TY - JOUR
T1 - Encoding of motion targets by waves in turtle visual cortex
AU - Du, Xiuxia
AU - Ghosh, Bijoy K.
AU - Ulinski, Philip
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2006/8
Y1 - 2006/8
N2 - Visual stimuli evoke wave activity in the visual cortex of freshwater turtles. Earlier work from our laboratory showed that information about the positions of stationary visual stimuli is encoded in the spatiotemporal dynamics of the waves and that the waves can be decoded using Bayesian detection theory. This paper extends these results in three ways. First, it shows that flashes of light separated in space and time and stimuli moving with three speeds can be discriminated statistically using the waves generated in a large-scale model of the cortex. Second, it compares the coding capabilities of spike rate and spike time codes. Spike rate codes were obtained by low-pass filtering the activities of individual neurons in the model with filters of different band widths. For the moving targets used in the study, detectability using spike rate codes is immune to the choice of a specific bandwidth, indicating that a coarse filter is able to adequately discriminate targets. Spike timing codes are binary sequences indicating the precise timing of spike activity of individual neurons across the cortex. Spike time codes generally perform better than do spike rate codes. Third, the encoding process is examined in terms of the underlying cellular mechanisms that result in the initiation, propagation and cessation of the wave. The period of peak detectability corresponds to the period in which waves are propagating across the cortex.
AB - Visual stimuli evoke wave activity in the visual cortex of freshwater turtles. Earlier work from our laboratory showed that information about the positions of stationary visual stimuli is encoded in the spatiotemporal dynamics of the waves and that the waves can be decoded using Bayesian detection theory. This paper extends these results in three ways. First, it shows that flashes of light separated in space and time and stimuli moving with three speeds can be discriminated statistically using the waves generated in a large-scale model of the cortex. Second, it compares the coding capabilities of spike rate and spike time codes. Spike rate codes were obtained by low-pass filtering the activities of individual neurons in the model with filters of different band widths. For the moving targets used in the study, detectability using spike rate codes is immune to the choice of a specific bandwidth, indicating that a coarse filter is able to adequately discriminate targets. Spike timing codes are binary sequences indicating the precise timing of spike activity of individual neurons across the cortex. Spike time codes generally perform better than do spike rate codes. Third, the encoding process is examined in terms of the underlying cellular mechanisms that result in the initiation, propagation and cessation of the wave. The period of peak detectability corresponds to the period in which waves are propagating across the cortex.
KW - Karhunen-Loeve (KL) decomposition
KW - Motion encoding
KW - Statistical hypothesis testing
KW - Turtle visual cortex
KW - β-space representation
UR - http://www.scopus.com/inward/record.url?scp=33746626906&partnerID=8YFLogxK
U2 - 10.1109/TBME.2006.877796
DO - 10.1109/TBME.2006.877796
M3 - Article
C2 - 16916104
AN - SCOPUS:33746626906
VL - 53
SP - 1688
EP - 1695
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
SN - 0018-9294
IS - 8
M1 - 1658164
ER -