5 research outputs found
Feature selection in simple neurons: how coding depends on spiking dynamics
The relationship between a neuron's complex inputs and its spiking output
defines the neuron's coding strategy. This is frequently and effectively
modeled phenomenologically by one or more linear filters that extract the
components of the stimulus that are relevant for triggering spikes, and a
nonlinear function that relates stimulus to firing probability. In many sensory
systems, these two components of the coding strategy are found to adapt to
changes in the statistics of the inputs, in such a way as to improve
information transmission. Here, we show for two simple neuron models how
feature selectivity as captured by the spike-triggered average depends both on
the parameters of the model and on the statistical characteristics of the
input.Comment: 23 Pages, LaTeX + 4 Figures. v2 is substantially expanded and
revised. v3 corrects minor errors in Sec. 3.
Stress-Induced Impairment of a Working Memory Task: Role of Spiking Rate and Spiking History Predicted Discharge
Stress, pervasive in society, contributes to over half of all work place accidents a year and over time can contribute to a variety of psychiatric disorders including depression, schizophrenia, and post-traumatic stress disorder. Stress impairs higher cognitive processes, dependent on the prefrontal cortex (PFC) and that involve maintenance and integration of information over extended periods, including working memory and attention. Substantial evidence has demonstrated a relationship between patterns of PFC neuron spiking activity (action-potential discharge) and components of delayed-response tasks used to probe PFC-dependent cognitive function in rats and monkeys. During delay periods of these tasks, persistent spiking activity is posited to be essential for the maintenance of information for working memory and attention. However, the degree to which stress-induced impairment in PFC-dependent cognition involves changes in task-related spiking rates or the ability for PFC neurons to retain information over time remains unknown. In the current study, spiking activity was recorded from the medial PFC of rats performing a delayed-response task of working memory during acute noise stress (93 db). Spike history-predicted discharge (SHPD) for PFC neurons was quantified as a measure of the degree to which ongoing neuronal discharge can be predicted by past spiking activity and reflects the degree to which past information is retained by these neurons over time. We found that PFC neuron discharge is predicted by their past spiking patterns for nearly one second. Acute stress impaired SHPD, selectively during delay intervals of the task, and simultaneously impaired task performance. Despite the reduction in delay-related SHPD, stress increased delay-related spiking rates. These findings suggest that neural codes utilizing SHPD within PFC networks likely reflects an additional important neurophysiological mechanism for maintenance of past information over time. Stress-related impairment of this mechanism is posited to contribute to the cognition-impairing actions of stress
Fast Inference of Interactions in Assemblies of Stochastic Integrate-and-Fire Neurons from Spike Recordings
We present two Bayesian procedures to infer the interactions and external
currents in an assembly of stochastic integrate-and-fire neurons from the
recording of their spiking activity. The first procedure is based on the exact
calculation of the most likely time courses of the neuron membrane potentials
conditioned by the recorded spikes, and is exact for a vanishing noise variance
and for an instantaneous synaptic integration. The second procedure takes into
account the presence of fluctuations around the most likely time courses of the
potentials, and can deal with moderate noise levels. The running time of both
procedures is proportional to the number S of spikes multiplied by the squared
number N of neurons. The algorithms are validated on synthetic data generated
by networks with known couplings and currents. We also reanalyze previously
published recordings of the activity of the salamander retina (including from
32 to 40 neurons, and from 65,000 to 170,000 spikes). We study the dependence
of the inferred interactions on the membrane leaking time; the differences and
similarities with the classical cross-correlation analysis are discussed.Comment: Accepted for publication in J. Comput. Neurosci. (dec 2010