title: Functional congruity in local auditory cortical microcircuits.
abstract: Functional columns of primary auditory cortex (AI) are arranged in layers, each composed of highly connected fine-scale networks. The basic response properties and interactions within these local subnetworks have only begun to be assessed. We examined the functional diversity of neurons within the laminar microarchitecture of cat AI to determine the relationship of spectrotemporal processing between neighboring neurons. Neuronal activity was recorded across the cortical layers while presenting a dynamically modulated broadband noise. Spectrotemporal receptive fields (STRFs) and their nonlinear input/output functions (nonlinearities) were constructed for each neuron and compared for pairs of neurons simultaneously recorded at the same contact site. Properties of these local neuron pairs showed greater similarity than non-paired neurons within the same column for all considered parameters including firing rate, envelope-phase precision, preferred spectral and temporal modulation frequency, as well as for the threshold and transition of the response nonlinearity. This higher functional similarity of paired versus non-paired neurons was most apparent in infragranular neuron pairs, and less for local supragranular and granular pairs. The functional similarity of local paired neurons for firing rate, best temporal modulation frequency and two nonlinearity aspects was laminar dependent, with infragranular local pair-wise differences larger than for granular or supragranular layers. Synchronous spiking events between pairs of neurons revealed that simultaneous 'Bicellular' spikes, in addition to carrying higher stimulus information than non-synchronized spikes, encoded faster modulation frequencies. Bicellular functional differences to the best matched of the paired neurons could be substantial. Bicellular nonlinearities showed that synchronous spikes act to transmit stimulus information with higher fidelity and precision than non-synchronous spikes of the individual neurons, thus, likely enhancing stimulus feature selectivity in their target neurons. Overall, the well-correlated and temporally precise processing within local subnetworks of cat AI showed laminar-dependent functional diversity in spectrotemporal processing, despite high intra-columnar congruity in frequency preference.
authors.affiliation: Coleman Memorial Laboratory, UCSF Center for Integrative Neuroscience, Kavli Institute for Fundamental Neuroscience, Department of Otolaryngology-HNS, University of California, San Francisco, United States. Electronic address: craig@phy.ucsf.edu.
authors.forename: C A
authors.initials: CA
authors.lastname: Atencio
authors.affiliation: Coleman Memorial Laboratory, UCSF Center for Integrative Neuroscience, Kavli Institute for Fundamental Neuroscience, Department of Otolaryngology-HNS, University of California, San Francisco, United States.
authors.forename: C E
authors.initials: CE
authors.lastname: Schreiner
mesh_terms: D000161:Acoustic Stimulation; D000200:Action Potentials / Q000502:physiology; D000818:Animals; D001303:Auditory Cortex / Q000166:cytology / Q000502:physiology*; D001306:Auditory Pathways / Q000502:physiology*; D001307:Auditory Perception / Q000502:physiology*; D002415:Cats; D005583:Fourier Analysis; D066298:In Vitro Techniques; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D011571:Psychoacoustics; D013997:Time Factors
keywords: fine-scale networks; local circuits; microarchitecture; microcircuits; subnetworks