Articulating: the neural mechanisms of speech production

Speech production is a highly complex sensorimotor task involving tightly coordinated processing across large expanses of the cerebral cortex. Historically, the study of the neural underpinnings of speech suffered from the lack of an animal model. The development of non-invasive structural and functional neuroimaging techniques in the late 20th century has dramatically improved our understanding of the speech network. Techniques for measuring regional cerebral blood flow have illuminated the neural regions involved in various aspects of speech, including feedforward and feedback control mechanisms. In parallel, we have designed, experimentally tested, and refined a neural network model detailing the neural computations performed by specific neuroanatomical regions during speech. Computer simulations of the model account for a wide range of experimental findings, including data on articulatory kinematics and brain activity during normal and perturbed speech. Furthermore, the model is being used to investigate a wide range of communication disorders.R01 DC002852 - NIDCD NIH HHS; R01 DC007683 - NIDCD NIH HHS; R01 DC016270 - NIDCD NIH HHSAccepted manuscrip

Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives

A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model-the N-STREAMS neural network model-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.Defense Advanced Research Projects Agency/Office of Naval Research (N00014-95-1-0409); National Institute of Mental Health (R01 DC02852

Adaptive Robotic Control Driven by a Versatile Spiking Cerebellar Network

The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.European Union (Human Brain Project) REALNET FP7-ICT270434 CEREBNET FP7-ITN238686 HBP-60410

The optogenetic revolution in cerebellar investigations

The cerebellum is most renowned for its role in sensorimotor control and coordination, but a growing number of anatomical and physiological studies are demonstrating its deep involvement in cognitive and emotional functions. Recently, the development and refinement of optogenetic techniques boosted research in the cerebellar field and, impressively, revolutionized the methodological approach and endowed the investigations with entirely new capabilities. This translated into a significant improvement in the data acquired for sensorimotor tests, allowing one to correlate single-cell activity with motor behavior to the extent of determining the role of single neuronal types and single connection pathways in controlling precise aspects of movement kinematics. These levels of specificity in correlating neuronal activity to behavior could not be achieved in the past, when electrical and pharmacological stimulations were the only available experimental tools. The application of optogenetics to the investigation of the cerebellar role in higher-order and cognitive functions, which involves a high degree of connectivity with multiple brain areas, has been even more significant. It is possible that, in this field, optogenetics has changed the game, and the number of investigations using optogenetics to study the cerebellar role in non-sensorimotor functions in awake animals is growing. The main issues addressed by these studies are the cerebellar role in epilepsy (through connections to the hippocampus and the temporal lobe), schizophrenia and cognition, working memory for decision making, and social behavior. It is also worth noting that optogenetics opened a new perspective for cerebellar neurostimulation in patients (e.g., for epilepsy treatment and stroke rehabilitation), promising unprecedented specificity in the targeted pathways that could be either activated or inhibited

Group and individual variability in speech production networks during delayed auditory feedback

Altering reafferent sensory information can have a profound effect on motor output. Introducing a short delay [delayed auditory feedback (DAF)] during speech production results in modulations of voice and loudness, and produces a range of speech dysfluencies. The ability of speakers to resist the effects of delayed feedback is variable yet it is unclear what neural processes underlie differences in susceptibility to DAF. Here, susceptibility to DAF is investigated by looking at the neural basis of within and between subject changes in speech fluency under 50 and 200 ms delay conditions. Using functional magnetic resonance imaging, networks involved in producing speech under two levels of DAF were identified, lying largely within networks active during normal speech production. Independent of condition, fluency ratings were associated with midbrain activity corresponding to periaqueductal grey matter. Across subject variability in ability to produce normal sounding speech under a 200 ms delay was associated with activity in ventral sensorimotor cortices, whereas ability to produce normal sounding speech under a 50 ms delay was associated with left inferior frontal gyrus activity. These data indicate whilst overlapping cortical mechanisms are engaged for speaking under different delay conditions, susceptibility to different temporal delays in speech feedback may involve different process

L’influence de l'anticipation sur les modulations de puissance dans la bande de fréquence bêta durant la préparation du mouvement et L'effet de la variance dans les rétroactions sensorielles sur la rétention à court terme

La production du mouvement est un aspect primordial de la vie qui permet aux organismes vivants d'interagir avec l'environnement. En ce sens, pour être efficaces, tous les mouvements doivent être planifiés et mis à jour en fonction de la complexité et de la variabilité de l'environnement. Des chercheurs du domaine du contrôle moteur ont étudié de manière approfondie les processus de planification et d’adaptation motrice. Puisque les processus de planification et d'adaptation motrice sont influencés par la variabilité de l'environnement, le présent mémoire cherche à fournir une compréhension plus profonde de ces deux processus moteurs à cet égard. La première contribution scientifique présentée ici tire parti du fait que les temps de réaction (TR) sont réduits lorsqu'il est possible d'anticiper l’objectif moteur, afin de déterminer si les modulations de TR associées à l'anticipation spatiale et temporelle sont sous-tendues par une activité préparatoire similaire. Cela a été fait en utilisant l'électroencéphalographie (EEG) de surface pour analyser l'activité oscillatoire dans la bande de fréquence bêta (13 - 30 Hz) au cours de la période de planification du mouvement. Les résultats ont révélé que l'anticipation temporelle était associée à la désynchronisation de la bande bêta au-dessus des régions sensorimotrices controlatérales à la main effectrice, en particulier autour du moment prévu de l'apparition de la cible. L’ampleur de ces modulations était corrélée aux modulations de TR à travers les participants. En revanche, l'anticipation spatiale a augmenté de manière sélective la puissance de la bande bêta au-dessus des régions pariéto-occipitales bilatérales pendant toute la période de planification. Ces résultats suggèrent des états de préparation distinct en fonction de l’anticipation temporelle et spatiale. D’un autre côté, le deuxième projet traite de la façon dont la variabilité de la rétroaction sensorielle interfère avec la rétention à court terme dans l’étude de l’adaptation motrice. Plus précisément, une tâche d'adaptation visuomotrice a été utilisée au cours de laquelle la variance des rotations a été manipulée de manière paramétrique à travers trois groupes, et ce, tout au long de la période d’acquisition. Par la suite, la rétention de cette nouvelle relation visuomotrice a été évaluée. Les résultats ont révélé que, même si le processus d'adaptation était robuste à la manipulation de la variance, la rétention à court terme était altérée par des plus hauts niveaux de variance. Finalement, la discussion a d'abord cherché à intégrer ces deux contributions en revisitant l'interprétation des résultats sous un angle centré sur l'incertitude et en fournissant un aperçu des potentielles représentations internes de l'incertitude susceptibles de sous-tendre les résultats expérimentaux observés. Par la suite, une partie de la discussion a été réservée à la manière dont le champ du contrôle moteur migre de plus en plus vers l’utilisation de tâches et d’approches expérimentales plus complexes, mais écologiques aux dépends des tâches simples, mais quelque peu dénaturées que l’on retrouve dans les laboratoires du domaine. La discussion a été couronnée par une brève proposition allant dans ce sens.Abstract: Motor behavior is a paramount aspect of life that enables the living to interact with the environment through the production of movement. In order to be efficient, movements need to be planned and updated according to the complexity and the ever-changing nature of the environment. Motor control experts have extensively investigated the planning and adaptation processes. Since both motor planning and motor adaptation processes are influenced by variability in the environment, the present thesis seeks to provide a deeper understanding of both these motor processes in this regard. More specifically, the first scientific contribution presented herein leverages the fact that reaction times (RTs) are reduced when the anticipation of the motor goal is possible to elucidate whether the RT modulations associated with temporal and spatial anticipation are subtended by similar preparatory activity. This was done by using scalp electroencephalography (EEG) to analyze the oscillatory activity in the beta frequency band (13 – 30 Hz) during the planning period. Results revealed that temporal anticipation was associated with beta-band desynchronization over contralateral sensorimotor regions, specifically around the expected moment of target onset, the magnitude of which was correlated with RT modulations across participants. In contrast, spatial anticipation selectively increased beta-band power over bilateral parieto-occipital regions during the entire planning period, suggesting that distinct states of preparation are incurred by temporal and spatial anticipation. Additionally, the second project addressed how variance in the sensory feedback interferes with short-term retention of motor adaptation. Specifically, a visuomotor adaptation task was used during which the variance of exposed rotation was parametrically manipulated across three groups, and retention of the adapted visuomotor relationship was assessed. Results revealed that, although the adaptation process was robust to the manipulation of variance, the short-term retention was impaired. The discussion first sought to integrate these two projects by revisiting the interpretation of both projects under the scope of uncertainty and by providing an overview of the internal representation of uncertainty that might subtend the experimental results. Subsequently, a part of the discussion was reserved to allude how the motor control field is transitioning from laboratory-based tasks to more naturalistic paradigms by using approaches to move motor control research toward real-world conditions. The discussion culminates with a brief scientific proposal along those lines

Adaptive intermittent control: A computational model explaining motor intermittency observed in human behavior

It is a fundamental question how our brain performs a given motor task in a real-time fashion with the slow sensorimotor system. Computational theory proposed an influential idea of feed-forward control, but it has mainly treated the case that the movement is ballistic (such as reaching) because the motor commands should be calculated in advance of movement execution. As a possible mechanism for operating feed-forward control in continuous motor tasks (such as target tracking), we propose a control model called "adaptive intermittent control" or "segmented control," that brain adaptively divides the continuous time axis into discrete segments and executes feed-forward control in each segment. The idea of intermittent control has been proposed in the fields of control theory, biological modeling and nonlinear dynamical system. Compared with these previous models, the key of the proposed model is that the system speculatively determines the segmentation based on the future prediction and its uncertainty. The result of computer simulation showed that the proposed model realized faithful visuo-manual tracking with realistic sensorimotor delays and with less computational costs (i.e., with fewer number of segments). Furthermore, it replicated "motor intermittency", that is, intermittent discontinuities commonly observed in human movement trajectories. We discuss that the temporally segmented control is an inevitable strategy for brain which has to achieve a given task with small computational (or cognitive) cost, using a slow control system in an uncertain variable environment, and the motor intermittency is the side-effect of this strategy

The role of planning in motor learning

Humans can learn a remarkable diversity of motor skills. While these skills are sometimes long lasting, they may also be subject to interference. For example, people can learn to reach in the presence of a dynamic (force-field) perturbation generated by a robotic interface. However, when two force fields that act in opposing directions are presented alternately, there is substantial interference, preventing learning of either. Here we examine the role of motor planning in motor memory formation and interference. We challenge a predominant view of motor learning, which suggests that multiple perturbations can only be learned when each is associated (closely in time) with a different physical (or perceived) state of the body. Instead, we show that two opposing perturbations which interfere when experienced over the same movement, can be learned if each is associated with a different neural state (i.e. motor plan). That is, distinct motor memories can be formed by planning each movement through the perturbation as part of a different, wider motor sequence, even if not executed. Exploring the implications of this result, we subsequently show that like planning, motor imagery of different future movements can change the neural state to affect the separation of motor memories. These results lead us to propose that situations which generate different neural responses in motor-related regions will naturally act as different contexts for learning. Interestingly however, we show that the same principle does not appear to underlie motor memory decay. Finally, having established the importance of planning in motor adaptation, we attempt to predict how motor plans should be divided and recombined when task sets become more complex. We simulate normative control policies under the hypothesis that motor chunking may arise from the need to efficiently represent motor commands, and test the implications for concurrent field learning. Together, these results highlight that the actions that humans plan are critical to the representation of motor skills that are learned. This suggests a key role for motor planning in the broad control repertoire humans develop.PhD funding by a Cambridge-Rutherford Memorial Scholarship, awarded by the Rutherford Foundatio