The role of cortical oscillations in a spiking neural network model of the basal ganglia.

Although brain oscillations involving the basal ganglia (BG) have been the target of extensive research, the main focus lies disproportionally on oscillations generated within the BG circuit rather than other sources, such as cortical areas. We remedy this here by investigating the influence of various cortical frequency bands on the intrinsic effective connectivity of the BG, as well as the role of the latter in regulating cortical behaviour. To do this, we construct a detailed neural model of the complete BG circuit based on fine-tuned spiking neurons, with both electrical and chemical synapses as well as short-term plasticity between structures. As a measure of effective connectivity, we estimate information transfer between nuclei by means of transfer entropy. Our model successfully reproduces firing and oscillatory behaviour found in both the healthy and Parkinsonian BG. We found that, indeed, effective connectivity changes dramatically for different cortical frequency bands and phase offsets, which are able to modulate (or even block) information flow in the three major BG pathways. In particular, alpha (8-12Hz) and beta (13-30Hz) oscillations activate the direct BG pathway, and favour the modulation of the indirect and hyper-direct pathways via the subthalamic nucleus-globus pallidus loop. In contrast, gamma (30-90Hz) frequencies block the information flow from the cortex completely through activation of the indirect pathway. Finally, below alpha, all pathways decay gradually and the system gives rise to spontaneous activity generated in the globus pallidus. Our results indicate the existence of a multimodal gating mechanism at the level of the BG that can be entirely controlled by cortical oscillations, and provide evidence for the hypothesis of cortically-entrained but locally-generated subthalamic beta activity. These two findings suggest new insights into the pathophysiology of specific BG disorders

The role of oscillation population activity in cortico-basal ganglia circuits.

The basal ganglia (BG) are a group of subcortical brain nuclei that are anatomically situated between the cortex and thalamus. Hitherto, models of basal ganglia function have been based solely on the anatomical connectivity and changes in the rate of neurons mediated by inhibitory and excitatory neurotransmitter interactions and modulated by dopamine. Depletion of striatal dopamine as occurs in Parkinson's Disease (PD) however, leads primarily to changes in the rhythmicity of basal ganglia neurons. The general aim of this thesis is to use frontal electrocorticogram (ECoG) and basal ganglia local field potential (LFP) recordings in the rat to further investigate the putative role for oscillations and synchronisation in these structures in the healthy and dopamine depleted brain. In the awake animal, lesion of the SNc lead to a dramatic increase in the power and synchronisation of P-frequency band oscillations in the cortex and subthalamic nucleus (STN) compared to the sham lesioned animal. These results are highly similar to those in human patients and provide further evidence for a direct pathophysological role for p-frequency band oscillations in PD. In the healthy, anaesthetised animal, LFPs recorded in the STN, globus pallidus (GP) and substantia nigra pars reticulata (SNr) were all found to be coherent with the ECoG. A detailed analysis of the interdependence and direction of these activities during two different brain states, prominent slow wave activity (SWA) and global activation, lead to the hypothesis that there were state dependant changes in the dominance of the cortico-subthalamic and cortico-striatal pathways. Multiple LFP recordings in the striatum and GP provided further evidence for this hypothesis, as coherence between the ECoG and GP was found to be dependent on the striatum. Together these results suggest that oscillations and synchronisation may mediate information flow in cortico-basal ganglia networks in both health and disease

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

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates

Prefrontal rhythms for cognitive control

Goal-directed behavior requires flexible selection among action plans and updating behavioral strategies when they fail to achieve desired goals. Lateral prefrontal cortex (LPFC) is implicated in the execution of behavior-guiding rule-based cognitive control while anterior cingulate cortex (ACC) is implicated in monitoring processes and updating rules. Rule-based cognitive control requires selective processing while process monitoring benefits from combinatorial processing. I used a combination of computational and experimental methods to investigate how network oscillations and neuronal heterogeneity contribute to cognitive control through their effects on selective versus combinatorial processing modes in LPFC and ACC. First, I adapted an existing LPFC model to explore input frequency- and coherence-based output selection mechanisms for flexible routing of rate-coded signals. I show that the oscillatory states of input encoding populations can exhibit a stronger influence over downstream competition than their activity levels. This enables an output driven by a weaker resonant input signal to suppress lower-frequency competing responses to stronger, less resonant (though possibly higher-frequency) input signals. While signals are encoded in population firing rates, output selection and signal routing can be governed independently by the frequency and coherence of oscillatory inputs and their correspondence with output resonant properties. Flexible response selection and gating can be achieved by oscillatory state control mechanisms operating on input encoding populations. These dynamic mechanisms enable experimentally-observed LPFC beta and gamma oscillations to flexibly govern the selection and gating of rate-coded signals for downstream read-out. Furthermore, I demonstrate how differential drives to distinct interneuron populations can switch working memory representations between asynchronous and oscillatory states that support rule-based selection. Next, I analyzed physiological data from the LeBeau laboratory and built a de novo model constrained by the biological data. Experimental data demonstrated that fast network oscillations at both the beta- and gamma frequency bands could be elicited in vitro in ACC and neurons exhibited a wide range of intrinsic properties. Computational modeling of the ACC network revealed that the frequency of network oscillation generated was dependent upon the time course of inhibition. Principal cell heterogeneity broadened the range of frequencies generated by the model network. In addition, with different frequency inputs to two neuronal assemblies, heterogeneity decreased competition and increased spike coherence between the networks thus conferring a combinatorial advantage to the network. These findings suggest that oscillating neuronal populations can support either response selection (routing), or combination, depending on the interplay between the kinetics of synaptic inhibition and the degree of heterogeneity of principal cell intrinsic conductances. Such differences may support functional differences between the roles of LPFC and ACC in cognitive control

Acetylcholine neuromodulation in normal and abnormal learning and memory: vigilance control in waking, sleep, autism, amnesia, and Alzheimer's disease

This article provides a unified mechanistic neural explanation of how learning, recognition, and cognition break down during Alzheimer's disease, medial temporal amnesia, and autism. It also clarifies whey there are often sleep disturbances during these disorders. A key mechanism is how acetylcholine modules vigilance control in cortical layer

The role of oscillatory synchrony in motor control.

Synchronized oscillations are manifest in various regions in the motor system. Their variable nature has increased the interest in the functional significance. Subcortical and cortical activity in the beta band is pathologically increased in Parkinson's disease (PD) - a state dominated by bradykinesia and rigidity. After the administration of the drug levodopa, beta activity and motor impairment are substantially decreased, while activity in the gamma band is increased. The function of beta bursts within the healthy motor system remains unknown. Recent evidence suggests that beta activity may promote the existing motor set and posture. In this thesis, with the use of positional hold tasks the role of beta activity on performance will be examined. It will be demonstrated that during bursts of beta synchrony in the corticomuscular system of healthy subjects there is an improvement, in the performance of these tasks. The findings will argue that physiological fluctuations in the beta band in the motor system may be of behavioural advantage during fine postural tasks involving the hand. The present work will also examine the role of population oscillations in the parkinsonian basal ganglia. It will demonstrate that under levodopa treatment the pattern of movement-related reactivity in the subthalamic nucleus (STN) and the pedunculopontine nucleus (PPN) as well as the background activity in the PPN change significantly. It will be shown that levodopa suppresses movement-related beta activity around the time of self-paced movements and promotes the increase of movement-related gamma activity contralateral to the movement side, following the same pattern as in the non dopamine-depleted brain. This suggests that dopaminergic therapy restores a more physiological pattern of reactivity in the STN. In the untreated state, beta activity in the STN will be shown to be modulated during repetitive self-paced movements, reflecting a role in ongoing performance, but only when motor performance is maximal and not when bradykinesia occurs. Finally, it will be demonstrated that levodopa promotes alpha band activity in the PPN at rest and before movement suggesting a possible physiological role of this activity in this nucleus. These observations provide further insight in the function of neuronal synchronization in the motor system in health and disease

The involvement of the primate frontal cortex-basal ganglia system in arbitrary visuomotor association learning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 97-103).It is the goal of this thesis to examine the frontal cortex-basal ganglia system during arbitrary visuomotor association learning, the forming of arbitrary links between visual stimuli and motor responses (e.g. red means stop), a fundamental learning process that underlies much of our complex behavior such as written language. The experiments contained in this thesis investigate the involvement of four components of this system in the acquisition of these associations: dorsolateral prefrontal cortex (dlPFC), caudate nucleus (Cd), frontal eye field (FEF), and the internal segment of the globus pallidus (GPi). Extracellular electrophysiological recordings were performed in awake-behaving primates performing three different learning tasks. In the different behavioral paradigms used in these studies, learning with and without reversals is investigated and compared both directly within the same experiment and indirectly across experiments. The results of these studies suggest that a complex interplay between brain areas in the frontal cortex-basal ganglia system exists. The study of FEF during reversal learning revealed that FEF contains task-related information from the start of learning, suggesting that it may be passing information onto PFC and Cd to aid the learning process. In addition, GPi is shown to contain more specific information about the learned association during the reversal task, providing evidence for an increase in the complexity of information processing through the basal ganglia.(cont.) The in-depth study of dlPFC and Cd suggests that the frontal cortex-basal ganglia system functions only when competition between learning contexts exist. When all competition is eliminated by removing reversal learning from the behavioral task, Cd does not show involvement in the learning process. But when competition exists, both Cd and PFC show learning-related changes in task-relevant information. As determined by coherence analysis of local field potentials, communication between dlPFC and Cd is greater during reversal learning, when competition is heightened. This communication also decreases as learning progresses suggesting a role in the transfer of information between areas in facilitating the learning process. Overall, these studies further the understanding of the role of the frontal cortex-basal ganglia system in arbitrary visuomotor learning and posit that the function of the system is dependent on the existence of competition between learned information.by Michelle S. Machon.Ph.D

Simultaneous activation of multiple memory systems during learning : insights from electrophysiology and modeling

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references.Parallel cortico-basal ganglia loops are thought to give rise to a diverse set of limbic, associative and motor functions, but little is known about how these loops operate and how their neural activities evolve during learning. To address these issues, single-unit activity was recorded simultaneously in dorsolateral (sensorimotor) and dorsomedial (associative) regions of the striatum as rats learned two versions of a conditional T-maze task. The results demonstrate that contrasting patterns of activity developed in these regions during task performance, and evolved with different training-related dynamics. Oscillatory activity is thought to enable memory storage and replay, and may encourage the efficient transmission of information between brain regions. In a second set of experiments, local field potentials (LFPs) were recorded simultaneously from the dorsal striatum and the CAl field of the hippocampus, as rats engaged in spontaneous and instructed behaviors in the T-maze. Two major findings are reported. First, striatal LFPs showed prominent theta-band rhythms that were strongly modulated during behavior. Second, striatal and hippocampal theta rhythms were modulated differently during T-maze performance, and in rats that successfully learned the task, became highly coherent during the choice period. To formalize the hypothesized contributions of dorsolateral and dorsomedial striatum during T-maze learning, a computational model was developed. This model localizes a model-free reinforcement learning (RL) system to the sensorimotor cortico-basal ganglia loop and localizes a model-based RL system to a network of structures including the associative cortico-basal ganglia loop and the hippocampus. Two models of dorsomedial striatal function were investigated, both of which can account for the patterns of activation observed during T-maze training. The two models make differing predictions regarding activation of the dorsomedial striatum following lesions of the model-free system, depending on whether it serves a direct role in action selection through participation in a model-based planning system or whether it participates in arbitrating between the model-free and model-based controllers. Combined, the work presented in this thesis shows that a large network of forebrain structures is engaged during procedural learning. The results suggest that coordination across regions may be required for successful learning and/or task performance, and that the different regions may contribute to behavioral performance by performing distinct RL computations.by Catherine Ann Thorn.Ph.D

The influence of dopamine on prediction, action and learning

In this thesis I explore functions of the neuromodulator dopamine in the context of autonomous learning and behaviour. I first investigate dopaminergic influence within a simulated agent-based model, demonstrating how modulation of synaptic plasticity can enable reward-mediated learning that is both adaptive and self-limiting. I describe how this mechanism is driven by the dynamics of agentenvironment interaction and consequently suggest roles for both complex spontaneous neuronal activity and specific neuroanatomy in the expression of early, exploratory behaviour. I then show how the observed response of dopamine neurons in the mammalian basal ganglia may also be modelled by similar processes involving dopaminergic neuromodulation and cortical spike-pattern representation within an architecture of counteracting excitatory and inhibitory neural pathways, reflecting gross mammalian neuroanatomy. Significantly, I demonstrate how combined modulation of synaptic plasticity and neuronal excitability enables specific (timely) spike-patterns to be recognised and selectively responded to by efferent neural populations, therefore providing a novel spike-timing based implementation of the hypothetical ‘serial-compound’ representation suggested by temporal difference learning. I subsequently discuss more recent work, focused upon modelling those complex spike-patterns observed in cortex. Here, I describe neural features likely to contribute to the expression of such activity and subsequently present novel simulation software allowing for interactive exploration of these factors, in a more comprehensive neural model that implements both dynamical synapses and dopaminergic neuromodulation. I conclude by describing how the work presented ultimately suggests an integrated theory of autonomous learning, in which direct coupling of agent and environment supports a predictive coding mechanism, bootstrapped in early development by a more fundamental process of trial-and-error learning