc:title>Functional Magnetic Resonance Imaging Evidence for a Hierarchical Organization of the Prefrontal Cortex.</dc:title>

    <dc:creator>David Badre</dc:creator>
    <dc:creator>Mark D'Esposito</dc:creator>
    <dc:identifier>doi:10.1162/jocn.2007.91201</dc:identifier>
    <dc:source>J Cogn Neurosci (24 September 2007)</dc:source>
    <dc:date>2007-09-27T13:58:38-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>J Cogn Neurosci</prism:publicationName>
    <prism:issn>0898-929X</prism:issn>
    <prism:category>controller</prism:category>
    <prism:category>fmri</prism:category>
    <prism:category>frontal</prism:category>
    <prism:category>task-complexity</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2633930">
    <title>Selection, Integration, and Conflict Monitoring: Assessing the Nature and Generality of Prefrontal Cognitive Control Mechanisms</title>
    <link>http://www.citeulike.org/user/davclark/article/2633930</link>
    <description>&lt;i&gt;Neuron, Vol. 41, No. 3. (5 February 2004), pp. 473-487.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Prefrontal cortex (PFC) supports flexible behavior by mediating cognitive control, though the elemental forms of control supported by PFC remain a central debate. Dorsolateral PFC (DLPFC) is thought to guide response selection under conditions of response conflict or, alternatively, may refresh recently active representations within working memory. Lateral frontopolar cortex (FPC) may also adjudicate response conflict, though others propose that FPC supports higher order control processes such as subgoaling and integration. Anterior cingulate cortex (ACC) is hypothesized to upregulate response selection by detecting response conflict; it remains unclear whether ACC functions generalize beyond monitoring response conflict. The present fMRI experiment directly tested these competing theories regarding the functional roles of DLPFC, FPC, and ACC. Results reveal dissociable control processes in PFC, with mid-DLPFC selectively mediating resolution of response conflict and FPC further mediating subgoaling/integration. ACC demonstrated a broad sensitivity to control demands, suggesting a generalized role in modulating cognitive control.</description>
    <dc:title>Selection, Integration, and Conflict Monitoring: Assessing the Nature and Generality of Prefrontal Cognitive Control Mechanisms</dc:title>

    <dc:creator>David Badre</dc:creator>
    <dc:creator>Anthony Wagner</dc:creator>
    <dc:identifier>doi:10.1016/S0896-6273(03)00851-1</dc:identifier>
    <dc:source>Neuron, Vol. 41, No. 3. (5 February 2004), pp. 473-487.</dc:source>
    <dc:date>2008-04-06T01:27:49-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Neuron</prism:publicationName>
    <prism:volume>41</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>473</prism:startingPage>
    <prism:endingPage>487</prism:endingPage>
    <prism:category>controller</prism:category>
    <prism:category>learning</prism:category>
    <prism:category>memory</prism:category>
    <prism:category>semantics</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2633931">
    <title>Semantic Retrieval, Mnemonic Control, and Prefrontal Cortex</title>
    <link>http://www.citeulike.org/user/davclark/article/2633931</link>
    <description>&lt;i&gt;Behav Cogn Neurosci Rev, Vol. 1, No. 3. (1 September 2002), pp. 206-218.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Accessing stored knowledge is a fundamental function of the cognitive and neural architectures of memory. Here, the authors review evidence from cognitive-behavioral paradigms, neuropsychological studies ofpatients with focal neural insult, and functional brain imaging concerning the mechanisms underlying retrieval ofsemantic knowledge and their association with prefrontal cortex. First, the authors examine behavioral and neuropsychological evidence distinguishing between controlled and automatic semantic retrieval. Then the authors review the subregions of prefrontal cortex that functional neuroimaging has associated with semantic retrieval across a range ofmemory demanding tasks. Finally, two hypotheses concerning the nature ofprocessing in these brain regions-the controlled semantic retrieval and selection hypotheses-are critically examined, and a possible synthesis is proposed. 10.1177/1534582302001003002</description>
    <dc:title>Semantic Retrieval, Mnemonic Control, and Prefrontal Cortex</dc:title>

    <dc:creator>David Badre</dc:creator>
    <dc:creator>Anthony Wagner</dc:creator>
    <dc:identifier>doi:10.1177/1534582302001003002</dc:identifier>
    <dc:source>Behav Cogn Neurosci Rev, Vol. 1, No. 3. (1 September 2002), pp. 206-218.</dc:source>
    <dc:date>2008-04-06T01:27:54-00:00</dc:date>
    <prism:publicationYear>2002</prism:publicationYear>
    <prism:publicationName>Behav Cogn Neurosci Rev</prism:publicationName>
    <prism:volume>1</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>206</prism:startingPage>
    <prism:endingPage>218</prism:endingPage>
    <prism:category>controller</prism:category>
    <prism:category>learning</prism:category>
    <prism:category>memory</prism:category>
    <prism:category>semantics</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2633644">
    <title>Differential cerebral activation during observation of expressive gestures and motor acts.</title>
    <link>http://www.citeulike.org/user/davclark/article/2633644</link>
    <description>&lt;i&gt;Neuropsychologia, Vol. 44, No. 10. (2006), pp. 1787-1795.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;We compared brain activation involved in the observation of isolated right hand movements (e.g. twisting a lid), body-referred movements (e.g. brushing teeth) and expressive gestures (e.g. threatening) in 20 healthy subjects by using functional magnetic resonance imaging (fMRI). Perception-related areas in the occipital and inferior temporal lobe but also the mirror neuron system in the lateral frontal (ventral premotor cortex and BA 44) and superior parietal lobe were active during all three conditions. Observation of body-referred compared to common hand actions induced increased activity in the bilateral posterior superior temporal sulcus (STS), the left temporo-parietal lobe and left BA 45. Expressive gestures involved additional areas related to social perception (bilateral STS, temporal poles, medial prefrontal lobe), emotional processing (bilateral amygdala, bilateral ventrolateral prefrontal cortex (VLPFC), speech and language processing (Broca's and Wernicke's areas) and the pre-supplementary motor area (pre-SMA). In comparison to body-referred actions, expressive gestures evoked additional activity only in the left VLPFC (BA 47). The valence-ratings for expressive gestures correlated significantly with activation intensity in the VLPFC during expressive gesture observation. Valence-ratings for negative expressive gestures correlated with right STS-activity. Our data suggest that both, the VLPFC and the STS are coding for differential emotional valence during the observation of expressive gestures.</description>
    <dc:title>Differential cerebral activation during observation of expressive gestures and motor acts.</dc:title>

    <dc:creator>M Lotze</dc:creator>
    <dc:creator>U Heymans</dc:creator>
    <dc:creator>N Birbaumer</dc:creator>
    <dc:creator>R Veit</dc:creator>
    <dc:creator>M Erb</dc:creator>
    <dc:creator>H Flor</dc:creator>
    <dc:creator>U Halsband</dc:creator>
    <dc:identifier>doi:10.1016/j.neuropsychologia.2006.03.016</dc:identifier>
    <dc:source>Neuropsychologia, Vol. 44, No. 10. (2006), pp. 1787-1795.</dc:source>
    <dc:date>2008-04-05T21:06:54-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Neuropsychologia</prism:publicationName>
    <prism:issn>0028-3932</prism:issn>
    <prism:volume>44</prism:volume>
    <prism:number>10</prism:number>
    <prism:startingPage>1787</prism:startingPage>
    <prism:endingPage>1795</prism:endingPage>
    <prism:category>emotion</prism:category>
    <prism:category>fmri</prism:category>
    <prism:category>mirror-system</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>observation</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2633612">
    <title>Prefrontal involvement in imitation learning of hand actions: effects of practice and expertise.</title>
    <link>http://www.citeulike.org/user/davclark/article/2633612</link>
    <description>&lt;i&gt;NeuroImage, Vol. 37, No. 4. (1 October 2007), pp. 1371-1383.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In this event-related fMRI study, we demonstrate the effects of a single session of practising configural hand actions (guitar chords) on cortical activations during observation, motor preparation and imitative execution. During the observation of non-practised actions, the mirror neuron system (MNS), consisting of inferior parietal and ventral premotor areas, was more strongly activated than for the practised actions. This finding indicates a strong role of the MNS in the early stages of imitation learning. In addition, the left dorsolateral prefrontal cortex (DLPFC) was selectively involved during observation and motor preparation of the non-practised chords. This finding confirms Buccino et al.'s [Buccino, G., Vogt, S., Ritzl, A., Fink, G.R., Zilles, K., Freund, H.-J., Rizzolatti, G., 2004a. Neural circuits underlying imitation learning of hand actions: an event-related fMRI study. Neuron 42, 323-334] model of imitation learning: for actions that are not yet part of the observer's motor repertoire, DLPFC engages in operations of selection and combination of existing, elementary representations in the MNS. The pattern of prefrontal activations further supports Shallice's [Shallice, T., 2004. The fractionation of supervisory control. In: Gazzaniga, M.S. (Ed.), The Cognitive Neurosciences, Third edition. MIT Press, Cambridge, MA, pp. 943-956] proposal of a dominant role of the left DLPFC in modulating lower level systems and of a dominant role of the right DLPFC in monitoring operations.</description>
    <dc:title>Prefrontal involvement in imitation learning of hand actions: effects of practice and expertise.</dc:title>

    <dc:creator>S Vogt</dc:creator>
    <dc:creator>G Buccino</dc:creator>
    <dc:creator>AM Wohlschläger</dc:creator>
    <dc:creator>N Canessa</dc:creator>
    <dc:creator>NJ Shah</dc:creator>
    <dc:creator>K Zilles</dc:creator>
    <dc:creator>SB Eickhoff</dc:creator>
    <dc:creator>HJ Freund</dc:creator>
    <dc:creator>G Rizzolatti</dc:creator>
    <dc:creator>GR Fink</dc:creator>
    <dc:identifier>doi:10.1016/j.neuroimage.2007.07.005</dc:identifier>
    <dc:source>NeuroImage, Vol. 37, No. 4. (1 October 2007), pp. 1371-1383.</dc:source>
    <dc:date>2008-04-05T20:28:49-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>NeuroImage</prism:publicationName>
    <prism:issn>1053-8119</prism:issn>
    <prism:volume>37</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>1371</prism:startingPage>
    <prism:endingPage>1383</prism:endingPage>
    <prism:category>following</prism:category>
    <prism:category>learning</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>movement</prism:category>
    <prism:category>observation</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1189991">
    <title>The mind of expert motor performance is cool and focused.</title>
    <link>http://www.citeulike.org/user/davclark/article/1189991</link>
    <description>&lt;i&gt;Neuroimage, Vol. 35, No. 2. (1 April 2007), pp. 804-813.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Extraordinary motor skills required for expert athletic or music performance require longstanding and intensive practice leading to two critical skills, a level of maximal performance that far exceeds that of non-experts and a degree of privileged focus on motor performance that excludes intrusions. This study of motor planning in expert golfers demonstrated their brain activation during their pre-shot routine to be radically different than in novices. The posterior cingulate, the amygdala-forebrain complex, and the basal ganglia were active only in novices, whereas experts had activation primarily in the superior parietal lobule, the dorsal lateral premotor area, and the occipital area. The fact that these differences are apparent before the golfer swings the club suggests that the disparity between the quality of the performance of novice and expert golfers lies at the level of the organization of neural networks during motor planning. In particular, we suggest that extensive practice over a long period of time leads experts to develop a focused and efficient organization of task-related neural networks, whereas novices have difficulty filtering out irrelevant information.</description>
    <dc:title>The mind of expert motor performance is cool and focused.</dc:title>

    <dc:creator>J Milton</dc:creator>
    <dc:creator>A Solodkin</dc:creator>
    <dc:creator>P Hlustík</dc:creator>
    <dc:creator>SL Small</dc:creator>
    <dc:identifier>doi:10.1016/j.neuroimage.2007.01.003</dc:identifier>
    <dc:source>Neuroimage, Vol. 35, No. 2. (1 April 2007), pp. 804-813.</dc:source>
    <dc:date>2007-03-27T19:54:10-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Neuroimage</prism:publicationName>
    <prism:issn>1053-8119</prism:issn>
    <prism:volume>35</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>804</prism:startingPage>
    <prism:endingPage>813</prism:endingPage>
    <prism:category>motor</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1206416">
    <title>Sequence learning in pianists and nonpianists: an fMRI study of motor expertise.</title>
    <link>http://www.citeulike.org/user/davclark/article/1206416</link>
    <description>&lt;i&gt;Cogn Affect Behav Neurosci, Vol. 6, No. 3. (September 2006), pp. 246-259.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Previous studies of motor learning have proposed a distinction betweenfast and slow learning, but these mechanisms have rarely been examined simultaneously. We examined the influence of long-term motor expertise (slow learning) while pianists and nonpianists performed alternating epochs of sequenced and random keypresses in response to visual cues (fast learning) during functional neuroimaging. All of the participants demonstrated learning of the sequence as demonstrated by decreasing reaction times (RTs) on sequence trials relative to random trials throughout the session. Pianists also demonstrated faster RTs and superior sequence acquisition in comparison with nonpianists. Within-session decreases in bilateral sensorimotor and parietal activation were observed for both groups. Additionally, there was more extensive activation throughout the session for pianists in comparison with nonpianists across a network of primarily right-lateralized prefrontal, sensorimotor, and parietal regions. These findings provide evidence that different neural systems subserve slow and fast phases of learning.</description>
    <dc:title>Sequence learning in pianists and nonpianists: an fMRI study of motor expertise.</dc:title>

    <dc:creator>SM Landau</dc:creator>
    <dc:creator>M D'esposito</dc:creator>
    <dc:source>Cogn Affect Behav Neurosci, Vol. 6, No. 3. (September 2006), pp. 246-259.</dc:source>
    <dc:date>2007-04-04T16:27:12-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Cogn Affect Behav Neurosci</prism:publicationName>
    <prism:issn>1530-7026</prism:issn>
    <prism:volume>6</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>246</prism:startingPage>
    <prism:endingPage>259</prism:endingPage>
    <prism:category>expertise</prism:category>
    <prism:category>fmri</prism:category>
    <prism:category>learning</prism:category>
    <prism:category>motor</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/257178">
    <title>Action Observation and Acquired Motor Skills: An fMRI Study with Expert Dancers</title>
    <link>http://www.citeulike.org/user/davclark/article/257178</link>
    <description>&lt;i&gt;Cerebral Cortex, Vol. 15, No. 8. (August 2005), pp. 1243-1249.&lt;/i&gt;</description>
    <dc:title>Action Observation and Acquired Motor Skills: An fMRI Study with Expert Dancers</dc:title>

    <dc:creator>B Calvo-Merino</dc:creator>
    <dc:creator>DE Glaser</dc:creator>
    <dc:creator>J Grezes</dc:creator>
    <dc:creator>RE Passingham</dc:creator>
    <dc:creator>P Haggard</dc:creator>
    <dc:identifier>doi:10.1093/cercor/bhi007</dc:identifier>
    <dc:source>Cerebral Cortex, Vol. 15, No. 8. (August 2005), pp. 1243-1249.</dc:source>
    <dc:date>2005-07-15T12:58:01-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Cerebral Cortex</prism:publicationName>
    <prism:issn>1047-3211</prism:issn>
    <prism:volume>15</prism:volume>
    <prism:number>8</prism:number>
    <prism:startingPage>1243</prism:startingPage>
    <prism:endingPage>1249</prism:endingPage>
    <prism:publisher>Oxford University Press</prism:publisher>
    <prism:category>dance</prism:category>
    <prism:category>fmri</prism:category>
    <prism:category>mirror-system</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>movement</prism:category>
    <prism:category>observation</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2557086">
    <title>Inhibitory motor control in stop paradigms: review and reinterpretation of neural mechanisms</title>
    <link>http://www.citeulike.org/user/davclark/article/2557086</link>
    <description>&lt;i&gt;Acta Psychologica, Vol. 101, No. 2-3. (April 1999), pp. 179-211.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;What is the neurophysiological locus of inhibition when preparation for a manual response is countermanded? This paper evaluates data and models that pertain to inhibitory mechanisms operating in stop paradigms. In a model of De Jong, Coles and Logan (1995), (Strategies and mechanisms in nonselective and selective inhibitory motor control. Journal of Experimental Psychology: Human Perception and Performance, 21, 3, 498-511), a mechanism for nonselective inhibition operates peripheral to the motor cortex, while a selective mechanism operates at a central cortical level. We argue, however, that a peripheral mechanism of inhibition is incorrectly inferred from inhibition data available to date. Neurophysiological and psychophysiological data suggest that inhibitory processes always involve the cortex, and inhibitory effects are exerted upstream from the primary motor cortex. The prefrontal cortex and basal ganglia are candidate agents of response inhibition, whereas possible sites of inhibition are the thalamus and motor cortex.</description>
    <dc:title>Inhibitory motor control in stop paradigms: review and reinterpretation of neural mechanisms</dc:title>

    <dc:creator>GPH Band</dc:creator>
    <dc:creator>GJM van Boxtel</dc:creator>
    <dc:identifier>doi:10.1016/S0001-6918(99)00005-0</dc:identifier>
    <dc:source>Acta Psychologica, Vol. 101, No. 2-3. (April 1999), pp. 179-211.</dc:source>
    <dc:date>2008-03-19T04:18:38-00:00</dc:date>
    <prism:publicationYear>1999</prism:publicationYear>
    <prism:publicationName>Acta Psychologica</prism:publicationName>
    <prism:volume>101</prism:volume>
    <prism:number>2-3</prism:number>
    <prism:startingPage>179</prism:startingPage>
    <prism:endingPage>211</prism:endingPage>
    <prism:category>controller</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>stop-signal</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2547853">
    <title>Electrophysiological correlates of interval timing in the Stop-Reaction-Time task.</title>
    <link>http://www.citeulike.org/user/davclark/article/2547853</link>
    <description>&lt;i&gt;Brain Res Cogn Brain Res, Vol. 21, No. 2. (October 2004), pp. 234-249.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Scalp-recorded event-related potentials were recorded while participants completed an auditory or a visual Stop-Reaction-Time task (Stop-RT task). Participants were asked to listen to a sequence of tones (Experiment 1) or view a sequence of LED flashes (Experiment 2) that had a constant stimulus onset asynchrony (SOA) of either 470 or 770 ms, and to respond as soon as the sequence ended. Sequence length varied across trials, so counting the tones or light flashes did not permit determination of sequence end. Instead, participants had to time the SOA, even though they were not explicitly instructed to do so, and respond when the SOA had been exceeded. At sequence end, a biphasic negative-positive ERP response was emitted following the point in time when a stimulus would have occurred had the sequence continued. The negative component of this omission potential (OP) had a right fronto-central focus, whereas the positive component had a parietal focus; a pattern that held across SOA duration and signal modality. Moreover, the mean peak latency of the negative OP was equivalent in the visual and auditory modalities, even though the behavioral Stop-RTs obtained in the auditory experiment were 200 ms faster than those obtained in the visual experiment. The amodal negative OP appears to be a correlate of an interval-timing process that precedes response initiation, whereas the positive OP is most likely a target P300.</description>
    <dc:title>Electrophysiological correlates of interval timing in the Stop-Reaction-Time task.</dc:title>

    <dc:creator>TB Penney</dc:creator>
    <dc:identifier>doi:10.1016/j.cogbrainres.2004.07.005</dc:identifier>
    <dc:source>Brain Res Cogn Brain Res, Vol. 21, No. 2. (October 2004), pp. 234-249.</dc:source>
    <dc:date>2008-03-17T22:39:14-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Brain Res Cogn Brain Res</prism:publicationName>
    <prism:issn>0926-6410</prism:issn>
    <prism:volume>21</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>234</prism:startingPage>
    <prism:endingPage>249</prism:endingPage>
    <prism:category>eeg</prism:category>
    <prism:category>stop-signal</prism:category>
    <prism:category>time</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/1142242">
    <title>Effects of stop-signal probability in the stop-signal paradigm: the N2/P3 complex further validated.</title>
    <link>http://www.citeulike.org/user/davclark/article/1142242</link>
    <description>&lt;i&gt;Brain Cogn, Vol. 56, No. 2. (November 2004), pp. 234-252.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The aim of this study was to examine the effects of frequency of occurrence of stop signals in the stop-signal paradigm. Presenting stop signals less frequently resulted in faster reaction times to the go stimulus and a lower probability of inhibition. Also, go stimuli elicited larger and somewhat earlier P3 responses when stop signals occurred less frequently. Since the amplitude effect was more pronounced on trials when go signals were followed by fast than slow reactions, it probably reflected a stronger set to produce fast responses. N2 and P3 components to stop signals were observed to be larger and of longer latency when stop signals occurred less frequently. The amplitude enhancement of these N2 and P3 components were more pronounced for unsuccessful than for successful stop-signal trials. Moreover, the successfully inhibited stop trials elicited a frontocentral P3 whereas unsuccessfully inhibited stop trials elicited a more posterior P3 that resembled the classical P3b. P3 amplitude in the unsuccessfully inhibited condition also differed between waveforms synchronized with the stop signal and waveforms synchronized with response onset whereas N2 amplitude did not. Taken together these findings suggest that N2 reflected a greater significance of failed inhibitions after low probability stop signals while P3 reflected continued processing of the erroneous response after response execution.</description>
    <dc:title>Effects of stop-signal probability in the stop-signal paradigm: the N2/P3 complex further validated.</dc:title>

    <dc:creator>JR Ramautar</dc:creator>
    <dc:creator>A Kok</dc:creator>
    <dc:creator>KR Ridderinkhof</dc:creator>
    <dc:identifier>doi:10.1016/j.bandc.2004.07.002</dc:identifier>
    <dc:source>Brain Cogn, Vol. 56, No. 2. (November 2004), pp. 234-252.</dc:source>
    <dc:date>2007-03-05T20:39:01-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Brain Cogn</prism:publicationName>
    <prism:issn>0278-2626</prism:issn>
    <prism:volume>56</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>234</prism:startingPage>
    <prism:endingPage>252</prism:endingPage>
    <prism:category>eeg</prism:category>
    <prism:category>stop-signal</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2547851">
    <title>Additive factors analysis of inhibitory processing in the stop-signal paradigm.</title>
    <link>http://www.citeulike.org/user/davclark/article/2547851</link>
    <description>&lt;i&gt;Brain Cogn, Vol. 56, No. 2. (November 2004), pp. 253-266.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;This article reports an additive factors analysis of choice reaction and selective stop processes manipulated in a stop-signal paradigm. Three experiments were performed in which stimulus discriminability (SD) and stimulus-response compatibility (SRC) were manipulated in a factorial fashion. In each experiment, the effects of SD and SRC were assessed first for going and next for stopping. Two experiments yielded the anticipated additive relation between SD and SRC for going but stopping appeared to be insensitive to the SD manipulation. Increasing the SD demands in the third experiment by using a different display resulted in a significant (over-additive) interaction between SD and SRC for going and a non-significant (under-additive) interaction for stopping. The pattern of results that emerged from this set of experiments was interpreted to suggest that going and stopping are both similar and different. They are similar in that distinct stages can be identified in both going and stopping but they are also different, as selective stopping seems to be less sensitive to discrimination manipulations relative to going.</description>
    <dc:title>Additive factors analysis of inhibitory processing in the stop-signal paradigm.</dc:title>

    <dc:creator>WP van den Wildenberg</dc:creator>
    <dc:creator>MW van der Molen</dc:creator>
    <dc:identifier>doi:10.1016/j.bandc.2004.06.006</dc:identifier>
    <dc:source>Brain Cogn, Vol. 56, No. 2. (November 2004), pp. 253-266.</dc:source>
    <dc:date>2008-03-17T22:38:05-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Brain Cogn</prism:publicationName>
    <prism:issn>0278-2626</prism:issn>
    <prism:volume>56</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>253</prism:startingPage>
    <prism:endingPage>266</prism:endingPage>
    <prism:category>eeg</prism:category>
    <prism:category>stop-signal</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/906124">
    <title>The auditory-evoked N2 and P3 components in the stop-signal task: Indices of inhibition, response-conflict or error-detection?</title>
    <link>http://www.citeulike.org/user/davclark/article/906124</link>
    <description>&lt;i&gt;Brain and Cognition, Vol. 62, No. 2. (November 2006), pp. 98-112.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The N2 and P3 components have been separately associated with response inhibition in the stop-signal task, and more recently, the N2 has been implicated in the detection of response-conflict. To isolate response inhibition activity from early sensory processing, the present study compared processing of the stop-signal with that of a task-irrelevant tone, which subjects were instructed to ignore. Stop-signals elicited a larger N2 on failed-stop trials and a larger P3 on successful-stop trials, relative to ignore-signal trials, likely reflecting activity related to failed and successful stopping, respectively. ERPs between fast and slow reaction-time (RT) groups were also examined as it was hypothesised that greater inhibitory activation to stop faster responses would manifest in the component reflecting this process. Successful-stop P3 showed the anticipated effect (globally larger amplitude in the fast than slow RT group), supporting its association with the stopping of an ongoing response. In contrast, N2 was larger in the slow than fast RT group, and in contrast to the predictions of the response-conflict hypothesis, successful-stop N2 and the response-locked error-negativity (Ne) differed in scalp distribution. These findings indicate that the successful-stop N2 may be better explained as a deliberate form of response control or selection, which the slow RT group employed as a means of increasing the likelihood of a successful-stop. Finally, a comparison of stimulus and response-locked ERPs revealed that the failed-stop N2 and P3 appeared to reflect error-related activity, best observed in the response-locked Ne and error-positivity (Pe). Together these findings indicate that the successful-stop N2 and P3 reflect functionally distinct aspects of response control that are dependent upon performance strategies, while failed-stop N2 and P3 reflect error-related activity.</description>
    <dc:title>The auditory-evoked N2 and P3 components in the stop-signal task: Indices of inhibition, response-conflict or error-detection?</dc:title>

    <dc:creator>Aneta Dimoska</dc:creator>
    <dc:creator>Stuart Johnstone</dc:creator>
    <dc:creator>Robert Barry</dc:creator>
    <dc:identifier>doi:10.1016/j.bandc.2006.03.011</dc:identifier>
    <dc:source>Brain and Cognition, Vol. 62, No. 2. (November 2006), pp. 98-112.</dc:source>
    <dc:date>2006-10-19T17:12:30-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Brain and Cognition</prism:publicationName>
    <prism:volume>62</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>98</prism:startingPage>
    <prism:endingPage>112</prism:endingPage>
    <prism:category>eeg</prism:category>
    <prism:category>stop-signal</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2547760">
    <title>Haptic tracking permits bimanual independence.</title>
    <link>http://www.citeulike.org/user/davclark/article/2547760</link>
    <description>&lt;i&gt;J Exp Psychol Hum Percept Perform, Vol. 32, No. 5. (October 2006), pp. 1266-1275.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;This study shows that in a novel task-bimanual haptic tracking-neurologically normal human adults can move their 2 hands independently for extended periods of time with little or no training. Participants lightly touched buttons whose positions were moved either quasi-randomly in the horizontal plane by 1 or 2 human drivers (Experiment 1), in circle and square patterns in the vertical plane by 2 human drivers (Experiment 2), or at different frequencies in the horizontal plane by 2 human drivers (Experiment 3). Bimanual contact was maintained equally well in all conditions even though in Experiment 1 the left- and right-hand motions were uncorrelated (in the 2-driver condition), in Experiment 2 the left- and right-hand motions were spatially incongruous when circles and squares were tracked at the same time, and in Experiment 3 the left- and right-hand motions maintained different frequency ratios. Because haptic tracking has revealed that humans can in fact move their 2 hands independently, it may have potential as a new behavioral tool for revealing other perceptual-motor capabilities.</description>
    <dc:title>Haptic tracking permits bimanual independence.</dc:title>

    <dc:creator>DA Rosenbaum</dc:creator>
    <dc:creator>AM Dawson</dc:creator>
    <dc:creator>JH Challis</dc:creator>
    <dc:identifier>doi:10.1037/0096-1523.32.5.1266</dc:identifier>
    <dc:source>J Exp Psychol Hum Percept Perform, Vol. 32, No. 5. (October 2006), pp. 1266-1275.</dc:source>
    <dc:date>2008-03-17T21:27:33-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>J Exp Psychol Hum Percept Perform</prism:publicationName>
    <prism:issn>0096-1523</prism:issn>
    <prism:volume>32</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>1266</prism:startingPage>
    <prism:endingPage>1275</prism:endingPage>
    <prism:category>bimanual</prism:category>
    <prism:category>controller</prism:category>
    <prism:category>following</prism:category>
    <prism:category>from-rich</prism:category>
    <prism:category>motor</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2544019">
    <title>A Cognitive Neuroscience Perspective On Bimanual Coordination And Interference</title>
    <link>http://www.citeulike.org/user/davclark/article/2544019</link>
    <description>&lt;i&gt;&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;We argue that bimanual coordination and interference depends critically on how these actions are represented on a cognitive level. We first review the literature on spatial interactions, focusing on the difference between movements directed at visual targets and movements cued symbolically. Interactions manifest during response planning are limited to the latter condition. These results suggest that interactions in the formation of the trajectories of the two hands are associated with processes ...</description>
    <dc:title>A Cognitive Neuroscience Perspective On Bimanual Coordination And Interference</dc:title>

    <dc:creator>Richard Ivry</dc:creator>
    <dc:creator>Jörn Diedrichsen</dc:creator>
    <dc:creator>Rebecca Spencer</dc:creator>
    <dc:creator>Eliot Hazeltine</dc:creator>
    <dc:creator>Andras Semjen</dc:creator>
    <dc:date>2008-03-17T01:03:04-00:00</dc:date>
    <prism:category>controller</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>srt</prism:category>
    <prism:category>symbolic</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2543977">
    <title>Ipsilateral Motor Cortex Activity During Unimanual Hand Movements Relates to Task Complexity</title>
    <link>http://www.citeulike.org/user/davclark/article/2543977</link>
    <description>&lt;i&gt;J Neurophysiol, Vol. 93, No. 3. (1 March 2005), pp. 1209-1222.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Functional imaging studies have revealed recruitment of ipsilateral motor areas during the production of sequential unimanual finger movements. This phenomenon is more prominent in the left hemisphere during left-hand movements than in the right hemisphere during right-hand movements. Here we investigate whether this lateralization pattern is related specifically to the sequential structure of the unimanual action or generalizes to other complex movements. Using event-related fMRI, we measured activation changes in the motor cortex during three types of unimanual movements: repetitions of a sequence of movements with multiple fingers, repetitive &#34;chords&#34; composed of three simultaneous key presses, and simple repetitive tapping movements with a single finger. During sequence and chord movements, strong ipsilateral activation was observed and was especially pronounced in the left hemisphere during left-hand movements. This pattern was evident for both right-handed and, to a lesser degree, left-handed individuals. Ipsilateral activation was less pronounced in the tapping condition. The site of ipsilateral activation was shifted laterally, ventrally, and anteriorly with respect to that observed during contralateral movements and the time course of activation implied a role in the execution rather than planning of the movement. A control experiment revealed that strong ipsilateral activity in left motor cortex is specific to complex movements and does not depend on the number of required muscles. These findings indicate a prominent role of left hemisphere in the execution of complex movements independent of the sequential nature of the task. 10.1152/jn.00720.2004</description>
    <dc:title>Ipsilateral Motor Cortex Activity During Unimanual Hand Movements Relates to Task Complexity</dc:title>

    <dc:creator>Timothy Verstynen</dc:creator>
    <dc:creator>Jorn Diedrichsen</dc:creator>
    <dc:creator>Neil Albert</dc:creator>
    <dc:creator>Paul Aparicio</dc:creator>
    <dc:creator>Richard Ivry</dc:creator>
    <dc:identifier>doi:10.1152/jn.00720.2004</dc:identifier>
    <dc:source>J Neurophysiol, Vol. 93, No. 3. (1 March 2005), pp. 1209-1222.</dc:source>
    <dc:date>2008-03-17T00:35:48-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>J Neurophysiol</prism:publicationName>
    <prism:volume>93</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>1209</prism:startingPage>
    <prism:endingPage>1222</prism:endingPage>
    <prism:category>controller</prism:category>
    <prism:category>motor</prism:category>
    <prism:category>srt</prism:category>
    <prism:category>task-complexity</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2504883">
    <title>Multiple synchronization strategies in rhythmic sensorimotor tasks: phase vs period correction</title>
    <link>http://www.citeulike.org/user/davclark/article/2504883</link>
    <description>&lt;i&gt;Biological Cybernetics, Vol. 79, No. 3. (5 October 1998), pp. 241-250.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;To characterize synchronisation strategies in the tracking of auditory rhythm with rhythmic finger tapping, the adaptation process after unexpected step changes of an interstimulus interval (ISI) of 500 ms was investigated. Step changes of 2% (10 ms), 4% (20 ms), and 10% (50 ms) of ISI were applied to the stimulus sequence. Synchronisation patterns of 5 subjects were analyzed based on synchronisation error (SE) and interresponse intervals (IRI). A strategy shift contigent upon the size of the introduced step change was detected. After small ISI changes, rapid IRI matching to the new ISI was accompanied by temporarily enlarged SE values, which slowly returned to preferred SE values before the step change. Large ISI changes showed quick SE adaptations accompanied by a temporary overcorrection of IRI. Response asymmetry between ISI decreases and increases emerged, showing a stronger adaptation during ISI increases. A two-dimensional difference equation was formulated to simulate the time series of intertap intervals and explain the control process during IRI and SE adjustments. The system constants were optimized to minimalize the deviations between the computed and the observed response trajectories, consisting of the time series of SE and IRI. It was shown that a successful model fit using a linear two-dimensional difference equation was based on the size and direction of the ISI changes. MANOVA procedures showed that differences in equation parameters during small and large step changes were statistically significant (P&#60;0.05). It is therefore suggested that a uniform model accounting for synchronization responses to all step changes would require the introduction of nonlinear system properties.</description>
    <dc:title>Multiple synchronization strategies in rhythmic sensorimotor tasks: phase vs period correction</dc:title>

    <dc:creator>Michael Thaut</dc:creator>
    <dc:creator>Robert Miller</dc:creator>
    <dc:creator>Leopold Schauer</dc:creator>
    <dc:identifier>doi:10.1007/s004220050474</dc:identifier>
    <dc:source>Biological Cybernetics, Vol. 79, No. 3. (5 October 1998), pp. 241-250.</dc:source>
    <dc:date>2008-03-10T23:37:11-00:00</dc:date>
    <prism:publicationYear>1998</prism:publicationYear>
    <prism:publicationName>Biological Cybernetics</prism:publicationName>
    <prism:volume>79</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>241</prism:startingPage>
    <prism:endingPage>250</prism:endingPage>
    <prism:category>motor</prism:category>
    <prism:category>synchronization</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2504808">
    <title>Getting synchronized with the metronome: Comparisons between phase and period correction</title>
    <link>http://www.citeulike.org/user/davclark/article/2504808</link>
    <description>&lt;i&gt;Psychological Research, Vol. 61, No. 1. (5 March 1998), pp. 44-55.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Most studies of synchronization have focused on how an established phase relationship between self-produced events (e.g., finger taps) and the clicks of a metronome is maintained when the metronome is regular or subject to unpredictable perturbations. Here we study how synchronization is initially established, using an experimental paradigm in which the metronome is activated after the subject has executed a series of self-paced finger taps. In Exp. 1, the metronome period was constant and equal to the mean of the self-paced inter-response intervals, whereas the initial phase difference of the metronome from the taps varied across trials. The synchronization error patterns could be predicted by a linear phase correction model. Experiment 2 involved both period and phase correction. The initial phase difference was constant, whereas the metronome period varied across trials. The observed synchronization error patterns suggest that the subjects achieved synchronization either by reacting to the second metronome signal or by aiming at the third metronome signal. The pattern of the residual synchronization errors was consistent with the linear phase correction model. These results support the notion that period and phase correction mechanisms are called for by different task variables and contribute differently to sensorimotor synchronization.</description>
    <dc:title>Getting synchronized with the metronome: Comparisons between phase and period correction</dc:title>

    <dc:creator>Andras Semjen</dc:creator>
    <dc:creator>Dirk Vorberg</dc:creator>
    <dc:creator>Hans-Henning Schulze</dc:creator>
    <dc:identifier>doi:10.1007/s004260050012</dc:identifier>
    <dc:source>Psychological Research, Vol. 61, No. 1. (5 March 1998), pp. 44-55.</dc:source>
    <dc:date>2008-03-10T23:07:09-00:00</dc:date>
    <prism:publicationYear>1998</prism:publicationYear>
    <prism:publicationName>Psychological Research</prism:publicationName>
    <prism:volume>61</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>44</prism:startingPage>
    <prism:endingPage>55</prism:endingPage>
    <prism:category>motor</prism:category>
    <prism:category>synchronization</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2504805">
    <title>A model of synchronization of motor acts to a stimulus sequence</title>
    <link>http://www.citeulike.org/user/davclark/article/2504805</link>
    <description>&lt;i&gt;Biological Cybernetics, Vol. 70, No. 5. (5 February 1994), pp. 463-473.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;A closed-loop timing model is proposed that accounts for several phenomena observed in tasks which require production of a sequence of motor acts in synchrony with a sequence of stimuli. In contrast to the previous models, variables available to the central nervous system of a subject (internal variables) and externally measurable variables are distinguished, and several physiologically justifiable internal variables are included. The model assumes the existence of (a) an internal time-keeper producing a reference interval that is used in a motor-control unit for timing of the next motor command; (b) an intrinsic (subjective) synchrony that relies on some a posteriori (feedback) information about the already executed onset of the motor act. A two-way error-corrective mechanism is hypothesized: (1) period (inverted frequency) corrections — the reference interval (period) is set at the beginning of the task according to the interstimulus-onset interval (s) and later corrected for differences between its duration and the actual duration of s; (2) phase corrections — internal synchronization errors (i.e., time gaps between the central temporal availability of internal representations of stimuli and of some feedback aspect of responses) are corrected for directly in the motor-control unit. Objectively measured systematic asynchrony of responses and stimuli is determined by the internal delays in information transduction. Finally, the model is used for making predictions of a subject's performance in some other experimental settings of the synchronization task.</description>
    <dc:title>A model of synchronization of motor acts to a stimulus sequence</dc:title>

    <dc:creator>Jiří Mates</dc:creator>
    <dc:identifier>doi:10.1007/BF00203239</dc:identifier>
    <dc:source>Biological Cybernetics, Vol. 70, No. 5. (5 February 1994), pp. 463-473.</dc:source>
    <dc:date>2008-03-10T23:06:39-00:00</dc:date>
    <prism:publicationYear>1994</prism:publicationYear>
    <prism:publicationName>Biological Cybernetics</prism:publicationName>
    <prism:volume>70</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>463</prism:startingPage>
    <prism:endingPage>473</prism:endingPage>
    <prism:category>motor</prism:category>
    <prism:category>synchronization</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2504802">
    <title>Rhythmicity, synchronization and binding in human and primate motor systems</title>
    <link>http://www.citeulike.org/user/davclark/article/2504802</link>
    <description>&lt;i&gt;J Physiol, Vol. 509, No. 1. (15 May 1998), pp. 3-14.&lt;/i&gt;</description>
    <dc:title>Rhythmicity, synchronization and binding in human and primate motor systems</dc:title>

    <dc:creator>SF Farmer</dc:creator>
    <dc:source>J Physiol, Vol. 509, No. 1. (15 May 1998), pp. 3-14.</dc:source>
    <dc:date>2008-03-10T23:05:24-00:00</dc:date>
    <prism:publicationYear>1998</prism:publicationYear>
    <prism:publicationName>J Physiol</prism:publicationName>
    <prism:volume>509</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>3</prism:startingPage>
    <prism:endingPage>14</prism:endingPage>
    <prism:category>motor</prism:category>
    <prism:category>synchronization</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2409815">
    <title>Memory traces unbound</title>
    <link>http://www.citeulike.org/user/davclark/article/2409815</link>
    <description>&lt;i&gt;Trends in Neurosciences, Vol. 26, No. 2. (February 2003), pp. 65-72.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The idea that new memories are initially `labile' and sensitive to disruption before becoming permanently stored in the wiring of the brain has been dogma for &#62;100 years. Recently, we have revisited the hypothesis that reactivation of a consolidated memory can return it to a labile, sensitive state - in which it can be modified, strengthened, changed or even erased! The data generated from some of the best-described paradigms in memory research, in conjunction with powerful neurobiological technologies, have provided striking support for a very dynamic neurobiological basis of memory, which is beginning to overturn the old dogma.</description>
    <dc:title>Memory traces unbound</dc:title>

    <dc:creator>Karim Nader</dc:creator>
    <dc:identifier>doi:10.1016/S0166-2236(02)00042-5</dc:identifier>
    <dc:source>Trends in Neurosciences, Vol. 26, No. 2. (February 2003), pp. 65-72.</dc:source>
    <dc:date>2008-02-22T01:22:44-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:publicationName>Trends in Neurosciences</prism:publicationName>
    <prism:volume>26</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>65</prism:startingPage>
    <prism:endingPage>72</prism:endingPage>
    <prism:category>memory</prism:category>
    <prism:category>reconsolidation</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2299388">
    <title>Optimal experimental design for event-related fMRI</title>
    <link>http://www.citeulike.org/user/davclark/article/2299388</link>
    <description>&lt;i&gt;Human Brain Mapping, Vol. 8, No. 2-3. (1999), pp. 109-114.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;An important challenge in the design and analysis of event-related or single-trial functional magnetic resonance imaging (fMRI) experiments is to optimize statistical efficiency, i.e., the accuracy with which the event-related hemodynamic response to different stimuli can be estimated for a given amount of imaging time. Several studies have suggested that using a fixed inter-stimulus-interval (ISI) of at least 15 sec results in optimal statistical efficiency or power and that using shorter ISIs results in a severe loss of power. In contrast, recent studies have demonstrated the feasibility of using ISIs as short as 500 ms while still maintaining considerable efficiency or power. Here, we attempt to resolve this apparent contradiction by a quantitative analysis of the relative efficiency afforded by different event-related experimental designs. This analysis shows that statistical efficiency falls off dramatically as the ISI gets sufficiently short, if the ISI is kept fixed for all trials. However, if the ISI is properly jittered or randomized from trial to trial, the efficiency improves monotonically with decreasing mean ISI. Importantly, the efficiency afforded by such variable ISI designs can be more than 10 times greater than that which can be achieved by fixed ISI designs. These results further demonstrate the feasibility of using identical experimental designs with fMRI and electro-/magnetoencephalography (EEG/MEG) without sacrificing statistical power or efficiency of either technique, thereby facilitating comparison and integration across imaging modalities. Hum. Brain Mapping 8:109-114, 1999. © 1999 Wiley-Liss, Inc.</description>
    <dc:title>Optimal experimental design for event-related fMRI</dc:title>

    <dc:creator>Anders Dale</dc:creator>
    <dc:identifier>doi:10.1002/(SICI)1097-0193(1999)8:2/3&#60;109::AID-HBM7&#62;3.0.CO;2-W</dc:identifier>
    <dc:source>Human Brain Mapping, Vol. 8, No. 2-3. (1999), pp. 109-114.</dc:source>
    <dc:date>2008-01-28T19:55:00-00:00</dc:date>
    <prism:publicationYear>1999</prism:publicationYear>
    <prism:publicationName>Human Brain Mapping</prism:publicationName>
    <prism:volume>8</prism:volume>
    <prism:number>2-3</prism:number>
    <prism:startingPage>109</prism:startingPage>
    <prism:endingPage>114</prism:endingPage>
    <prism:category>fmri</prism:category>
    <prism:category>methods</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2306203">
    <title>Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activity.</title>
    <link>http://www.citeulike.org/user/davclark/article/2306203</link>
    <description>&lt;i&gt;Nature Neuroscience, Vol. 10, No. 10. (October 2007), pp. 1308-1312.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In noninvasive neuroimaging, neural activity is inferred from local fluctuations in deoxyhemoglobin. A fundamental question of functional magnetic resonance imaging (fMRI) is whether the inferred neural activity is driven primarily by synaptic or spiking activity. The answer is critical for the interpretation of the blood oxygen level–dependent (BOLD) signal in fMRI. Here, we have used well-established visual-system circuitry to create a stimulus that elicits synaptic activity without associated spike discharge. In colocalized recordings of neural and metabolic activity in cat primary visual cortex, we observed strong coupling between local field potentials (LFPs) and changes in tissue oxygen concentration in the absence of spikes. These results imply that the BOLD signal is more closely coupled to synaptic activity.</description>
    <dc:title>Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activity.</dc:title>

    <dc:creator>A Viswanathan</dc:creator>
    <dc:creator>RD Freeman</dc:creator>
    <dc:source>Nature Neuroscience, Vol. 10, No. 10. (October 2007), pp. 1308-1312.</dc:source>
    <dc:date>2008-01-30T07:31:12-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Nature Neuroscience</prism:publicationName>
    <prism:volume>10</prism:volume>
    <prism:number>10</prism:number>
    <prism:startingPage>1308</prism:startingPage>
    <prism:endingPage>1312</prism:endingPage>
    <prism:category>cogneuro-spring2008</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2306219">
    <title>Transcranial magnetic stimulation elicits coupled neural and hemodynamic consequences.</title>
    <link>http://www.citeulike.org/user/davclark/article/2306219</link>
    <description>&lt;i&gt;Science, Vol. 317, No. 5846. (28 September 2007), pp. 1918-1921.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Transcranial magnetic stimulation (TMS) is an increasingly common technique used to selectively modify neural processing. However, application of TMS is limited by uncertainty concerning its physiological effects. We applied TMS to the cat visual cortex and evaluated the neural and hemodynamic consequences. Short TMS pulse trains elicited initial activation (~1 minute) and prolonged suppression (5 to 10 minutes) of neural responses. Furthermore, TMS disrupted the temporal structure of activity by altering phase relationships between neural signals. Despite the complexity of this response, neural changes were faithfully reflected in hemodynamic signals; quantitative coupling was present over a range of stimulation parameters. These results demonstrate long-lasting neural responses to TMS and support the use of hemodynamic-based neuroimaging to effectively monitor these changes over time.</description>
    <dc:title>Transcranial magnetic stimulation elicits coupled neural and hemodynamic consequences.</dc:title>

    <dc:creator>EA Allen</dc:creator>
    <dc:creator>BN Pasley</dc:creator>
    <dc:creator>T Duong</dc:creator>
    <dc:creator>RD Freeman</dc:creator>
    <dc:source>Science, Vol. 317, No. 5846. (28 September 2007), pp. 1918-1921.</dc:source>
    <dc:date>2008-01-30T07:39:11-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Science</prism:publicationName>
    <prism:volume>317</prism:volume>
    <prism:number>5846</prism:number>
    <prism:startingPage>1918</prism:startingPage>
    <prism:endingPage>1921</prism:endingPage>
    <prism:category>cogneuro-spring2008</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2306227">
    <title>Adaptation: from single cells to BOLD signals</title>
    <link>http://www.citeulike.org/user/davclark/article/2306227</link>
    <description>&lt;i&gt;Trends in Neuroscience, Vol. 29, No. 5. (May 2006), pp. 250-256.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Functional magnetic resonance imaging adaptation (fMRIa) is an increasingly popular method that aims to provide insight into the functional properties of subpopulations of neurons within an imaging voxel. The technique relies on the assumption that neural adaptation reduces activity when two successive stimuli activate the same subpopulation but not when they stimulate different subpopulations. Here, we assess the validity of fMRIa by comparing single-cell recordings with functional imaging of orientation, motion and face processing. We find that fMRIa provides novel insight into neural representations in the human brain. However, network responses in general and adaptation in particular are more complex than is often assumed, and an unequivocal interpretation of fMRIa results can be achieved only with great care.</description>
    <dc:title>Adaptation: from single cells to BOLD signals</dc:title>

    <dc:creator>B Krekelberg</dc:creator>
    <dc:creator>GM Boynton</dc:creator>
    <dc:creator>RJ van Wezel</dc:creator>
    <dc:source>Trends in Neuroscience, Vol. 29, No. 5. (May 2006), pp. 250-256.</dc:source>
    <dc:date>2008-01-30T07:43:13-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Trends in Neuroscience</prism:publicationName>
    <prism:volume>29</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>250</prism:startingPage>
    <prism:endingPage>256</prism:endingPage>
    <prism:category>cogneuro-spring2008</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2316767">
    <title>Using FMRI brain activation to identify cognitive States associated with perception of tools and dwellings.</title>
    <link>http://www.citeulike.org/user/davclark/article/2316767</link>
    <description>&lt;i&gt;PLoS ONE, Vol. 3, No. 1. (2008)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Previous studies have succeeded in identifying the cognitive state corresponding to the perception of a set of depicted categories, such as tools, by analyzing the accompanying pattern of brain activity, measured with fMRI. The current research focused on identifying the cognitive state associated with a 4s viewing of an individual line drawing (1 of 10 familiar objects, 5 tools and 5 dwellings, such as a hammer or a castle). Here we demonstrate the ability to reliably (1) identify which of the 10 drawings a participant was viewing, based on that participant's characteristic whole-brain neural activation patterns, excluding visual areas; (2) identify the category of the object with even higher accuracy, based on that participant's activation; and (3) identify, for the first time, both individual objects and the category of the object the participant was viewing, based only on other participants' activation patterns. The voxels important for category identification were located similarly across participants, and distributed throughout the cortex, focused in ventral temporal perceptual areas but also including more frontal association areas (and somewhat left-lateralized). These findings indicate the presence of stable, distributed, communal, and identifiable neural states corresponding to object concepts.</description>
    <dc:title>Using FMRI brain activation to identify cognitive States associated with perception of tools and dwellings.</dc:title>

    <dc:creator>SV Shinkareva</dc:creator>
    <dc:creator>RA Mason</dc:creator>
    <dc:creator>VL Malave</dc:creator>
    <dc:creator>W Wang</dc:creator>
    <dc:creator>TM Mitchell</dc:creator>
    <dc:creator>MA Just</dc:creator>
    <dc:identifier>doi:10.1371/journal.pone.0001394</dc:identifier>
    <dc:source>PLoS ONE, Vol. 3, No. 1. (2008)</dc:source>
    <dc:date>2008-01-31T22:52:19-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>PLoS ONE</prism:publicationName>
    <prism:issn>1932-6203</prism:issn>
    <prism:volume>3</prism:volume>
    <prism:number>1</prism:number>
    <prism:category>cogneuro-spring2008</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2316784">
    <title>Inverse retinotopy: Inferring the visual content of images from brain activation patterns</title>
    <link>http://www.citeulike.org/user/davclark/article/2316784</link>
    <description>&lt;i&gt;NeuroImage, Vol. 33, No. 4. (December 2006), pp. 1104-1116.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Traditional inference in neuroimaging consists in describing brain activations elicited and modulated by different kinds of stimuli. Recently, however, paradigms have been studied in which the converse operation is performed, thus inferring behavioral or mental states associated with activation images. Here, we use the well-known retinotopy of the visual cortex to infer the visual content of real or imaginary scenes from the brain activation patterns that they elicit. We present two decoding algorithms: an explicit technique, based on the current knowledge of the retinotopic structure of the visual areas, and an implicit technique, based on supervised classifiers. Both algorithms predicted the stimulus identity with significant accuracy. Furthermore, we extend this principle to mental imagery data: in five data sets, our algorithms could reconstruct and predict with significant accuracy a pattern imagined by the subjects.</description>
    <dc:title>Inverse retinotopy: Inferring the visual content of images from brain activation patterns</dc:title>

    <dc:creator>Bertrand Thirion</dc:creator>
    <dc:creator>Edouard Duchesnay</dc:creator>
    <dc:creator>Edward Hubbard</dc:creator>
    <dc:creator>Jessica Dubois</dc:creator>
    <dc:creator>Jean-Baptiste Poline</dc:creator>
    <dc:creator>Denis Lebihan</dc:creator>
    <dc:creator>Stanislas Dehaene</dc:creator>
    <dc:identifier>doi:10.1016/j.neuroimage.2006.06.062</dc:identifier>
    <dc:source>NeuroImage, Vol. 33, No. 4. (December 2006), pp. 1104-1116.</dc:source>
    <dc:date>2008-01-31T22:58:38-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>NeuroImage</prism:publicationName>
    <prism:volume>33</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>1104</prism:startingPage>
    <prism:endingPage>1116</prism:endingPage>
    <prism:category>cogneuro-spring2008</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2142312">
    <title>Individual faces elicit distinct response patterns in human anterior temporal cortex</title>
    <link>http://www.citeulike.org/user/davclark/article/2142312</link>
    <description>&lt;i&gt;Proceedings of the National Academy of Sciences, Vol. 104, No. 51. (18 December 2007), pp. 20600-20605.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Visual face identification requires distinguishing between thousands of faces we know. This computational feat involves a network of brain regions including the fusiform face area (FFA) and anterior inferotemporal cortex (aIT), whose roles in the process are not well understood. Here, we provide the first demonstration that it is possible to discriminate cortical response patterns elicited by individual face images with high-resolution functional magnetic resonance imaging (fMRI). Response patterns elicited by the face images were distinct in aIT but not in the FFA. Individual-level face information is likely to be present in both regions, but our data suggest that it is more pronounced in aIT. One interpretation is that the FFA detects faces and engages aIT for identification. 10.1073/pnas.0705654104</description>
    <dc:title>Individual faces elicit distinct response patterns in human anterior temporal cortex</dc:title>

    <dc:creator>Nikolaus Kriegeskorte</dc:creator>
    <dc:creator>Elia Formisano</dc:creator>
    <dc:creator>Bettina Sorger</dc:creator>
    <dc:creator>Rainer Goebel</dc:creator>
    <dc:identifier>doi:10.1073/pnas.0705654104</dc:identifier>
    <dc:source>Proceedings of the National Academy of Sciences, Vol. 104, No. 51. (18 December 2007), pp. 20600-20605.</dc:source>
    <dc:date>2007-12-18T19:48:02-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Proceedings of the National Academy of Sciences</prism:publicationName>
    <prism:volume>104</prism:volume>
    <prism:number>51</prism:number>
    <prism:startingPage>20600</prism:startingPage>
    <prism:endingPage>20605</prism:endingPage>
    <prism:category>cogneuro-spring2008</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/davclark/article/2316795">
    <title>Neuronal Population Coding of Movement Direction</title>
    <link>http://www.citeulike.org/user/davclark/article/2316795</link>
    <description>&lt;i&gt;Science, Vol. 233, No. 4771. (26 September 1986), pp. 1416-1419.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Although individual neurons in the arm area of the primate motor cortex are only broadly tuned to a particular direction in three-dimensional space, the animal can very precisely control the movement of its arm. The direction of movement was found to be uniquely predicted by the action of a population of motor cortical neurons. When individual cells were represented as vectors that make weighted contributions along the axis of their preferred direction (according to changes in their activity during the movement under consideration) the resulting vector sum of all cell vectors (population vector) was in a direction congruent with the direction of movement. This population vector can be monitored during various tasks, and similar measures in other neuronal populations could be of heuristic value where there is a neural representation of variables with vectorial attributes.</description>
    <dc:title>Neuronal Population Coding of Movement Direction</dc:title>

    <dc:creator>Apostolos Georgopoulos</dc:creator>
    <dc:creator>Andrew Schwartz</dc:creator>
    <dc:creator>Ronald Kettner</dc:creator>
    <dc:source>Science, Vol. 233, No. 4771. (26 September 1986), pp. 1416-1419.</dc:source>
    <dc:date>2008-01-31T23:03:35-00:00</dc:date>
    <prism:publicationYear>1986</prism:publicationYear>
    <prism:publicationName>Science</prism:publicationName>
    <prism:volume>233</prism:volume>
    <prism:number>4771</prism:number>
    <prism:startingPage>1416</prism:startingPage>
    <prism:endingPage>1419</prism:endingPage>
    <prism:category>cogneuro-spring2008</prism:category>
</item>



</rdf:RDF>

