Biomedical subjects

Daniel J Amit

Publications and source records attributed to Daniel J Amit.

4 recordsLinked to original sources

PubMed2003

Retrospective and prospective persistent activity induced by Hebbian learning in a recurrent cortical network.

Recordings from cells in the associative cortex of monkeys performing visual working memory tasks link persistent neuronal activity, long-term memory and associative memory. In particular, delayed pair-associate tasks have revealed neuronal correlates of long-term memory of associations between stimuli. Here, a recurrent cortical network model with Hebbian plastic synapses is subjected to the pair-associate protocol. In a first stage, learning leads to the appearance of delay activity, representing individual images ('retrospective' activity). As learning proceeds, the same learning mechanism uses retrospective delay activity together with choice stimulus activity to potentiate synapses connecting neural populations representing associated images. As a result, the neural population corresponding to the pair-associate of the image presented is activated prior to its visual stimulation ('prospective' activity). The probability of appearance of prospective activity is governed by the strength of the inter-population connections, which in turn depends on the frequency of pairings during training. The time course of the transitions from retrospective to prospective activity during the delay period is found to depend on the fraction of slow, N-methyl-d-aspartate-like receptors at excitatory synapses. For fast recurrent excitation, transitions are abrupt; slow recurrent excitation renders transitions gradual. Both scenarios lead to a gradual rise of delay activity when averaged over many trials, because of the stochastic nature of the transitions. The model reproduces most of the neuro-physiological data obtained during such tasks, makes experimentally testable predictions and demonstrates how persistent activity (working memory) brings about the learning of long-term associations.

Animals↗

PubMed2003

The eye and the hand: neural mechanisms and network models for oculomanual coordination in parietal cortex.

The coordinated action of the eye and the hand is necessary for the successful performance of a large variety of motor tasks based on visual information. Although at the output level the neural control systems for the eye and the hand are largely segregated, in the parietal cortex of the macaque monkey there exist populations of neurons able to combine ocular and manual signals on the basis of their spatial congruence. An expression of this congruence is the clustering of eye- and hand-related preferred directions of these neurons into a restricted region of the workspace, defined as field of global tuning. This domain may represent a neural substrate for the early composition of commands for coordinated oculo-manual actions. Here we study two different prototypical network models integrating inputs about retinal target location, eye position and hand position. In the first one, we model the interaction of these different signals, as it occurs at the afferent level, in a feed-forward fashion. In the second model, we assume that recurrent interactions are responsible for their combination. Both models account surprisingly well for the experimentally observed global tuning fields of parietal neurons. When we compare them with the experimental findings, no significant difference emerges between the two. Experiments potentially able to discriminate between these models could be performed.

Adaptation, Physiological↗

PubMed2003

Selective delay activity in the cortex: phenomena and interpretation.

The present article does not intend to present technical progress nor recent successes in accounting for experiments, as this issue of the journal presents a rich inventory. Rather, the paper presents a retrospective reflection on the history of the subject; on the relation between the different aspects of the concepts and the phenomena involved; on its strengths and weaknesses; and on some future prospects. It is a tribute to an extremely rich and growing wealth of physiological phenomena and of interpretative concepts. Yet the extent of achievement is used to expose open questions, which appear to become ever deeper. It is also an attempt to make the subject a matter of discourse between biologists and modelers, without the distraction of technical details.

Animals↗

PubMed2003

Spike-driven synaptic dynamics generating working memory states.

The collective behavior of a network, modeling a cortical module of spiking neurons connected by plastic synapses is studied. A detailed spike-driven synaptic dynamics is simulated in a large network of spiking neurons, implementing the full double dynamics of neurons and synapses. The repeated presentation of a set of external stimuli is shown to structure the network to the point of sustaining working memory (selective delay activity). When the synaptic dynamics is analyzed as a function of pre- and postsynaptic spike rates in functionally defined populations, it reveals a novel variation of the Hebbian plasticity paradigm: in any functional set of synapses between pairs of neurons (e.g., stimulated-stimulated, stimulated-delay, stimulated-spontaneous), there is a finite probability of potentiation as well as of depression. This leads to a saturation of potentiation or depression at the level of the ratio of the two probabilities. When one of the two probabilities is very high relative to the other, the familiar Hebbian mechanism is recovered. But where correlated working memory is formed, it prevents overlearning. Constraints relevant to the stability of the acquired synaptic structure and the regimes of global activity allowing for structuring are expressed in terms of the parameters describing the single-synapse dynamics. The synaptic dynamics is discussed in the light of experiments observing precise spike timing effects and related issues of biological plausibility.

Action Potentials↗