Balanced synaptic input shapes the correlation between neural spike trains.
Stimulus properties, attention, and behavioral context influence correlations between the spike times produced by a pair of neurons. However, the biophysical mechanisms that modulate these correlations are poorly understood. With a combined theoretical and experimental approach, we show that the rate of balanced excitatory and inhibitory synaptic input modulates the magnitude and timescale of pairwise spike train correlation. High rate synaptic inputs promote spike time synchrony rather than long timescale spike rate correlations, while low rate synaptic inputs produce opposite results. This correlation shaping is due to a combination of enhanced high frequency input transfer and reduced firing rate gain in the high input rate state compared to the low state. Our study extends neural modulation from single neuron responses to population activity, a necessary step in understanding how the dynamics and processing of neural activity change across distinct brain states.
Program for Neural Computation, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. alk@cmu.edu
Ashok
A
Litwin-Kumar
Anne-Marie M
AM
Oswald
Nathaniel N
NN
Urban
Brent
B
Doiron
D000200:Action Potentials / Q000502:physiology; D000818:Animals; D001921:Brain / Q000502:physiology; D051379:Mice; D008815:Mice, Inbred Strains; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*