A Short Route for Reach Planning between Human V6A and the Motor Cortex.

In the macaque monkey, area V6A, located in the medial posterior parietal cortex, contains cells that encode the spatial position of a reaching target. It has been suggested that during reach planning this information is sent to the frontal cortex along a parieto-frontal pathway that connects V6A-premotor cortex-M1. A similar parieto-frontal network may also exist in the human brain, and we aimed here to study the timing of this functional connection during planning of a reaching movement toward different spatial positions. We probed the functional connectivity between human area V6A (hV6A) and the primary motor cortex (M1) using dual-site, paired-pulse transcranial magnetic stimulation with a short (4 ms) and a longer (10 ms) interstimulus interval while healthy participants (18 men and 18 women) planned a visually-guided or a memory-guided reaching movement toward positions located at different depths and directions. We found that, when the stimulation over hV6A is sent 4 ms before the stimulation over M1, hV6A inhibits motor-evoked potentials during planning of either rightward or leftward reaching movements. No modulations were found when the stimulation over hV6A was sent 10 ms before the stimulation over M1, suggesting that only short medial parieto-frontal routes are active during reach planning. Moreover, the short route of hV6A-premotor cortex-M1 is active during reach planning irrespectively of the nature (visual or memory) of the reaching target. These results agree with previous neuroimaging studies and provide the first demonstration of the flow of inhibitory signals between hV6A and M1.SIGNIFICANCE STATEMENT All our dexterous movements depend on the correct functioning of the network of brain areas. Knowing the functional timing of these networks is useful to gain a deeper understanding of how the brain works to enable accurate arm movements. In this article, we probed the parieto-frontal network and demonstrated that it takes 4 ms for the medial posterior parietal cortex to send inhibitory signals to the frontal cortex during reach planning. This fast flow of information seems not to be dependent on the availability of visual information regarding the reaching target. This study opens the way for future studies to test how this timing could be impaired in different neurological disorders.

Claustral Input to the Macaque Medial Posterior Parietal Cortex (Superior Parietal Lobule and Adjacent Areas).

The projections from the claustrum to cortical areas within and adjacent to the superior parietal lobule were studied in 10 macaque monkeys, using retrograde tracers, computerized reconstructions, and quantitative methods. In contrast with the classical view that posterior parietal areas receive afferents primarily from the dorsal and posterior regions of the claustrum, we found that these areas receive more extensive projections, including substantial afferents from the anterior and ventral regions of the claustrum. Moreover, our findings uncover a previously unsuspected variability in the precise regions of the claustrum that originate the projections, according to the target areas. For example, areas dominated by somatosensory inputs for control of body movements tend to receive most afferents from the dorsal-posterior claustrum, whereas those which also receive significant visual inputs tend to receive more afferents from the ventral claustrum. In addition, different areas within these broadly defined groups differ in terms of quantitative emphasis in the origin of projections. Overall, these results argue against a simple model whereby adjacency in the cortex determines adjacency in the sectors of claustral origin of projections and indicate that subnetworks defined by commonality of function may be an important factor in defining claustrocortical topography.

Modulation of reaching by spatial attention.

Attention is needed to perform goal-directed vision-guided movements. We investigated whether the direction of covert attention modulates movement outcomes and dynamics. Right-handed and left-handed volunteers attended to a spatial location while planning a reach toward the same hemifield, the opposite one, or planned a reach without constraining attention. We measured behavioral variables as outcomes of ipsilateral and contralateral reaching and the tangling of behavioral trajectories obtained through principal component analysis as a measure of the dynamics of motor control. We found that the direction of covert attention had significant effects on the dynamics of motor control, specifically during contralateral reaching. Data suggest that motor control was more feedback-driven when attention was directed leftward than when attention was directed rightward or when it was not constrained, irrespectively of handedness. These results may help to better understand the neural bases of asymmetrical neurological diseases like hemispatial neglect.

Similar neural states, but dissimilar decoding patterns for motor control in parietal cortex.

Discrete neural states are associated with reaching movements across the fronto-parietal network. Here, the Hidden Markov Model (HMM) applied to spiking activity of the somato-motor parietal area PE revealed a sequence of states similar to those of the contiguous visuomotor areas PEc and V6A. Using a coupled clustering and decoding approach, we proved that these neural states carried spatiotemporal information regarding behaviour in all three posterior parietal areas. However, comparing decoding accuracy, PE was less informative than V6A and PEc. In addition, V6A outperformed PEc in target inference, indicating functional differences among the parietal areas. To check the consistency of these differences, we used both a supervised and an unsupervised variant of the HMM, and compared its performance with two more common classifiers, Support Vector Machine and Long-Short Term Memory. The differences in decoding between areas were invariant to the algorithm used, still showing the dissimilarities found with HMM, thus indicating that these dissimilarities are intrinsic in the information encoded by parietal neurons. These results highlight that, when decoding from the parietal cortex, for example, in brain machine interface implementations, attention should be paid in selecting the most suitable source of neural signals, given the great heterogeneity of this cortical sector.

Applying HMMs to spiking activity recorded from the somato-motor parietal area PE revealed discrete neural states related to reaching movements. These states were extremely similar to those present in the neighbouring visuomotor areas PEc and V6A. Our decoding approach showed that these states conveyed spatiotemporal behaviour information across all three posterior parietal areas. However, decoding accuracy was lower in PE compared to V6A and PEc, with V6A excelling in target inference. These differences held true even when changing the decoding algorithm, indicating intrinsic dissimilarities in information encoding by parietal different areas. These findings highlight the importance of selecting the appropriate neural signal sources in applications such as brain machine interfaces and pave the way for further investigation of the nontrivial diversity within the parietal cortex.

Visual sensitivity at the service of action control in posterior parietal cortex.

The posterior parietal cortex (PPC) serves as a crucial hub for the integration of sensory with motor cues related to voluntary actions. Visual input is used in different ways along the dorsomedial and the dorsolateral visual pathways. Here we focus on the dorsomedial pathway and recognize a visual representation at the service of action control. Employing different experimental paradigms applied to behaving monkeys while single neural activity is recorded from the medial PPC (area V6A), we show how plastic visual representation can be, matching the different contexts in which the same object is proposed. We also present data on the exchange between vision and arm actions and highlight how this rich interplay can be used to weight different sensory inputs in order to monitor and correct arm actions online. Indeed, neural activity during reaching or reach-to-grasp actions can be excited or inhibited by visual information, suggesting that the visual perception of action, rather than object recognition, is the most effective factor for area V6A. Also, three-dimensional object shape is encoded dynamically by the neural population, according to the behavioral context of the monkey. Along this line, mirror neuron discharges in V6A indicate the plasticity of visual representation of the graspable objects, that changes according to the context and peaks when the object is the target of one's own action. In other words, object encoding in V6A is a visual encoding for action.

New insights on single-neuron selectivity in the era of population-level approaches.

In the past, neuroscience was focused on individual neurons seen as the functional units of the nervous system, but this approach fell short over time to account for new experimental evidence, especially for what concerns associative and motor cortices. For this reason and thanks to great technological advances, a part of modern research has shifted the focus from the responses of single neurons to the activity of neural ensembles, now considered the real functional units of the system. However, on a microscale, individual neurons remain the computational components of these networks, thus the study of population dynamics cannot prescind from studying also individual neurons which represent their natural substrate. In this new framework, ideas such as the capability of single cells to encode a specific stimulus (neural selectivity) may become obsolete and need to be profoundly revised. One step in this direction was made by introducing the concept of "mixed selectivity," the capacity of single cells to integrate multiple variables in a flexible way, allowing individual neurons to participate in different networks. In this review, we outline the most important features of mixed selectivity and we also present recent works demonstrating its presence in the associative areas of the posterior parietal cortex. Finally, in discussing these findings, we present some open questions that could be addressed by future studies.

A Poisson generalized linear model application to disentangle the effects of various parameters on neurophysiological discharges.

The protocol provides an extensive guide to apply the generalized linear model framework to neurophysiological recordings. This flexible technique can be adapted to test and quantify the contributions of many different parameters (e.g., kinematics, target position, choice, reward) on neural activity. To weight the influence of each parameter, we developed an intuitive metric ("w-value") that can be used to build a "functional fingerprint" characteristic for each neuron. We also provide suggestions to extract complementary useful information from the method. For complete details on the use and execution of this protocol, please refer to Diomedi et al. (2020).

Erratum: A Poisson generalized linear model application to disentangle the effects of various parameters on neurophysiological discharges.

[This corrects the article DOI: 10.1016/j.xpro.2021.100413.].

Mixed Selectivity in Macaque Medial Parietal Cortex during Eye-Hand Reaching.

The activity of neurons of the medial posterior parietal area V6A in macaque monkeys is modulated by many aspects of reach task. In the past, research was mostly focused on modulating the effect of single parameters upon the activity of V6A cells. Here, we used Generalized Linear Models (GLMs) to simultaneously test the contribution of several factors upon V6A cells during a fix-to-reach task. This approach resulted in the definition of a representative "functional fingerprint" for each neuron. We first studied how the features are distributed in the population. Our analysis highlighted the virtual absence of units strictly selective for only one factor and revealed that most cells are characterized by "mixed selectivity." Then, exploiting our GLM framework, we investigated the dynamics of spatial parameters encoded within V6A. We found that the tuning is not static, but changed along the trial, indicating the sequential occurrence of visuospatial transformations helpful to guide arm movement.