The accuracy of membrane potential reconstruction based on spiking receptive fields

Center for Perceptual Systems, Section of Neurobiology, School of Biological Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX, USA.
Journal of Neurophysiology (Impact Factor: 2.89). 01/2012; 107(8):2143-53. DOI: 10.1152/jn.01176.2011
Source: PubMed


A common technique used to study the response selectivity of neurons is to measure the relationship between sensory stimulation and action potential responses. Action potentials, however, are only indirectly related to the synaptic inputs that determine the underlying, subthreshold, response selectivity. We present a method to predict membrane potential, the measurable result of the convergence of synaptic inputs, based on spike rate alone and then test its utility by comparing predictions to actual membrane potential recordings from simple cells in primary visual cortex. Using a noise stimulus, we found that spike rate receptive fields were in precise correspondence with membrane potential receptive fields (R(2) = 0.74). On average, spike rate alone could predict 44% of membrane potential fluctuations to dynamic noise stimuli, demonstrating the utility of this method to extract estimates of subthreshold responses. We also found that the nonlinear relationship between membrane potential and spike rate could also be extracted from spike rate data alone by comparing predictions from the noise stimulus with the actual spike rate. Our analysis reveals that linear receptive field models extracted from noise stimuli accurately reflect the underlying membrane potential selectivity and thus represent a method to generate estimates of the underlying average membrane potential from spike rate data alone.

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    • "In order to avoid the spurious impact of low level firing on the STA estimate of the spiking receptive field, we computed intracellular estimates of linear kernel with DN to recover the linear prediction of the response waveform without being concerned by noise contamination. Our results confirm the previous claim of accuracy of Vm reconstruction based on the spiking RF (Mohanty et al., 2012) when using DN stimuli only. Concerning low spatial frequencies, the DN noise stimulates equally all the spatial frequencies, so there is no a priori reason to believe that it could not estimate properly the low spatial frequencies. "
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    ABSTRACT: Synaptic Noise is thought to be a limiting factor for computational efficiency in the Brain. In visual cortex (V1), ongoing activity is present in vivo, and spiking responses to simple stimuli are highly unreliable across trials. Stimulus statistics used to plot receptive fields, however, are quite different from those experienced during natural visuomotor exploration. We recorded V1 neurons intracellularly in the anaesthetized and paralyzed cat and compared their spiking and synaptic responses to full field natural images animated by simulated eye-movements to those evoked by simpler (grating) or higher dimensionality statistics (dense noise). In most cells, natural scene animation was the only condition where high temporal precision (in the 10-20 ms range) was maintained during sparse and reliable activity. At the subthreshold level, irregular but highly reproducible membrane potential dynamics were observed, even during long (several 100 ms) “spike-less” periods. We showed that both the spatial structure of natural scenes and the temporal dynamics of eye-movements increase the signal-to-noise ratio by a non linear amplification of the signal combined with a reduction of the subthreshold contextual noise. These data support the view that the sparsening and the time precision of the neural code in V1 may depend primarily on three factors: 1) broadband input spectrum: the bandwidth must be rich enough for recruiting optimally the diversity of spatial and time constants during recurrent processing; 2) tight temporal interplay of excitation and inhibition: conductance measurements demonstrate that natural scene statistics narrow selectively the duration of the spiking opportunity window during which the balance between excitation and inhibition changes transiently and reversibly; 3) signal energy in the lower frequency band: a minimal level of power is needed below 10 Hz to reach consistently the spiking threshold, a situation rarely reached with visual dense noise.
    Full-text · Article · Dec 2013 · Frontiers in Neural Circuits
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    • "Review comparable to that recorded directly from V m responses (Mohanty et al., 2012). Threshold is also likely to provide the explanation for why pharmacological blockade of GABA A -mediated inhibition broadens orientation tuning in cortical cells (Sillito, 1975). "
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    ABSTRACT: Orientation selectivity in the primary visual cortex (V1) is a receptive field property that is at once simple enough to make it amenable to experimental and theoretical approaches and yet complex enough to represent a significant transformation in the representation of the visual image. As a result, V1 has become an area of choice for studying cortical computation and its underlying mechanisms. Here we consider the receptive field properties of the simple cells in cat V1--the cells that receive direct input from thalamic relay cells--and explore how these properties, many of which are highly nonlinear, arise. We have found that many receptive field properties of V1 simple cells fall directly out of Hubel and Wiesel's feedforward model when the model incorporates realistic neuronal and synaptic mechanisms, including threshold, synaptic depression, response variability, and the membrane time constant.
    Preview · Article · Jul 2012 · Neuron
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    ABSTRACT: Intracellular records in the neocortex reveal not only the membrane potential of neurons, but small unipolar or bipolar deflections that are termed spikelets. Spikelets have been proposed to originate from various sources, including active dendritic mechanisms, gap junctions, or extracellular signals. Here we examine the functional characteristics of spikelets measured in neurons from cat primary visual cortex in vivo. Spiking statistics and our functional characterization of spikelet activity indicate they originate from a separate, nearby cell. Spikelet kinetics and lack of a direct effect on spikelet activity from hyperpolarizing current injection suggest they do not arise from electrical coupling to the principal neuron being recorded. Spikelets exhibited matched orientation tuning preference and ocular dominance to the principal neuron. In contrast, binocular disparity preferences of spikelets and the principal neuron were unrelated. Finally, we examined the impact of spikelets on the principal neuron's membrane potential; we did observe some records for which spikelets were correlated with the membrane potential of the principal neuron, suggesting that these neurons were synaptically coupled or received common input from the cortical network. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
    No preview · Article · Sep 2015 · The Journal of Physiology