Structural connectivity and functional properties of the macaque superior parietal lobule

Despite the consolidated belief that the macaque superior parietal lobule (SPL) is entirely occupied by Brodmann’s area 5, recent data show that macaque SPL also hosts a large cortical region with structural and functional features similar to that of Brodmann’s area 7. According to these data, the anterior part of SPL is occupied by a somatosensory-dominated cortical region that hosts three architectural and functional distinct regions (PE, PEci, PEip) and the caudal half of SPL by a bimodal somato-visual region that hosts four areas: PEc, MIP, PGm, V6A. To date, the most studied areas of SPL are PE, PEc, and V6A. PE is essentially a high-order somatomotor area, while PEc and V6A are bimodal somatomotor–visuomotor areas, the former with predominant somatosensory input and the latter with predominant visual input. The functional properties of these areas and their anatomical connectivity strongly suggest their involvement in the control of limb movements. PE is suggested to be involved in the preparation/execution of limb movements, in particular, the movements of the upper limb; PEc in the control of movements of both upper and lower limbs, as well as in their interaction with the visual environment; V6A in the control of reach-to-grasp movements performed with the upper limb. In humans, SPL is traditionally considered to have a different organization with respect to macaques. Here, we review several lines of evidence suggesting that this is not the case, showing a similar structure for human and non-human primate SPLs

The cognitive neuroscience of visual working memory

Visual working memory allows us to temporarily maintain and manipulate visual information in order to solve a task. The study of the brain mechanisms underlying this function began more than half a century ago, with Scoville and Milner’s (1957) seminal discoveries with amnesic patients. This timely collection of papers brings together diverse perspectives on the cognitive neuroscience of visual working memory from multiple fields that have traditionally been fairly disjointed: human neuroimaging, electrophysiological, behavioural and animal lesion studies, investigating both the developing and the adult brain

Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface

Calcium imaging is a powerful tool for recording from large populations of neurons in vivo. Imaging in rhesus macaque motor cortex can enable the discovery of fundamental principles of motor cortical function and can inform the design of next generation brain-computer interfaces (BCIs). Surface two-photon imaging, however, cannot presently access somatic calcium signals of neurons from all layers of macaque motor cortex due to photon scattering. Here, we demonstrate an implant and imaging system capable of chronic, motion-stabilized two-photon imaging of neuronal calcium signals from macaques engaged in a motor task. By imaging apical dendrites, we achieved optical access to large populations of deep and superficial cortical neurons across dorsal premotor (PMd) and gyral primary motor (M1) cortices. Dendritic signals from individual neurons displayed tuning for different directions of arm movement. Combining several technical advances, we developed an optical BCI (oBCI) driven by these dendritic signalswhich successfully decoded movement direction online. By fusing two-photon functional imaging with CLARITY volumetric imaging, we verified that many imaged dendrites which contributed to oBCI decoding originated from layer 5 output neurons, including a putative Betz cell. This approach establishes new opportunities for studying motor control and designing BCIs via two photon imaging

Neuron-level dynamics of oscillatory network structure and markerless tracking of kinematics during grasping

Oscillatory synchrony is proposed to play an important role in flexible sensory-motor transformations. Thereby, it is assumed that changes in the oscillatory network structure at the level of single neurons lead to flexible information processing. Yet, how the oscillatory network structure at the neuron-level changes with different behavior remains elusive. To address this gap, we examined changes in the fronto-parietal oscillatory network structure at the neuron-level, while monkeys performed a flexible sensory-motor grasping task. We found that neurons formed separate subnetworks in the low frequency and beta bands. The beta subnetwork was active during steady states and the low frequency network during active states of the task, suggesting that both frequencies are mutually exclusive at the neuron-level. Furthermore, both frequency subnetworks reconfigured at the neuron-level for different grip and context conditions, which was mostly lost at any scale larger than neurons in the network. Our results, therefore, suggest that the oscillatory network structure at the neuron-level meets the necessary requirements for the coordination of flexible sensory-motor transformations. Supplementarily, tracking hand kinematics is a crucial experimental requirement to analyze neuronal control of grasp movements. To this end, a 3D markerless, gloveless hand tracking system was developed using computer vision and deep learning techniques. 2021-11-3

Neural Correlates of Reach Planning and Execution

Humans and other primates often interact with the world by reaching and grabbing objects with their hands. This seemingly simple activity is a challenging computational problem that requires the nervous system to transform sensory input into muscle activations that move the hand appropriately through space. This dissertation investigates neural activity in the dorsal premotor cortex of the macaque monkey while simple and complex reaching movements are planned and executed. A novel virtual-reality obstacle-avoidance task is used to decorrelate the direction of the initial segment of the trajectory from the direction of the final target. An unobstructed center-out task is used as a comparison. The firing rates of many neurons are modulated by kinematic factors including hand position and movement direction. During obstacle-avoidance reaching, both the initial segment and final target directions are represented in the firing of dorsal premotor neurons. Population decoders for position, velocity and target direction were built using the indirect optimal linear estimator method, a variant of the population vector algorithm. The decoding model constructed from the direct-reaching task ultimately predicts the direction of movement, not the final target, during the planning period before movement begins. A separate decoding model predicts the target direction when the hand must move elsewhere initially. The time course of neural activity during planning suggests that the two monkeys utilized different preparatory strategies during the obstacle-avoidance task, leading to differences in performance on a subset of trials. A position-based population decoder predicts the hand trajectory during movement, anticipating the real hand position by approximately 200 ms. These findings demonstrate that multiple kinematic parameters of hand movement are represented in dorsal premotor cortex during planning and execution of voluntary reaching behavior. A simple linear decoding scheme based on roughly cosine-tuned spiking activity can extract relevant information from the population of neurons. This work contributes to the overall understanding of the factors that influence dorsal premotor cortical activity during complex reaching movements

Visual salience of the stop signal affects the neuronal dynamics of controlled inhibition

The voluntary control of movement is often tested by using the countermanding, or stop-signal task that sporadically requires the suppression of a movement in response to an incoming stop-signal. Neurophysiological recordings in monkeys engaged in the countermanding task have shown that dorsal premotor cortex (PMd) is implicated in movement control. An open question is whether and how the perceptual demands inherent the stop-signal affects inhibitory performance and their underlying neuronal correlates. To this aim we recorded multi-unit activity (MUA) from the PMd of two male monkeys performing a countermanding task in which the salience of the stop-signals was modulated. Consistently to what has been observed in humans, we found that less salient stimuli worsened the inhibitory performance. At the neuronal level, these behavioral results were subtended by the following modulations: when the stop-signal was not noticeable compared to the salient condition the preparatory neuronal activity in PMd started to be affected later and with a less sharp dynamic. This neuronal pattern is probably the consequence of a less efficient inhibitory command useful to interrupt the neural dynamic that supports movement generation in PMd

The Role of the Dorsal Premotor and Superior Parietal Cortices in Decoupled Visuomotor Transformations

In order to successfully interact with objects located within our environment, the brain must be capable of combining visual information with the appropriate felt limb position (i.e. proprioception) in order compute an appropriate coordinated muscle plan for accurate motor control. Eye-hand coordination is essential to our independence as a species and relies heavily on the reciprocally-connected regions of the parieto-frontal reach network. The dorsal premotor cortex (PMd) and the superior parietal lobule (SPL) remain prime candidates within this network for controlling the transformations required during visually-guided reaching movements. Our brains are primed to reach directly towards a viewed object, a situation that has been termed a “standard” or coupled reach. Such direct eye-hand coordination is common across species and is crucial for basic survival. Humans, however, have developed the capacity for tool-use and thus have learned to interact indirectly with an object. In such “non-standard” or decoupled situations, the directions of gaze and arm movement have been spatially decoupled and rely on both the implementation of a cognitive rule and on online feedback of the decoupled limb. The studies included within this dissertation were designed to further characterize the role of PMd and SPL during situations in which when a reach requires a spatial transformation between the actions of the eyes and the hand. More specifically, we were interested in examining whether regions within PMd (PMdr, PMdc) and SPL (PEc, MIP) responded differently during coupled versus decoupled visuomotor transformations. To address the relative contribution of these various cortical regions during decoupled reaching movements, we trained two female rhesus macaques on both coupled and decoupled visually-guided reaching tasks. We recorded the neural activity (single units and local field potentials) within each region while the animals performed each condition. We found that two separate networks emerged each contributing in a distinct ways to the performance of coupled versus decoupled eye-hand reaches. While PMdr and PEc showed enhanced activity during decoupled reach conditions, PMdc and MIP were more enhanced during coupled reaches. Taken together, these data presented here provide further evidence for the existence of alternate task-dependent neural pathways for visuomotor integration

Bihemispheric reorganization of neuronal activity during hand movements after unilateral inactivation of the primary motor cortex

Le cortex moteur primaire (M1) est souvent endommagé lors des lésions cérébrales telles que les accidents vasculaires cérébraux. Ceci entraîne des déficits moteurs tels qu'une perte de contrôle des membres controlatéraux. La récupération des lésions M1 s'accompagne d'une réorganisation hémodynamique dans les zones motrices intactes des deux hémisphères. Cette réorganisation est plus prononcée dans les premiers jours et semaines qui suivent la lésion. Toutefois, nous avons une compréhension limitée de la réorganisation neuronale rapide qui se produit dans ce réseau moteur cortical complexe. Ces changements neuronaux nous informent sur l’évolution possible de la plasticité subaiguë impliquée dans la récupération motrice. Par conséquent il était grand temps qu’une caractérisation de la réorganisation rapide de l'activité neuronale dans les régions motrices des deux hémisphères soit entreprise. Dans cette thèse nous avons exploré l'impact d'une lésion corticale localisée, unilatérale et réversible dans M1 sur l'activité neuronale des zones motrices des hémisphères ipsi et contralésionnel lorsque des primates non humains ont effectués des mouvements d’atteinte et de saisie. Notre modèle d'inactivation nous a permis d'enregistrer en continu des neurones isolés avant et après l'apparition des déficits moteurs. Dans une première étude, la réorganisation rapide qui se produit dans le cortex prémoteur ventral (PMv) des deux hémisphères a été étudiée (Chapitre 2). Le PMv est une zone connue pour être impliquée dans le contrôle moteur de la main et la récupération des lésions M1. Dans une seconde étude, la réorganisation rapide du M1 contralésionnel (cM1) a été étudiée et comparée à celles se produisant dans les PMv bilatérales (Chapitre 3). Le cM1 joue un rôle complexe dans la récupération des mouvements de précision de la main suite à une blessure à son homologue. Nous révélons une réorganisation neuronale importante et beaucoup plus complexe que prévu dans les deux hémisphères lors de l’apparition initiale des déficiences motrices. Nos données démontrent que les changements neuronaux survenant quelques minutes après une lésion cérébrale sont hétérogènes à la fois dans et entre les zones du réseau moteur cortical. Ils se produisent dans les deux hémisphères lors des mouvements des bras parétiques et non parétiques, et ils varient au cours des différentes phases du mouvement. Ces découvertes constituent une première étape nécessaire pour démêler les corrélats neuronaux complexes de la réorganisation au travers du réseau moteur des deux hémisphères à la suite d’une lésion cérébrale.After brain injuries such as stroke, the primary motor cortex (M1) is often damaged leading to motor deficits that include a loss of fine motor skills of the contralateral limbs. Recovery from M1 lesions is accompanied by hemodynamic reorganization in motor areas distal to the site of injury in both hemispheres that are most pronounced early after injury. However, we have limited understanding of the rapid neuronal reorganization that occurs in this complex and distributed cortical motor network. As these neural changes reflect the landscape on which subacute plasticity involved in motor recovery will take place, an exploration of the rapid reorganization in neural activity that occurs in motor regions of both hemispheres is long overdue. In the current thesis, we set out to explore the impact of a localized, unilateral and reversible cortical injury to the M1 hand area on neuronal activity in motor-related areas of both the ipsi and contralesional hemispheres as non-human primates performed a reach and grasp task. Our inactivation model allowed us to continuously record isolated neurons before and after the onset of motor deficits. In a first study, the rapid reorganization taking place in the ventral premotor cortex (PMv) of both hemispheres was investigated (Chapter 2). The PMv is an area well-known to be critically involved in hand motor control and recovery from M1 lesions. In a second study, the rapid reorganization taking place in the contralesional M1 (cM1) was studied and compared to those occurring in bilateral PMv (Chapter 3). The cM1 has a complex role in recovery of dexterous hand movements following injury to its homologue. We reveal extensive, and much more complex than expected, neuronal reorganization in both hemispheres at the very onset of motor impairments. Our data demonstrate that neuronal changes occurring within minutes after brain injury are heterogenous both within and across areas of the cortical motor network. They occur in the two hemispheres during movements of both the paretic and non-paretic arms, and they vary during different phases of movement. These findings constitute a first step in a much needed and timely effort to unravel the complex neuronal correlates of the reorganization that takes place across the distributed motor network after brain injury

EEG-Based Quantification of Cortical Current Density and Dynamic Causal Connectivity Generalized across Subjects Performing BCI-Monitored Cognitive Tasks.

Quantification of dynamic causal interactions among brain regions constitutes an important component of conducting research and developing applications in experimental and translational neuroscience. Furthermore, cortical networks with dynamic causal connectivity in brain-computer interface (BCI) applications offer a more comprehensive view of brain states implicated in behavior than do individual brain regions. However, models of cortical network dynamics are difficult to generalize across subjects because current electroencephalography (EEG) signal analysis techniques are limited in their ability to reliably localize sources across subjects. We propose an algorithmic and computational framework for identifying cortical networks across subjects in which dynamic causal connectivity is modeled among user-selected cortical regions of interest (ROIs). We demonstrate the strength of the proposed framework using a "reach/saccade to spatial target" cognitive task performed by 10 right-handed individuals. Modeling of causal cortical interactions was accomplished through measurement of cortical activity using (EEG), application of independent component clustering to identify cortical ROIs as network nodes, estimation of cortical current density using cortically constrained low resolution electromagnetic brain tomography (cLORETA), multivariate autoregressive (MVAR) modeling of representative cortical activity signals from each ROI, and quantification of the dynamic causal interaction among the identified ROIs using the Short-time direct Directed Transfer function (SdDTF). The resulting cortical network and the computed causal dynamics among its nodes exhibited physiologically plausible behavior, consistent with past results reported in the literature. This physiological plausibility of the results strengthens the framework's applicability in reliably capturing complex brain functionality, which is required by applications, such as diagnostics and BCI