Functional laminar architecture of the rat primary auditory cortex

The goal of this thesis is to investigate the functional role of the cortical column architecture within some of the existing brain coding theories. Here I focus on the hierarchical models of predictive coding and the 'phase of firing' coding hypothesis. Using an oddball paradigm consisting of a sequence of identical sounds interspersed with rare, unexpected sounds, one can observe a difference between the scalp potentials evoked by oddball and common sounds. This difference has been linked to predictive coding and novelty detection, and Stimulus Specific Adaptation (SSA) has been suggested as a likely substrate at the single neuron level. In order to simultaneously constrain hierarchical models of predictive coding, and so as to investigate the contributions that neural processing within the different cytoarchitectonic layers of the primary auditory cortex (A1) may make to SSA, I simultaneously recorded multi-unit activity and current source density (CSD) profiles across all layers in A1 of the rat in response to standard and oddball tones. Our results suggest that SSA arises at the level of the thalamocortical synapse and is further enhanced in the supragranular layers. The phase of low-frequency Local Field Potentials (LFPs) in primary sensory cortices carries stimulus related information and disambiguates the information about different stimuli evoking similar spike rates. However, it is yet unclear how these informative LFP phase values arise within the laminar organization of cortical columns. To address this issue, I performed CSD recordings in the area A1 of anaesthetized rats during the presentation of complex naturalistic sounds. Information theoretic analysis revealed that most LFP phase information originates from discrete CSD events consisting of strong granular-superficial-layer dipoles, likely triggered by bursts of thalamocortical activation. These events, which occur at rates of 2-4 Hz, reliably reset LFP phases at times of strong network excitation. They therefore provide a useful reference frame to measure neural activity with respect to salient times of stimulus history. CSD events display a diverse, stimulus-dependent morphology: these reflect the outcomes of cortical computations which result in varying extents of activation of infragranular output layers.