|Title||Dynamical microstates in primary auditory cortex|
|Publication Type||Conference Paper|
|Year of Publication||2013|
|Authors||Neymotin, S. A., Lytton WW., Oconnell M. N., & Lakatos P.|
|Conference Name||Society for Neuroscience 2013 (SFN '13)|
|Keywords||SFN, Society for Neuroscience|
Neuronal oscillations reflect coordinated excitability fluctuations of neuronal ensembles on multiple temporal and spatial scales. Although recent data indicates that different cortical layers exhibit dominant neuronal oscillations in distinctly different frequency bands, the temporal evolution of these spectral patterns during spontaneous or ongoing brain activity is difficult to quantify. We hypothesized the presence of distinct cortical microstates, or localized activity patterns, that would have different signatures in the ongoing neuronal activity within and across the cortical layers. We further hypothesized that these microstates would reflect signal complexity within the layers, the role of layers in information processing, and the routing of information. To investigate these issues, we took complementary approaches: analysis of an electrophysiological dataset of bilateral, laminar electrophysiological recording of spontaneous field, current source density (CSD) and unit activity from primary auditory cortex, with modeling of the dataset with detailed computer simulations, based on our prior models. We identified several recurring microstates in the data, based on the temporal evolution of neuronal oscillations in distinct frequency bands within and across cortical layers and their relation to neuronal firing. Microstate recurrence rates and levels differed between the granular and extragranular layers. Distinct recurrences appeared to be consistent with the role of the granular layer in receiving specific thalamocortical inputs carrying stimulus-specific information, versus the modulatory role of the extragranular layers. We evaluated the computer model in order to better understand the genesis of microstates of different forms, analyzing our models of sensory neocortex to also look at fields, CSD, and spike patterns. We demonstrated realistic oscillatory spectra with recurrent microstates that differed by laminar depth. Simulation in two conditions, spontaneous vs rhythmic stimulation, demonstrated distinct patterns of recurrence. Our work demonstrates that the microstates of neuronal activity in the neocortex have distinct layer-specific signatures and suggests that these reflect the contrasting roles of the individual layers in information processing.