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Banbury Center Workshop Series

Neurocomputational Strategies: From Synapses to Behavior (1998)
Functional Organization of the Thalamus and Cortex and their Interactions (1999)
Toward Animal Models of Attention and Consciousness (2000)
Persistent Neural Activity (2000)
Can a Machine Be Conscious? (2001)
Communication in Brain Systems (2004)
Neurobiology of Decision-Making (2005)
Computational Approaches to Cortical Functions (2006)
New Frontiers in Studies of Nonconscious Processing (2007)
Theoretical and Experimental Approaches to Auditory and Visual Attention (2008)
Searching for Principles Underlying Memory in Biological Systems (2009)
Neuronal Response Variability and Cortical Computation (2011)
Connections and Communication in the Brain (2014)

P. Drew and L.F. Abbott

Modeling Temporal Combination Selective Neurons in the Songbird

Brandeis University

Neurons in the high vocal center (HVc) of the songbird respond vigorously to sequences of syllables as they appear in the birds own song (such as AB), but they respond weakly or not at all when the same syllables are played individually (A or B), or in a different order (BA). We have constructed a network model that replicates this temporal-sequence selectivity. The model is based on a recurrently connected network that produces a strong resonant response when the pattern of excitation evoked by a stimulus matches the excitation generated within the network. In the model, stimulus B does not generate a strong response by itself because inhibition within the network prevents a matching internally generated resonant signal from arising. However, if stimulus A is presented prior to B, the pattern of activity evoked by A modifies the effective connectivity of the network, making it resonantly responsive to stimulus B. This produces a strong selective network response to the sequence of syllables AB, but not to any other combination.