Signal, Noise, and Variation in Neural and Sensory-Motor Latency.

Autor: Lee J; Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea. Electronic address: joonyeol@skku.edu., Joshua M; Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem 91904, Israel., Medina JF; Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA., Lisberger SG; Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA.
Jazyk: angličtina
Zdroj: Neuron [Neuron] 2016 Apr 06; Vol. 90 (1), pp. 165-76. Date of Electronic Publication: 2016 Mar 10.
DOI: 10.1016/j.neuron.2016.02.012
Abstrakt: Analysis of the neural code for sensory-motor latency in smooth pursuit eye movements reveals general principles of neural variation and the specific origin of motor latency. The trial-by-trial variation in neural latency in MT comprises a shared component expressed as neuron-neuron latency correlations and an independent component that is local to each neuron. The independent component arises heavily from fluctuations in the underlying probability of spiking, with an unexpectedly small contribution from the stochastic nature of spiking itself. The shared component causes the latency of single-neuron responses in MT to be weakly predictive of the behavioral latency of pursuit. Neural latency deeper in the motor system is more strongly predictive of behavioral latency. A model reproduces both the variance of behavioral latency and the neuron-behavior latency correlations in MT if it includes realistic neural latency variation, neuron-neuron latency correlations in MT, and noisy gain control downstream of MT.
(Copyright © 2016 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE