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[edit] Cortical Receptive fields and spatial spread

    Posted by: YOU today

Nicole C. Rust, Odelia Schwartz, J. Anthony Movshon, and Eero P. Simoncelli1
Neuron / 16 June 2005
New York University
    Neurons in primary visual cortex (V1) are commonly classified as simple or complex based upon their sensitivity to the sign of stimulus contrast. The responses of both cell types can be described by a general model in which the outputs of a set of linear filters are nonlinearly combined. We estimated the model for a population of V1 neurons by analyzing the mean and covariance of the spatiotemporal distribution of random bar stimuli that were associated with spikes. This analysis reveals an unsuspected richness of neuronal computation within V1. Specifically, simple and complex cell responses are best described using more linear filters than the one or two found in standard models. Many filters revealed by the model contribute suppressive signals that appear to have a predominantly divisive influence on neuronal firing. Suppressive signals are especially potent in direction-selective cells, where they reduce responses to stimuli moving in the nonpreferred direction.
    Posted by: JW, 12.30.2009

Bao-hua Liu, Pingyang Li, Yujiao J Sun, Ya-tang Li, Li I Zhang & Huizhong Whit Tao
Nature Neuroscience / 29 November 2009
University of Southern California, Los Angeles, California, USA
    Synaptic inputs underlying spike receptive fields are important for understanding mechanisms of neuronal processing. Using whole-cell voltage-clamp recordings from neurons in mouse primary visual cortex, we examined the spatial patterns of their excitatory and inhibitory synaptic inputs evoked by On and Off stimuli. Neurons with either segregated or overlapped On/Off spike subfields had substantial overlaps between all the four synaptic subfields. The segregated receptive-field structures were generated by the integration of excitation and inhibition with a stereotypic 'overlap-but-mismatched' pattern: the peaks of excitatory On/Off subfields were separated and flanked colocalized peaks of inhibitory On/Off subfields. The small mismatch of excitation/inhibition led to an asymmetric inhibitory shaping of On/Off spatial tunings, resulting in a great enhancement of their distinctiveness. Thus, slightly separated On/Off excitation, together with intervening inhibition, can create simple-cell receptive-field structure and the dichotomy of receptive-field structures may arise from a fine-tuning of the spatial arrangement of synaptic inputs..
    Posted by: JW, 12/30.09

Laura Busse1, Alex R. Wade and Matteo Carandini
Neuron / 24 December 2009
University College London, Smith-Kettlewell Eye Research Institute , UCSF
    How do neuronal populations represent concurrent stimuli? We measured population responses in cat primary visual cortex (V1) using electrode arrays. Population responses to two superimposed gratings were weighted sums of the individual grating responses. The weights depended strongly on the relative contrasts of the gratings. When the contrasts were similar, the population performed an approximately equal summation. When the contrasts differed markedly, however, the population performed approximately a winner-take-all competition. Stimuli that were intermediate to these extremes elicited intermediate responses. This entire range of behaviors was explained by a single model of contrast normalization. Normalization captured both the spike responses and the local field potential responses; it even predicted visually evoked currents source-localized to V1 in human subjects. Normalization has profound effects on V1 population responses and is likely to shape the interpretation of these responses by higher cortical areas..
    Posted by: JW, 12.30.2009

Yiu Fai Sit, Yuzhi Chen, Wilson S. Geisler, Risto Miikkulainen and Eyal Seidemann
Neuron / 24 December 2009
The University of Texas at Austin
    To understand sensory encoding and decoding, it is essential to characterize the dynamics of population responses in sensory cortical areas. Using voltage-sensitive dye imaging in awake, fixating monkeys, we obtained complete quantitative measurements of the spatiotemporal dynamics of V1 responses over the entire region activated by small, briefly presented stimuli. The responses exhibit several complex properties: they begin to rise approximately simultaneously over the entire active region, but reach their peak more rapidly at the center. However, at stimulus offset the responses fall simultaneously and at the same rate at all locations. Although response onset depends on stimulus contrast, both the peak spatial profile and the offset dynamics are independent of contrast. We show that these results are consistent with a simple population gain-control model that generalizes earlier single-neuron contrast gain-control models. This model provides valuable insight and is likely to be applicable to other brain areas..
    Posted by: JW, 12.30.2009

Yevgeniy B. Sirotin, Elizabeth M. C. Hillman, Clemence Bordier and Aniruddha Das
PNAS / October 27, 2009
Columbia University
    In functional brain imaging there is controversy over which hemodynamic signal best represents neural activity. Intrinsic signal optical imaging (ISOI) suggests that the best signal is the early darkening observed at wavelengths absorbed preferentially by deoxyhemoglobin (HbR). It is assumed that this darkening or “initial dip” reports local conversion of oxyhemoglobin (HbO) to HbR, i.e., oxygen consumption caused by local neural activity, thus giving the most specific measure of such activity. The blood volume signal, by contrast, is believed to be more delayed and less specific. Here, we used multiwavelength ISOI to simultaneously map oxygenation and blood volume [i.e., total hemoglobin (HbT)] in primary visual cortex (V1) of the alert macaque. We found that the hemodynamic “point spread,” i.e., impulse response to a minimal visual stimulus, was as rapid and retinotopically specific when imaged by using blood volume as when using the initial dip. Quantitative separation of the imaged signal into HbR, HbO, and HbT showed, moreover, that the initial dip was dominated by a fast local increase in HbT, with no increase in HbR. We found only a delayed HbR decrease that was broader in retinotopic spread than HbO or HbT. Further, we show that the multiphasic time course of typical ISOI signals and the strength of the initial dip may reflect the temporal interplay of monophasic HbO, HbR, and HbT signals. Characterizing the hemodynamic response is important for understanding neurovascular coupling and elucidating the physiological basis of imaging techniques such as fMRI. .
    Posted by: JW, 12.30.2009

G. Bjorn Christianson, Maneesh Sahani, and Jennifer F. Linden
The Journal of Neuroscience / January 9, 2008
University College London
    Neurons in the central auditory system are often described by the spectrotemporal receptive field (STRF), conventionally defined as the best linear fit between the spectrogram of a sound and the spike rate it evokes. An STRF is often assumed to provide an estimate of the receptive field of a neuron, i.e., the spectral and temporal range of stimuli that affect the response. However, when the true stimulus–response function is nonlinear, the STRF will be stimulus dependent, and changes in the stimulus properties can alter estimates of the sign and spectrotemporal extent of receptive field components. We demonstrate analytically and in simulations that, even when uncorrelated stimuli are used, interactions between simple neuronal nonlinearities and higher-order structure in the stimulus can produce STRFs that show contributions from time–frequency combinations to which the neuron is actually insensitive. Only when spectrotemporally independent stimuli are used does the STRF reliably indicate features of the underlying receptive field, and even then it provides only a conservative estimate. One consequence of these observations, illustrated using natural stimuli, is that a stimulus-induced change in an STRF could arise from a consistent but nonlinear neuronal response to stimulus ensembles with differing higher-order dependencies. Thus, although the responses of higher auditory neurons may well involve adaptation to the statistics of different stimulus ensembles, stimulus dependence of STRFs alone, or indeed of any overly constrained stimulus–response mapping, cannot demonstrate the nature or magnitude of such effects. .
    Posted by: JW, 12.30.2009. This one is on the auditory system, but deals with many of the same issues of non-linear receptive fields that we face with visual receptive fields. Suggested by Rory.

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