A temporal basis for predicting the sensory consequences of motor commands in an electric fish

To adaptively navigate their environments organisms need to predict and cancel out the sensory consequences of their actions. Here the authors show that granule cells within the cerebellum-like structure of weakly electric fish have delayed responses that closely match the timing of self-generated s...

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Veröffentlicht in:Nature neuroscience 2014-03, Vol.17 (3), p.416-422
Hauptverfasser: Kennedy, Ann, Wayne, Greg, Kaifosh, Patrick, Alviña, Karina, Abbott, L F, Sawtell, Nathaniel B
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Sprache:eng
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Zusammenfassung:To adaptively navigate their environments organisms need to predict and cancel out the sensory consequences of their actions. Here the authors show that granule cells within the cerebellum-like structure of weakly electric fish have delayed responses that closely match the timing of self-generated sensory inputs. This enables corollary discharges to be transformed into negative images that are well-tuned to the animal's own behavior. Mormyrid electric fish are a model system for understanding how neural circuits predict the sensory consequences of motor acts. Medium ganglion cells in the electrosensory lobe create negative images that predict sensory input resulting from the fish's electric organ discharge (EOD). Previous studies have shown that negative images can be created through plasticity at granule cell–medium ganglion cell synapses, provided that granule cell responses to the brief EOD command are sufficiently varied and prolonged. Here we show that granule cells indeed provide such a temporal basis and that it is well-matched to the temporal structure of self-generated sensory inputs, allowing rapid and accurate sensory cancellation and explaining paradoxical features of negative images. We also demonstrate an unexpected and critical role of unipolar brush cells (UBCs) in generating the required delayed responses. These results provide a mechanistic account of how copies of motor commands are transformed into sensory predictions.
ISSN:1097-6256
1546-1726
DOI:10.1038/nn.3650