19,835 research outputs found
Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation
To date a number of studies have shown that receptive field shapes of early
sensory neurons can be reproduced by optimizing coding efficiency of natural
stimulus ensembles. A still unresolved question is whether the efficient coding
hypothesis explains formation of neurons which explicitly represent
environmental features of different functional importance. This paper proposes
that the spatial selectivity of higher auditory neurons emerges as a direct
consequence of learning efficient codes for natural binaural sounds. Firstly,
it is demonstrated that a linear efficient coding transform - Independent
Component Analysis (ICA) trained on spectrograms of naturalistic simulated
binaural sounds extracts spatial information present in the signal. A simple
hierarchical ICA extension allowing for decoding of sound position is proposed.
Furthermore, it is shown that units revealing spatial selectivity can be
learned from a binaural recording of a natural auditory scene. In both cases a
relatively small subpopulation of learned spectrogram features suffices to
perform accurate sound localization. Representation of the auditory space is
therefore learned in a purely unsupervised way by maximizing the coding
efficiency and without any task-specific constraints. This results imply that
efficient coding is a useful strategy for learning structures which allow for
making behaviorally vital inferences about the environment.Comment: 22 pages, 9 figure
Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information
Local field potentials (LFPs) reflect subthreshold integrative processes that complement spike train measures. However, little is yet known about the differences between how LFPs and spikes encode rich naturalistic sensory stimuli. We addressed this question by recording LFPs and spikes from the primary visual cortex of anesthetized macaques while presenting a color movie.Wethen determined
how the power of LFPs and spikes at different frequencies represents the visual features in the movie.Wefound that the most informative LFP frequency ranges were 1– 8 and 60 –100 Hz. LFPs in the range of 12– 40 Hz carried little information about the stimulus, and may primarily reflect neuromodulatory inputs. Spike power was informative only at frequencies <12 Hz. We further quantified “signal
correlations” (correlations in the trial-averaged power response to different stimuli) and “noise correlations” (trial-by-trial correlations in the fluctuations around the average) of LFPs and spikes recorded from the same electrode. We found positive signal correlation between high-gamma LFPs (60 –100 Hz) and spikes, as well as strong positive signal correlation within high-gamma LFPs, suggesting that high-gamma LFPs and spikes are generated within the same network. LFPs<24 Hz shared strong positive noise correlations, indicating that they are influenced by a common source, such as a diffuse neuromodulatory input. LFPs<40 Hz showed very little signal and noise correlations with LFPs>40Hzand with spikes, suggesting that low-frequency LFPs reflect neural processes that in natural conditions are fully decoupled from those giving rise to spikes and to high-gamma LFPs
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