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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)

Adam Kepecs

Biophysical basis for Differentiate-and-Burst neurons

Brandeis University

Brief bursts of high-frequency action potentials are commonly observed in neuronal recordings and are thought to represent a special neural code. Here I discuss detection of specific temporal features of stimuli by spike bursts. Using a computational model we show that as a consequence of the biophysical mechanisms that lead to burst generation, bursts act as a differentiator and signal the slope of the input current rather than its amplitude. Furthermore, the number of spikes per burst signals the magnitude of the slope in a graded manner, establishing a burst duration code. Because the firing rate during bursts is so high, variations in spike number can efficiently transmit information in brief periods. I illustrate this general result by the example of upstroke detection by bursting cells in the electric fish. Thus some neurons may differentiate and burst and thereby provide a useful computation quite distinct from neurons that integrate and fire.