A recurrent circuit implements normalization, simulating the dynamics of V1 activity

The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model’s defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. Despite the success of the normalization model, there are three unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another’s normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can recapitulate key experimental observations of the dynamics of neural activity in V1.

Download Full-text

Dynamic Normalization

10.1101/2020.03.22.002634 ◽

2020 ◽

Cited By ~ 2

Author(s):

David J. Heeger ◽

Klavdia O. Zemlianova

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Neural Activity ◽

Complex Dynamics ◽

Gamma Oscillations ◽

Neural Systems ◽

New Family ◽

Wide Range ◽

Neural Computations ◽

Key Aspects

AbstractThe normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model’s defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. In spite of the success of the normalization model, there are 3 unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how nor-malization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another’s normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a new family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can reca-pitulate key experimental observations of the dynamics of neural activity in V1.Significance StatementA family of recurrent circuit models is proposed to explain the dynamics of neural activity in primary visual cortex (V1). Each of the models in this family exhibits steady state output responses that are already known to fit a wide range of experimental data from diverse neural systems. These models can recapitulate the complex dynamics of V1 activity, including oscillations (so-called gamma oscillations, ∼30-80 Hz). This theoretical framework may also be used to explain key aspects of working memory and motor control. Consequently, the same circuit architecture is applicable to a variety of neural systems, and V1 can be used as a model system for understanding the neural computations in many brain areas.

Download Full-text

Superimposed gratings induce diverse response patterns of gamma oscillations in primary visual cortex

Scientific Reports ◽

10.1038/s41598-021-83923-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Bin Wang ◽

Chuanliang Han ◽

Tian Wang ◽

Weifeng Dai ◽

Yang Li ◽

...

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Field Potential ◽

Gamma Oscillations ◽

Neural Mechanisms ◽

Model Parameters ◽

Response Patterns ◽

Region Difference ◽

High Gamma ◽

Spiking Activity

AbstractStimulus-dependence of gamma oscillations (GAMMA, 30–90 Hz) has not been fully understood, but it is important for revealing neural mechanisms and functions of GAMMA. Here, we recorded spiking activity (MUA) and the local field potential (LFP), driven by a variety of plaids (generated by two superimposed gratings orthogonal to each other and with different contrast combinations), in the primary visual cortex of anesthetized cats. We found two distinct narrow-band GAMMAs in the LFPs and a variety of response patterns to plaids. Similar to MUA, most response patterns showed that the second grating suppressed GAMMAs driven by the first one. However, there is only a weak site-by-site correlation between cross-orientation interactions in GAMMAs and those in MUAs. We developed a normalization model that could unify the response patterns of both GAMMAs and MUAs. Interestingly, compared with MUAs, the GAMMAs demonstrated a wider range of model parameters and more diverse response patterns to plaids. Further analysis revealed that normalization parameters for high GAMMA, but not those for low GAMMA, were significantly correlated with the discrepancy of spatial frequency between stimulus and sites’ preferences. Consistent with these findings, normalization parameters and diversity of high GAMMA exhibited a clear transition trend and region difference between area 17 to 18. Our results show that GAMMAs are also regulated in the form of normalization, but that the neural mechanisms for these normalizations might differ from those of spiking activity. Normalizations in different brain signals could be due to interactions of excitation and inhibitions at multiple stages in the visual system.

Download Full-text

Blindsight and Unconscious Vision: What They Teach Us about the Human Visual System

The Neuroscientist ◽

10.1177/1073858416673817 ◽

2016 ◽

Vol 23 (5) ◽

pp. 529-541 ◽

Cited By ~ 18

Author(s):

Sara Ajina ◽

Holly Bridge

Keyword(s):

Visual Cortex ◽

Visual System ◽

Primary Visual Cortex ◽

Neural Activity ◽

Human Visual System ◽

Visual Information ◽

Visual Loss ◽

Physiological Conditions ◽

The World ◽

The Brain

Damage to the primary visual cortex removes the major input from the eyes to the brain, causing significant visual loss as patients are unable to perceive the side of the world contralateral to the damage. Some patients, however, retain the ability to detect visual information within this blind region; this is known as blindsight. By studying the visual pathways that underlie this residual vision in patients, we can uncover additional aspects of the human visual system that likely contribute to normal visual function but cannot be revealed under physiological conditions. In this review, we discuss the residual abilities and neural activity that have been described in blindsight and the implications of these findings for understanding the intact system.

Download Full-text

Neural Representation of the Luminance and Brightness of a Uniform Surface in the Macaque Primary Visual Cortex

Journal of Neurophysiology ◽

10.1152/jn.2001.86.5.2559 ◽

2001 ◽

Vol 86 (5) ◽

pp. 2559-2570 ◽

Cited By ~ 107

Author(s):

Masaharu Kinoshita ◽

Hidehiko Komatsu

Keyword(s):

Visual Cortex ◽

Receptive Field ◽

Primary Visual Cortex ◽

Neural Activity ◽

Dynamic Range ◽

Neural Representation ◽

Homogeneous Surface ◽

V1 Neurons ◽

Classical Receptive Field ◽

Multiple Unit

The perceived brightness of a surface is determined not only by the luminance of the surface (local information), but also by the luminance of its surround (global information). To better understand the neural representation of surface brightness, we investigated the effects of local and global luminance on the activity of neurons in the primary visual cortex (V1) of awake macaque monkeys. Single- and multiple-unit recordings were made from V1 while the monkeys were performing a visual fixation task. The classical receptive field of each neuron was identified as a region responding to a spot stimulus. Neural responses were assessed using homogeneous surfaces at least three times as large as the receptive field as stimuli. We first examined the sensitivity of neurons to variation in local surface luminance, while the luminance of the surround was held constant. The activity of a large majority of surface-responsive neurons (106/115) varied monotonically with changes in surface luminance; in some the dynamic range was over 3 log units. This monotonic relation between surface luminance and neural activity was more evident later in the stimulus period than early on. The effect of the global luminance on neural activity was then assessed in 81 of the surface-responsive neurons by varying the luminance of the surround while holding the luminance of the surface constant. The activity of one group of neurons (25/81) was unaffected by the luminance of the surround; these neurons appear to encode the physical luminance of a surface covering the receptive field. The responses of the other neurons were affected by the luminance of the surround. The effects of the luminances of the surface and the surround on the activities of 26 of these neurons were in the same direction (either increased or decreased), while the effects on the remaining 25 neurons were in opposite directions. The activities of the latter group of neurons seemed to parallel the perceived brightness of the surface, whereas the former seemed to encode the level of illumination. There were differences across different types of neurons with regard to the layer distribution. These findings indicate that global luminance information significantly modulates the activity of surface-responsive V1 neurons and that not only physical luminance, but also perceived brightness, of a homogeneous surface is represented in V1.

Download Full-text

Blockade of retinal or cortical activity does not prevent the development of callosal patches normally associated with ocular dominance columns in primary visual cortex

Visual Neuroscience ◽

10.1017/s0952523821000110 ◽

2021 ◽

Vol 38 ◽

Author(s):

Hsueh Chung Lu ◽

Robyn J. Laing ◽

Jaime F. Olavarria

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Neural Activity ◽

Single Injection ◽

Ocular Dominance ◽

Cell Activity ◽

Ocular Dominance Columns ◽

Callosal Connections ◽

Monocular Enucleation ◽

Physiological Evaluation

Abstract Callosal patches in primary visual cortex of Long Evans rats, normally associated with ocular dominance columns, emerge by postnatal day 10 (P10), but they do not form in rats monocularly enucleated a few days before P10. We investigated whether we could replicate the results of monocular enucleation by using tetrodotoxin (TTX) to block neural activity in one eye, or in primary visual cortex. Animals received daily intravitreal (P6–P9) or intracortical (P7–P9) injections of TTX, and our physiological evaluation of the efficacy of these injections indicated that the blockade induced by a single injection lasted at least 24 h. Four weeks later, the patterns of callosal connections in one hemisphere were revealed after multiple injections of horseradish peroxidase in the other hemisphere. We found that in rats receiving either intravitreal or cortical injections of TTX, the patterns of callosal patches analyzed in tangential sections from the flattened cortex were not significantly different from the pattern in normal rats. Our findings, therefore, suggest that the effects of monocular enucleation on the distribution of callosal connections are not due to the resulting imbalance of afferent ganglion cell activity, and that factors other than neural activity are likely involved.

Download Full-text

Microstimulation in the primary visual cortex: activity patterns and their relation to visual responses and evoked saccades

10.1101/2020.05.03.072322 ◽

2020 ◽

Cited By ~ 1

Author(s):

R. Oz ◽

H. Edelman-Klapper ◽

S. Nivinsky-Margalit ◽

H. Slovin

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Neural Activity ◽

Visual Processing ◽

Visual Stimuli ◽

Temporal Patterns ◽

Visual Responses ◽

Population Activity ◽

Spatio Temporal ◽

Saccade Generation

AbstractIntra cortical microstimulation (ICMS) in the primary visual cortex (V1) can generate the visual perception of phosphenes and evoke saccades directed to the stimulated location in the retinotopic map. Although ICMS is widely used, little is known about the evoked spatio-temporal patterns of neural activity and their relation to neural responses evoked by visual stimuli or saccade generation. To investigate this, we combined ICMS with Voltage Sensitive Dye Imaging in V1 of behaving monkeys and measured neural activity at high spatial (meso-scale) and temporal resolution. Small visual stimuli and ICMS evoked population activity spreading over few mm that propagated to extrastriate areas. The population responses evoked by ICMS showed faster dynamics and different spatial propagation patterns. Neural activity was higher in trials w/saccades compared with trials w/o saccades. In conclusion, our results uncover the spatio-temporal patterns evoked by ICMS and their relation to visual processing and saccade generation.

Download Full-text

Anticipatory Changes in Regional Cerebral Hemodynamics: A New Role for Dopamine?

Journal of Neurophysiology ◽

10.1152/jn.00141.2009 ◽

2009 ◽

Vol 101 (6) ◽

pp. 2738-2740 ◽

Cited By ~ 12

Author(s):

Can Ozan Tan

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Neural Activity ◽

Cerebral Hemodynamics ◽

Physiological Data ◽

Cerebral Microcirculation ◽

Hemodynamic Responses ◽

On Demand ◽

Demand Allocation

Recently, adaptively timed, anticipatory changes in hemodynamic responses, independent of neural activity, were described in primate primary visual cortex. Task-related properties of these responses point to a possible link between regional cerebral microcirculation and dopaminergic signaling. In this report, this link is elaborated on the basis of known physiological data and further experiments are proposed to test the possible role of dopamine in task-dependent, “on-demand” allocation of metabolic resources.

Download Full-text

Long-wavelength (reddish) hues induce unusually large gamma oscillations in the primate primary visual cortex

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1717334115 ◽

2018 ◽

Vol 115 (17) ◽

pp. 4489-4494 ◽

Cited By ~ 25

Author(s):

Vinay Shirhatti ◽

Supratim Ray

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Gamma Oscillations ◽

Full Field ◽

Long Wavelength ◽

Natural Vision ◽

Cortex Area ◽

Electrophysiological Signals ◽

Size Contrast ◽

Highly Correlated

Gamma oscillations (∼30–80 Hz) are a prominent signature of electrophysiological signals, with a purported role in natural vision. Previous studies in the primary visual cortex (area V1) have shown that achromatic gratings or gabor stimuli generate salient gamma oscillations, whose strength and frequency depend on stimulus properties such as their size, contrast, and orientation. Surprisingly, although natural images are rarely achromatic, the effect of chromatic input on gamma has not been thoroughly investigated. Recording from primate V1, we show that gamma oscillations of extremely high magnitude (peak increase of ∼300-fold in some cases), far exceeding the gamma generated by optimally tuned achromatic gratings, are induced in the local field potentials by full-field color stimuli of different hues. Furthermore, gamma oscillations are sensitive to the hue of the chromatic input, with the strongest oscillations for long-wavelength (reddish) hues and another, smaller gamma response peak for hues in the short-wavelength (bluish) range, which lie approximately on the two cardinal chromatic response axes of the upstream lateral geniculate nucleus neurons. These oscillations depended critically on the purity of the hue, decreasing with hue desaturation, but remained robust for pure hue stimuli even at reduced luminance. Importantly, the magnitude of gamma oscillations was highly correlated with positive L−M cone contrast produced by the stimuli, suggesting that gamma could be a marker of the specific mechanisms underlying this computation. These findings provide insights into the generation of gamma oscillations, as well as the processing of color along the visual pathway.

Download Full-text