[Comp-neuro] Spikes, synchrony, and attentive learning by laminar thalamocortical circuits

Stephen Grossberg steve at cns.bu.edu
Mon Apr 14 18:24:59 CEST 2008

The following article is now available at 

Grossberg, S. and Versace, M.
Spikes, synchrony, and attentive learning by laminar thalamocortical circuits
Brain Research, in press

This article develops the Synchronous Matching Adaptive Resonance 
Theory (SMART) neural model to explain how the brain may coordinate 
multiple levels of thalamocortical and corticocortical processing to 
rapidly learn, and stably remember, important information about a 
changing world. The model clarifies how bottom-up and top-down 
processes work together to realize this goal, notably how processes 
of learning, expectation, attention, resonance, and synchrony are 
coordinated. The model hereby clarifies, for the first time, how the 
following levels of brain organization coexist to realize cognitive 
processing properties that regulate fast learning and stable memory 
of brain representations: single cell properties, such as spiking 
dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine 
modulation; detailed laminar thalamic and cortical circuit designs 
and their interactions; aggregate cell recordings, such as 
current-source densities and local field potentials; and single cell 
and large-scale inter-areal oscillations in the gamma and beta 
frequency domains. In particular, the model predicts how laminar 
circuits of multiple cortical areas interact with primary and 
higher-order specific thalamic nuclei and nonspecific thalamic nuclei 
to carry out attentive visual learning and information processing. 
The model simulates how synchronization of neuronal spiking occurs 
within and across brain regions, and triggers STDP. Matches between 
bottom-up adaptively filtered input patterns and learned top-down 
expectations cause gamma oscillations that support attention, 
resonance, learning, and consciousness. Mismatches inhibit learning 
while causing beta oscillations during reset and hypothesis testing 
operations that are initiated in the deeper cortical layers. The 
generality of learned recognition codes is controlled by a vigilance 
process mediated by acetylcholine.

Keywords: attention; learning; STDP; bottom-up filter; top-down 
expectation; match; prediction; mismatch; LGN; pulvinar; V1; V2; 
spikes; gamma oscillations; beta oscillations; synchronization; local 
field potentials; mismatch negativity; acetylcholine; cortical 
layers; Adaptive Resonance Theory

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