Neural responses to relative speed in the primary visual cortex of rhesus monkey

2003 ◽  
Vol 20 (1) ◽  
pp. 77-84 ◽  
Author(s):  
AN CAO ◽  
PETER H. SCHILLER
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Relative Motion ◽  
Motion Parallax ◽  
Relative Speed ◽  
Neural Responses ◽  
Tuning Curves ◽  
V1 Neurons ◽  
Cortex Area ◽  
Ground Segmentation

Relative motion information, especially relative speed between different input patterns, is required for solving many complex tasks of the visual system, such as depth perception by motion parallax and motion-induced figure/ground segmentation. However, little is known about the neural substrate for processing relative speed information. To explore the neural mechanisms for relative speed, we recorded single-unit responses to relative motion in the primary visual cortex (area V1) of rhesus monkeys while presenting sets of random-dot arrays moving at different speeds. We found that most V1 neurons were sensitive to the existence of a discontinuity in speed, that is, they showed higher responses when relative motion was presented compared to homogenous field motion. Seventy percent of the neurons in our sample responded predominantly to relative rather than to absolute speed. Relative speed tuning curves were similar at different center–surround velocity combinations. These relative motion-sensitive neurons in macaque area V1 probably contribute to figure/ground segmentation and motion discontinuity detection.

scholarly journals Suppression of Neural Responses to Nonoptimal Stimuli Correlates With Tuning Selectivity in Macaque V1

2002 ◽  
Vol 87 (2) ◽  
pp. 1018-1027 ◽  
Author(s):  
D. L. Ringach ◽  
C. E. Bredfeldt ◽  
R. M. Shapley ◽  
M. J. Hawken
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Neural Circuitry ◽  
Response Suppression ◽  
Neural Responses ◽  
Firing Rates ◽  
V1 Neurons ◽  
Cortex Area ◽  
Sinusoidal Gratings ◽  
Feed Forward Inhibition

Neural responses in primary visual cortex (area V1) are selective for the orientation and spatial frequency of luminance-modulated sinusoidal gratings. Selectivity could arise from enhancement of the cell's response by preferred stimuli, suppression by nonoptimal stimuli, or both. Here, we report that the majority of V1 neurons do not only elevate their activity in response to preferred stimuli, but their firing rates are also suppressed by nonoptimal stimuli. The magnitude of suppression is similar to that of enhancement. There is a tendency for net response suppression to peak at orientations near orthogonal to the optimal for the cell, but cases where suppression peaks at oblique orientations are observed as well. Interestingly, selectivity and suppression correlate in V1: orientation and spatial frequency selectivity are higher for neurons that are suppressed by nonoptimal stimuli than for cells that are not. This finding is consistent with the idea that suppression plays an important role in the generation of sharp cortical selectivity. We show that nonlinear suppression is required to account for the data. However, the precise structure of the neural circuitry generating the suppressive signal remains unresolved. Our results are consistent with both feedback and (nonlinear) feed-forward inhibition.

scholarly journals Causal role for sleep-dependent reactivation of learning-activated sensory ensembles for fear memory consolidation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Brittany C. Clawson ◽  
Emily J. Pickup ◽  
Amy Ensing ◽  
Laura Geneseo ◽  
James Shaver ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Memory Consolidation ◽  
Critical Role ◽  
Visual Presentation ◽  
Fear Memory ◽  
Memory Recall ◽  
Visual Cue ◽  
V1 Neurons ◽  
Targeted Recombination

AbstractLearning-activated engram neurons play a critical role in memory recall. An untested hypothesis is that these same neurons play an instructive role in offline memory consolidation. Here we show that a visually-cued fear memory is consolidated during post-conditioning sleep in mice. We then use TRAP (targeted recombination in active populations) to genetically label or optogenetically manipulate primary visual cortex (V1) neurons responsive to the visual cue. Following fear conditioning, mice respond to activation of this visual engram population in a manner similar to visual presentation of fear cues. Cue-responsive neurons are selectively reactivated in V1 during post-conditioning sleep. Mimicking visual engram reactivation optogenetically leads to increased representation of the visual cue in V1. Optogenetic inhibition of the engram population during post-conditioning sleep disrupts consolidation of fear memory. We conclude that selective sleep-associated reactivation of learning-activated sensory populations serves as a necessary instructive mechanism for memory consolidation.

scholarly journals A direct interareal feedback-to-feedforward circuit in primate visual cortex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Caitlin Siu ◽  
Justin Balsor ◽  
Sam Merlin ◽  
Frederick Federer ◽  
Alessandra Angelucci
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Projection Neurons ◽  
V1 Neurons ◽  
Cortical Areas ◽  
Area V2 ◽  
Computational Work ◽  
Primate Visual Cortex ◽  
Similar Area ◽  
Hierarchical Computation

AbstractThe mammalian sensory neocortex consists of hierarchically organized areas reciprocally connected via feedforward (FF) and feedback (FB) circuits. Several theories of hierarchical computation ascribe the bulk of the computational work of the cortex to looped FF-FB circuits between pairs of cortical areas. However, whether such corticocortical loops exist remains unclear. In higher mammals, individual FF-projection neurons send afferents almost exclusively to a single higher-level area. However, it is unclear whether FB-projection neurons show similar area-specificity, and whether they influence FF-projection neurons directly or indirectly. Using viral-mediated monosynaptic circuit tracing in macaque primary visual cortex (V1), we show that V1 neurons sending FF projections to area V2 receive monosynaptic FB inputs from V2, but not other V1-projecting areas. We also find monosynaptic FB-to-FB neuron contacts as a second motif of FB connectivity. Our results support the existence of FF-FB loops in primate cortex, and suggest that FB can rapidly and selectively influence the activity of incoming FF signals.

Differential contributions of magnocellular and parvocellular pathways to the contrast response of neurons in bush baby primary visual cortex (V1)

2000 ◽  
Vol 17 (1) ◽  
pp. 71-76 ◽  
Author(s):  
JOHN D. ALLISON ◽  
PETER MELZER ◽  
YUCHUAN DING ◽  
A.B. BONDS ◽  
VIVIEN A. CASAGRANDE
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Response Amplitude ◽  
Contrast Threshold ◽  
Peak Response ◽  
V1 Neurons ◽  
Bush Baby ◽  
High Stimulus ◽  
Average Contrast ◽  
Contrast Response

How neurons in the primary visual cortex (V1) of primates process parallel inputs from the magnocellular (M) and parvocellular (P) layers of the lateral geniculate nucleus (LGN) is not completely understood. To investigate whether signals from the two pathways are integrated in the cortex, we recorded contrast-response functions (CRFs) from 20 bush baby V1 neurons before, during, and after pharmacologically inactivating neural activity in either the contralateral LGN M or P layers. Inactivating the M layer reduced the responses of V1 neurons (n = 10) to all stimulus contrasts and significantly elevated (t = 8.15, P < 0.01) their average contrast threshold from 8.04 (± 4.1)% contrast to 22.46 (± 6.28)% contrast. M layer inactivation also significantly reduced (t = 4.06, P < 0.01) the average peak response amplitude. Inactivating the P layer did not elevate the average contrast threshold of V1 neurons (n = 10), but significantly reduced (t = 4.34, P < 0.01) their average peak response amplitude. These data demonstrate that input from the M pathway can account for the responses of V1 neurons to low stimulus contrasts and also contributes to responses to high stimulus contrasts. The P pathway appears to influence mainly the responses of V1 neurons to high stimulus contrasts. None of the cells in our sample, which included cells in all output layers of V1, appeared to receive input from only one pathway. These findings support the view that many V1 neurons integrate information about stimulus contrast carried by the LGN M and P pathways.

A model for the estimate of local image velocity by cells in the visual cortex

1990 ◽  
Vol 239 (1295) ◽  
pp. 129-161 ◽  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Spatial Integration ◽  
Temporal Area ◽  
Image Velocity ◽  
Tuning Curves ◽  
Spatio Temporal ◽  
Local Image

Some computational theories of motion perception assume that the first stage en route to this perception is the local estimate of image velocity. However, this assumption is not supported by data from the primary visual cortex. Its motion sensitive cells are not selective to velocity, but rather are directionally selective and tuned to spatio-temporal frequen­cies. Accordingly, physiologically based theories start with filters selec­tive to oriented spatio-temporal frequencies. This paper shows that computational and physiological theories do not necessarily conflict, because such filters may, as a population, compute velocity locally. To prove this point, we show how to combine the outputs of a class of frequency tuned filters to detect local image velocity. Furthermore, we show that the combination of filters may simulate ‘Pattern’ cells in the middle temporal area (MT), whereas each filter simulates primary visual cortex cells. These simulations include three properties of the primary cortex. First, the spatio-temporal frequency tuning curves of the in­dividual filters display approximate space-time separability. Secondly, their direction-of-motion tuning curves depend on the distribution of orientations of the components of the Fourier decomposition and speed of the stimulus. Thirdly, the filters show facilitation and suppression for responses to apparent motions in the preferred and null directions, respect­ively. It is suggested that the MT’s role is not to solve the aperture problem, but to estimate velocities from primary cortex information. The spatial integration that accounts for motion coherence may be postponed to a later cortical stage.

scholarly journals Traumatic brain injury to primary visual cortex produces long-lasting circuit dysfunction

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jan C. Frankowski ◽  
Andrzej T. Foik ◽  
Alexa Tierno ◽  
Jiana R. Machhor ◽  
David C. Lyon ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Visual Cortex ◽  
Brain Injury ◽  
Primary Visual Cortex ◽  
Visual Stimuli ◽  
Orientation Tuning ◽  
V1 Neurons ◽  
Adult Mice ◽  
Electrophysiological Recordings

AbstractPrimary sensory areas of the mammalian neocortex have a remarkable degree of plasticity, allowing neural circuits to adapt to dynamic environments. However, little is known about the effects of traumatic brain injury on visual circuit function. Here we used anatomy and in vivo electrophysiological recordings in adult mice to quantify neuron responses to visual stimuli two weeks and three months after mild controlled cortical impact injury to primary visual cortex (V1). We found that, although V1 remained largely intact in brain-injured mice, there was ~35% reduction in the number of neurons that affected inhibitory cells more broadly than excitatory neurons. V1 neurons showed dramatically reduced activity, impaired responses to visual stimuli and weaker size selectivity and orientation tuning in vivo. Our results show a single, mild contusion injury produces profound and long-lasting impairments in the way V1 neurons encode visual input. These findings provide initial insight into cortical circuit dysfunction following central visual system neurotrauma.

Parallel Advantage: Further Evidence for Bottom-up Saliency Computation by Human Primary Visual Cortex

Perception ◽  
2022 ◽  
Vol 51 (1) ◽  
pp. 60-69
Author(s):  
Li Zhaoping
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Surround Suppression ◽  
Bottom Up ◽  
Black Disk ◽  
V1 Neurons ◽  
Behavioral Observations ◽  
White Disk ◽  
Special Case

Finding a target among uniformly oriented non-targets is typically faster when this target is perpendicular, rather than parallel, to the non-targets. The V1 Saliency Hypothesis (V1SH), that neurons in the primary visual cortex (V1) signal saliency for exogenous attentional attraction, predicts exactly the opposite in a special case: each target or non-target comprises two equally sized disks displaced from each other by 1.2 disk diameters center-to-center along a line defining its orientation. A target has two white or two black disks. Each non-target has one white disk and one black disk, and thus, unlike the target, activates V1 neurons less when its orientation is parallel rather than perpendicular to the neurons’ preferred orientations. When the target is parallel, rather than perpendicular, to the uniformly oriented non-targets, the target’s evoked V1 response escapes V1’s iso-orientation surround suppression, making the target more salient. I present behavioral observations confirming this prediction.

scholarly journals Pure tones modulate the representation of orientation and direction in the primary visual cortex

2019 ◽  
Vol 121 (6) ◽  
pp. 2202-2214 ◽  
Author(s):  
John P. McClure ◽  
Pierre-Olivier Polack
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Stimulus ◽  
Visual Stimuli ◽  
Direction Selectivity ◽  
Multimodal Integration ◽  
Visual Responses ◽  
V1 Neurons ◽  
Pure Tones ◽  
The Impact

Multimodal sensory integration facilitates the generation of a unified and coherent perception of the environment. It is now well established that unimodal sensory perceptions, such as vision, are improved in multisensory contexts. Whereas multimodal integration is primarily performed by dedicated multisensory brain regions such as the association cortices or the superior colliculus, recent studies have shown that multisensory interactions also occur in primary sensory cortices. In particular, sounds were shown to modulate the responses of neurons located in layers 2/3 (L2/3) of the mouse primary visual cortex (V1). Yet, the net effect of sound modulation at the V1 population level remained unclear. In the present study, we performed two-photon calcium imaging in awake mice to compare the representation of the orientation and the direction of drifting gratings by V1 L2/3 neurons in unimodal (visual only) or multimodal (audiovisual) conditions. We found that sound modulation depended on the tuning properties (orientation and direction selectivity) and response amplitudes of V1 L2/3 neurons. Sounds potentiated the responses of neurons that were highly tuned to the cue’s orientation and direction but weakly active in the unimodal context, following the principle of inverse effectiveness of multimodal integration. Moreover, sound suppressed the responses of neurons untuned for the orientation and/or the direction of the visual cue. Altogether, sound modulation improved the representation of the orientation and direction of the visual stimulus in V1 L2/3. Namely, visual stimuli presented with auditory stimuli recruited a neuronal population better tuned to the visual stimulus orientation and direction than when presented alone. NEW & NOTEWORTHY The primary visual cortex (V1) receives direct inputs from the primary auditory cortex. Yet, the impact of sounds on visual processing in V1 remains controverted. We show that the modulation by pure tones of V1 visual responses depends on the orientation selectivity, direction selectivity, and response amplitudes of V1 neurons. Hence, audiovisual stimuli recruit a population of V1 neurons better tuned to the orientation and direction of the visual stimulus than unimodal visual stimuli.

Man's Triune Conscious Mind: Part III

1995 ◽  
Vol 81 (2) ◽  
pp. 463-466
Author(s):  
Carl G. Aurell
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Conscious Mind ◽  
Perceptual Model ◽  
Cortex Area ◽  
Layer 4

The perceptual model, discussed previously in Part II, is applied to the organization of the visual cortex in a search for “consciousness neurons,” i.e., sources of sensations, images, and percepts. It is hypothesized that these three conscious phenomena emerge in the primary visual cortex, Area VI, possibly from neurons in its Layer 4.

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