Cone Inputs in Macaque Primary Visual Cortex

2004 ◽  
Vol 91 (6) ◽  
pp. 2501-2514 ◽  
Author(s):  
Elizabeth N. Johnson ◽  
Michael J. Hawken ◽  
Robert Shapley
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Weight Ratio ◽  
Broad Distribution ◽  
V1 Neurons ◽  
A Value ◽  
Cone Type ◽  
Almost All

To understand the role of primary visual cortex (V1) in color vision, we measured directly the input from the 3 cone types in macaque V1 neurons. Cells were classified as luminance-preferring, color-luminance, or color-preferring from the ratio of the peak amplitudes of spatial frequency responses to red/green equiluminant and to black/white (luminance) grating patterns, respectively. In this study we used L-, M-, and S-cone–isolating gratings to measure spatial frequency response functions for each cone type separately. From peak responses to cone-isolating stimuli we estimated relative cone weights and whether cone inputs were the same or opposite sign. For most V1 cells the relative S-cone weight was <0.1. All color-preferring cells were cone opponent and their L/M cone weight ratio was clustered around a value of –1, which is roughly equal and opposite L and M cone signals. Almost all cells (88%) classified as luminance cells were cone nonopponent, with a broad distribution of cone weights. Most cells (73%) classified as color-luminance cells were cone opponent. This result supports our conclusion that V1 color-luminance cells are double-opponent. Such neurons are more sensitive to color boundaries than to areas of color and thereby could play an important role in color perception. The color-luminance population had a broad distribution of L/M cone weight ratios, implying a broad distribution of preferred colors for the double-opponent cells.

scholarly journals Coherent representations of subjective spatial position in primary visual cortex and hippocampus

2017 ◽  
Author(s):  
Aman B. Saleem ◽  
E. Mika Diamanti ◽  
Julien Fournier ◽  
Kenneth D. Harris ◽  
Matteo Carandini
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Spatial Location ◽  
Visual Responses ◽  
V1 Neurons ◽  
Neuronal Populations ◽  
Subjective Estimate ◽  
Ca1 Region ◽  
Navigational Systems

A major role of vision is to guide navigation, and navigation is strongly driven by vision1-4. Indeed, the brain’s visual and navigational systems are known to interact5, 6, and signals related to position in the environment have been suggested to appear as early as in visual cortex6, 7. To establish the nature of these signals we recorded in primary visual cortex (V1) and in the CA1 region of the hippocampus while mice traversed a corridor in virtual reality. The corridor contained identical visual landmarks in two positions, so that a purely visual neuron would respond similarly in those positions. Most V1 neurons, however, responded solely or more strongly to the landmarks in one position. This modulation of visual responses by spatial location was not explained by factors such as running speed. To assess whether the modulation is related to navigational signals and to the animal’s subjective estimate of position, we trained the mice to lick for a water reward upon reaching a reward zone in the corridor. Neuronal populations in both CA1 and V1 encoded the animal’s position along the corridor, and the errors in their representations were correlated. Moreover, both representations reflected the animal’s subjective estimate of position, inferred from the animal’s licks, better than its actual position. Indeed, when animals licked in a given location – whether correct or incorrect – neural populations in both V1 and CA1 placed the animal in the reward zone. We conclude that visual responses in V1 are tightly controlled by navigational signals, which are coherent with those encoded in hippocampus, and reflect the animal’s subjective position in the environment. The presence of such navigational signals as early as in a primary sensory area suggests that these signals permeate sensory processing in the cortex.

scholarly journals Model-based characterization of the selectivity of neurons in primary visual cortex

2021 ◽  
Author(s):  
Felix Bartsch ◽  
Bruce G Cumming ◽  
Daniel A Butts
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Visual Processing ◽  
Frequency Tuning ◽  
Nonlinear Models ◽  
Field Size ◽  
V1 Neurons ◽  
Model Based ◽  
Spatial Frequencies

To understand the complexity of stimulus selectivity in primary visual cortex (V1), models constructed to match observed responses to complex time-varying stimuli, instead of to explain responses to simple parametric stimuli, are increasingly used. While such models often can more accurately reflect the computations performed by V1 neurons in more natural visual environments, they do not by themselves provide insight into established measures of V1 neural selectivity such as receptive field size, spatial frequency tuning and phase invariance. Here, we suggest a series of analyses that can be directly applied to encoding models to link complex encoding models to more interpretable aspects of stimulus selectivity, applied to nonlinear models of V1 neurons recorded in awake macaque in response to random bar stimuli. In linking model properties to more classical measurements, we demonstrate several novel aspects of V1 selectivity not available to simpler experimental measurements. For example, we find that individual spatiotemporal elements of the V1 models often have a smaller spatial scale than the overall neuron sensitivity, and that this results in non-trivial tuning to spatial frequencies. Additionally, our proposed measures of nonlinear integration suggest that more classical classifications of V1 neurons into simple versus complex cells are spatial-frequency dependent. In total, rather than obfuscate classical characterizations of V1 neurons, model-based characterizations offer a means to more fully understand their selectivity, and provide a means to link their classical tuning properties to their roles in more complex, natural, visual processing.

scholarly journals Adaptation to contingencies in macaque primary visual cortex

1997 ◽  
Vol 352 (1358) ◽  
pp. 1149-1154 ◽  
Author(s):  
Matteo Carandini ◽  
Horace B. Barlow ◽  
Lawrence P. O'keefe ◽  
Allen B. Poirson ◽  
J. Anthony Movshon
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Compound Stimulus ◽  
The Other ◽  
Single Neurons ◽  
Simultaneous Presence ◽  
V1 Neurons ◽  
Series Of Experiments ◽  
The Individual

We tested the hypothesis that neurons in the primary visual cortex adapt selectively to contingencies in the attributes of visual stimuli. We recorded from single neurons in macaque V1 and measured the effects of adaptation either to the sum of two gratings (compound stimulus) or to the individual gratings. According to our hypothesis, there would be a component of adaptation that is specific to the compound stimulus. In a first series of experiments, the two gratings differed in orientation. One grating had optimal orientation and the other was orthogonal to it, and therefore did not activate the neuron under study. These experiments provided evidence in favour of our hypothesis. In most cells adaptation to the compound stimulus reduced responses to the compound stimulus more than it reduced responses to the optimal grating, and adaptation to the optimal grating reduced responses to the optimal grating more than it reduced responses to the compound stimulus. This suggests that a component of adaptation was specific to (and caused by) the simultaneous presence of the two orientations in the compound stimulus. To test whether V1 neurons could adapt to other contingencies in the stimulus attributes, we performed a second series of experiments, in which the component gratings were parallel but differed in spatial frequency, and were both effective in activating the neuron under study. These experiments failed to reveal convincing contingent effects of adaptation, suggesting that neurons cannot adapt equally well to all types of contingency.

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.

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.

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