A multielectrode study of the inferotemporal cortex in the monkey: effects of grouping on spike rates and synchrony

We measured spiking activity from 175 pairs of visually selective neurons while a monkey performed a visual classification task in which the same image pairs appeared in informative and uninformative contexts. Spike counts and synchrony counts were higher during fixations of informative configurations. Spike field coherence showed low frequency (∼5–15 Hz) desynchronization when viewing informative stimulus configurations. Jitter statistics, which quantify synchrony and control for spike rates, showed less probable, more surprising patterns of synchronies when the monkey made the correct response than when he erred. Our results suggest that changes in spike counts parallel changes in raw synchrony counts and that both track aspects of stimulus context. Synchrony unexplained by rates changes, however, also occurs and correlates with performance.

[1]  Asohan Amarasingham,et al.  At what time scale does the nervous system operate? , 2003, Neurocomputing.

[2]  M. Mishkin,et al.  Learning increases stimulus salience in anterior inferior temporal cortex of the macaque. , 2001, Journal of neurophysiology.

[3]  R. Eckhorn,et al.  A new method for the insertion of multiple microprobes into neural and muscular tissue, including fiber electrodes, fine wires, needles and microsensors , 1993, Journal of Neuroscience Methods.

[4]  R. Zahler.  Principles of Neurobiological Signal Analysis , 1979, The Yale Journal of Biology and Medicine.

[5]  Peter Földiák,et al.  Adaptation and decorrelation in the cortex , 1989 .

[6]  E. Rolls,et al.  Object perception in natural scenes: encoding by inferior temporal cortex simultaneously recorded neurons. , 2005, Journal of neurophysiology.

[7]  Christoph von der Malsburg,et al.  The What and Why of Binding The Modeler’s Perspective , 1999, Neuron.

[8]  W. Freiwald,et al.  Oscillatory synchrony in the monkey temporal lobe correlates with performance in a visual short-term memory task. , 2004, Cerebral cortex.

[9]  P. Good,et al.  Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses , 1995 .

[10]  Stuart Geman,et al.  An Exact Jitter Method using Dynamic Programming , 2004 .

[11]  Richard Durbin,et al.  The computing neuron , 1989 .

[12]  Carlos D. Brody,et al.  Correlations Without Synchrony , 1999, Neural Computation.

[13]  Michael N. Shadlen,et al.  Synchrony Unbound A Critical Evaluation of the Temporal Binding Hypothesis , 1999, Neuron.

[14]  Shun-ichi Amari,et al.  Information-Geometric Measure for Neural Spikes , 2002, Neural Computation.

[15]  Britt Anderson,et al.  XOR style tasks for testing visual object processing in monkeys , 2006, Vision Research.

[16]  Y. Dan,et al.  Coding of visual information by precisely correlated spikes in the lateral geniculate nucleus , 1998, Nature Neuroscience.

[17]  V. Mountcastle,et al.  Adaptation of the Reitboeck method of multiple microelectrode recording to the neocortex of the waking monkey , 1991, Journal of Neuroscience Methods.

[18]  Matthew T. Harrison,et al.  Discovering Compositional Structure , 2005 .