Temporal Evolution and Strength of Neural Activity in Parietal Cortex during Eye and Hand Movements

A growing number of studies show that visual mental imagery recruits the same brain areas as visual perception. Although the necessity of hV5/MT+ for motion perception has been revealed by means of TMS, its relevance for motion imagery remains unclear. We induced a direction-selective adaptation in hV5/MT+ by means of an MAE while subjects performed a mental rotation task that elicits imagined motion. We concurrently measured behavioral performance and neural activity with fMRI, enabling us to directly assess the effect of a perturbation of hV5/MT+ on other cortical areas involved in the mental rotation task. The activity in hV5/MT+ increased as more mental rotation was required, and the perturbation of hV5/MT+ affected behavioral performance as well as the neural activity in this area. Moreover, several regions in the posterior parietal cortex were also affected by this perturbation. Our results show that hV5/MT+ is required for imagined visual motion and engages in an interaction with parietal cortex during this cognitive process.

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Hand-Movement-Related Neurons of the Posterior Parietal Cortex of the Monkey: Their Role in the Visual Guidance of Hand Movements

Control of Arm Movement in Space ◽

10.1007/978-3-642-77235-1_12 ◽

1992 ◽

pp. 185-198 ◽

Cited By ~ 16

Author(s):

H. Sakata ◽

M. Taira ◽

S. Mine ◽

A. Murata

Keyword(s):

Parietal Cortex ◽

Posterior Parietal Cortex ◽

Hand Movement ◽

Hand Movements ◽

Visual Guidance ◽

Posterior Parietal

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Parietal Representation of Hand Velocity in a Copy Task

Journal of Neurophysiology ◽

10.1152/jn.00357.2004 ◽

2005 ◽

Vol 93 (1) ◽

pp. 508-518 ◽

Cited By ~ 35

Author(s):

Bruno B. Averbeck ◽

Matthew V. Chafee ◽

David A. Crowe ◽

Apostolos P. Georgopoulos

Keyword(s):

Transfer Function ◽

Linear Model ◽

Parietal Cortex ◽

Neural Activity ◽

Nonlinear Models ◽

Linear Representation ◽

Pass Filter ◽

Low Pass Filter ◽

Filter Width ◽

Low Pass

We recorded neural activity from ensembles of neurons in areas 5 and 2 of parietal cortex, while two monkeys copied triangles, squares, trapezoids, and inverted triangles and used both linear and nonlinear models to predict the hand velocity from the neural activity of the ensembles. The linear model generally outperformed the nonlinear model, suggesting a reasonably linear relation between the neural activity and the hand velocity. We also found that the average transfer function of the linear model fit to individual cells was a low-pass filter because the neural response had considerable high-frequency power, whereas the hand velocity only had power at frequencies below ∼5 Hz. Increasing the width of the transfer function, up to a width of 700–800 ms, improved the fit of the model. Furthermore, the Rsqr of the linear model improved monotonically with the number of cells in the ensemble, saturating at 60–80% for a filter width of 700 ms. Finally, it was found that including an interaction term, which allowed the transfer function to shift with the eye position, did not improve the fit of the model. Thus ensemble neural responses in superior parietal cortex provide a high-fidelity, linear representation of hand kinematics within our task.

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Temporal Evolution of Regional Energy Metabolism following Focal Cerebral Ischemia in the Rat

Journal of Cerebral Blood Flow & Metabolism ◽

10.1038/jcbfm.1988.87 ◽

1988 ◽

Vol 8 (4) ◽

pp. 462-473 ◽

Cited By ~ 46

Author(s):

J.-P. Nowicki ◽

C. Assumel-Lurdin ◽

D. Duverger ◽

E. T. MacKenzie

Keyword(s):

Energy Metabolism ◽

Cerebral Ischemia ◽

Middle Cerebral Artery ◽

Parietal Cortex ◽

Cerebral Artery ◽

Temporal Evolution ◽

Focal Cerebral Ischemia ◽

Biochemical Changes ◽

Regional Energy ◽

Cortical Regions

Focal cerebral ischemia in the rat was induced by occlusion of the left middle cerebral artery. The temporal evolution of regional energy metabolism was studied over the 14 days consequent to the induction of ischemia in the frontal, cingulate, parietal, and occipital cortices as well as in the striatum. Regional concentrations of adenosine triphosphate (ATP), phosphocreatine, and lactate and, in addition, glucose and the cerebral/plasma glucose ratio (C/P) were measured in the hemispheres both ipsilateral and contralateral to the occlusion. Two hours after middle cerebral artery occlusion, the biochemical changes were severe in the striatum and moderate in cortical regions. Later on (at 24 and 48 h), an overall aggravated metabolic status was noted while lactate declined and glucose markedly increased. These latter biochemical changes likely indicate a marked inhibition of the rate of glucose utilization. At 48 h, the energy reserves (ATP, phosphocreatine) of parietal cortex no longer equaled those of other cortical regions, but abruptly fell to the levels found in the striatum without any increase in lactate level. Finally, at 7 and 14 days, the levels of the various metabolites in most cortical regions returned toward control values, although signs of a depressed glucose metabolism remained. However, in both striatum and parietal cortex, ATP and phosphocreatine concentrations, although higher than those observed at 48 h, remained significantly decreased. Our present biochemical study permits the classification of these selected brain regions into three categories. First there are those that are outside the area of infarction: the frontal, cingulate, and occipital cortices. These regions show little temporal evolution of brain energy metabolism but, notwithstanding, they are regions in which glucose use would appear to be greatly depressed. Second is a region considered to be the focus of infarction: the striatum. The caudate-putamen is a region with early and profound metabolic disturbances with no final restitution. Last is the region of metabolic penumbra—the parietal cortex, in which there is a time-related exacerbation of the consequences of middle cerebral occlusion in the rat.

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Nicotine Modulates Reorienting of Visuospatial Attention and Neural Activity in Human Parietal Cortex

Neuropsychopharmacology ◽

10.1038/sj.npp.1300633 ◽

2005 ◽

Vol 30 (4) ◽

pp. 810-820 ◽

Cited By ~ 127

Author(s):

Christiane M Thiel ◽

Karl Zilles ◽

Gereon R Fink

Keyword(s):

Parietal Cortex ◽

Neural Activity ◽

Visuospatial Attention

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Temporal evolution of neural activity during motor planning and motor preparation in humans

Neuroscience Research ◽

10.1016/j.neures.2009.09.458 ◽

2009 ◽

Vol 65 ◽

pp. S104

Author(s):

Yu Shimizu ◽

Hiroshi Imamizu ◽

Masaaki Sato ◽

Mitsuo Kawato

Keyword(s):

Neural Activity ◽

Temporal Evolution ◽

Motor Planning ◽

Motor Preparation

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Neural dynamics of causal inference in the macaque frontoparietal circuit

10.1101/2021.12.06.469042 ◽

2021 ◽

Author(s):

Guangyao Qi ◽

Wen Fang ◽

Shenghao Li ◽

Junru Li ◽

Liping Wang

Keyword(s):

Causal Inference ◽

Parietal Cortex ◽

Neural Activity ◽

Multisensory Processing ◽

Causal Structure ◽

Premotor Cortex ◽

Common Source ◽

Sensory Representation ◽

Historical Information ◽

Sensory Inputs

ABSTRACTNatural perception relies inherently on inferring causal structure in the environment. However, the neural mechanisms and functional circuits that are essential for representing and updating the hidden causal structure and corresponding sensory representations during multisensory processing are unknown. To address this, monkeys were trained to infer the probability of a potential common source from visual and proprioceptive signals on the basis of their spatial disparity in a virtual reality system. The proprioceptive drift reported by monkeys demonstrated that they combined historical information and current multisensory signals to estimate the hidden common source and subsequently updated both the causal structure and sensory representation. Single-unit recordings in premotor and parietal cortices revealed that neural activity in premotor cortex represents the core computation of causal inference, characterizing the estimation and update of the likelihood of integrating multiple sensory inputs at a trial-by-trial level. In response to signals from premotor cortex, neural activity in parietal cortex also represents the causal structure and further dynamically updates the sensory representation to maintain consistency with the causal inference structure. Thus, our results indicate how premotor cortex integrates historical information and sensory inputs to infer hidden variables and selectively updates sensory representations in parietal cortex to support behavior. This dynamic loop of frontal-parietal interactions in the causal inference framework may provide the neural mechanism to answer long-standing questions regarding how neural circuits represent hidden structures for body-awareness and agency.

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Large- and multi-scale networks in the rodent brain during novelty exploration

10.1101/2020.12.08.416248 ◽

2020 ◽

Author(s):

Michael X Cohen ◽

Bernhard Englitz ◽

Arthur S C França

Keyword(s):

Prefrontal Cortex ◽

Parietal Cortex ◽

Local Field ◽

Neural Activity ◽

Large Scale ◽

Field Potential ◽

Brain Regions ◽

Data Availability ◽

Data Matrix ◽

Temporal Scales

AbstractNeural activity is coordinated across multiple spatial and temporal scales, and these patterns of coordination are implicated in both healthy and impaired cognitive operations. However, empirical cross-scale investigations are relatively infrequent, due to limited data availability and to the difficulty of analyzing rich multivariate datasets. Here we applied frequency-resolved multivariate source-separation analyses to characterize a large-scale dataset comprising spiking and local field potential activity recorded simultaneously in three brain regions (prefrontal cortex, parietal cortex, hippocampus) in freely-moving mice. We identified a constellation of multidimensional, inter-regional networks across a range of frequencies (2-200 Hz). These networks were reproducible within animals across different recording sessions, but varied across different animals, suggesting individual variability in network architecture. The theta band (~4-10 Hz) networks had several prominent features, including roughly equal contribution from all regions and strong inter-network synchronization. Overall, these findings demonstrate a multidimensional landscape of large-scale functional activations of cortical networks operating across multiple spatial, spectral, and temporal scales during open-field exploration.Significance statementNeural activity is synchronized over space, time, and frequency. To characterize the dynamics of large-scale networks spanning multiple brain regions, we recorded data from the prefrontal cortex, parietal cortex, and hippocampus in awake behaving mice, and pooled data from spiking activity and local field potentials into one data matrix. Frequency-specific multivariate decomposition methods revealed a cornucopia of neural networks defined by coherent spatiotemporal patterns over time. These findings reveal a rich, dynamic, and multivariate landscape of large-scale neural activity patterns during foraging behavior.

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