Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity

Valois, Russell L. De; Cottaris, Nicolas P.; Mahon, Luke; Elfar, S.D.; Wilson, Joshua

doi:10.1016/s0042-6989(00)00210-8

Cited by 161 publications

(258 citation statements)

References 46 publications

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“…Neurons in the magnocellular stream are typically more sensitive to low spatial frequencies and have shorter response latencies than those in the parvocellular stream (21,22). Consistent with other recent studies (27,28), this finding suggests that single V1 neurons receive convergent input from the magno-and parvocellular processing streams.…”

Section: Discussionsupporting

confidence: 89%

Spatial frequency and orientation tuning dynamics in area V1

Mazer

Vinje²,

McDermott³

et al. 2002

Proc. Natl. Acad. Sci. U.S.A.

263

246

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Spatial frequency (SF) and orientation tuning are intrinsic properties of neurons in primary visual cortex (area V1). To investigate the neural mechanisms mediating selectivity in the awake animal, we measured the temporal dynamics of SF and orientation tuning. We adapted a high-speed reverse-correlation method previously used to characterize orientation tuning dynamics in anesthetized animals to estimate efficiently the complete spatiotemporal receptive fields in area V1 of behaving macaques. We found that SF and orientation tuning are largely separable over time in single neurons. However, spatiotemporal receptive fields also contain a small nonseparable component that reflects a significant difference in response latency for low and high SF stimuli. The observed relationship between stimulus SF and latency represents a dynamic shift in SF tuning, and suggests that single V1 neurons might receive convergent input from the magno-and parvocellular processing streams. Although previous studies with anesthetized animals suggested that orientation tuning could change dramatically over time, we find no substantial evidence of dynamic changes in orientation tuning.reverse correlation ͉ striate cortex S patial frequency (SF) and orientation tuning are two of the most prominent features of neuronal selectivity in primary visual cortex (area V1) (1). The dynamics of SF and orientation tuning and their interactions are of particular interest to neurophysiologists because they can reveal important information about the specific circuits and mechanisms of neuronal selectivity (2). Dynamic tuning properties may also be critical for understanding natural vision, where eye movements can introduce complex temporal stimulus dynamics (3, 4).We simultaneously measured the temporal dynamics of both SF and orientation tuning in single V1 neurons in the awake primate. Conventional methods for estimating selectivity in V1 use stationary or drifting gratings of constant SF and orientation. Stimuli are presented for relatively long periods (0.3-1 s), and responses are quantified by mean firing rate. Often one stimulus parameter is varied at a time (e.g., orientation tuning is measured at the best SF). Although this approach can yield accurate orientation and SF tuning estimates, it fails to capture both stimulus interactions and temporal response dynamics that can be obscured by nonspecific onset transients. In addition, methods based on static stimuli can be time-consuming. Efficient characterization methods are particularly important when working with behaving animals, where time is almost always at a premium.One efficient way to characterize tuning that also captures temporal response dynamics is to estimate spatiotemporal receptive fields (STRFs) by using reverse correlation. The STRF describes the probability that a particular spatial stimulus will elicit a spike at a particular latency. In effect, the STRF provides a linear model of a neuron's spatiotemporal filtering characteristics (5, 6).In the visual system, STRFs are traditi...

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Section: Discussionsupporting

confidence: 89%

Spatial frequency and orientation tuning dynamics in area V1

Mazer

Vinje²,

McDermott³

et al. 2002

Proc. Natl. Acad. Sci. U.S.A.

263

246

View full text Add to dashboard Cite

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“…to identify (De Valois and Cottaris, 1998;De Valois et al, 2000;Livingstone and Conway, 2007;Priebe et al, 2010), and, as a consequence, the relative spatial configuration of these inputs remains unknown. We believe the stereotyped and welldescribed input architecture to T4 and T5, combined with our measurements and modeling of their STRFs, will pave the way for new mechanistic models to reveal the specific contributions of individual cell types to the generation of the highly structured, spatiotemporally tilted T4 and T5 STRFs.…”

Section: Complementary Genetic and Functional Approaches To Isolatingmentioning

confidence: 99%

Direction Selectivity in Drosophila Emerges from Preferred-Direction Enhancement and Null-Direction Suppression

Leong¹,

Esch

Poole³

et al. 2016

Journal of Neuroscience

118

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Across animal phyla, motion vision relies on neurons that respond preferentially to stimuli moving in one, preferred direction over the opposite, null direction. In the elementary motion detector of Drosophila, direction selectivity emerges in two neuron types, T4 and T5, but the computational algorithm underlying this selectivity remains unknown. We find that the receptive fields of both T4 and T5 exhibit spatiotemporally offset light-preferring and dark-preferring subfields, each obliquely oriented in spacetime. In a linear-nonlinear modeling framework, the spatiotemporal organization of the T5 receptive field predicts the activity of T5 in response to motion stimuli. These findings demonstrate that direction selectivity emerges from the enhancement of responses to motion in the preferred direction, as well as the suppression of responses to motion in the null direction. Thus, remarkably, T5 incorporates the essential algorithmic strategies used by the Hassenstein-Reichardt correlator and the Barlow-Levick detector. Our model for T5 also provides an algorithmic explanation for the selectivity of T5 for moving dark edges: our model captures all two-and three-point spacetime correlations relevant to motion in this stimulus class. More broadly, our findings reveal the contribution of input pathway visual processing, specifically centersurround, temporally biphasic receptive fields, to the generation of direction selectivity in T5. As the spatiotemporal receptive field of T5 in Drosophila is common to the simple cell in vertebrate visual cortex, our stimulus-response model of T5 will inform efforts in an experimentally tractable context to identify more detailed, mechanistic models of a prevalent computation.

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“…These models have gained wide use in physiologically inspired computer simulations of motion perception (Heeger, 1987;Grzywacz and Yuille, 1990;Nowlan and Sejnowski, 1995;Simoncelli and Heeger, 1998) and have received additional support from experimental studies (Reid et al, 1991;Emerson et al, 1992;Emerson, 1997;De Valois et al, 2000;Touryan et al, 2002). If the response of a DS neuron can be described effectively by such simple combinations of spatiotemporal filters, then the envelop of the filter, essentially the receptive field (RF) profile, should be stable for a given cell and easily mapped in space and time (Touryan et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Adaptive Temporal Integration of Motion in Direction-Selective Neurons in Macaque Visual Cortex

Bair¹,

Movshon²

2004

J. Neurosci.

123

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Direction-selective neurons in the primary visual cortex (V1) and the extrastriate motion area MT/V5 constitute a critical channel that links early cortical mechanisms of spatiotemporal integration to downstream signals that underlie motion perception. We studied how temporal integration in direction-selective cells depends on speed, spatial frequency (SF), and contrast using randomly moving sinusoidal gratings and spike-triggered average (STA) analysis. The window of temporal integration revealed by the STAs varied substantially with stimulus parameters, extending farther back in time for slow motion, high SF, and low contrast. At low speeds and high SF, STA peaks were larger, indicating that a single spike often conveyed more information about the stimulus under conditions in which the mean firing rate was very low. The observed trends were similar in V1 and MT and offer a physiological correlate for a large body of psychophysical data on temporal integration. We applied the same visual stimuli to a model of motion detection based on oriented linear filters (a motion energy model) that incorporated an integrate-and-fire mechanism and found that it did not account for the neuronal data. Our results show that cortical motion processing in V1 and in MT is highly nonlinear and stimulus dependent. They cast considerable doubt on the ability of simple oriented filter models to account for the output of direction-selective neurons in a general manner. Finally, they suggest that spike rate tuning functions may miss important aspects of the neural coding of motion for stimulus conditions that evoke low firing rates.

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Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity

Cited by 161 publications

References 46 publications

Spatial frequency and orientation tuning dynamics in area V1

Spatial frequency and orientation tuning dynamics in area V1

Direction Selectivity in Drosophila Emerges from Preferred-Direction Enhancement and Null-Direction Suppression

Adaptive Temporal Integration of Motion in Direction-Selective Neurons in Macaque Visual Cortex

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