The Effect of synchronized inputs at the single neuron level

It is commonly assumed that temporal synchronization of excitatory synaptic inputs onto a single neuron increases its firing rate. We investigate here the role of synaptic synchronization for the leaky integrate-and-fire neuron as well as for a biophysically and anatomically detailed compartmental model of a cortical pyramidal cell. We find that if the number of excitatory inputs, N, is on the same order as the number of fully synchronized inputs necessary to trigger a single action potential, N_t, synchronization always increases the firing rate (for both constant and Poisson-distributed input). However, for large values of N compared to N_t, ''overcrowding'' occurs and temporal synchronization is detrimental to firing frequency. This behavior is caused by the conflicting influence of the low-pass nature of the passive dendritic membrane on the one hand and the refractory period on the other. If both temporal synchronization as well as the fraction of synchronized inputs (Murthy and Fetz 1993) is varied, synchronization is only advantageous if either N or the average input frequency, ƒ(in), are small enough

The Laminar Organization of Visual Cortex: A Unified View of Development, Learning, and Grouping

Why are all sensory and cognitive neocortex organized into layered circuits? How do these layers organize circuits that form functional columns in cortical maps? How do bottom-up, top-down, and horizontal interactions within the cortical layers generate adaptive behaviors. This chapter summarizes an evolving neural model which suggests how these interactions help the visual cortex to realize: (1) the binding process whereby cortex groups distributed data into coherent object representations; (2) the attentional process whereby cortex selectively processes important events; and (3) the developmental and learning processes whereby cortex shapes its circuits to match environmental constraints. It is suggested that the mechanisms which achieve property (3) imply properties of (I) and (2). New computational ideas about feedback systems suggest how neocortex develops and learns in a stable way, and why top-down attention requires converging bottom-up inputs to fully activate cortical cells, whereas perceptual groupings do not.Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI-97-20333); Office of Naval Research (N00014-95-1-0657

Death and rebirth of neural activity in sparse inhibitory networks

In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of the neural activity, as expected, but it can also promote neural reactivation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neurons' death). However, the random pruning of the connections is able to reverse the action of inhibition, i.e. in a sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of the neurons (neurons' rebirth). Thus the number of firing neurons reveals a minimum at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by the neurons with higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving an analytic mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, the system passes from a perfectly regular evolution to an irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.Comment: 19 pages, 10 figures, submitted to NJ