Phase-of-firing coding of natural visual stimuli in primary visual cortex (original) (raw)
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Natural Movies Evoke Spike Trains with Low Spike Time Variability in Cat Primary Visual Cortex
Journal of Neuroscience, 2011
Neuronal responses in primary visual cortex have been found to be highly variable. This has led to the widespread notion that neuronal responses have to be averaged over large numbers of neurons to obtain suitably invariant responses that can be used to reliably encode or represent external stimuli. However, it is possible that the high variability of neuronal responses may result from the use of simple, artificial stimuli and that the visual cortex may respond differently to dynamic, naturalistic images. To investigate this question, we recorded the responses of primary visual cortical neurons in the anesthetized cat under stimulation with time-varying natural movies. We found that cortical neurons on the whole exhibited a high degree of spike count variability, but a surprisingly low degree of spike time variability. The spike count variability was further reduced when all but the first spike in a burst were removed. We also found that responses exhibiting low spike time variability exhibited low spike count variability, suggesting that rate coding and temporal coding might be more compatible than previously thought. In addition, we found the spike time variability to be significantly lower when stimulated by natural movies as compared with stimulation using drifting gratings. Our results indicate that response variability in primary visual cortex is stimulus dependent and significantly lower than previous measurements have indicated.
The Possible Role of Spike Patterns in Cortical Information Processing
Journal of Computational Neuroscience, 2005
When the same visual stimulus is presented across many trials, neurons in the visual cortex receive stimulus-related synaptic inputs that are reproducible across trials (S) and inputs that are not (N). The variability of spike trains recorded in the visual cortex and their apparent lack of spike-to-spike correlations beyond that implied by firing rate fluctuations, has been taken as evidence for a low S/N ratio. A recent re-analysis of in vivo cortical data revealed evidence for spike-to-spike correlations in the form of spike patterns. We examine neural dynamics at a higher S/N in order to determine what possible role spike patterns could play in cortical information processing.
The Episodic Nature of Spike Trains in the Early Visual Pathway
Journal of Neurophysiology, 2010
An understanding of the neural code in a given visual area is often confounded by the immense complexity of visual stimuli combined with the number of possible meaningful patterns that comprise the response spike train. In the lateral geniculate nucleus (LGN), visual stimulation generates spike trains comprised of short spiking episodes ("events") separated by relatively long intervals of silence, which establishes a basis for in-depth analysis of the neural code. By studying this event structure in both artificial and natural visual stimulus contexts and at different contrasts, we are able to describe the dependence of event structure on stimulus class and discern which aspects generalize. We find that the event structure on coarse time scales is robust across stimulus and contrast and can be explained by receptive field processing. However, the relationship between the stimulus and fine-time-scale features of events is less straightforward, partially due to a significant amount of trial-to-trial variability. A new measure called "label information" identifies structural elements of events that can contain Յ30% more information in the context of natural movies compared with what is available from the overall event timing. The first interspike interval of an event most robustly conveys additional information about the stimulus and is somewhat more informative than the event spike count and much more informative than the presence of bursts. Nearly every event is preserved across contrast despite changes in their fine-timescale features, suggesting that-at least on a coarse level-the stimulus selectivity of LGN neurons is contrast invariant. Event-based analysis thus casts previously studied elements of LGN coding such as contrast adaptation and receptive field processing in a new light and leads to broad conclusions about the composition of the LGN neuronal code.
Journal of Computational Neuroscience, 1997
To analyze the information provided about individual visual stimuli in the responses of single neurons in the primate temporal lobe visual cortex, neuronal responses to a set of 65 visual stimuli were recorded in macaques performing a visual fixation task and analyzed using information theoretical measures. The population of neurons analyzed responded primarily to faces. The stimuli included 23 faces and 42 nonface images of real-world scenes, so that the function of this brain region could be analyzed when it was processing relatively natural scenes.
Overview of facts and issues about neural coding by spikes
2009
In the present overview, our wish is to demystify some aspects of coding with spike-timing, through a simple review of well-understood technical facts regarding spike coding. Our goal is a better understanding of the extent to which computing and modeling with spiking neuron networks might be biologically plausible and computationally efficient. We intentionally restrict ourselves to a deterministic imp lementation