CiteULike: awooga's calcium

Functional Significance of Long-Term Potentiation for Sequence Learning and Prediction

Abbott — 2008-03-28T10:43:33-00:00

Cereb. Cortex, Vol. 6, No. 3. (1 May 1996), pp. 406-416.

Population coding, where neurons with broad and overlapping firing rate tuning curves collectively encode information about a stimulus, is a common feature of sensory systems. We use decoding methods and measured properties of NMDA-mediated LTP induction to study the impact of long-term potentiation of synapses between the neurons of such a coding array. We find that, due to a temporal asymmetry in the induction of NMDA-mediated LTP, firing patterns in a neuronal array that initially represent the current value of a sensory input will, after training, provide an experienced-based prediction of that input instead. We compute how this prediction arises from and depends on the training experience. We also show how the encoded prediction can be used to generate learned motor sequences, such as the movement of a limb. This involves a novel form of memory recall that is driven by the motor response so that it automatically generates new information at a rate appropriate for the task being performed. 10.1093/cercor/6.3.406

Spike timing, calcium signals and synaptic plasticity

Per Sjostrom — 2008-03-19T11:19:32-00:00

Current Opinion in Neurobiology, Vol. 12, No. 3. (1 June 2002), pp. 305-314.

Plasticity at central synapses depends critically on the timing of presynaptic and postsynaptic action potentials. Key initial steps in synaptic plasticity involve the back-propagation of action potentials into the dendritic tree and calcium influx that depends nonlinearly on the action potential and synaptic input. These initial steps are now better understood. In addition, recent studies of processes as diverse as gene expression and channel inactivation suggest that responses to calcium transients depend not only their amplitude, but on their time course and on the location of their origin.

Transient Calcium and Dopamine Increase PKA Activity and DARPP-32 Phosphorylation

Maria Lindskog — 2007-08-24T16:10:11-00:00

PLoS Computational Biology, Vol. 2, No. 9. (1 September 2006), e119.

Reinforcement learning theorizes that strengthening of synaptic connections in medium spiny neurons of the striatum occurs when glutamatergic input (from cortex) and dopaminergic input (from substantia nigra) are received simultaneously. Subsequent to learning, medium spiny neurons with strengthened synapses are more likely to fire in response to cortical input alone. This synaptic plasticity is produced by phosphorylation of AMPA receptors, caused by phosphorylation of various signalling molecules. A key signalling molecule is the phosphoprotein DARPP-32, highly expressed in striatal medium spiny neurons. DARPP-32 is regulated by several neurotransmitters through a complex network of intracellular signalling pathways involving cAMP (increased through dopamine stimulation) and calcium (increased through glutamate stimulation). Since DARPP-32 controls several kinases and phosphatases involved in striatal synaptic plasticity, understanding the interactions between cAMP and calcium, in particular the effect of transient stimuli on DARPP-32 phosphorylation, has major implications for understanding reinforcement learning. We developed a computer model of the biochemical reaction pathways involved in the phosphorylation of DARPP-32 on Thr34 and Thr75. Ordinary differential equations describing the biochemical reactions were implemented in a single compartment model using the software XPPAUT. Reaction rate constants were obtained from the biochemical literature. The first set of simulations using sustained elevations of dopamine and calcium produced phosphorylation levels of DARPP-32 similar to that measured experimentally, thereby validating the model. The second set of simulations, using the validated model, showed that transient dopamine elevations increased the phosphorylation of Thr34 as expected, but transient calcium elevations also increased the phosphorylation of Thr34, contrary to what is believed. When transient calcium and dopamine stimuli were paired, PKA activation and Thr34 phosphorylation increased compared with dopamine alone. This result, which is robust to variation in model parameters, supports reinforcement learning theories in which activity-dependent long-term synaptic plasticity requires paired glutamate and dopamine inputs.

Dopamine D1 receptor actions in layers V-VI rat prefrontal cortex neurons in vitro: modulation of dendritic-somatic signal integration.

CR Yang — 2007-05-03T09:33:40-00:00

J Neurosci, Vol. 16, No. 5. (1 March 1996), pp. 1922-1935.

The ionic mechanisms by which dopamine (DA) regulates the excitability of layers V-VI prefrontal cortex (PFC) output neurons (including those that project to the nucleus accumbens) were investigated in rat brain slices using in vitro intracellular recording techniques. DA or the D1 receptor agonist SKF38393, but not the D2 agonist quinpirole, reduced the first spike latency and lowered the firing threshold of the PFC neurons in response to depolarizing current pulses. This was accomplished by enhancing the duration of a tetradotoxinsensitive, slowly inactivating Na+ current and attenuating a slowly inactivating, outwardly rectifying, dendrotoxin-sensitive K+ current. Furthermore, D1 receptor stimulation attenuated high-threshold Ca2+ spike(s) (HTS) evoked primarily from the apical dendrites of these PFC neurons. Taken together, these data suggest that D1 receptor stimulation on layers V-VI pyramidal PFC neurons: (1) restricts the effects of inputs to the apical dendrites of these neurons by attenuating the dendritic HTS-mediated amplification of such inputs; and (2) potentiates the influence of local inputs from neighboring deep layers V-VI neurons by enhancing the slowly inactivating Na+ current and attenuating the slowly inactivating K+ current. By influencing the input/output characteristics of PFC-->NAc neurons, DA may play an important role in the processes through which PFC signals are translated into action.

Neural representation of interval time.

D Durstewitz — 2007-01-15T14:52:34-00:00

Neuroreport, Vol. 15, No. 5. (9 April 2004), pp. 745-749.

Animals can predict the time of occurrence of a forthcoming event relative to a preceding stimulus, i.e. the interval time between those two, given previous learning experience with the temporal contingency between them. Accumulating evidence suggests that a particular pattern of neural activity observed during tasks involving fixed temporal intervals might carry interval time information: the activity of some cortical and subcortical neurons ramps up slowly and linearly during the interval, like a temporal integrator, and peaks around the time at which the event is due to occur. The slope of this climbing activity, and hence the peak time, adjusts to the length of a temporal interval during repetitive experience with it. Various neural mechanisms for producing climbing activity with variable slopes, representing the length of learned intervals, are discussed.

Self-organizing neural integrator predicts interval times through climbing activity.

D Durstewitz — 2007-01-15T14:48:52-00:00

J Neurosci, Vol. 23, No. 12. (15 June 2003), pp. 5342-5353.

Mammals can reliably predict the time of occurrence of an expected event after a predictive stimulus. Climbing activity is a prominent profile of neural activity observed in prefrontal cortex and other brain areas that is related to the anticipation of forthcoming events. Climbing activity might span intervals from hundreds of milliseconds to tens of seconds and has a number of properties that make it a plausible candidate for representing interval time. A biophysical model is presented that produces climbing, temporal integrator-like activity with variable slopes as observed empirically, through a single-cell positive feedback loop between firing rate, spike-driven Ca2+ influx, and Ca2+-activated inward currents. It is shown that the fine adjustment of this feedback loop might emerge in a self-organizing manner if the cell can use the variance in intracellular Ca2+ fluctuations as a learning signal. This self-organizing process is based on the present observation that the variance of the intracellular Ca2+ concentration and the variance of the neural firing rate and of activity-dependent conductances reach a maximum as the biophysical parameters of a cell approach a configuration required for temporal integration. Thus, specific mechanisms are proposed for (1) how neurons might represent interval times of variable length and (2) how neurons could acquire the biophysical properties that enable them to work as timers.