Brain tissue properties differentiate between motor and limbic basal ganglia circuits

Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high-resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcom

Decisional impulsivity and the associative-limbic subthalamic nucleus in obsessive-compulsive disorder: stimulation and connectivity.

Why do we make hasty decisions for short-term gain? Rapid decision-making with limited accumulation of evidence and delay discounting are forms of decisional impulsivity. The subthalamic nucleus is implicated in inhibitory function but its role in decisional impulsivity is less well-understood. Here we assess decisional impulsivity in subjects with obsessive compulsive disorder who have undergone deep brain stimulation of the limbic and associative subthalamic nucleus. We show that stimulation of the subthalamic nucleus is causally implicated in increasing decisional impulsivity with less accumulation of evidence during probabilistic uncertainty and in enhancing delay discounting. Subthalamic stimulation shifts evidence accumulation in subjects with obsessive-compulsive disorder towards a functional less cautious style closer to that of healthy controls emphasizing its adaptive nature. Thus, subjects with obsessive compulsive disorder on subthalamic stimulation may be less likely to check for evidence (e.g. checking that the stove is on) with no difference in subjective confidence (or doubt). In a separate study, we replicate in humans (154 healthy controls) using resting state functional connectivity, tracing studies conducted in non-human primates dissociating limbic, associative and motor frontal hyper-direct connectivity with anterior and posterior subregions of the subthalamic nucleus. We show lateralization of functional connectivity of bilateral ventral striatum to right anterior ventromedial subthalamic nucleus consistent with previous observations of lateralization of emotionally evoked activity to right ventral subthalamic nucleus. We use a multi-echo sequence with independent components analysis, which has been shown to have enhanced signal-to-noise ratio, thus optimizing visualization of small subcortical structures. These findings in healthy controls converge with the effective contacts in obsessive compulsive disorder patients localized within the anterior and ventral subthalamic nucleus. We further show that evidence accumulation is associated with anterior associative-limbic subthalamic nucleus and right dorsolateral prefrontal functional connectivity in healthy controls, a region implicated in decision-making under uncertainty. Together, our findings highlight specificity of the anterior associative-limbic subthalamic nucleus in decisional impulsivity. Given increasing interest in the potential for subthalamic stimulation in psychiatric disorders and the neuropsychiatric symptoms of Parkinson's disease, these findings have clinical implications for behavioural symptoms and cognitive effects as a function of localization of subthalamic stimulation.This work was supported by Agence Nationale de la Recherche (grant number ANR-14-CE13-0030-01 Physiobs); and University Hospital of Grenoble (Direction de la Recherche Clinique et de l’Innovation). This work was supported by a Wellcome Trust Fellowship grant to V.V. (983705/Z/10/Z)

A resting state network in the motor control circuit of the basal ganglia

<p>Abstract</p> <p>Background</p> <p>In the absence of overt stimuli, the brain shows correlated fluctuations in functionally related brain regions. Approximately ten largely independent resting state networks (RSNs) showing this behaviour have been documented to date. Recent studies have reported the existence of an RSN in the basal ganglia - albeit inconsistently and without the means to interpret its function. Using two large study groups with different resting state conditions and MR protocols, the reproducibility of the network across subjects, behavioural conditions and acquisition parameters is assessed. Independent Component Analysis (ICA), combined with novel analyses of temporal features, is applied to establish the basis of signal fluctuations in the network and its relation to other RSNs. Reference to prior probabilistic diffusion tractography work is used to identify the basal ganglia circuit to which these fluctuations correspond.</p> <p>Results</p> <p>An RSN is identified in the basal ganglia and thalamus, comprising the pallidum, putamen, subthalamic nucleus and substantia nigra, with a projection also to the supplementary motor area. Participating nuclei and thalamo-cortical connection probabilities allow this network to be identified as the motor control circuit of the basal ganglia. The network was reproducibly identified across subjects, behavioural conditions (fixation, eyes closed), field strength and echo-planar imaging parameters. It shows a frequency peak at 0.025 ± 0.007 Hz and is most similar in spectral composition to the Default Mode (DM), a network of regions that is more active at rest than during task processing. Frequency features allow the network to be classified as an RSN rather than a physiological artefact. Fluctuations in this RSN are correlated with those in the task-positive fronto-parietal network and anticorrelated with those in the DM, whose hemodynamic response it anticipates.</p> <p>Conclusion</p> <p>Although the basal ganglia RSN has not been reported in most ICA-based studies using a similar methodology, we demonstrate that it is reproducible across subjects, common resting state conditions and imaging parameters, and show that it corresponds with the motor control circuit. This characterisation of the basal ganglia network opens a potential means to investigate the motor-related neuropathologies in which the basal ganglia are involved.</p

Hitting the right target : noninvasive localization of the subthalamic nucleus motor part for specific deep brain stimulation

Deep brain stimulation of the subthalamic nucleus (STN) has gained momentum as a therapy for advanced Parkinson’s disease. The stimulation effectively alleviates the patients’ typical motor symptoms on a long term, but can give rise to cognitive and psychiatric adverse effects as well. Based on primate studies, the STN has been divided into three functionally different parts, which were distinguished by their afferent and efferent connections. The largest part is the motor area, followed by an associative and a limbic area. The serious adverse effects on cognition and behavior occurring after deep brain stimulation are assumed to be caused by electrical current spread to the associative and limbic areas of the STN. Therefore, selective stimulation of the motor part of the STN seems crucial, both to obtain the best possible therapeutic effect on the motor symptoms and to minimize the debilitating effects on cognition and behavior. However, current medical imaging techniques do not yet facilitate the required accurate identification of the STN itself, let alone its different functional areas. The final target for DBS is still often adjusted using intraoperative electrophysiology. Therefore, in this thesis we aimed to improve imaging for deep brain stimulation using noninvasive MRI protocols, in order to identify the STN and its motor part. We studied the advantages and drawbacks of already available noninvasive methods to target the STN. This review did not lead to a straightforward conclusion; identification of the STN motor part remained an open question. In follow-up on this question, we investigated the possibility to distinguish the different functional STN parts based on their connectivity information. Three types of information were carefully analyzed in this thesis. First, we looked into the clustering of local diffusion information within the STN region. We visually inspected the complex diffusion profiles, derived from postmortem rat brain data with high angular resolution, and augmented this manual segmentation method using k-means and graph cuts clustering. Because the weighing of different orders of diffusion information in the traditionally used L2 norm on the orientation distribution functions (ODFs) remained an open issue, we developed a specialized distance measure, the so-called Sobolev norm. This norm does not only take into account the amplitudes of the diffusion profiles, but also their extrema. We showed it to perform better than the L2 norm on synthetic phantom data and real brain (thalamus) data. The research done on this topic facilitates better classification by clustering of gray matter structures in the (deep) brain. Secondly, we were the first to analyze the STN’s full structural connectivity, based on probabilistic fiber tracking in diffusion MRI data of healthy volunteers. The results correspond well to topical literature on STN projections. Furthermore, we assessed the structural connectivity per voxel of the STN seed region and discovered a gradient in connectivity to the premotor cortex within the STN. While going from the medial to the lateral part of the STN, the connectivity increases, confirming the expected lateral location of the STN motor part. Finally, the connectivity analysis produced evidence for the existence of a "hyperdirect" pathway between the motor cortex and the STN in humans, which is very useful for future research into stimulation targets. The results of these experiments indicate that it is possible to find the motor part of the STN as specific target for deep brain stimulation using structural connectivity information acquired in a noninvasive way. Third and last, we studied functional connectivity using resting state functional MRI data of healthy volunteers. The resulting significant clusters provided us with the first complete description of the STN’s resting state functional connectivity, which corresponds with the expectations based on available literature. Moreover, we performed a reverse regression procedure with the average time series signals in motor and limbic areas as principal regressors. The results were analyzed for each STN voxel separately and also showed mediolateral gradients in functional connectivity within the STN. The lateral STN part exhibited more motor connectivity, while the medial part seemed to be more functionally connected to limbic brain areas, as described in neuronal tracer studies. These results show that functional connectivity analysis also is a viable noninvasive method to find the motor part of the STN. The work on noninvasive MRI methods for identification of the STN and its functional parts, as presented in this thesis, thus contributes to future specific stimulation of the motor part of the STN for deep brain stimulation in patients with Parkinson’s disease. This may help to maximize the motor effects and minimize severe cognitive and psychiatric side effects

The rostro-caudal gradient in the prefrontal cortex and its modulation by subthalamic deep brain stimulation in Parkinson’s disease

Acknowledgements The authors thank Benjamin Rahm (University of Freiburg) and Michael Fox (Harvard Medical School) for valuable comments on a previous version of this manuscript. This work was supported by a grant of the BrainLinks-BrainTools Cluster of Excellence funded by the German Research Foundation (DFG, grant number EXC 1086) to C.P.K., F.A., T.P., B.O.S., C.W, and V.A.C.; A.H. was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft, Emmy Noether Stipend 410169619 and 424778381 – TRR 295) as well as Deutsches Zentrum für Luft- und Raumfahrt (DynaSti grant within the EU Joint Programme Neurodegenerative Disease Research, JPND). Funding Open Access funding enabled and organized by Projekt DEAL.Peer reviewedPublisher PD

Basal Ganglia Pathways Associated With Therapeutic Pallidal Deep Brain Stimulation for Tourette Syndrome

BACKGROUND: Deep brain stimulation (DBS) targeting the globus pallidus internus (GPi) can improve tics and comorbid obsessive-compulsive behavior (OCB) in patients with treatment-refractory Tourette syndrome (TS). However, some patients’ symptoms remain unresponsive, the stimulation applied across patients is variable, and the mechanisms underlying improvement are unclear. Identifying the fiber pathways surrounding the GPi that are associated with improvement could provide mechanistic insight and refine targeting strategies to improve outcomes. METHODS: Retrospective data were collected for 35 patients who underwent bilateral GPi DBS for TS. Computational models of fiber tract activation were constructed using patient-specific lead locations and stimulation settings to evaluate the effects of DBS on basal ganglia pathways and the internal capsule. We first evaluated the relationship between activation of individual pathways and symptom improvement. Next, linear mixed-effects models with combinations of pathways and clinical variables were compared in order to identify the best-fit predictive models of tic and OCB improvement. RESULTS: The best-fit model of tic improvement included baseline severity and the associative pallido-subthalamic pathway. The best-fit model of OCB improvement included baseline severity and the sensorimotor pallidosubthalamic pathway, with substantial evidence also supporting the involvement of the prefrontal, motor, and premotor internal capsule pathways. The best-fit models of tic and OCB improvement predicted outcomes across the cohort and in cross-validation. CONCLUSIONS: Differences in fiber pathway activation likely contribute to variable outcomes of DBS for TS. Computational models of pathway activation could be used to develop novel approaches for preoperative targeting and selecting stimulation parameters to improve patient outcomes

A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder

BACKGROUND: Multiple deep brain stimulation (DBS) targets have been proposed for treating intractable obsessive-compulsive disorder (OCD). Here, we investigated whether stimulation effects of different target sites would be mediated by one common or several segregated functional brain networks. METHODS: First, seeding from active electrodes of 4 OCD patient cohorts (N = 50) receiving DBS to anterior limb of the internal capsule or subthalamic nucleus zones, optimal functional connectivity profiles for maximal Yale-Brown Obsessive Compulsive Scale improvements were calculated and cross-validated in leave-one-cohort-out and leave-one-patient-out designs. Second, we derived optimal target-specific connectivity patterns to determine brain regions mutually predictive of clinical outcome for both targets and others predictive for either target alone. Functional connectivity was defined using resting-state functional magnetic resonance imaging data acquired in 1000 healthy participants. RESULTS: While optimal functional connectivity profiles showed both commonalities and differences between target sites, robust cross-predictions of clinical improvements across OCD cohorts and targets suggested a shared network. Connectivity to the anterior cingulate cortex, insula, and precuneus, among other regions, was predictive regardless of stimulation target. Regions with maximal connectivity to these commonly predictive areas included the insula, superior frontal gyrus, anterior cingulate cortex, and anterior thalamus, as well as the original stereotactic targets. CONCLUSIONS: Pinpointing the network modulated by DBS for OCD from different target sites identified a set of brain regions to which DBS electrodes associated with optimal outcomes were functionally connected-regardless of target choice. On these grounds, we establish potential brain areas that could prospectively inform additional or alternative neuromodulation targets for obsessive-compulsive disorder

Cerebellar atrophy in Parkinson's disease and its implication for network connectivity.

Pathophysiological and atrophic changes in the cerebellum are documented in Parkinson's disease. Without compensatory activity, such abnormalities could potentially have more widespread effects on both motor and non-motor symptoms. We examined how atrophic change in the cerebellum impacts functional connectivity patterns within the cerebellum and between cerebellar-cortical networks in 42 patients with Parkinson's disease and 29 control subjects. Voxel-based morphometry confirmed grey matter loss across the motor and cognitive cerebellar territories in the patient cohort. The extent of cerebellar atrophy correlated with decreased resting-state connectivity between the cerebellum and large-scale cortical networks, including the sensorimotor, dorsal attention and default networks, but with increased connectivity between the cerebellum and frontoparietal networks. The severity of patients' motor impairment was predicted by a combination of cerebellar atrophy and decreased cerebellar-sensorimotor connectivity. These findings demonstrate that cerebellar atrophy is related to both increases and decreases in cerebellar-cortical connectivity in Parkinson's disease, identifying potential cerebellar driven functional changes associated with sensorimotor deficits. A post hoc analysis exploring the effect of atrophy in the subthalamic nucleus, a cerebellar input source, confirmed that a significant negative relationship between grey matter volume and intrinsic cerebellar connectivity seen in controls was absent in the patients. This suggests that the modulatory relationship of the subthalamic nucleus on intracerebellar connectivity is lost in Parkinson's disease, which may contribute to pathological activation within the cerebellum. The results confirm significant changes in cerebellar network activity in Parkinson's disease and reveal that such changes occur in association with atrophy of the cerebellum

Cortical - Basal Ganglia Circuits: Control of Behaviour and Alcohol Misuse

Highly organised and differentiated neural circuits form and unite to link the cortex with the basal ganglia and thalamus to mediate movement, cognition and behaviour. Previous assertions that the basal ganglia primarily acted to filter cortical information to facilitate motor outputs only have since given way to an understanding of the basal ganglia as a relay and gating structure with functionally and structurally segregated inputs, functions and outputs. Thus, cortical – basal ganglia circuits can be segregated into three broadly separable functional domains mediating motor (primary and supplementary motor cortex (SMA) and putamen), cognitive (dorsolateral prefrontal cortex (dlPFC) and caudate), and limbic (ventromedial prefrontal cortex and ventral striatum (VS)) processes. In addition, cognitive and behavioural programs that pass through the cortical – basal ganglia circuitry can be subject to filtering by the subthalamic nucleus (STN), which receives direct projections from the cortex. This work first demonstrated the functional organisation of segregated intrinsic cortical – basal ganglia circuits in humans, alongside a detailed map of functional subzones within STN, a small and technically inaccessible midbrain structure. The behavioural relevance of the defined cortical – basal ganglia circuits was investigated by examining the cognitive constructs of impulsivity and compulsivity. Waiting impulsivity, a tendency towards rapid premature responses that has been associated with compulsive drug use, was associated with connectivity between limbic regions including subgenual anterior cingulate cortex, VS and STN. However, motor impulsivity, in the form of stopping ability, was associated with motoric regions including pre-SMA and STN. Compulsivity was captured as deficits in: reversal learning, implicating lateral orbitofrontal cortex; attentional shifting, implicating dlPFC; and habit learning, implicating SMA. Neural circuit changes were also examined in individuals with alcohol dependence and binge drinkers. Waiting impulsivity was elevated in both groups and the functional connectivity, microstructural integrity and anatomical connectivity of the neural circuit underlying waiting impulsivity were associated with problematic drinking behaviours in both groups. Together, this work establishes that discrete functional subzones of small subcortical regions can be differentiated in humans and that their behavioural correlates can be similarly mapped. The definition of intrinsic network architecture underlying a particular behaviour and the demonstration its disturbance in psychiatric groups will crucially inform the development of future diagnostic and therapeutic models

The effect of subthalamic deep brain stimulation on motor learning in Parkinson’s disease

Deep brain stimulation (DBS) of the subthalamic nucleus is an effective and adjustable treatment for Parkinson’s disease patients with (early) motor complications and has been shown to elicit changes in motor and non-motor cortico-basal ganglia circuits through modulation of distributed neural networks. Recent findings on subcortical basal ganglia - cerebellar anatomy have revealed projections from the subthalamic nucleus to cerebellar hemispheres, which might be modulated by subthalamic DBS. Both the basal ganglia and the cerebellum are known to be involved in motor learning and Parkinson’s disease. This study aimed at investigating the effect of subthalamic DBS on motor learning in Parkinson’s disease (PD) and characterizing underlying neural networks. To this end, 20 Parkinson’s disease patients undergoing subthalamic DBS and 20 age-matched healthy controls performed a visuomotor task. Motor learning was assessed as reduction in movement times from beginning to end of task for each group. DBS electrodes were localized and projected to a publicly available normative connectome (1000 healthy subjects) and a connectivity map for DBS induced improvement in motor learning was calculated. Region of interest analysis was performed to assess the role of connectivity to motor cortex (M1) and cerebellar hemispheres in DBS induced learning. Permutation tests and multiple regressions were conducted for the main statistical analyses; for significant regression models and correlations leave one out cross validation (LOOCV) was performed. Motor learning was impaired in Parkinson’s disease patients off DBS comparing with healthy controls (PD off DBS: 12.2±5.4% from 1311±160ms to 1089±118ms; mean ± standard error of mean; healthy controls: 33.48±3.6% from 729±63ms to 473±42ms; off DBS vs. healthy controls P=0.002). STN-DBS led to a statistically significant improvement in motor learning (PD on DBS: 27.7±6.1% from 940±120ms to 615±84ms; on vs. off DBS P=0.01). There was no statistically significant difference between patients on DBS and healthy controls (P=0.4). DBS induced improvement in motor learning was not correlated with improvement in motor deficits (R=-0.02, P=0.5). A specific connectivity profile including the right cerebellar hemisphere was associated with improved motor learning through DBS (R²=0.33, P=0.01; LOOCV: R=0.43, P=0.028). Region of interest analysis revealed the ipsilateral cerebellum to be the best predictor of DBS induced motor learning (R2=0.34, P=0.008; LOOCV: R=0.045, P=0.02). Here, connectivity to the STN was higher than to M1, suggesting a putative role of the recently discovered basal ganglia - cerebellar circuit bypassing the cortex. This study extends current knowledge on motor learning in Parkinson’s disease and highlights the notion of network modulation in DBS.Die Tiefe Hirnstimulation (THS) des Nucleus subthalamicus ist eine effektive Therapiealternative für Patienten mit idiopathischem Parkinson Syndrom (IPS) und (frühen) motorischen Komplikationen, welche zu verschiedenen motorischen und nicht-motorischen Effekten in der Kortex-Basalganglienschleife führt. Es ist lange bekannt, dass die Basalganglien und das Kleinhirn sowohl beim IPS als auch beim motorischen Lernen eine Rolle spielen. Neue anatomische Studien zeigten eine disynaptische subkortikale Verbindung zwischen den Nucleus subthalamicus und den Kleinhirnhemisphären mit bisher unklarer funktioneller Bedeutung. Die vorliegende Studie untersucht den Effekt subthalamischer THS auf motorisches Lernen beim idiopathischen Parkinson Syndrom mit dem Ziel, zugrundeliegende neuronale Netzwerke zu charakterisieren. Hierfür führten 20 Patienten mit IPS unter THS und 20 altersgepaarte gesunde Probanden eine visuomotorische Reaktionszeitaufgabe durch. Motorisches Lernen wurde als Verbesserung der Bewegungszeiten durch Wiederholung der Aufgabe definiert. THS Elektroden wurden lokalisiert und auf ein öffentlich verfügbares normatives funktionelles MRT Konnektom projiziert (1000 gesunde Probanden). Das optimale Konnektivitätsprofil für THS induziertes motorisches Lernen wurde berechnet. Zusätzlich wurde eine Konnektivitätsanalyse durchgeführt, um die Rolle der Verbindung von aktiven THS Kontakten zum motorischen Kortex und zu den Kleinhirnhemisphären für THS induziertes Lernen zu untersuchen. Die statistische Auswertung der Hauptergebnisse erfolgte durch Monte Carlo Permutation und multiple Regressionen; statistisch signifikante Regressionsmodelle und Korrelationen wurden mittels der „Leave one out“ Methode kreuzvalidiert. Patienten mit IPS und ausgeschalteter THS zeigten ein signifikant beeinträchtigtes motorisches Lernen im Vergleich zu gesunden Kontrollen (IPS mit THS OFF: 12.2±5.4%, von 1311±160ms auf 1089±118ms; gesunde Kontrollen: 33.48±3.6%, von 729±63ms auf 473±42ms; P=0.002). Die subthalamische THS führte zu einer statistisch signifikanten Verbesserung des motorischen Lernens in Patienten mit IPS (IPS mit THS ON: 27.7±6.1%, von 940±120ms auf 615±84ms; P=0.01). Es ergab sich kein signifikanter Unterschied zwischen Patienten mit eingeschalteter THS und gesunden Kontrollen (P=0.4). THS induziertes motorisches Lernen korrelierte nicht mit Linderung motorischer Symptome (R=-0.02, P=0.5). Es konnte ein spezifisches fMRT Konnektivitätsprofil von den aktiven THS Kontakten definiert werden, welches prädiktiv für den Effekt der THS auf motorisches Lernen war (R²=0.33, P=0.01; LOOCV: R=0.43, P=0.028). Eine weiterführende Analyse ergab einen gesonderten Einfluss der rechten Kleinhirnhemisphäre als bester Prädiktor für THS induziertes motorisches Lernen (R2=0.34, P=0.008; LOOCV: R=0.045, P=0.02). In diesen Voxels war funktionelle Konnektivität zum Nucleus subthalamicus höher als zum motorischen Kortex, hinweisend auf eine relevante Rolle der beschriebenen direkten Verbindung vom Nucleus subthalamicus zu den Kleinhirnhemisphären. Diese Studie liefert neue Erkenntnisse über den Zusammenhang von motorischem Lernen und der Neuromodulation motorischer Netzwerke beim idiopathischen Parkinson Syndrom und erweitert das Konzept der Netzwerkmodulation als mechanistisches Modell zur Wirksamkeit der THS