The Journal of Neuroscience, March 15, 2002, 22(6):2374-2382
Stimulus Encoding and Feature Extraction by Multiple Sensory
Neurons
Rüdiger
Krahe1,
Gabriel
Kreiman2,
Fabrizio
Gabbiani3,
Christof
Koch2, and
Walter
Metzner1
1 Department of Biology, University of California,
Riverside, California 92521, 2 Computation and Neural
Systems Program, Division of Biology, Caltech, Pasadena, California
91125, and 3 Division of Neuroscience, Baylor College of
Medicine, Houston, Texas 77030
Neighboring cells in topographical sensory maps may transmit
similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the
performance of single cells is a very important question for
understanding the functioning of the nervous system. To tackle this
problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells
constitute the output neurons of the first central nervous stage of
electrosensory processing. Using random amplitude modulations (RAMs) of
a mimic of the fish's own electric field within behaviorally relevant
frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To
quantify the encoding of the RAM time course, we estimated the stimuli
from simultaneously recorded spike trains and found significant
improvements over single spike trains. The quality of stimulus
reconstruction, however, was still inferior to the one measured for
single primary sensory afferents. In an analysis of feature extraction,
we found that spikes of pyramidal cell pairs coinciding within a time
window of a few milliseconds performed significantly better at
detecting upstrokes and downstrokes of the stimulus compared with
isolated spikes and even spike bursts of single cells. Coincident
spikes can thus be considered "distributed bursts." Our results
suggest that stimulus encoding by primary sensory afferents is
transformed into feature extraction at the next processing stage.
There, stimulus-induced coincident activity can improve the extraction
of behaviorally relevant features from the stimulus.
Key words:
stimulus estimation; signal detection; correlated
activity; weakly electric fish; bursting; neural coding
Copyright © 2002 Society for Neuroscience 0270-6474/02/2262374-09$05.00/0
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