Spike-timing Patterns Research Articles

Excess synchrony in motor cortical neurons provides redundant direction information with that from coarse temporal measures.

Previous studies have shown that measures of fine temporal correlation, such as synchronous spikes, across responses of motor cortical neurons carries more directional information than that predicted from statistically independent neurons. It is also known, however, that the coarse temporal measures of responses, such as spike count, are not independent. We therefore examined whether the information carried by coincident firing was related to that of coarsely defined spike counts and their correlation. Synchronous spikes were counted in the responses from 94 pairs of simultaneously recorded neurons in primary motor cortex (MI) while monkeys performed arm movement tasks. Direct measurement of the movement-related information indicated that the coincident spikes (1- to 5-ms precision) carry approximately 10% of the information carried by a code of the two spike counts. Inclusion of the numbers of synchronous spikes did not add information to that available from the spike counts and their coarse temporal correlation. To assess the significance of the numbers of coincident spikes, we extended the stochastic spike count matched (SCM) model to include correlations between spike counts of the individual neural responses and slow temporal dependencies within neural responses (approximately 30 Hz bandwidth). The extended SCM model underestimated the numbers of synchronous spikes. Therefore as with previous studies, we found that there were more synchronous spikes in the neural data than could be accounted for by this stochastic model. However, the SCM model accounts for most (R(2) = 0.93 +/- 0.05, mean +/- SE) of the differences in the observed number of synchronous spikes to different directions of arm movement, indicating that synchronous spiking is directly related to spike counts and their broad correlation. Further, this model supports the information theoretic analysis that the synchronous spikes do not provide directional information beyond that available from the firing rates of the same pool of directionally tuned MI neurons. These results show that detection of precisely timed spike patterns above chance levels does not imply that those spike patterns carry information unavailable from coarser population codes but leaves open the possibility that excess synchrony carries other forms of information or serves other roles in cortical information processing not studied here.

Characterization of a high-voltage-activated IA current with a role in spike timing and locomotor pattern generation.

Transient A-type K+ channels (I(A)) in neurons have been implicated in the delay of the spike onset and the decrease in the firing frequency. Here we have characterized biophysically and pharmacologically an I(A) current in lamprey locomotor network neurons that is activated by suprathreshold depolarization and is specifically blocked by catechol at 100 microM. The biophysical properties of this current are similar to the mammalian Kv3.4 channel. The role of the I(A) current both in single neuron firing and in locomotor pattern generation was analyzed. The I(A) current facilitates Na+ channel recovery from inactivation and thus sustains repetitive firing. The role of the I(A) current in motor pattern generation was examined by applying catechol during fictive locomotion induced by N-methyl-d-aspartate. Blockade of this current increased the locomotor burst frequency and decreased the firing of motoneurons. Although an alternating motor pattern could still be generated, the cycle duration was less regular, with ventral roots bursts failing on some cycles. Our results thus provide insights into the contribution of a high-voltage-activated I(A) current to the regulation of firing properties and motor coordination in the lamprey spinal cord.

Allergic reactions to drugs: involvement of T cells

<h3>ABSTRACT</h3> The problem of deciphering how low-level patterns (action potentials in the brain, amino acids in a protein, etc.) drive high-level biological features (sensorimotor behavior, enzymatic function) represents the central...

Stochastic nature of precisely timed spike patterns in visual system neuronal responses.

It is not clear how information related to cognitive or psychological processes is carried by or represented in the responses of single neurons. One provocative proposal is that precisely timed spike patterns play a role in carrying such information. This would require that these spike patterns have the potential for carrying information that would not be available from other measures such as spike count or latency. We examined exactly timed (1-ms precision) triplets and quadruplets of spikes in the stimulus-elicited responses of lateral geniculate nucleus (LGN) and primary visual cortex (V1) neurons of the awake fixating rhesus monkey. Large numbers of these precisely timed spike patterns were found. Information theoretical analysis showed that the precisely timed spike patterns carried only information already available from spike count, suggesting that the number of precisely timed spike patterns was related to firing rate. We therefore examined statistical models relating precisely timed spike patterns to response strength. Previous statistical models use observed properties of neuronal responses such as the peristimulus time histogram, interspike interval, and/or spike count distributions to constrain the parameters of the model. We examined a new stochastic model, which unlike previous models included all three of these constraints and unlike previous models predicted the numbers and types of observed precisely timed spike patterns. This shows that the precise temporal structures of stimulus-elicited responses in LGN and V1 can occur by chance. We show that any deviation of the spike count distribution, no matter how small, from a Poisson distribution necessarily changes the number of precisely timed spike patterns expected in neural responses. Overall the results indicate that the fine temporal structure of responses can only be interpreted once all the coarse temporal statistics of neural responses have been taken into account.

Response features determining spike times.

Interpreting messages encoded in single neuronal responses requires knowing which features of the responses carry information. That the number of spikes is an important part of the code has long been obvious. In recent years, it has been shown that modulation of the firing rate with about 25 ms precision carries information that is not available from the total number of spikes across the whole response. It has been proposed that patterns of exactly timed (1 ms precision) spikes, such as repeating triplets or quadruplets, might carry information that is not available from knowing about spike count and rate modulation. A model using the spike count distribution, the low pass filtered PSTH (bandwidth below 30 Hz), and, to a small degree, the interspike interval distribution predicts the numbers and types of exactly-timed triplets and quadruplets that are indistinguishable from those found in the data. From this it can be concluded that the coarse (<30 Hz) sequential correlation structure over time gives rise to the exactly timed patterns present in the recorded spike trains. Because the coarse temporal structure predicts the fine temporal structure, the information carried by the fine temporal structure must be completely redundant with that carried by the coarse structure. Thus, the existence of precisely timed spike patterns carrying stimulus-related information does not imply control of spike timing at precise time scales.

Meeting report

This report does not capture the raw vitality of the Sde-Boker workshop. We did not anticipate that so many presentations would focus on the importance of spike timing in the operations of cortical microcircuits and the profound effect of this on other cortical and subcortical networks. The roles of individual spikes, temporal firing patterns, neuronal synchronization, intrinsic neuronal and network oscillation, coincidence detection, integration by individual cells or even individual dendritic spines were also strong themes of nearly all presentations. The cortex could be viewed as a network, which, is similar to an orchestra, where each neuron (musician) generates particular timed spike patterns (notes) for which 'every spike counts' (the symphony). This assertion would have been the butt of considerable skepticism less than a decade ago. The conference led to a view that the cerebral cortex is a spatially distributed timing network. As such, the consensus reached provides a conceptual framework for exciting new discoveries in the next decade. One of the truly exciting outcomes of the workshop was the seamless integration of concepts derived from studies employing direct approaches such as brain slices to cell cultures and computer simulations to whole animal physiology. The availability of an ever expanding armamentarium of increasingly sophisticated techniques and cross-fertilization promises develop the field in a direction that is as flexible and as subtle as the cortical tissue it seeks to explain. It was perhaps symbolic that this meeting was held at a place in the desert where David Ben-Gurion, the first Prime Minister of the modern state of Israel, had a vision of pioneers settling the untamed Negev that had intrigued and intimidated mankind for so long. The hauntingly beautiful Negev, like the cerebral cortex, was an unyielding frontier. Now thanks to modern ingenuity and technology the Negev can, like the cerebral cortex, finally be conquered.

A model of neocortex

Prompted by considerations about (i) the compositionality of cognitive functions, (ii) the physiology of individual cortical neurons, (iii) the role of accurately timed spike patterns in cortex, and (iv) the regulation of global cortical activity, we suggest that the dynamics of cortex on the 1-ms time scale may be described as the activation of circuits of the synfire-chain type (Abeles 1982, 1991). We suggest that the fundamental computational unit in cortex may be a wave-like spatio-temporal pattern of synfire type, and that the binding mechanism underlying compositionality in cognition may be the accurate synchronization of synfire waves that propagate simultaneously on distinct, weakly coupled, synfire chains. We propose that Hebbian synaptic plasticity may result in a superposition of synfire chains in cortical connectivity, whereby a given neuron participates in many distinct chains. We investigate the behaviour of a much-simplified model of cortical dynamics devised along these principles. Calculations and numerical experiments are performed based on an assumption of randomness of stored chains, in the style of statistical physics. It is demonstrated that: (i) there exists a critical value for the total length of stored chains; (ii) this storage capacity is linear in the network's size; (iii) the behaviour of the network around the critical point is characterized by the self-regulation of the number of synfire waves coactive in the network at any given time.

A model of neocortex

Prompted by considerations about (i) the compositionality of cognitive functions, (ii) the physiology of individual cortical neurons, (iii) the role of accurately timed spike patterns in cortex, and (iv) the regulation of global cortical activity, we suggest that the dynamics of cortex on the 1-ms time scale may be described as the activation of circuits of the synfire-chain type (Abeles 1982, 1991). We suggest that the fundamental computational unit in cortex may be a wave-like spatio-temporal pattern of synfire type, and that the binding mechanism underlying compositionality in cognition may be the accurate synchronization of synfire waves that propagate simultaneously on distinct, weakly coupled, synfire chains. We propose that Hebbian synaptic plasticity may result in a superposition of synfire chains in cortical connectivity, whereby a given neuron participates in many distinct chains. We investigate the behaviour of a much-simplified model of cortical dynamics devised along these principles. Calcula...