Basal ganglia physiology and pathophysiology: a reappraisal

Challenges for future theories of Parkinson pathophysiology

Current theories on the basal ganglia-thalamic-cortical circuitry address the phenomena of hypokinesia and hyperkinesia. In this Perspective, we question whether the current models can address the orchestration of the motor units which is the common final pathway of the motor system. We conclude that the current theories do not to address this orchestration in health and disease. One alternative approach worthy of consideration is nonmonotonic nonlinear dynamics that contrast with a fundamentally linear or monotonic nonlinear approach that are presumed by current theories of basal ganglia-thalamic-cortical system. The purpose here is to make the case that current theories do presuppose a linear or monotonic nonlinear perspective which will be demonstrated as failing to adequately explicate the complex orchestration of motor unit activities in normal movement and in movement disorders. The notion of nonlinear dynamics is not new to neurophysiology; however, it is argued that it is new to the concepts of the physiology and pathophysiology of the basal ganglia-thalamic-cortical system. Providing a wholesale reconceptualization of the basal ganglia-thalamic-cortical system is beyond the scope of this effort. Rather, the contribution of the essay is convincing that there is a need to reconceptualize theories as nonlinear dynamical systems and there are metaphors and analogies from nonlinear science that can be productive in the reconsideration.

Deep brain stimulation: a review of the open neural engineering challenges

OBJECTIVE

Deep brain stimulation (DBS) is an established and valid therapy for a variety of pathological conditions ranging from motor to cognitive disorders. Still, much of the DBS-related mechanism of action is far from being understood, and there are several side effects of DBS whose origin is unclear. In the last years DBS limitations have been tackled by a variety of approaches, including adaptive deep brain stimulation (aDBS), a technique that relies on using chronically implanted electrodes on 'sensing mode' to detect the neural markers of specific motor symptoms and to deliver on-demand or modulate the stimulation parameters accordingly. Here we will review the state of the art of the several approaches to improve DBS and summarize the main challenges toward the development of an effective aDBS therapy.

APPROACH

We discuss models of basal ganglia disorders pathogenesis, hardware and software improvements for conventional DBS, and candidate neural and non-neural features and related control strategies for aDBS.

MAIN RESULTS

We identify then the main operative challenges toward optimal DBS such as (i) accurate target localization, (ii) increased spatial resolution of stimulation, (iii) development of in silico tests for DBS, (iv) identification of specific motor symptoms biomarkers, in particular (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) clarify how stimulation affects the cortico-basal-ganglia-thalamic network to (vii) design optimal stimulation patterns.

SIGNIFICANCE

This roadmap will lead neural engineers novel to the field toward the most relevant open issues of DBS, while the in-depth readers might find a careful comparison of advantages and drawbacks of the most recent attempts to improve DBS-related neuromodulatory strategies.

The Psychopharmacology of Obsessive-Compulsive Disorder: A Preclinical Roadmap

This review evaluates current knowledge about obsessive-compulsive disorder (OCD), with the goal of providing a roadmap for future directions in research on the psychopharmacology of the disorder. It first addresses issues in the description and diagnosis of OCD, including the structure, measurement, and appropriate description of the disorder and issues of differential diagnosis. Current pharmacotherapies for OCD are then reviewed, including monotherapy with serotonin reuptake inhibitors and augmentation with antipsychotic medication and with psychologic treatment. Neuromodulatory therapies for OCD are also described, including psychosurgery, deep brain stimulation, and noninvasive brain stimulation. Psychotherapies for OCD are then reviewed, focusing on behavior therapy, including exposure and response prevention and cognitive therapy, and the efficacy of these interventions is discussed, touching on issues such as the timing of sessions, the adjunctive role of pharmacotherapy, and the underlying mechanisms. Next, current research on the neurobiology of OCD is examined, including work probing the role of various neurotransmitters and other endogenous processes and etiology as clues to the neurobiological fault that may underlie OCD. A new perspective on preclinical research is advanced, using the Research Domain Criteria to propose an adaptationist viewpoint that regards OCD as the dysfunction of a normal motivational system. A systems-design approach introduces the security motivation system (SMS) theory of OCD as a framework for research. Finally, a new perspective on psychopharmacological research for OCD is advanced, exploring three approaches: boosting infrastructure facilities of the brain, facilitating psychotherapeutic relearning, and targeting specific pathways of the SMS network to fix deficient SMS shut-down processes. SIGNIFICANCE STATEMENT: A significant proportion of patients with obsessive-compulsive disorder (OCD) do not achieve remission with current treatments, indicating the need for innovations in psychopharmacology for the disorder. OCD may be conceptualized as the dysfunction of a normal, special motivation system that evolved to manage the prospect of potential danger. This perspective, together with a wide-ranging review of the literature, suggests novel directions for psychopharmacological research, including boosting support systems of the brain, facilitating relearning that occurs in psychotherapy, and targeting specific pathways in the brain that provide deficient stopping processes in OCD.

Local field potential dynamics in the primate cortex in relation to parkinsonism reveled by machine learning: A comparison between the primary motor cortex and the supplementary area

The present study compares the cortical local field potentials (LFPs) in the primary motor cortex (M1) and the supplementary motor area (SMA) of non-human primates rendered Parkinsonian with administration of dopaminergic neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The dynamic of the LFPs was investigated under several mathematical frameworks and machine learning was used to discriminate the recordings based on these features between healthy, parkinsonian with off-medication and parkinsonian with on-medication states. The importance of each feature in the discrimination process was further investigated. The dynamic of the LFPs in M1 and SMA was affected regarding its variability (time domain analysis), oscillatory activities (frequency domain analysis) and complex patterns (non-linear domain analysis). Machine learning algorithms achieved accuracy near 0.90 for comparisons between conditions. The TreeBagger algorithm provided best accuracy. The relative importance of these features differed with the cortical location, condition and treatment. Overall, the most important features included beta oscillation, fractal dimension, gamma oscillation, entropy and asymmetry of amplitude fluctuation. The importance of features in discriminating between normal and pathological states, and on- or off-medication states depends on the pair-comparison and it is region-specific. These findings are discussed regarding the refinement of current models for movement disorders and the development of on-demand therapies.

Obsessive compulsive disorder (OCD): Current treatments and a framework for neurotherapeutic research

We briefly review current approaches to the diagnosis and treatment of OCD, noting their lack of a strong theoretical foundation. In keeping with the Research Domain Criteria project (RDoC) calls for reconceptualizing psychopathology in ways that better link up with normal brain systems, we advance an adaptationist, brain-network perspective on OCD and propose that OCD represents a dysfunction in the stopping dynamics of a normal brain network that evolved to handle potential danger. We then illustrate how this theoretical perspective can be used to organize possibilities for research on neurotherapeutics for OCD and suggest novel directions for future work.

Subthalamic Stimulation Reduces Vowel Space at the Initiation of Sustained Production: Implications for Articulatory Motor Control in Parkinson's Disease

Background: Stimulation of the subthalamic nuclei (STN) is an effective treatment for Parkinson’s disease, but complaints of speech difficulties after surgery have been difficult to quantify. Speech measures do not convincingly account for such reports.

Objective: This study examined STN stimulation effects on vowel production, in order to probe whether DBS affects articulatory posturing. The objective was to compare positioning during the initiation phase with the steady prolongation phase by measuring vowel spaces for three “corner” vowels at these two time frames.

Methods: Vowel space was measured over the initial 0.25 sec of sustained productions of high front (/i/), high back (/u/) and low vowels (/a/), and again during a 2 sec segment at the midpoint. Eight right-handed male subjects with bilateral STN stimulation and seven age-matched male controls were studied based on their participation in a larger study that included functional imaging. Mean values: age = 57±4.6 yrs; PD duration = 12.3±2.7 yrs; duration of DBS = 25.6±21.2 mos, and UPDRS III speech score = 1.6±0.7. STN subjects were studied off medication at their therapeutic DBS settings and again with their stimulators off, counter-balanced order.

Results: Vowel space was larger in the initiation phase compared to the midpoint for both the control and the STN subjects off stimulation. With stimulation on, however, the initial vowel space was significantly reduced to the area measured at the mid-point. For the three vowels, the acoustics were differentially affected, in accordance with expected effects of front versus back position in the vocal tract.

Conclusions: STN stimulation appears to constrain initial articulatory gestures for vowel production, raising the possibility that articulatory positions normally used in speech are similarly constrained.

Subcortical Effects on Voice and Fluency in Dysarthria: Observations from Subthalamic Nucleus Stimulation

OBJECTIVE

Parkinson's disease (PD), caused by basal ganglia dysfunction, is associated with motor disturbances including dysarthria. Stimulation of the subthalamic nucleus, a preferred treatment targeting basal ganglia function, improves features of the motor disorder, but has uncertain effects on speech.We studied speech during contrasting stimulation states to reveal subcortical effects on voice and articulation. Measures were made on selected samples of spontaneous and repeated speech.

METHODS

Persons with Parkinson's disease (PWP) who had undergone bilateral deep brain stimulation of the subthalamic nucleus (DBS-STN) provided spontaneous speech samples and then repeated portions of their monologue both on and off stimulation. Excerpts were presented in a listening protocol probing intelligibility. Also analysed were a continuous phrase repetition task and a second spontaneous speech sample. Fundamental frequency (F0), harmonic-to-noise ratio (HNR), jitter, shimmer and fluency were measured in these three speech samples performed with DBS stimulation on and off.

RESULTS

During subcortical stimulation, spontaneous excerpts were less intelligible than repeated excerpts. F0 and HNR were higher and shimmer was decreased in repetition and stimulation. Articulatory dysfluencies were increased for spontaneous speech and during stimulation in all three speech samples.

CONCLUSION

Deep brain stimulation disrupts fluency and improves voice in spontaneous speech, reflecting an inverse influence of subcortical systems on articulatory posturing and laryngeal mechanisms. Better voice and less dysfluency in repetition may occur because an external model reduces the speech planning burden, as seen for gait and arm reach. These orthogonal results for fluency versus phonatory competence may account for ambivalent reports from dysarthric speakers and reveal the complexity of subcortical control of motor speech.

Structure Function Revisited: A Simple Tool for Complex Analysis of Neuronal Activity

Neural systems are characterized by their complex dynamics, reflected on signals produced by neurons and neuronal ensembles. This complexity exhibits specific features in health, disease and in different states of consciousness, and can be considered a hallmark of certain neurologic and neuropsychiatric conditions. To measure complexity from neurophysiologic signals, a number of different nonlinear tools of analysis are available. However, not all of these tools are easy to implement, or able to handle clinical data, often obtained in less than ideal conditions in comparison to laboratory or simulated data. Recently, the temporal structure function emerged as a powerful tool for the analysis of complex properties of neuronal activity. The temporal structure function is efficient computationally and it can be robustly estimated from short signals. However, the application of this tool to neuronal data is relatively new, making the interpretation of results difficult. In this methods paper we describe a step by step algorithm for the calculation and characterization of the structure function. We apply this algorithm to oscillatory, random and complex toy signals, and test the effect of added noise. We show that: (1) the mean slope of the structure function is zero in the case of random signals; (2) oscillations are reflected on the shape of the structure function, but they don't modify the mean slope if complex correlations are absent; (3) nonlinear systems produce structure functions with nonzero slope up to a critical point, where the function turns into a plateau. Two characteristic numbers can be extracted to quantify the behavior of the structure function in the case of nonlinear systems: (1). the point where the plateau starts (the inflection point, where the slope change occurs), and (2). the height of the plateau. While the inflection point is related to the scale where correlations weaken, the height of the plateau is related to the noise present in the signal. To exemplify our method we calculate structure functions of neuronal recordings from the basal ganglia of parkinsonian and healthy rats, and draw guidelines for their interpretation in light of the results obtained from our toy signals.

Modeling and Theories of Pathophysiology and Physiology of the Basal Ganglia-Thalamic-Cortical System: Critical Analysis

Theories impact the movement disorders clinic, not only affecting the development of new therapies but determining how current therapies are used. Models are theories that are procedural rather than declarative. Theories and models are important because, as argued by Kant, one cannot know the thing-in-itself (das Ding an sich) and only a model is knowable. Further, biological variability forces higher level abstraction relevant for all variants. It is that abstraction that is raison d'être of theories and models. Theories "connect the dots" to move from correlation to causation. The necessity of theory makes theories helpful or counterproductive. Theories and models of the pathophysiology and physiology of the basal ganglia-thalamic-cortical system do not spontaneously arise but have a history and consequently are legacies. Over the last 40 years, numerous theories and models of the basal ganglia have been proposed only to be forgotten or dismissed, rarely critiqued. It is not harsh to say that current popular theories positing increased neuronal activities in the Globus Pallidus Interna (GPi), excessive beta oscillations and increased synchronization not only fail to provide an adequate explication but are inconsistent with many observations. It is likely that their shared intellectual and epistemic inheritance plays a factor in their shared failures. These issues are critically examined. How one is to derive theories and models and have hope these will be better is explored as well.

Deep Brain Stimulation Frequency-A Divining Rod for New and Novel Concepts of Nervous System Function and Therapy

The efficacy of Deep Brain Stimulation (DBS) for an expanding array of neurological and psychiatric disorders demonstrates directly that DBS affects the basic electroneurophysiological mechanisms of the brain. The increasing array of active electrode configurations, stimulation currents, pulse widths, frequencies, and pulse patterns provides valuable tools to probe electroneurophysiological mechanisms. The extension of basic electroneurophysiological and anatomical concepts using sophisticated computational modeling and simulation has provided relatively straightforward explanations of all the DBS parameters except frequency. This article summarizes current thought about frequency and relevant observations. Current methodological and conceptual errors are critically examined in the hope that future work will not replicate these errors. One possible alternative theory is presented to provide a contrast to many current theories. DBS, conceptually, is a noisy discrete oscillator interacting with the basal ganglia–thalamic–cortical system of multiple re-entrant, discrete oscillators. Implications for positive and negative resonance, stochastic resonance and coherence, noisy synchronization, and holographic memory (related to movement generation) are presented. The time course of DBS neuronal responses demonstrates evolution of the DBS response consistent with the dynamics of re-entrant mechanisms. Finally, computational modeling demonstrates identical dynamics as seen by neuronal activities recorded from human and nonhuman primates, illustrating the differences of discrete from continuous harmonic oscillators and the power of conceptualizing the nervous system as composed on interacting discrete nonlinear oscillators.

High Frequency Deep Brain Stimulation and Neural Rhythms in Parkinson's Disease

High frequency (HF) deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease (PD). It effectively treats the cardinal motor signs of PD, including tremor, bradykinesia, and rigidity. The most common neural target is the subthalamic nucleus, located within the basal ganglia, the region most acutely affected by PD pathology. Using chronically-implanted DBS electrodes, researchers have been able to record underlying neural rhythms from several nodes in the PD network as well as perturb it using DBS to measure the ensuing neural and behavioral effects, both acutely and over time. In this review, we provide an overview of the PD neural network, focusing on the pathophysiological signals that have been recorded from PD patients as well as the mechanisms underlying the therapeutic benefits of HF DBS. We then discuss evidence for the relationship between specific neural oscillations and symptoms of PD, including the aberrant relationships potentially underlying functional connectivity in PD as well as the use of different frequencies of stimulation to more specifically target certain symptoms. Finally, we briefly describe several current areas of investigation and how the ability to record neural data in ecologically-valid settings may allow researchers to explore the relationship between brain and behavior in an unprecedented manner, culminating in the future automation of neurostimulation therapy for the treatment of a variety of neuropsychiatric diseases.

A new biomarker for subthalamic deep brain stimulation for patients with advanced Parkinson's disease--a pilot study

OBJECTIVE

Deep brain stimulation (DBS) has become the standard treatment for advanced stages of Parkinson's disease (PD) and other motor disorders. Although the surgical procedure has improved in accuracy over the years thanks to imaging and microelectrode recordings, the underlying principles that render DBS effective are still debated today. The aim of this paper is to present initial findings around a new biomarker that is capable of assessing the efficacy of DBS treatment for PD which could be used both as a research tool, as well as in the context of a closed-loop stimulator.

APPROACH

We have used a novel multi-channel stimulator and recording device capable of measuring the response of nervous tissue to stimulation very close to the stimulus site with minimal latency, rejecting most of the stimulus artefact usually found with commercial devices. We have recorded and analyzed the responses obtained intraoperatively in two patients undergoing DBS surgery in the subthalamic nucleus (STN) for advanced PD.

MAIN RESULTS

We have identified a biomarker in the responses of the STN to DBS. The responses can be analyzed in two parts, an initial evoked compound action potential arising directly after the stimulus onset, and late responses (LRs), taking the form of positive peaks, that follow the initial response. We have observed a morphological change in the LRs coinciding with a decrease in the rigidity of the patients.

SIGNIFICANCE

These initial results could lead to a better characterization of the DBS therapy, and the design of adaptive DBS algorithms that could significantly improve existing therapies and help us gain insights into the functioning of the basal ganglia and DBS.

Closed-loop stimulation of a delayed neural fields model of parkinsonian STN-GPe network: a theoretical and computational study

Several disorders are related to pathological brain oscillations. In the case of Parkinson's disease, sustained low-frequency oscillations (especially in the β-band, 13-30 Hz) correlate with motor symptoms. It is still under debate whether these oscillations are the cause of parkinsonian motor symptoms. The development of techniques enabling selective disruption of these β-oscillations could contribute to the understanding of the underlying mechanisms, and could be exploited for treatments. A particularly appealing technique is Deep Brain Stimulation (DBS). With clinical electrical DBS, electrical currents are delivered at high frequency to a region made of potentially heterogeneous neurons (the subthalamic nucleus (STN) in the case of Parkinson's disease). Even more appealing is DBS with optogenetics, which is until now a preclinical method using both gene transfer and deep brain light delivery and enabling neuromodulation at the scale of one given neural network. In this work, we rely on delayed neural fields models of STN and the external Globus Pallidus (GPe) to develop, theoretically validate and test in silico a closed-loop stimulation strategy to disrupt these sustained oscillations with optogenetics. First, we rely on tools from control theory to provide theoretical conditions under which sustained oscillations can be attenuated by a closed-loop stimulation proportional to the measured activity of STN. Second, based on this theoretical framework, we show numerically that the proposed closed-loop stimulation efficiently attenuates sustained oscillations, even in the case when the photosensitization effectively affects only 50% of STN neurons. We also show through simulations that oscillations disruption can be achieved when the same light source is used for the whole STN population. We finally test the robustness of the proposed strategy to possible acquisition and processing delays, as well as parameters uncertainty.

Neuronal Complexity in Subthalamic Nucleus is Reduced in Parkinson's Disease

Several theories posit increased Subthalamic Nucleus (STN) activity is causal to Parkinsonism, yet in our previous study we showed that activity from 113 STN neurons from two epilepsy patients and 103 neurons from nine Parkinson's disease (PD) patients demonstrated no significant differences in frequencies or in the coefficients of variation of mean discharge frequencies per 1-s epochs. We continued our analysis using point process modeling to capture higher order temporal dynamics; in particular, bursting, beta-band oscillations, excitatory and inhibitory ensemble interactions, and neuronal complexity. We used this analysis as input to a logistic regression classifier and were able to differentiate between PD and epilepsy neurons with an accuracy of 92%. We also found neuronal complexity, i.e., the number of states in a neuron's point process model, and inhibitory ensemble dynamics, which can be interpreted as a reduction in complexity, to be the most important features with respect to classification accuracy. Even in a dataset with no significant differences in firing rate, we observed differences between PD and epilepsy for other single-neuron measures. Our results suggest PD comes with a reduction in neuronal "complexity," which translates to a neuron's ability to encode information; the more complexity, the more information the neuron can encode. This is also consistent with studies correlating disease to loss of variability in neuronal activity, as the lower the complexity, the less variability.

Sixty hertz neurostimulation amplifies subthalamic neural synchrony in Parkinson's disease

High frequency subthalamic nucleus (STN) deep brain stimulation (DBS) improves the cardinal motor signs of Parkinson's disease (PD) and attenuates STN alpha/beta band neural synchrony in a voltage-dependent manner. While there is a growing interest in the behavioral effects of lower frequency (60 Hz) DBS, little is known about its effect on STN neural synchrony. Here we demonstrate for the first time that during intra-operative 60 Hz STN DBS, one or more bands of resting state neural synchrony were amplified in the STN in PD. We recorded intra-operative STN resting state local field potentials (LFPs) from twenty-eight STNs in seventeen PD subjects after placement of the DBS lead (model 3389, Medtronic, Inc.) before and during three randomized neurostimulation sets (130 Hz/1.35V, 130 Hz/2V, 60 Hz/2V). During 130 Hz/2V DBS, baseline (no DBS) STN alpha (8-12 Hz) and beta (13-35 Hz) band power decreased (N=14, P < 0.001 for both), whereas during 60 Hz/2V DBS, alpha band and peak frequency power increased (P = 0.012, P = 0.007, respectively). The effect of 60 Hz/2V DBS opposed that of power-equivalent (130 Hz/1.35V) DBS (alpha: P < 0.001, beta: P = 0.006). These results show that intra-operative 60 Hz STN DBS amplified whereas 130 Hz STN DBS attenuated resting state neural synchrony in PD; the effects were frequency-specific. We demonstrate that neurostimulation may be useful as a tool to selectively modulate resting state resonant bands of neural synchrony and to investigate its influence on motor and non-motor behaviors in PD and other neuropsychiatric diseases.

Neural code alterations and abnormal time patterns in Parkinson's disease

OBJECTIVE

The neural code used by the basal ganglia is a current question in neuroscience, relevant for the understanding of the pathophysiology of Parkinson's disease. While a rate code is known to participate in the communication between the basal ganglia and the motor thalamus/cortex, different lines of evidence have also favored the presence of complex time patterns in the discharge of the basal ganglia. To gain insight into the way the basal ganglia code information, we studied the activity of the globus pallidus pars interna (GPi), an output node of the circuit.

APPROACH

We implemented the 6-hydroxydopamine model of Parkinsonism in Sprague-Dawley rats, and recorded the spontaneous discharge of single GPi neurons, in head-restrained conditions at full alertness. Analyzing the temporal structure function, we looked for characteristic scales in the neuronal discharge of the GPi.

MAIN RESULTS

At a low-scale, we observed the presence of dynamic processes, which allow the transmission of time patterns. Conversely, at a middle-scale, stochastic processes force the use of a rate code. Regarding the time patterns transmitted, we measured the word length and found that it is increased in Parkinson's disease. Furthermore, it showed a positive correlation with the frequency of discharge, indicating that an exacerbation of this abnormal time pattern length can be expected, as the dopamine depletion progresses.

SIGNIFICANCE

We conclude that a rate code and a time pattern code can co-exist in the basal ganglia at different temporal scales. However, their normal balance is progressively altered and replaced by pathological time patterns in Parkinson's disease.

Therapeutic mechanisms of high-frequency stimulation in Parkinson's disease and neural restoration via loop-based reinforcement

High-frequency deep brain stimulation (HFS) is clinically recognized to treat parkinsonian movement disorders, but its mechanisms remain elusive. Current hypotheses suggest that the therapeutic merit of HFS stems from increasing the regularity of the firing patterns in the basal ganglia (BG). Although this is consistent with experiments in humans and animal models of Parkinsonism, it is unclear how the pattern regularization would originate from HFS. To address this question, we built a computational model of the cortico-BG-thalamo-cortical loop in normal and parkinsonian conditions. We simulated the effects of subthalamic deep brain stimulation both proximally to the stimulation site and distally through orthodromic and antidromic mechanisms for several stimulation frequencies (20-180 Hz) and, correspondingly, we studied the evolution of the firing patterns in the loop. The model closely reproduced experimental evidence for each structure in the loop and showed that neither the proximal effects nor the distal effects individually account for the observed pattern changes, whereas the combined impact of these effects increases with the stimulation frequency and becomes significant for HFS. Perturbations evoked proximally and distally propagate along the loop, rendezvous in the striatum, and, for HFS, positively overlap (reinforcement), thus causing larger poststimulus activation and more regular patterns in striatum. Reinforcement is maximal for the clinically relevant 130-Hz stimulation and restores a more normal activity in the nuclei downstream. These results suggest that reinforcement may be pivotal to achieve pattern regularization and restore the neural activity in the nuclei downstream and may stem from frequency-selective resonant properties of the loop.

Rethinking energy in parkinsonian motor symptoms: a potential role for neural metabolic deficits

Parkinson’s disease (PD) is characterized as a chronic and progressive neurodegenerative disorder that results in a variety of debilitating symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. Research spanning several decades has emphasized basal ganglia dysfunction, predominantly resulting from dopaminergic (DA) cell loss, as the primarily cause of the aforementioned parkinsonian features. But, why those particular features manifest themselves remains an enigma. The goal of this paper is to develop a theoretical framework that parkinsonian motor features are behavioral consequence of a long-term adaptation to their inability (inflexibility or lack of capacity) to meet energetic demands, due to neural metabolic deficits arising from mitochondrial dysfunction associated with PD. Here, we discuss neurophysiological changes that are generally associated with PD, such as selective degeneration of DA neurons in the substantia nigra pars compacta (SNc), in conjunction with metabolic and mitochondrial dysfunction. We then characterize the cardinal motor symptoms of PD, bradykinesia, resting tremor, rigidity and gait disturbance, reviewing literature to demonstrate how these motor patterns are actually energy efficient from a metabolic perspective. We will also develop three testable hypotheses: (1) neural metabolic deficits precede the increased rate of neurodegeneration and onset of behavioral symptoms in PD; (2) motor behavior of persons with PD are more sensitive to changes in metabolic/bioenergetic state; and (3) improvement of metabolic function could lead to better motor performance in persons with PD. These hypotheses are designed to introduce a novel viewpoint that can elucidate the connections between metabolic, neural and motor function in PD.

Multiple-time-scale framework for understanding the progression of Parkinson's disease

Parkinson's disease is marked by neurodegenerative processes that affect the pattern of discharge of basal ganglia neurons. The main features observed in the parkinsonian globus pallidus pars interna (GPi), a subdomain of the basal ganglia that is involved in the regulation of voluntary movement, are pathologically increased and synchronized neuronal activity. How these changes affect the implemented neuronal code is not well understood. Our experimental temporal structure-function analysis shows that in parkinsonian animals the rate-coding window of GPi neurons needed for the proper performance of voluntary actions is reduced. The model of the GPi network that we develop and discuss here reveals indeed that the size of the rate-coding window shrinks as the network activity increases and is expanded if the coupling strength among the neurons is increased. This leads to the novel interpretation that the pathological neuronal synchronization in Parkinson's disease in the GPi is the result of a collective attempt to counterbalance the shrinking of the rate-coding window due to increased activity in GPi neurons.

Behavior modulates effective connectivity between cortex and striatum

It has been notoriously difficult to understand interactions in the basal ganglia because of multiple recurrent loops. Another complication is that activity there is strongly dependent on behavior, suggesting that directional interactions, or effective connections, can dynamically change. A simplifying approach would be to examine just the direct, monosynaptic projections from cortex to striatum and contrast this with the polysynaptic feedback connections from striatum to cortex. Previous work by others on effective connectivity in this pathway indicated that activity in cortex could be used to predict activity in striatum, but that striatal activity could not predict cortical activity. However, this work was conducted in anesthetized or seizing animals, making it impossible to know how free behavior might influence effective connectivity. To address this issue, we applied Granger causality to local field potential signals from cortex and striatum in freely behaving rats. Consistent with previous results, we found that effective connectivity was largely unidirectional, from cortex to striatum, during anesthetized and resting states. Interestingly, we found that effective connectivity became bidirectional during free behaviors. These results are the first to our knowledge to show that striatal influence on cortex can be as strong as cortical influence on striatum. In addition, these findings highlight how behavioral states can affect basal ganglia interactions. Finally, we suggest that this approach may be useful for studies of Parkinson's or Huntington's diseases, in which effective connectivity may change during movement.

Non-linear dynamics in parkinsonism

Over the last 30 years, the functions (and dysfunctions) of the sensory-motor circuitry have been mostly conceptualized using linear modelizations which have resulted in two main models: the “rate hypothesis” and the “oscillatory hypothesis.” In these two models, the basal ganglia data stream is envisaged as a random temporal combination of independent simple patterns issued from its probability distribution of interval interspikes or its spectrum of frequencies respectively. More recently, non-linear analyses have been introduced in the modelization of motor circuitry activities, and they have provided evidences that complex temporal organizations exist in basal ganglia neuronal activities. Regarding movement disorders, these complex temporal organizations in the basal ganglia data stream differ between conditions (i.e., parkinsonism, dyskinesia, healthy control) and are responsive to treatments (i.e., l-DOPA, deep brain stimulation). A body of evidence has reported that basal ganglia neuronal entropy (a marker for complexity/irregularity in time series) is higher in hypokinetic state. In line with these findings, an entropy-based model has been recently formulated to introduce basal ganglia entropy as a marker for the alteration of motor processing and a factor of motor inhibition. Importantly, non-linear features have also been identified as a marker of condition and/or treatment effects in brain global signals (EEG), muscular activities (EMG), or kinetic of motor symptoms (tremor, gait) of patients with movement disorders. It is therefore warranted that the non-linear dynamics of motor circuitry will contribute to a better understanding of the neuronal dysfunctions underlying the spectrum of parkinsonian motor symptoms including tremor, rigidity, and hypokinesia.

Non-linear dynamical analysis of EEG time series distinguishes patients with Parkinson's disease from healthy individuals

The pathophysiology of Parkinson’s disease (PD) is known to involve altered patterns of neuronal firing and synchronization in cortical-basal ganglia circuits. One window into the nature of the aberrant temporal dynamics in the cerebral cortex of PD patients can come from analysis of the patients electroencephalography (EEG). Rather than using spectral-based methods, we used data models based on delay differential equations (DDE) as non-linear time-domain classification tools to analyze EEG recordings from PD patients on and off dopaminergic therapy and healthy individuals. Two sets of 50 1-s segments of 64-channel EEG activity were recorded from nine PD patients on and off medication and nine age-matched controls. The 64 EEG channels were grouped into 10 clusters covering frontal, central, parietal, and occipital brain regions for analysis. DDE models were fitted to individual trials, and model coefficients and error were used as features for classification. The best models were selected using repeated random sub-sampling validation and classification performance was measured using the area under the ROC curve A′. In a companion paper, we show that DDEs can uncover hidden dynamical structure from short segments of simulated time series of known dynamical systems in high noise regimes. Using the same method for finding the best models, we found here that even short segments of EEG data in PD patients and controls contained dynamical structure, and moreover, that PD patients exhibited a greater dynamic range than controls. DDE model output on the means from one set of 50 trials provided nearly complete separation of PD patients off medication from controls: across brain regions, the area under the receiver-operating characteristic curves, A′, varied from 0.95 to 1.0. For distinguishing PD patients on vs. off medication, classification performance A′ ranged from 0.86 to 1.0 across brain regions. Moreover, the generalizability of the model to the second set of 50 trials was excellent, with A′ ranging from 0.81 to 0.94 across brain regions for controls vs. PD off medication, and from 0.62 to 0.82 for PD on medication vs. off. Finally, model features significantly predicted individual patients’ motor severity, as assessed with standard clinical rating scales.

Primary motor cortex of the parkinsonian monkey: altered neuronal responses to muscle stretch

Exaggeration of the long-latency stretch reflex (LLSR) is a characteristic neurophysiologic feature of Parkinson's disease (PD) that contributes to parkinsonian rigidity. To explore one frequently-hypothesized mechanism, we studied the effects of fast muscle stretches on neuronal activity in the macaque primary motor cortex (M1) before and after the induction of parkinsonism by unilateral administration of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). We compared results from the general population of M1 neurons and two antidromically-identified subpopulations: distant-projecting pyramidal-tract type neurons (PTNs) and intra-telecenphalic-type corticostriatal neurons (CSNs). Rapid rotations of elbow or wrist joints evoked short-latency responses in 62% of arm-related M1 neurons. As in PD, the late electromyographic responses that constitute the LLSR were enhanced following MPTP. This was accompanied by a shortening of M1 neuronal response latencies and a degradation of directional selectivity, but surprisingly, no increase in single unit response magnitudes. The results suggest that parkinsonism alters the timing and specificity of M1 responses to muscle stretch. Observation of an exaggerated LLSR with no change in the magnitude of proprioceptive responses in M1 is consistent with the idea that the increase in LLSR gain that contributes to parkinsonian rigidity is localized to the spinal cord.

Synchrony in Parkinson's disease: importance of intrinsic properties of the external globus pallidus

The mechanisms for the emergence and transmission of synchronized oscillations in Parkinson's disease, which are potentially causal to motor deficits, remain debated. Aside from the motor cortex and the subthalamic nucleus, the external globus pallidus (GPe) has been shown to be essential for the maintenance of these oscillations and plays a major role in sculpting neural network activity in the basal ganglia (BG). While neural activity of the healthy GPe shows almost no correlations between pairs of neurons, prominent synchronization in the β frequency band arises after dopamine depletion. Several studies have proposed that this shift is due to network interactions between the different BG nuclei, including the GPe. However, recent studies demonstrate an important role for the properties of neurons within the GPe. In this review, we will discuss these intrinsic GPe properties and review proposed mechanisms for activity decorrelation within the dopamine-intact GPe. Failure of the GPe to desynchronize correlated inputs can be a possible explanation for synchronization in the whole BG. Potential triggers of synchronization involve the enhancement of GPe-GPe inhibition and changes in ion channel function in GPe neurons.

What basal ganglia changes underlie the parkinsonian state? The significance of neuronal oscillatory activity

One well accepted functional feature of the parkinsonian state is the recording of enhanced beta oscillatory activity in the basal ganglia. This has been demonstrated in patients with Parkinson's disease (PD) and in animal models such as the rat with 6-hydroxydopamine (6-OHDA)-induced lesion and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys, all of which are associated with severe striatal dopamine depletion. Neuronal hyper-synchronization in the beta (or any other) band is not present despite the presence of bradykinetic features in the rat and monkey models, suggesting that increased beta band power may arise when nigro-striatal lesion is advanced and that it is not an essential feature of the early parkinsonian state. Similar observations and conclusions have been previously made for increased neuronal firing rate in the subthalamic and globus pallidus pars interna nuclei. Accordingly, it is suggested that early parkinsonism may be associated with dynamic changes in basal ganglia output activity leading to reduced movement facilitation that may be an earlier feature of the parkinsonian state.

Central thalamic deep brain stimulation for support of forebrain arousal regulation in the minimally conscious state

This chapter considers the use of central thalamic deep brain stimulation (CT/DBS) to support arousal regulation mechanisms in the minimally conscious state (MCS). CT/DBS for selected patients in a MCS is first placed in the historical context of prior efforts to use thalamic electrical brain stimulation to treat the unconscious clinical conditions of coma and vegetative state. These previous studies and a proof of concept result from a single-subject study of a patient in a MCS are reviewed against the background of new population data providing benchmarks of the natural history of vegetative and MCSs. The conceptual foundations for CT/DBS in selected patients in a MCS are then presented with consideration of both circuit and cellular mechanisms underlying recovery of consciousness identified from empirical studies. Directions for developing future generalizable criteria for CT/DBS that focus on the integrity of necessary brain systems and behavioral profiles in patients in a MCS that may optimally response to support of arousal regulation mechanisms are proposed.

A Point Process Model-based Framework Reveals Reinforcement Mechanisms in Striatum during High Frequency STN DBS

Striatum is a major stage of the motor loop but, despite a pivotal role in the execution of movements, it has been poorly studied thus far under Parkinsonian conditions and Deep Brain Stimulation (DBS). We propose a computational framework to analyze the spiking activity of striatal neurons under several conditions. This framework combines point process models and single unit recordings, and separately evaluates the effects of the spiking history, DBS frequency, and other cells on the neuronal discharge pattern, thus giving a full characterization of non-stationary neuronal dynamics and inter-neuronal dependencies. We applied this framework to 166 striatal neurons collected in a monkey both at rest and during DBS (30-130 Hz). Our analysis was conducted both before and after treatment of the animal with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which evoked Parkinsonian-like motor disorders. We reported that high frequency (≥100 Hz) DBS reduces non-stationary dynamics and inter-neuronal dependencies by regularizing the discharge patterns both in MPTP and normal striatum, while the combination of MPTP and low frequency (30-80 Hz) DBS enhances these features, thus suggesting that pattern regularization in striatum might contribute to the therapeutic effect of high frequency DBS and presumably results from the overlap of feed-forward and feedback activation along the motor loop (reinforcement).

The epistemology of Deep Brain Stimulation and neuronal pathophysiology

Deep Brain Stimulation (DBS) is a remarkable therapy succeeding where all manner of pharmacological manipulations and brain transplants fail. The success of DBS has resurrected the relevance of electrophysiology and dynamics on the order of milliseconds. Despite the remarkable effects of DBS, its mechanisms of action are largely unknown. There has been an expanding catalogue of various neuronal and neural responses to DBS or DBS-like stimulation but no clear conceptual encompassing explanatory scheme has emerged despite the technological prowess and intellectual sophistication of the scientists involved. Something is amiss. If the scientific observations are sound, then why has there not been more progress? The alternative is that it may be the hypotheses that frame the questions are at fault as well as the methods of inference (logic) used to validate the hypotheses. An analysis of the past and current notions of the DBS mechanisms of action is the subject in order to identify the presuppositions (premises) and logical fallacies that may be at fault. The hope is that these problems will be avoided in the future so the DBS can realize its full potential quickly. In this regard, the discussion of the methods of inference and presuppositions that underlie many current notions is no different then a critique of experimental methods common in scientific discussions and consequently, examinations of the epistemology and logic are appropriate. This analysis is in keeping with the growing appreciation among scientists and philosophers of science, the scientific observations (data) to not “speak for themselves” nor is the scientific method self-evidently true and that consideration of the underlying inferential methods is necessary.

Moving toward a generalizable application of central thalamic deep brain stimulation for support of forebrain arousal regulation in the severely injured brain

This review considers the challenges ahead for developing a generalizable strategy for the use of central thalamic deep brain stimulation (CT/DBS) to support arousal regulation mechanisms in the severely injured brain. Historical efforts to apply CT/DBS to patients with severe brain injuries and a proof-of-concept result from a single-subject study are discussed. Circuit and cellular mechanisms underlying the recovery of consciousness are considered for their relevance to the application of CT/DBS, to improve consciousness and cognition in nonprogressive brain injuries. Finally, directions for development, and testing of generalizable criteria for CT/DBS are suggested, which aim to identify neuronal substrates and behavioral profiles that may optimally benefit from support of arousal regulation mechanisms.

Intermittent neural synchronization in Parkinson's disease

Motor symptoms of Parkinson's disease are related to the excessive synchronized oscillatory activity in the beta frequency band (around 20Hz) in the basal ganglia and other parts of the brain. This review explores the dynamics and potential mechanisms of these oscillations employing ideas and methods from nonlinear dynamics. We present extensive experimental documentation of the relevance of synchronized oscillations to motor behavior in Parkinson's disease, and we discuss the intermittent character of this synchronization. The reader is introduced to novel time-series analysis techniques aimed at the detection of the fine temporal structure of intermittent phase locking observed in the brains of parkinsonian patients. Modeling studies of brain networks are reviewed, which may describe the observed intermittent synchrony, and we discuss what these studies reveal about brain dynamics in Parkinson's disease. The parkinsonian brain appears to exist on the boundary between phase-locked and nonsynchronous dynamics. Such a situation may be beneficial in the healthy state, as it may allow for easy formation and dissociation of transient patterns of synchronous activity which are required for normal motor behavior. Dopaminergic degeneration in Parkinson's disease may shift the brain networks closer to this boundary, which would still permit some motor behavior while accounting for the associated motor deficits. Understanding the mechanisms of the intermittent synchrony in Parkinson's disease is also important for biomedical engineering since efficient control strategies for suppression of pathological synchrony through deep brain stimulation require knowledge of the dynamics of the processes subjected to control.

FINITE DIMENSIONAL STRUCTURE OF THE GPI DISCHARGE IN PATIENTS WITH PARKINSON'S DISEASE

Stochastic systems are infinitely dimensional and deterministic systems are low dimensional, while real systems lie somewhere between these two limit cases. If the calculation of a low (finite) dimension is in fact possible, one could conclude that the system under study is not purely random. In the present work we calculate the maximal Lyapunov exponent from interspike intervals time series recorded from the internal segment of the Globus Pallidusfrom patients with Parkinson's disease. We show the convergence of the maximal Lyapunov exponent at a dimension equal to 7 or 8, which is therefore our estimation of the embedding dimension for the system. For dimensions below 7 the observed behavior is what would be expected from a stochastic system or a complex system projecting onto lower dimensional spaces. The maximal Lyapunov exponent did not show any differences between tremor and akineto-rigid forms of the disease. However, it did decay with the value of motor Unified Parkinson's Disease Rating Scale -OFF scores. Patients with a more severe disease (higher UPDRS-OFF score) showed a lower value of the maximal Lyapunov exponent. Taken together, both indexes (the maximal Lyapunov exponent and the embedding dimension) remark the importance of taking into consideration the system's non-linear properties for a better understanding of the information transmission in the basal ganglia.

High-frequency deep brain stimulation of the putamen improves bradykinesia in Parkinson's disease

Deep brain stimulation is effective for a wide range of neurological disorders; however, its mechanisms of action remain unclear. With respect to Parkinson's disease, the existence of multiple effective targets suggests that putamen stimulation also may be effective and raises questions as to the mechanisms of action. Are there as many mechanisms of action as there are effective targets or some single or small set of mechanisms common to all effective targets? During the course of routine surgery of the globus pallidus interna in patients with Parkinson's disease, the deep brain stimulation lead was placed in the putamen en route to the globus pallidus interna. Recordings of hand opening and closing during high-frequency and no stimulation were made. Speed of the movements, based on the amplitude and frequency of the repetitive hand movements as well as the decay in amplitude, were studied. Hand speed in 6 subjects was statistically significantly faster during active deep brain stimulation than the no-stimulation condition. There were no statistically significant differences in decay in the amplitude of hand movements. High-frequency deep brain stimulation of the putamen improves bradykinesia in a hand-opening and -closing task in patients with Parkinson's disease. Consequently, high-frequency deep brain stimulation of virtually every structure in the basal ganglia-thalamic-cortical system improves bradykinesia. These observations, together with microelectrode recordings reported in the literature, argue that deep brain stimulation effects may be system specific and not structure specific.

Primary motor cortex of the parkinsonian monkey: differential effects on the spontaneous activity of pyramidal tract-type neurons

Dysfunction of primary motor cortex (M1) is thought to contribute to the pathophysiology of parkinsonism. What specific aspects of M1 function are abnormal remains uncertain, however. Moreover, few models consider the possibility that distinct cortical neuron subtypes may be affected differently. Those questions were addressed by studying the resting activity of intratelencephalic-type corticostriatal neurons (CSNs) and distant-projecting lamina 5b pyramidal-tract type neurons (PTNs) in the macaque M1 before and after the induction of parkinsonism by administration of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Contrary to previous reports, the general population of M1 neurons (i.e., PTNs, CSNs, and unidentified neurons) showed reduced baseline firing rates following MPTP, attributable largely to a marked decrease in PTN firing rates. CSN firing rates were unmodified. Although burstiness and firing patterns remained constant in M1 neurons as a whole and CSNs in particular, PTNs became more bursty post-MPTP and less likely to fire in a regular-spiking pattern. Rhythmic spiking (found in PTNs predominantly) occurred at beta frequencies (14-32 Hz) more frequently following MPTP. These results indicate that MPTP intoxication induced distinct modifications in the activity of different M1 neuronal subtypes. The particular susceptibility of PTNs suggests that PTN dysfunction may be an important contributor to the pathophysiology of parkinsonian motor signs.

One View of the Current State of Understanding in Basal Ganglia Pathophysiology and What is Needed for the Future

Deep Brain Stimulation (DBS), arguably, is the most dramatic development in movement disorders since the levodopa for Parkinson's disease. Yet, its mechanisms of action of DBS are unknown. However, DBS related research already has demonstrated that current concepts of basal ganglia pathophysiology are wrong. Specifically, the notion that over-activity of the globus pallidus interna causes parkinsonism, the basis for the most current theories, is no longer tenable. The development of any new theory will be aided by an understanding of how current theories are wrong and why have these flawed theories persist. Many of the problems of current theories are more matters of inference, assumptions, presumptions, and the accepted level of ambiguity than they are of fact. Consequently, it is imperative that these issues be addressed. Just as the inappropriate use of a tool or method is grounds for criticism, methods of reasoning are tools that can be used inappropriately and should be subject to discussion just as misuse of any other tool. Thorough criticism can provide very important lesions though the process could be mistaken as harsh or personal; neither is the case here. At the least, such analyzes can point to potential pitfalls that could be avoided in the development of new theories. As will be discussed, theories are important for the development of therapies but perhaps most important, for the acceptance of new therapies, as was the case for the recent resurgence of interest in surgical therapies.

Activation of subthalamic neurons by contralateral subthalamic deep brain stimulation in Parkinson disease

Multiple studies have shown bilateral improvement in motor symptoms in Parkinson disease (PD) following unilateral deep brain stimulation (DBS) of the subthalamic nucleus (STN) and internal segment of the globus pallidus, yet the mechanism(s) underlying this phenomenon are poorly understood. We hypothesized that STN neuronal activity is altered by contralateral STN DBS. This hypothesis was tested intraoperatively in humans with advanced PD using microelectrode recordings of the STN during contralateral STN DBS. We demonstrate alterations in the discharge pattern of STN neurons in response to contralateral STN DBS including short latency, temporally precise, stimulation frequency-independent responses consistent with antidromic activation. Furthermore, the total discharge frequency during contralateral high frequency stimulation (160 Hz) was greater than during low frequency stimulation (30 Hz) and the resting state. These findings demonstrate complex responses to DBS and imply that output activation throughout the basal ganglia-thalamic-cortical network rather than local inhibition is a therapeutic mechanism of DBS.

Fine temporal structure of beta oscillations synchronization in subthalamic nucleus in Parkinson's disease

Synchronous oscillatory dynamics in the beta frequency band is a characteristic feature of neuronal activity of basal ganglia in Parkinson's disease and is hypothesized to be related to the disease's hypokinetic symptoms. This study explores the temporal structure of this synchronization during episodes of oscillatory beta-band activity. Phase synchronization (phase locking) between extracellular units and local field potentials (LFPs) from the subthalamic nucleus (STN) of parkinsonian patients is analyzed here at a high temporal resolution. We use methods of nonlinear dynamics theory to construct first-return maps for the phases of oscillations and quantify their dynamics. Synchronous episodes are interrupted by less synchronous episodes in an irregular yet structured manner. We estimate probabilities for different kinds of these "desynchronization events." There is a dominance of relatively frequent yet very brief desynchronization events with the most likely desynchronization lasting for about one cycle of oscillations. The chances of longer desynchronization events decrease with their duration. The observed synchronization may primarily reflect the relationship between synaptic input to STN and somatic/axonal output from STN at rest. The intermittent, transient character of synchrony even on very short time scales may reflect the possibility for the basal ganglia to carry out some informational function even in the parkinsonian state. The dominance of short desynchronization events suggests that even though the synchronization in parkinsonian basal ganglia is fragile enough to be frequently destabilized, it has the ability to reestablish itself very quickly.

Relief of acquired stuttering associated with Parkinson's disease by unilateral left subthalamic brain stimulation

PURPOSE

In this article, the authors report a case of acquired stuttering associated with Parkinson's disease (PD) that was responsive to unilateral subthalamic nucleus deep-brain stimulation (STN DBS) in the language-dominant hemisphere.

METHOD

A single-subject, masked, multiple baseline design was used to evaluate the effects of unilateral left STN DBS on stuttering associated with PD. The patient underwent 3 formal speech assessments of spontaneous speech and the reading of passages with DBS off and on. Speech samples were videotaped and placed in random order, and 2 independent speech-language pathologists calculated the percentage of stuttered syllables and classified individual stuttering events.

RESULTS

Stuttering improved significantly in the DBS-on condition. In total, 10% of syllables were affected by stuttering events with DBS off, and less than 1% of syllables were affected by stuttering events with DBS on (n = 2,281 syllables, p < .00001, in a chi(2) test). The effect of unilateral STN DBS on stuttering was relatively independent of whether the patient was on or off dopaminergic medications.

CONCLUSION

This article emphasizes the important role of the subthalamic region in the motor control of speech and language.

Network perspectives on the mechanisms of deep brain stimulation

Deep brain stimulation (DBS) is an established medical therapy for the treatment of movement disorders and shows great promise for several other neurological disorders. However, after decades of clinical utility the underlying therapeutic mechanisms remain undefined. Early attempts to explain the mechanisms of DBS focused on hypotheses that mimicked an ablative lesion to the stimulated brain region. More recent scientific efforts have explored the wide-spread changes in neural activity generated throughout the stimulated brain network. In turn, new theories on the mechanisms of DBS have taken a systems-level approach to begin to decipher the network activity. This review provides an introduction to some of the network based theories on the function and pathophysiology of the cortico-basal-ganglia-thalamo-cortical loops commonly targeted by DBS. We then analyze some recent results on the effects of DBS on these networks, with a focus on subthalamic DBS for the treatment of Parkinson's disease. Finally we attempt to summarize how DBS could be achieving its therapeutic effects by overriding pathological network activity.