CiteULike: klouie's review

Cortical mechanisms of action selection: the affordance competition hypothesis

Paul Cisek — 2007-08-06T00:33:15-00:00

Philosophical Transactions of the Royal Society B: Biological Sciences

At every moment, the natural world presents animals with two fundamental pragmatic problems: selection between actions that are currently possible and specification of the parameters or metrics of those actions. It is commonly suggested that the brain addresses these by first constructing representations of the world on which to build knowledge and make a decision, and then by computing and executing an action plan. However, neurophysiological data argue against this serial viewpoint. In contrast, it is proposed here that the brain processes sensory information to specify, in parallel, several potential actions that are currently available. These potential actions compete against each other for further processing, while information is collected to bias this competition until a single response is selected. The hypothesis suggests that the dorsal visual system specifies actions which compete against each other within the fronto-parietal cortex, while a variety of biasing influences are provided by prefrontal regions and the basal ganglia. A computational model is described, which illustrates how this competition may take place in the cerebral cortex. Simulations of the model capture qualitative features of neurophysiological data and reproduce various behavioural phenomena.

Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.

R Bogacz — 2008-05-28T13:43:02-00:00

Philosophical transactions of the Royal Society of London. Series B, Biological sciences, Vol. 362, No. 1485. (29 September 2007), pp. 1655-1670.

The leaky competing accumulator (LCA) is a biologically inspired model of choice. It describes the processes of leaky accumulation and competition observed in neuronal populations during choice tasks and it accounts for reaction time distributions observed in psychophysical experiments. This paper discusses recent analyses and extensions of the LCA model. First, it reviews the dynamics and examines the conditions that make the model achieve optimal performance. Second, it shows that nonlinearities of the type present in biological neurons improve performance when the number of choice alternatives increases. Third, the model is extended to value-based choice, where it is shown that nonlinearities in the value function explain risk aversion in risky choice and preference reversals in choice between alternatives characterized across multiple dimensions.

Separate visual pathways for perception and action.

MA Goodale — 2007-05-15T21:29:09-00:00

Trends Neurosci, Vol. 15, No. 1. (January 1992), pp. 20-25.

Accumulating neuropsychological, electrophysiological and behavioural evidence suggests that the neural substrates of visual perception may be quite distinct from those underlying the visual control of actions. In other words, the set of object descriptions that permit identification and recognition may be computed independently of the set of descriptions that allow an observer to shape the hand appropriately to pick up an object. We propose that the ventral stream of projections from the striate cortex to the inferotemporal cortex plays the major role in the perceptual identification of objects, while the dorsal stream projecting from the striate cortex to the posterior parietal region mediates the required sensorimotor transformations for visually guided actions directed at such objects.

Models and Methods in Delay Discounting

Tesch — 2008-05-03T22:15:41-00:00

Annals of the New York Academy of Sciences, Vol. 1128, No. 1. (April 2008), pp. 90-94.

The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology

Morten Kringelbach — 2007-08-27T14:27:49-00:00

Progress in Neurobiology, Vol. 72, No. 5. (April 2004), pp. 341-372.

The human orbitofrontal cortex is an important brain region for the processing of rewards and punishments, which is a prerequisite for the complex and flexible emotional and social behaviour which contributes to the evolutionary success of humans. Yet much remains to be discovered about the functions of this key brain region, and new evidence from functional neuroimaging and clinical neuropsychology is affording new insights into the different functions of the human orbitofrontal cortex. We review the neuroanatomical and neuropsychological literature on the human orbitofrontal cortex, and propose two distinct trends of neural activity based on a meta-analysis of neuroimaging studies. One is a mediolateral distinction, whereby medial orbitofrontal cortex activity is related to monitoring the reward value of many different reinforcers, whereas lateral orbitofrontal cortex activity is related to the evaluation of punishers which may lead to a change in ongoing behaviour. The second is a posterior-anterior distinction with more complex or abstract reinforcers (such as monetary gain and loss) represented more anteriorly in the orbitofrontal cortex than simpler reinforcers such as taste or pain. Finally, we propose new neuroimaging methods for obtaining further evidence on the localisation of function in the human orbitofrontal cortex.

The prefrontal cortex: categories, concepts and cognition.

EK Miller — 2008-05-12T02:59:57-00:00

Philosophical transactions of the Royal Society of London. Series B, Biological sciences, Vol. 357, No. 1424. (29 August 2002), pp. 1123-1136.

The ability to generalize behaviour-guiding principles and concepts from experience is key to intelligent, goal-directed behaviour. It allows us to deal efficiently with a complex world and to adapt readily to novel situations. We review evidence that the prefrontal cortex-the cortical area that reaches its greatest elaboration in primates-plays a central part in acquiring and representing this information. The prefrontal cortex receives highly processed information from all major forebrain systems, and neurophysiological studies suggest that it synthesizes this into representations of learned task contingencies, concepts and task rules. In short, the prefrontal cortex seems to underlie our internal representations of the 'rules of the game'. This may provide the necessary foundation for the complex behaviour of primates, in whom this structure is most elaborate.

An integrative theory of prefrontal cortex function.

EK Miller — 2006-01-23T23:03:09-00:00

Annu Rev Neurosci, Vol. 24 (2001), pp. 167-202.

The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task. We review neurophysiological, neurobiological, neuroimaging, and computational studies that support this theory and discuss its implications as well as further issues to be addressed

The prefrontal cortex and cognitive control.

EK Miller — 2006-01-20T19:33:26-00:00

Nat Rev Neurosci, Vol. 1, No. 1. (October 2000), pp. 59-65.

One of the enduring mysteries of brain function concerns the process of cognitive control. How does complex and seemingly willful behaviour emerge from interactions between millions of neurons? This has long been suspected to depend on the prefrontal cortex--the neocortex at the anterior end of the brain--but now we are beginning to uncover its neural basis. Nearly all intended behaviour is learned and so depends on a cognitive system that can acquire and implement the 'rules of the game' needed to achieve a given goal in a given situation. Studies indicate that the prefrontal cortex is central in this process. It provides an infrastructure for synthesizing a diverse range of information that lays the foundation for the complex forms of behaviour observed in primates.

The prefrontal cortex: complex neural properties for complex behavior.

EK Miller — 2008-05-12T02:52:22-00:00

Neuron, Vol. 22, No. 1. (January 1999), pp. 15-17.

Architecture of the prefrontal cortex and the central executive.

PS Goldman-Rakic — 2008-05-12T02:51:09-00:00

Annals of the New York Academy of Sciences, Vol. 769 (15 December 1995), pp. 71-83.

Orbitofrontal Cortex and Its Contribution to Decision-Making.

Jonathan D Wallis — 2007-05-04T15:29:59-00:00

Annu Rev Neurosci (6 April 2007)

Damage to orbitofrontal cortex (OFC) produces an unusual pattern of deficits. Patients have intact cognitive abilities but are impaired in making everyday decisions. Here we review anatomical, neuropsychological, and neurophysiological evidence to determine the neuronal mechanisms that might underlie these impairments. We suggest that OFC plays a key role in processing reward: It integrates multiple sources of information regarding the reward outcome to derive a value signal. In effect, OFC calculates how rewarding a reward is. This value signal can then be held in working memory where it can be used by lateral prefrontal cortex to plan and organize behavior toward obtaining the outcome, and by medial prefrontal cortex to evaluate the overall action in terms of its success and the effort that was required. Thus, acting together, these prefrontal areas can ensure that our behavior is most efficiently directed towards satisfying our needs. Expected online publication date for the Annual Review of Neuroscience Volume 30 is June 16, 2007. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

What We Know and Do Not Know about the Functions of the Orbitofrontal Cortex after 20 Years of Cross-Species Studies

Elisabeth Murray — 2007-08-03T09:13:20-00:00

J. Neurosci., Vol. 27, No. 31. (1 August 2007), pp. 8166-8169.

When Pat Goldman-Rakic described the circuitry and function of primate prefrontal cortex in her influential 1987 monograph (Goldman-Rakic, 1987), she included only a few short paragraphs on the orbitofrontal cortex (OFC). That year, there were only nine papers published containing the term "orbitofrontal," an average of less than one paper per month. Twenty years later, this rate has increased to 32 papers per month. This explosive growth is partly attributable to the remarkable similarities that exist in structure and function across species. These similarities suggest that OFC function can be usefully modeled in nonhuman and even nonprimate species. Here, we review some of these similarities. 10.1523/JNEUROSCI.1556-07.2007

Functional Specialization of the Primate Frontal Cortex during Decision Making

Daeyeol Lee — 2007-08-03T09:16:35-00:00

J. Neurosci., Vol. 27, No. 31. (1 August 2007), pp. 8170-8173.

Economic theories of decision making are based on the principle of utility maximization, and reinforcement-learning theory provides computational algorithms that can be used to estimate the overall reward expected from alternative choices. These formal models not only account for a large range of behavioral observations in human and animal decision makers, but also provide useful tools for investigating the neural basis of decision making. Nevertheless, in reality, decision makers must combine different types of information about the costs and benefits associated with each available option, such as the quality and quantity of expected reward and required work. In this article, we put forward the hypothesis that different subdivisions of the primate frontal cortex may be specialized to focus on different aspects of dynamic decision-making processes. In this hypothesis, the lateral prefrontal cortex is primarily involved in maintaining the state representation necessary to identify optimal actions in a given environment. In contrast, the orbitofrontal cortex and the anterior cingulate cortex might be primarily involved in encoding and updating the utilities associated with different sensory stimuli and alternative actions, respectively. These cortical areas are also likely to contribute to decision making in a social context. 10.1523/JNEUROSCI.1561-07.2007

Specialized elements of orbitofrontal cortex in primates.

H Barbas — 2008-05-12T02:41:34-00:00

Annals of the New York Academy of Sciences, Vol. 1121 (December 2007), pp. 10-32.

The orbitofrontal cortex is associated with encoding the significance of stimuli within an emotional context, and its connections can be understood in this light. This large cortical region is architectonically heterogeneous, but its connections and functions can be summarized by a broad grouping of areas by cortical type into posterior and anterior sectors. The posterior (limbic) orbitofrontal region is composed of agranular and dysgranular-type cortices and has unique connections with primary olfactory areas and rich connections with high-order sensory association cortices. Posterior orbitofrontal areas are further distinguished by dense and distinct patterns of connections with the amygdala and memory-related anterior temporal lobe structures that may convey signals about emotional import and their memory. The special sets of connections suggest that the posterior orbitofrontal cortex is the primary region for the perception of emotions. In contrast to orbitofrontal areas, posterior medial prefrontal areas in the anterior cingulate are not multi-modal, but have strong connections with auditory association cortices, brain stem vocalization, and autonomic structures, in pathways that may mediate emotional communication and autonomic activation in emotional arousal. Posterior orbitofrontal areas communicate with anterior orbitofrontal areas and, through feedback projections, with lateral prefrontal and other cortices, suggesting a sequence of information processing for emotions. Pathology in orbitofrontal cortex may remove feedback input to sensory cortices, dissociating emotional context from sensory content and impairing the ability to interpret events.

Definition of the orbital cortex in relation to specific connections with limbic and visceral structures and other cortical regions.

JL Price — 2008-05-12T02:40:16-00:00

Annals of the New York Academy of Sciences, Vol. 1121 (December 2007), pp. 54-71.

The orbitofrontal cortex is often defined topographically as the cortex on the ventral surface of the frontal lobe. Unfortunately, this definition is not consistently used, and it obscures distinct connectional and functional systems within the orbital cortex. It is difficult to interpret data on the orbital cortex that do not take these different systems into account. Analysis of cortico-cortical connections between areas in the orbital and medial prefrontal cortex indicate two distinct networks in this region. One system, called the orbital network, involves most of the areas in the central orbital cortex. The other system, has been called the medial prefrontal network, though it is actually more complex, since it includes areas on the medial wall, in the medial orbital cortex, and in the posterolateral orbital cortex. Some areas in the medial orbital cortex are involved in both networks. Connections to other brain areas support the distinction between the networks. The orbital network receives several sensory inputs, from olfactory cortex, taste cortex, somatic sensory association cortex, and visual association cortex, and is connected with multisensory areas in the ventrolateral prefrontal cortex and perirhinal cortex. The medial network has outputs to the hypothalamus and brain stem and connects to a cortical circuit that includes the rostral part of the superior temporal gyrus and dorsal bank of the superior temporal sulcus, the cingulate and retrosplenial cortex, the entorhinal and posterior parahippocampal cortex, and the dorsomedial prefrontal cortex.

Neuroeconomics.

George Loewenstein — 2007-11-15T13:58:41-00:00

Annu Rev Psychol (17 September 2007)

blacksquare, square, filled Abstract Neuroeconomics has further bridged the once disparate fields of economics and psychology. Such convergence is almost exclusively attributable to changes within economics. Neuroeconomics has inspired more change within economics than within psychology because the most important findings in neuroeconomics have posed more of a challenge to the standard economic perspective. Neuroeconomics has primarily challenged the standard economic assumption that decision making is a unitary process-a simple matter of integrated and coherent utility maximization-suggesting instead that it is driven by the interaction between automatic and controlled processes. This article reviews neuroeconomic research in three domains of interest to both economists and psychologists: decision making under risk and uncertainty, intertemporal choice, and social decision making. In addition to reviewing new economic models inspired by this research, we also discuss how neuroeconomics may influence future work in psychology. Expected final online publication date for the Annual Review of Psychology Volume 59 is November 30, 2007. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

Neuroeconomics: cardinal utility in the orbitofrontal cortex?

V Stuphorn — 2006-09-12T18:59:31-00:00

Curr Biol, Vol. 16, No. 15. (8 August 2006)

Modern economics no longer uses the concept of cardinal utility, which describes the value of a good independently of a comparison with another good. New electrophysiological recordings in primates performing economic choices suggest a neurological substrate for cardinal utility, a finding that economists should perhaps take note of.

Feature-based attention in visual cortex.

JH Maunsell — 2007-03-01T17:52:53-00:00

Trends Neurosci, Vol. 29, No. 6. (June 2006), pp. 317-322.

Although most studies of visual attention have examined the effects of shifting attention between different locations in the visual field, attention can also be directed to particular visual features, such as a color, orientation or a direction of motion. Single-unit studies have shown that attention to a feature modulates neuronal signals in a range of areas in monkey visual cortex. The location-independent property of feature-based attention makes it particularly well suited to modify selectively the neural representations of stimuli or parts within complex visual scenes that match the currently attended feature. This review is part of the TINS special issue on The Neural Substrates of Cognition.

Orienting of attention.

MI Posner — 2007-05-15T22:44:46-00:00

Q J Exp Psychol, Vol. 32, No. 1. (February 1980), pp. 3-25.

Visual attention: control, representation, and time course.

HE Egeth — 2005-07-25T15:11:00-00:00

Annu Rev Psychol, Vol. 48 (1997), pp. 269-297.

Three central problems in the recent literature on visual attention are reviewed. The first concerns the control of attention by top-down (or goal-directed) and bottom-up (or stimulus-driven) processes. The second concerns the representational basis for visual selection, including how much attention can be said to be location- or object-based. Finally, we consider the time course of attention as it is directed to one stimulus after another.

Neural mechanisms of selective visual attention.

R Desimone — 2006-07-25T19:54:27-00:00

Annu Rev Neurosci, Vol. 18 (1995), pp. 193-222.

Fundamental Components of Attention.

Eric I Knudsen — 2007-06-19T12:19:53-00:00

Annu Rev Neurosci (6 April 2007)

A mechanistic understanding of attention is necessary for the elucidation of the neurobiological basis of conscious experience. This chapter presents a framework for thinking about attention that facilitates the analysis of this cognitive process in terms of underlying neural mechanisms. Four processes are fundamental to attention: working memory, top-down sensitivity control, competitive selection, and automatic bottom-up filtering for salient stimuli. Each process makes a distinct and essential contribution to attention. Voluntary control of attention involves the first three processes (working memory, top-down sensitivity control, and competitive selection) operating in a recurrent loop. Recent results from neurobiological research on attention are discussed within this framework. Expected online publication date for the Annual Review of Neuroscience Volume 30 is June 16, 2007. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

Glucosamine in osteoarthritis: questions remain.

CJ Lozada — 2008-04-21T13:54:31-00:00

Cleveland Clinic journal of medicine, Vol. 74, No. 1. (January 2007), pp. 65-71.

Glucosamine is now widely used in the hope that it will relieve symptoms of osteoarthritis and stop its progression, yet studies have so far failed to prove convincingly that it works, how it might work, or whether it is safe to take long-term. This is an overview of the evidence to date for currently available glucosamine preparations, as well as for glucosamine used in combination with another popular nutraceutical, chondroitin sulfate.

Socially biased learning in monkeys.

D Fragaszy — 2008-03-28T15:26:48-00:00

Learn Behav, Vol. 32, No. 1. (February 2004), pp. 24-35.

We review socially biased learning about food and problem solving in monkeys, relying especially on studies with tufted capuchin monkeys (Cebus apella) and callitrichid monkeys. Capuchin monkeys most effectively learn to solve a new problem when they can act jointly with an experienced partner in a socially tolerant setting and when the problem can be solved by direct action on an object or substrate, but they do not learn by imitation. Capuchin monkeys are motivated to eat foods, whether familiar or novel, when they are with others that are eating, regardless of what the others are eating. Thus, social bias in learning about foods is indirect and mediated by facilitation of feeding. In most respects, social biases in learning are similar in capuchins and callitrichids, except that callitrichids provide more specific behavioral cues to others about the availability and palatability of foods. Callitrichids generally are more tolerant toward group members and coordinate their activity in space and time more closely than capuchins do. These characteristics support stronger social biases in learning in callitrichids than in capuchins in some situations. On the other hand, callitrichids' more limited range of manipulative behaviors, greater neophobia, and greater sensitivity to the risk of predation restricts what these monkeys learn in comparison with capuchins. We suggest that socially biased learning is always the collective outcome of interacting physical, social, and individual factors, and that differences across populations and species in social bias in learning reflect variations in all these dimensions. Progress in understanding socially biased learning in nonhuman species will be aided by the development of appropriately detailed models of the richly interconnected processes affecting learning.

Inhibition, Spike Threshold, and Stimulus Selectivity in Primary Visual Cortex

Nicholas Priebe — 2008-02-28T13:45:14-00:00

Neuron, Vol. 57, No. 4. (28 February 2008), pp. 482-497.

Ever since Hubel and Wiesel described orientation selectivity in the visual cortex, the question of how precise selectivity emerges has been marked by considerable debate. There are essentially two views of how selectivity arises. Feed-forward models rely entirely on the organization of thalamocortical inputs. Feedback models rely on lateral inhibition to refine selectivity relative to a weak bias provided by thalamocortical inputs. The debate is driven by two divergent lines of evidence. On the one hand, many response properties appear to require lateral inhibition, including precise orientation and direction selectivity and crossorientation suppression. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. Here we demonstrate a resolution to this paradox. Feed-forward models incorporating the intrinsic nonlinear properties of cortical neurons and feed-forward circuits (i.e., spike threshold, contrast saturation, and spike-rate rectification) can account for properties that have previously appeared to require lateral inhibition.

Developmental regulation of cognitive abilities: modified composition of a molecular switch turns on associative learning.

TC Dumas — 2008-01-28T03:13:41-00:00

Prog Neurobiol, Vol. 76, No. 3. (June 2005), pp. 189-211.

N-methyl-D-aspartate receptors (NMDARs) act as molecular coincidence detectors and allow for association or dissociation between pre- and postsynaptic neurons. NMDA receptors are central to remodeling of synaptic connections during postnatal development and associative learning abilities in adults. The ability to remodel neural networks is altered during postnatal development, possibly due to a change in the composition of NMDARs. That is, as forebrain systems (and cerebellum) develop, synaptic NR2B-containing NMDARs (NR2B-NMDARs) are replaced by NR2A-containing NMDARs (NR2A-NMDARs) and NR2B-NMDARs move to extrasynaptic sites. During the initial phase of the switch, synapses contain both NR2A- and NR2B-NMDARs and both long-term potentiation and long-term depression are enhanced. As NMDAR subunit expression decreases and NR2A-NMDARs come to predominate in the synapse, channel function and synaptic plasticity are reduced, and remodeling ability dissipates. The end result is a balance of plasticity and stability that is optimal for information processing and storage. Associative learning abilities involving different sensory modalities emerge sequentially, in accordance with synaptic maturation in related cortical and underlying brain structures. Thus, developmental alterations in NMDAR composition that occur at different ages in various brain structures may explain the protracted nature of the maturation of various associative learning abilities.

Calorie restriction in nonhuman primates: assessing effects on brain and behavioral aging.

DK Ingram — 2008-01-26T16:13:38-00:00

Neuroscience, Vol. 145, No. 4. (14 April 2007), pp. 1359-1364.

Dietary caloric restriction (CR) is the only intervention repeatedly demonstrated to retard the onset and incidence of age-related diseases, maintain function, and extend both lifespan and health span in mammals, including brain and behavioral function. In 70 years of study, such beneficial effects have been demonstrated in rodents and lower animals. Recent results emerging from ongoing studies of CR in humans and nonhuman primates suggest that many of the same anti-disease and anti-aging benefits observed in rodent studies may be applicable to long-lived species. Results of studies in rhesus monkeys indicate that CR animals (30% less than controls) are healthier than fully-fed counterparts based on reduced incidence of various diseases, exhibit significantly better indices of predisposition to disease and may be aging at a slower rate based on analysis of selected indices of aging. The current review discusses approaches taken in studies of rhesus monkeys to analyze age-related changes in brain and behavioral function and the impact of CR on these changes. Approaches include analyses of gross and fine locomotor performance as well as brain imaging. In a related study it was observed that short-term CR (6 months) in adult rhesus monkeys can provide protection against a neurotoxic insult. Increasing interest in the CR paradigm will expand its role in demonstrating how nutrition can modulate the rate of aging and the mechanisms responsible for this modulation.

Energy intake, meal frequency, and health: a neurobiological perspective.

MP Mattson — 2007-02-06T02:53:51-00:00

Annu Rev Nutr, Vol. 25 (2005), pp. 237-260.

The size and frequency of meals are fundamental aspects of nutrition that can have profound effects on the health and longevity of laboratory animals. In humans, excessive energy intake is associated with increased incidence of cardiovascular disease, diabetes, and certain cancers and is a major cause of disability and death in industrialized countries. On the other hand, the influence of meal frequency on human health and longevity is unclear. Both caloric (energy) restriction (CR) and reduced meal frequency/intermittent fasting can suppress the development of various diseases and can increase life span in rodents by mechanisms involving reduced oxidative damage and increased stress resistance. Many of the beneficial effects of CR and fasting appear to be mediated by the nervous system. For example, intermittent fasting results in increased production of brain-derived neurotrophic factor (BDNF), which increases the resistance of neurons in the brain to dysfunction and degeneration in animal models of neurodegenerative disorders; BDNF signaling may also mediate beneficial effects of intermittent fasting on glucose regulation and cardiovascular function. A better understanding of the neurobiological mechanisms by which meal size and frequency affect human health may lead to novel approaches for disease prevention and treatment.

Seminars in medicine of the Beth Israel Deaconess Medical Center. Caloric intake and aging.

R Weindruch — 2008-01-25T20:20:43-00:00

N Engl J Med, Vol. 337, No. 14. (2 October 1997), pp. 986-994.

Alternate-day fasting and chronic disease prevention: a review of human and animal trials.

KA Varady — 2007-08-23T15:51:51-00:00

Am J Clin Nutr, Vol. 86, No. 1. (July 2007), pp. 7-13.

Calorie restriction (CR) and alternate-day fasting (ADF) represent 2 different forms of dietary restriction. Although the effects of CR on chronic disease prevention were reviewed previously, the effects of ADF on chronic disease risk have yet to be summarized. Accordingly, we review here animal and human evidence concerning ADF and the risk of certain chronic diseases, such as type 2 diabetes, cardiovascular disease, and cancer. We also compare the magnitude of risk reduction resulting from ADF with that resulting from CR. In terms of diabetes risk, animal studies of ADF find lower diabetes incidence and lower fasting glucose and insulin concentrations, effects that are comparable to those of CR. Human trials to date have reported greater insulin-mediated glucose uptake but no effect on fasting glucose or insulin concentrations. In terms of cardiovascular disease risk, animal ADF data show lower total cholesterol and triacylglycerol concentrations, a lower heart rate, improved cardiac response to myocardial infarction, and lower blood pressure. The limited human evidence suggests higher HDL-cholesterol concentrations and lower triacylglycerol concentrations but no effect on blood pressure. In terms of cancer risk, there is no human evidence to date, yet animal studies found decreases in lymphoma incidence, longer survival after tumor inoculation, and lower rates of proliferation of several cell types. The findings in animals suggest that ADF may effectively modulate several risk factors, thereby preventing chronic disease, and that ADF may modulate disease risk to an extent similar to that of CR. More research is required to establish definitively the consequences of ADF.

Neural correlates of attention in primate visual cortex.

S Treue — 2008-01-07T19:13:10-00:00

Trends Neurosci, Vol. 24, No. 5. (May 2001), pp. 295-300.

The processing of visual information combines bottom-up sensory aspects with top-down influences, most notably attentional processes. Attentional influences have now been demonstrated throughout visual cortex, and their influence on the processing of visual information is profound. Neuronal responses to attended locations or stimulus features are enhanced, whereas those from unattended locations or features are suppressed. This influence of attention increases as one ascends the hierarchy of visual areas in primate cortex, ultimately resulting in a neural representation of the visual world that is dominated by the behavioral relevance of the information, rather than designed to provide an accurate and complete description of it. This realization has led to a rethinking of the role of areas that have previously been considered to be "purely sensory".

Understanding Neural Coding through the Model-Based Analysis of Decision Making

Greg Corrado — 2007-08-03T09:38:54-00:00

J. Neurosci., Vol. 27, No. 31. (1 August 2007), pp. 8178-8180.

The study of decision making poses new methodological challenges for systems neuroscience. Whereas our traditional approach linked neural activity to external variables that the experimenter directly observed and manipulated, many of the key elements that contribute to decisions are internal to the decider. Variables such as subjective value or subjective probability may be influenced by experimental conditions and manipulations but can neither be directly measured nor precisely controlled. Pioneering work on the neural basis of decision circumvented this difficulty by studying behavior in static conditions, in which knowledge of the average state of these quantities was sufficient. More recently, a new wave of studies has confronted the conundrum of internal decision variables more directly by leveraging quantitative behavioral models. When these behavioral models are successful in predicting a subject's choice, the model's internal variables may serve as proxies for the unobservable decision variables that actually drive behavior. This new methodology has allowed researchers to localize neural subsystems that encode hidden decision variables related to free choice and to study these variables under dynamic conditions. 10.1523/JNEUROSCI.1590-07.2007

Mapping the matrix: the ways of neocortex.

RJ Douglas — 2007-11-05T15:52:30-00:00

Neuron, Vol. 56, No. 2. (25 October 2007), pp. 226-238.

While we know that the neocortex occupies 85% of our brains and that its circuits allow an enormous flexibility and repertoire of behavior (not to mention unexplained phenomena like consciousness), a century after Cajal we have very little knowledge of the details of the cortical circuits or their mode of function. One simplifying hypothesis that has existed since Cajal is that the neocortex consists of repeated copies of the same fundamental circuit. However, finding that fundamental circuit has proved elusive, although partial drafts of a "canonical circuit" appear in many different guises of structure and function. Here, we review some critical stages in the history of this quest. In doing so, we consider the style of cortical computation in relation to the neuronal machinery that supports it. We conclude that the structure and function of cortex honors two major computational principles: "just-enough" and "just-in-time."

Recurrent neuronal circuits in the neocortex.

RJ Douglas — 2007-12-20T22:08:47-00:00

Curr Biol, Vol. 17, No. 13. (3 July 2007)

Neuronal circuits of the neocortex.

RJ Douglas — 2007-12-20T21:48:20-00:00

Annu Rev Neurosci, Vol. 27 (2004), pp. 419-451.

We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.

Nonlinear neural networks: Principles, mechanisms, and architectures

S Grossberg — 2007-12-07T21:50:42-00:00

Neural Networks, Vol. 1, No. 1. (1988), pp. 17-61.

An historical discussion is provided of the intellectual trends that caused nineteenth century interdisciplinary studies of physics and psychobiology by leading scientists such as Helmholtz, Maxwell, and Mach to splinter into separate twentieth-century scientific movements. The nonlinear, nonstationary, and nonlocal nature of behavioral and brain data are emphasized. Three sources of contemporary neural network research - the binary, linear, and continuous-nonlinear models - are noted. The remainder of the article describes results about continuous-nonlinear models.

Small-world brain networks.

DS Bassett — 2007-10-04T14:24:38-00:00

Neuroscientist, Vol. 12, No. 6. (December 2006), pp. 512-523.

Many complex networks have a small-world topology characterized by dense local clustering or cliquishness of connections between neighboring nodes yet a short path length between any (distant) pair of nodes due to the existence of relatively few long-range connections. This is an attractive model for the organization of brain anatomical and functional networks because a small-world topology can support both segregated/specialized and distributed/integrated information processing. Moreover, small-world networks are economical, tending to minimize wiring costs while supporting high dynamical complexity. The authors introduce some of the key mathematical concepts in graph theory required for small-world analysis and review how these methods have been applied to quantification of cortical connectivity matrices derived from anatomical tract-tracing studies in the macaque monkey and the cat. The evolution of small-world networks is discussed in terms of a selection pressure to deliver cost-effective information-processing systems. The authors illustrate how these techniques and concepts are increasingly being applied to the analysis of human brain functional networks derived from electroencephalography/magnetoencephalography and fMRI experiments. Finally, the authors consider the relevance of small-world models for understanding the emergence of complex behaviors and the resilience of brain systems to pathological attack by disease or aberrant development. They conclude that small-world models provide a powerful and versatile approach to understanding the structure and function of human brain systems.

Metastability, criticality and phase transitions in brain and its models

Gerhard Werner — 2007-09-29T08:11:41-00:00

Biosystems, Vol. 90, No. 2. ( 2007), pp. 496-508.

This survey of experimental findings and theoretical insights of the past 25 years places the brain firmly into the conceptual framework of nonlinear dynamics, operating at the brink of criticality, which is achieved and maintained by self-organization. It is here the basis for proposing that the application of the twin concepts of scaling and universality of the theory of non-equilibrium phase transitions can serve as an informative approach for elucidating the nature of underlying neural-mechanisms, with emphasis on the dynamics of recursively reentrant activity flow in intracortical and cortico-subcortical neuronal loops.

Do We Know What the Early Visual System Does?

Matteo Carandini — 2005-12-07T18:11:14-00:00

J. Neurosci., Vol. 25, No. 46. (16 November 2005), pp. 10577-10597.

We can claim that we know what the visual system does once we can predict neural responses to arbitrary stimuli, including those seen in nature. In the early visual system, models based on one or more linear receptive fields hold promise to achieve this goal as long as the models include nonlinear mechanisms that control responsiveness, based on stimulus context and history, and take into account the nonlinearity of spike generation. These linear and nonlinear mechanisms might be the only essential determinants of the response, or alternatively, there may be additional fundamental determinants yet to be identified. Research is progressing with the goals of defining a single "standard model" for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes. These predictive models represent, at a given stage of the visual pathway, a compact description of visual computation. They would be an invaluable guide for understanding the underlying biophysical and anatomical mechanisms and relating neural responses to visual perception.

Beating a dead horse: Dopamine and Parkinson disease

Eric Ahlskog — 2007-11-20T23:05:30-00:00

Neurology, Vol. 69, No. 17. (23 October 2007), pp. 1701-1711.

Our collective thinking about Parkinson disease (PD) has been heavily influenced by the dramatic response to dopamine replacement therapy. For progress to continue, however, we need to take a broad view of this disorder, which includes recognition of the following. First, substantial evidence now indicates that dopamine oxidation is unlikely to substantially contribute to the pathogenesis of PD. Second, levodopa therapy is not associated with neurotoxicity. Third, the first neurons affected in PD are nondopaminergic; the substantia nigra and other dopaminergic nuclei are affected only later in the course. Thus, PD is much more than degeneration of the dopaminergic nigrostriatal system. Fourth, in the current era, most of the disability of advancing PD is from involvement of nondopaminergic systems, including levodopa-refractory motor symptoms, dementia, and dysautonomia. Motor complications associated with levodopa therapy can be problematic, but they can be controlled in most, using available medications and deep brain stimulation surgery. We have reached the point of diminishing therapeutic returns with drugs acting on dopamine systems; more dopaminergic medications will provide only modest incremental benefit over current therapies. Finally, the benefits from transplantation surgeries aimed at restoring dopaminergic neurotransmission will be limited because later-stage PD disability comes from nondopaminergic substrates. GLOSSARY: CDS = continuous dopaminergic stimulation; DBS = deep brain stimulation; GABAergic = gamma-aminobutyric acidmediated; MPTP = 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine; PD = Parkinson disease; STN = subthalamic nucleus; UPDRS = Unified Parkinson's Disease Rating Scale. 10.1212/01.wnl.0000296942.14309.4a

From Thought to Action: The Parietal Cortex as a Bridge between Perception, Action, and Cognition

Jacqueline Gottlieb — 2007-01-11T19:27:59-00:00

Neuron, Vol. 53, No. 1. (4 January 2007), pp. 9-16.

The lateral intraparietal area (LIP) is a subdivision of the inferior parietal lobe that has been implicated in the guidance of spatial attention. In a variety of tasks, LIP provides a "salience representation" of the external world--a topographic visual representation that encodes the locations of salient or behaviorally relevant objects. Recent neurophysiological experiments show that this salience representation incorporates information about multiple behavioral variables--such as a specific motor response, reward, or category membership--associated with the task-relevant object. This integration occurs in a wide variety of tasks, including those requiring eye or limb movements or goal-directed or nontargeting operant responses. Thus, LIP acts as a multifaceted behavioral integrator that binds visuospatial, motor, and cognitive information into a topographically organized signal of behavioral salience. By specifying attentional priority as a synthesis of multiple task demands, LIP operates at the interface of perception, action, and cognition.

Extending the Bounds of Rationality: Evidence and Theories of Preferential Choice

Jorg Rieskamp — 2007-09-25T21:30:40-00:00

pp. 631-661.

Most economists define rationality in terms of consistency principles. These principles place "bounds" on rationality—bounds that range from perfect consistency to weak stochastic transitivity. Several decades of research on preferential choice has demonstrated how and when people violate these bounds. Many of these violations are interconnected and reflect systematic behavioral principles. We discuss the robustness of the violations and review the theories that are able to predict them. We further discuss the adaptive functions of the violations. From this perspective, choices do more than reveal preferences; they also reflect subtle, yet often quite reasonable, dependencies on the environment.

Anomalies: Intertemporal Choice

George Loewenstein — 2007-09-24T21:19:41-00:00

The Journal of Economic Perspectives, Vol. 3, No. 4. (1989), pp. 181-193.

The choice axiom after twenty years

Duncan Luce — 2007-09-21T12:34:26-00:00

Journal of Mathematical Psychology, Vol. 15, No. 3. (June 1977), pp. 215-233.

How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science

Gary King — 2006-08-28T16:22:01-00:00

American Journal of Political Science, Vol. 30, No. 3. (1986), pp. 666-687.

This article identifies a set of serious theoretical mistakes appearing with troublingly high frequency throughout the quantitative political science literature. These mistakes are all based on faulty statistical theory or on erroneous statistical analysis. Through algebraic and interpretive proofs, some of the most commonly made mistakes are explicated and illustrated. The theoretical problem underlying each is highlighted, and suggested solutions are provided throughout. It is argued that closer attention to these problems and solutions will result in more reliable quantitative analyses and more useful theoretical contributions

Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians.

J Carpenter — 2007-07-20T21:23:47-00:00

Stat Med, Vol. 19, No. 9. (15 May 2000), pp. 1141-1164.

Since the early 1980s, a bewildering array of methods for constructing bootstrap confidence intervals have been proposed. In this article, we address the following questions. First, when should bootstrap confidence intervals be used. Secondly, which method should be chosen, and thirdly, how should it be implemented. In order to do this, we review the common algorithms for resampling and methods for constructing bootstrap confidence intervals, together with some less well known ones, highlighting their strengths and weaknesses. We then present a simulation study, a flow chart for choosing an appropriate method and a survival analysis example.

Decisions, decisions, decisions: choosing a biological science of choice.

P Glimcher — 2007-07-20T18:44:53-00:00

Neuron, Vol. 36, No. 2. (10 October 2002), pp. 323-332.

Behavioral ecologists argue that evolution drives animal behavior to efficiently solve the problems animals face in their environmental niches. The ultimate evolutionary causes of decision making, they contend, can be found in economic analyses of organisms and their environments. Neurobiologists interested in how animals make decisions have, in contrast, focused their efforts on understanding the neurobiological hardware that serves as a more proximal cause of that same behavior. Describing the flow of information within the nervous system without regard to these larger goals has been their focus. Recent work in a number of laboratories has begun to suggest that these two approaches are beginning to fuse. It may soon be possible to view the nervous system as a representational process that solves the mathematically defined economic problems animals face by making efficient decisions. These developments in the neurobiological theory of choice, and the new schema they imply, form the subject of this article.

Translational principles of deep brain stimulation

Morten Kringelbach — 2007-07-20T18:29:33-00:00

Nat Rev Neurosci, Vol. 8, No. 8. (2007), pp. 623-635.

Bootstrap Confidence Intervals

Thomas Diciccio — 2007-07-10T18:08:56-00:00

Statistical Science, Vol. 11, No. 3. (1996), pp. 189-212.

This article surveys bootstrap methods for producing good approximate confidence intervals. The goal is to improve by an order of magnitude upon the accuracy of the standard intervals $θ ± z^(α) σ)$, în â wây thât âllôws rôûtînê âpplîcâtîôn êvên tô vêry cômplîcâtêd prôblêms. Bôth thêôry ând êxâmplês ârê ûsêd tô shôw hôw thîs îs dônê. Thê fîrst sêvên sêctîôns prôvîdê â hêûrîstîc ôvêrvîêw ôf fôûr bôôtstrâp cônfîdêncê întêrvâl prôcêdûrês: $BC_â$, bôôtstrâp-$t$, ÂBC ând câlîbrâtîôn. Sêctîôns 8 ând 9 dêscrîbê thê thêôry bêhînd thêsê mêthôds, ând thêîr clôsê cônnêctîôn wîth thê lîkêlîhôôd-bâsêd cônfîdêncê întêrvâl thêôry dêvêlôpêd by Bârndôrff-Nîêlsên, Côx ând Rêîd ând ôthêrs.

Better Bootstrap Confidence Intervals

Bradley Efron — 2007-07-09T20:25:03-00:00

Journal of the American Statistical Association, Vol. 82, No. 397. (1987), pp. 171-185.