Neural mechanisms of oculomotor abnormalities in the infantile strabismus syndrome

Infantile strabismus is characterized by numerous visual and oculomotor abnormalities. Recently nonhuman primate models of infantile strabismus have been established, with characteristics that closely match those observed in human patients. This has made it possible to study the neural basis for visual and oculomotor symptoms in infantile strabismus. In this review, we consider the available evidence for neural abnormalities in structures related to oculomotor pathways ranging from visual cortex to oculomotor nuclei. These studies provide compelling evidence that a disturbance of binocular vision during a sensitive period early in life, whatever the cause, results in a cascade of abnormalities through numerous brain areas involved in visual functions and eye movements.

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Remembrance of things practiced with fast and slow learning in cortical and subcortical pathways

Nature Communications ◽

10.1038/s41467-020-19788-5 ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

James M. Murray ◽

G. Sean Escola

Keyword(s):

Motor Cortex ◽

Motor Learning ◽

Motor Skills ◽

Neural Mechanisms ◽

Neural Basis ◽

Brain Areas ◽

Multiple Timescales ◽

Learned Behaviors ◽

Future Learning ◽

Slow Learning

AbstractThe learning of motor skills unfolds over multiple timescales, with rapid initial gains in performance followed by a longer period in which the behavior becomes more refined, habitual, and automatized. While recent lesion and inactivation experiments have provided hints about how various brain areas might contribute to such learning, their precise roles and the neural mechanisms underlying them are not well understood. In this work, we propose neural- and circuit-level mechanisms by which motor cortex, thalamus, and striatum support motor learning. In this model, the combination of fast cortical learning and slow subcortical learning gives rise to a covert learning process through which control of behavior is gradually transferred from cortical to subcortical circuits, while protecting learned behaviors that are practiced repeatedly against overwriting by future learning. Together, these results point to a new computational role for thalamus in motor learning and, more broadly, provide a framework for understanding the neural basis of habit formation and the automatization of behavior through practice.

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Remembrance of things practiced: Fast and slow learning in cortical and subcortical pathways

10.1101/797548 ◽

2019 ◽

Cited By ~ 1

Author(s):

James M. Murray ◽

G. Sean Escola

Keyword(s):

Motor Cortex ◽

Motor Skills ◽

Learning Process ◽

Neural Mechanisms ◽

Neural Basis ◽

Brain Areas ◽

Multiple Timescales ◽

Learned Behaviors ◽

Future Learning ◽

Slow Learning

The learning of motor skills unfolds over multiple timescales, with rapid initial gains in performance followed by a longer period in which the behavior becomes more refined, habitual, and automatized. While recent lesion and inactivation experiments have provided hints about how various brain areas might contribute to such learning, their precise roles and the neural mechanisms underlying them are not well understood. In this work, we propose neural- and circuit-level mechanisms by which motor cortex, thalamus, and striatum support such learning. In this model, the combination of fast cortical learning and slow subcortical learning gives rise to a covert learning process through which control of behavior is gradually transferred from cortical to subcortical circuits, while protecting learned behaviors that are practiced repeatedly against overwriting by future learning. Together, these results point to a new computational role for thalamus in motor learning, and, more broadly, provide a framework for understanding the neural basis of habit formation and the automatization of behavior through practice.

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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.

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Neural Basis of Visually Guided Head Movements Studied With fMRI

Journal of Neurophysiology ◽

10.1152/jn.00988.2002 ◽

2003 ◽

Vol 89 (5) ◽

pp. 2516-2527 ◽

Cited By ~ 56

Author(s):

Laurent Petit ◽

Michael S. Beauchamp

Keyword(s):

Eye Movements ◽

Head Movement ◽

Brain Activity ◽

Posterior Part ◽

Vestibular Stimulation ◽

Head Movements ◽

Oculomotor Control ◽

Imaging Studies ◽

Neural Basis ◽

Temporoparietal Junction

We used event-related fMRI to measure brain activity while subjects performed saccadic eye, head, and gaze movements to visually presented targets. Two distinct patterns of response were observed. One set of areas was equally active during eye, head, and gaze movements and consisted of the superior and inferior subdivisions of the frontal eye fields, the supplementary eye field, the intraparietal sulcus, the precuneus, area MT in the lateral occipital sulcus and subcortically in basal ganglia, thalamus, and the superior colliculus. These areas have been previously observed in functional imaging studies of human eye movements, suggesting that a common set of brain areas subserves both oculomotor and head movement control in humans, consistent with data from single-unit recording and microstimulation studies in nonhuman primates that have described overlapping eye- and head-movement representations in oculomotor control areas. A second set of areas was active during head and gaze movements but not during eye movements. This set of areas included the posterior part of the planum temporale and the cortex at the temporoparietal junction, known as the parieto-insular vestibular cortex (PIVC). Activity in PIVC has been observed during imaging studies of invasive vestibular stimulation, and we confirm its role in processing the vestibular cues accompanying natural head movements. Our findings demonstrate that fMRI can be used to study the neural basis of head movements and show that areas that control eye movements also control head movements. In addition, we provide the first evidence for brain activity associated with vestibular input produced by natural head movements as opposed to invasive caloric or galvanic vestibular stimulation.

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fMRI-Guided TMS on Cortical Eye Fields: The Frontal But Not Intraparietal Eye Fields Regulate the Coupling Between Visuospatial Attention and Eye Movements

Journal of Neurophysiology ◽

10.1152/jn.00350.2009 ◽

2009 ◽

Vol 102 (6) ◽

pp. 3469-3480 ◽

Cited By ~ 25

Author(s):

H. M. Van Ettinger-Veenstra ◽

W. Huijbers ◽

T. P. Gutteling ◽

M. Vink ◽

J. L. Kenemans ◽

...

Keyword(s):

Visual Cortex ◽

Eye Movements ◽

Visual Processing ◽

Discrimination Performance ◽

Visual Image ◽

Single Pulse ◽

Visuospatial Attention ◽

Movement Direction ◽

Key Factor ◽

And Shifts

It is well known that parts of a visual scene are prioritized for visual processing, depending on the current situation. How the CNS moves this focus of attention across the visual image is largely unknown, although there is substantial evidence that preparation of an action is a key factor. Our results support the view that direct corticocortical feedback connections from frontal oculomotor areas to the visual cortex are responsible for the coupling between eye movements and shifts of visuospatial attention. Functional magnetic resonance imaging (fMRI)–guided transcranial magnetic stimulation (TMS) was applied to the frontal eye fields (FEFs) and intraparietal sulcus (IPS). A single pulse was delivered 60, 30, or 0 ms before a discrimination target was presented at, or next to, the target of a saccade in preparation. Results showed that the known enhancement of discrimination performance specific to locations to which eye movements are being prepared was enhanced by early TMS on the FEF contralateral to eye movement direction, whereas TMS on the IPS resulted in a general performance increase. The current findings indicate that the FEF affects selective visual processing within the visual cortex itself through direct feedback projections.

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Man, Monkey, and Blindsight

The Neuroscientist ◽

10.1177/107385849800400410 ◽

1998 ◽

Vol 4 (4) ◽

pp. 227-230 ◽

Cited By ~ 17

Author(s):

Tirin Moore ◽

Hillary R. Rodman ◽

Charles G. Gross

Keyword(s):

Visual Cortex ◽

Visual System ◽

Primary Visual Cortex ◽

Visual Function ◽

Forced Choice ◽

Neural Mechanisms ◽

Residual Vision ◽

Choice Testing

The visual function that survives damage to the primary visual cortex (V1) in humans is often unaccompanied by awareness. This type of residual vision, called “blindsight,” has raised considerable interest because it implies a separation of conscious from unconscious vision mechanisms. The monkey visual system has proven to be a useful model in elucidating the possible neural mechanisms of residual vision and blindsight in humans. Clear similarities, however, between the phenomenology of human and monkey residual vision have only recently become evident. This article summarizes parallels between residual vision in monkeys and humans with damage to V1. These parallels Include the tendency of the remaining vision to require forced-choice testing and the fact that more robust residual vision remains when V1 damage is sustained early in life. NEUROSCIENTIST 4:227–230

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Prefrontal and Parietal Attractor Networks Mediate Working Memory Judgments

10.1101/2020.06.01.128173 ◽

2020 ◽

Author(s):

Sihai Li ◽

Christos Constantinidis ◽

Xue-Lian Qi

Keyword(s):

Working Memory ◽

Prefrontal Cortex ◽

Dorsolateral Prefrontal Cortex ◽

Critical Role ◽

Memory Task ◽

Delayed Response ◽

Persistent Activity ◽

Neural Basis ◽

Brain Areas ◽

Dorsolateral Prefrontal

ABSTRACTThe dorsolateral prefrontal cortex plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here we addressed whether this predictive ability extends to categorical judgments based on information retained in working memory, and is present in other brain areas. We trained monkeys in a novel, Match-Stay, Nonmatch-Go task, which required them to observe two stimuli presented in sequence with an intervening delay period between them. If the two stimuli were different, the monkeys had to saccade to the location of the second stimulus; if they were the same, they held fixation. Neurophysiological recordings were performed in areas 8a and 46 of the dlPFC and 7a and lateral intraparietal cortex (LIP) of the PPC. We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and towards the location of the second stimulus would result in categorical errors. Indeed, for both areas, when the first stimulus appeared in a neuron’s preferred location, the neuron showed significantly higher firing rates in correct than in error trials. When the first stimulus appeared at a nonpreferred location and the second stimulus at a preferred, activity in error trials was higher than in correct. The results indicate that the activity of both dlPFC and PPC neurons is predictive of categorical judgments of information maintained in working memory, and the magnitude of neuronal firing rate deviations is revealing of the contents of working memory as it determines performance.SIGNIFICANCE STATEMENTThe neural basis of working memory and the areas mediating this function is a topic of controversy. Persistent activity in the prefrontal cortex has traditionally been thought to be the neural correlate of working memory, however recent studies have proposed alternative mechanisms and brain areas. Here we show that persistent activity in both the dorsolateral prefrontal cortex and posterior parietal cortex predicts behavior in a working memory task that requires a categorical judgement. Our results offer support to the idea that a network of neurons in both areas act as an attractor network that maintains information in working memory, which informs behavior.

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