Local orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain.

A central challenge of neuroscience is to elucidate how brain function supports consciousness. Here, we combine the specificity of focal deep brain stimulation with fMRI coverage of the entire cortex, in awake and anaesthetised non-human primates. During propofol, sevoflurane, or ketamine anaesthesia, and subsequent restoration of responsiveness by electrical stimulation of the central thalamus, we investigate how loss of consciousness impacts distributed patterns of structure-function organisation across scales. We report that distributed brain activity under anaesthesia is increasingly constrained by brain structure across scales, coinciding with anaesthetic-induced collapse of multiple dimensions of hierarchical cortical organisation. These distributed signatures are observed across different anaesthetics, and they are reversed by electrical stimulation of the central thalamus, coinciding with recovery of behavioural markers of arousal. No such effects were observed upon stimulating the ventral lateral thalamus, demonstrating specificity. Overall, we identify consistent distributed signatures of consciousness that are orchestrated by specific thalamic nuclei.

Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks.

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs.

Deep brain stimulation is a treatment option for patients with drug-resistant epilepsy. The precise mechanism of neuromodulation in epilepsy is unknown, and biomarkers are needed for optimizing treatment. The aim of this study was to describe the neural network associated with deep brain stimulation targets for epilepsy and to explore its potential application as a novel biomarker for neuromodulation. Using seed-to-voxel functional connectivity maps, weighted by seizure outcomes, brain areas associated with stimulation were identified in normative resting state functional scans of 1000 individuals. To pinpoint specific regions in the normative epilepsy deep brain stimulation network, we examined overlapping areas of functional connectivity between the anterior thalamic nucleus, centromedian thalamic nucleus, hippocampus and less studied epilepsy deep brain stimulation targets. Graph network analysis was used to describe the relationship between regions in the identified network. Furthermore, we examined the associations of the epilepsy deep brain stimulation network with disease pathophysiology, canonical resting state networks and findings from a systematic review of resting state functional MRI studies in epilepsy deep brain stimulation patients. Cortical nodes identified in the normative epilepsy deep brain stimulation network were in the anterior and posterior cingulate, medial frontal and sensorimotor cortices, frontal operculum and bilateral insulae. Subcortical nodes of the network were in the basal ganglia, mesencephalon, basal forebrain and cerebellum. Anterior thalamic nucleus was identified as a central hub in the network with the highest betweenness and closeness values, while centromedian thalamic nucleus and hippocampus showed average centrality values. The caudate nucleus and mammillothalamic tract also displayed high centrality values. The anterior cingulate cortex was identified as an important cortical hub associated with the effect of deep brain stimulation in epilepsy. The neural network of deep brain stimulation targets shared hubs with known epileptic networks and brain regions involved in seizure propagation and generalization. Two cortical clusters identified in the epilepsy deep brain stimulation network included regions corresponding to resting state networks, mainly the default mode and salience networks. Our results were concordant with findings from a systematic review of resting state functional MRI studies in patients with deep brain stimulation for epilepsy. Our findings suggest that the various epilepsy deep brain stimulation targets share a common cortico-subcortical network, which might in part underpin the antiseizure effects of stimulation. Interindividual differences in this network functional connectivity could potentially be used as biomarkers in selection of patients, stimulation parameters and neuromodulation targets.

Probing responses to deep brain stimulation with functional magnetic resonance imaging.

BACKGROUND: Deep brain stimulation (DBS) is an established treatment for certain movement disorders and has additionally shown promise for various psychiatric, cognitive, and seizure disorders. However, the mechanisms through which stimulation exerts therapeutic effects are incompletely understood. A technique that may help to address this knowledge gap is functional magnetic resonance imaging (fMRI). This is a non-invasive imaging tool which permits the observation of DBS effects in vivo. OBJECTIVE: The objective of this review was to provide a comprehensive overview of studies in which fMRI during active DBS was performed, including studied disorders, stimulated brain regions, experimental designs, and the insights gleaned from stimulation-evoked fMRI responses. METHODS: We conducted a systematic review of published human studies in which fMRI was performed during active stimulation in DBS patients. The search was conducted using PubMED and MEDLINE. RESULTS: The rate of fMRI DBS studies is increasing over time, with 37 studies identified overall. The median number of DBS patients per study was 10 (range = 1-67, interquartile range = 11). Studies examined fMRI responses in various disease cohorts, including Parkinson's disease (24 studies), essential tremor (3 studies), epilepsy (3 studies), obsessive-compulsive disorder (2 studies), pain (2 studies), Tourette syndrome (1 study), major depressive disorder, anorexia, and bipolar disorder (1 study), and dementia with Lewy bodies (1 study). The most commonly stimulated brain region was the subthalamic nucleus (24 studies). Studies showed that DBS modulates large-scale brain networks, and that stimulation-evoked fMRI responses are related to the site of stimulation, stimulation parameters, patient characteristics, and therapeutic outcomes. Finally, a number of studies proposed fMRI-based biomarkers for DBS treatment, highlighting ways in which fMRI could be used to confirm circuit engagement and refine DBS therapy. CONCLUSION: A review of the literature reflects an exciting and expanding field, showing that the combination of DBS and fMRI represents a uniquely powerful tool for simultaneously manipulating and observing neural circuitry. Future work should focus on relatively understudied disease cohorts and stimulated regions, while focusing on the prospective validation of putative fMRI-based biomarkers.

Deep brain stimulation of the thalamus restores signatures of consciousness in a nonhuman primate model.

Loss of consciousness is associated with the disruption of long-range thalamocortical and corticocortical brain communication. We tested the hypothesis that deep brain stimulation (DBS) of central thalamus might restore both arousal and awareness following consciousness loss. We applied anesthesia to suppress consciousness in nonhuman primates. During anesthesia, central thalamic stimulation induced arousal in an on-off manner and increased functional magnetic resonance imaging activity in prefrontal, parietal, and cingulate cortices. Moreover, DBS restored a broad dynamic repertoire of spontaneous resting-state activity, previously described as a signature of consciousness. None of these effects were obtained during the stimulation of a control site in the ventrolateral thalamus. Last, DBS restored a broad hierarchical response to auditory violations that was disrupted under anesthesia. Thus, DBS restored the two dimensions of consciousness, arousal and conscious access, following consciousness loss, paving the way to its therapeutical translation in patients with disorders of consciousness.

Deep brain stimulation targets in epilepsy: Systematic review and meta-analysis of anterior and centromedian thalamic nuclei and hippocampus.

Deep brain stimulation (DBS) is a neuromodulatory treatment used in patients with drug-resistant epilepsy (DRE). The primary goal of this systematic review and meta-analysis is to describe recent advancements in the field of DBS for epilepsy, to compare the results of published trials, and to clarify the clinical utility of DBS in DRE. A systematic literature search was performed by two independent authors. Forty-four articles were included in the meta-analysis (23 for anterior thalamic nucleus [ANT], 8 for centromedian thalamic nucleus [CMT], and 13 for hippocampus) with a total of 527 patients. The mean seizure reduction after stimulation of the ANT, CMT, and hippocampus in our meta-analysis was 60.8%, 73.4%, and 67.8%, respectively. DBS is an effective and safe therapy in patients with DRE. Based on the results of randomized controlled trials and larger clinical series, the best evidence exists for DBS of the anterior thalamic nucleus. Further randomized trials are required to clarify the role of CMT and hippocampal stimulation. Our analysis suggests more efficient deep brain stimulation of ANT for focal seizures, wider use of CMT for generalized seizures, and hippocampal DBS for temporal lobe seizures. Factors associated with clinical outcome after DBS for epilepsy are electrode location, stimulation parameters, type of epilepsy, and longer time of stimulation. Recent advancements in anatomical targeting, functional neuroimaging, responsive neurostimulation, and sensing of local field potentials could potentially lead to improved outcomes after DBS for epilepsy and reduced sudden, unexpected death of patients with epilepsy. Biomarkers are needed for successful patient selection, targeting of electrodes and optimization of stimulation parameters.

A Network-Based Approach to Glioma Surgery: Insights from Functional Neurosurgery.

The evaluation and manipulation of structural and functional networks, which has been integral to advancing functional neurosurgery, is beginning to transcend classical subspecialty boundaries. Notably, its application in neuro-oncologic surgery has stimulated an exciting paradigm shift from the traditional localizationist approach, which is lacking in nuance and optimization. This manuscript reviews the existing literature and explores how structural and functional connectivity analyses have been leveraged to revolutionize and individualize pre-operative tumor evaluation and surgical planning. We describe how this novel approach may improve cognitive and neurologic preservation after surgery and attenuate tumor spread. Furthermore, we demonstrate how connectivity analysis combined with neuromodulation techniques can be employed to induce post-operative neuroplasticity and personalize neurorehabilitation. While the landscape of functional neuro-oncology is still evolving and requires further study to encourage more widespread adoption, this functional approach can transform the practice of neuro-oncologic surgery and improve the care and outcomes of patients with intra-axial tumors.

Blood oxygen level-dependent (BOLD) response patterns with thalamic deep brain stimulation in patients with medically refractory epilepsy.

OBJECTIVE: Anterior nucleus of thalamus (ANT) deep brain stimulation (DBS) has shown promise as a treatment for medically refractory epilepsy. To better understand the mechanism of this intervention, we used functional magnetic resonance imaging (fMRI) to map the acute blood oxygen level-dependent (BOLD) response pattern to thalamic DBS in fully implanted patients with epilepsy. METHODS: Two patients with epilepsy implanted with bilateral ANT-DBS devices underwent four fMRI acquisitions each, during which active left-sided monopolar stimulation was delivered in a 30-s DBS-ON/OFF cycling paradigm. Each fMRI acquisition featured left-sided stimulation of a different electrode contact to vary the locus of stimulation within the thalamus and to map the brain regions modulated as a function of different contact selection. To determine the extent of peri-electrode stimulation and the engagement of local structures during each fMRI acquisition, volume of tissue activated (VTA) modeling was also performed. RESULTS: Marked changes in the pattern of BOLD response were produced with thalamic stimulation, which varied with the locus of the active contact in each patient. BOLD response patterns to stimulation that directly engaged at least 5% of the anterior nuclear group by volume were characterized by changes in the bilateral putamen, thalamus, and posterior cingulate cortex, ipsilateral middle cingulate cortex and precuneus, and contralateral medial prefrontal and anterior cingulate. SIGNIFICANCE: The differential BOLD response patterns associated with varying thalamic DBS parameters provide mechanistic insights and highlight the possibilities of fMRI biomarkers of optimizing stimulation in patients with epilepsy.

Combining brain perturbation and neuroimaging in non-human primates.

Brain perturbation studies allow detailed causal inferences of behavioral and neural processes. Because the combination of brain perturbation methods and neural measurement techniques is inherently challenging, research in humans has predominantly focused on non-invasive, indirect brain perturbations, or neurological lesion studies. Non-human primates have been indispensable as a neurobiological system that is highly similar to humans while simultaneously being more experimentally tractable, allowing visualization of the functional and structural impact of systematic brain perturbation. This review considers the state of the art in non-human primate brain perturbation with a focus on approaches that can be combined with neuroimaging. We consider both non-reversible (lesions) and reversible or temporary perturbations such as electrical, pharmacological, optical, optogenetic, chemogenetic, pathway-selective, and ultrasound based interference methods. Method-specific considerations from the research and development community are offered to facilitate research in this field and support further innovations. We conclude by identifying novel avenues for further research and innovation and by highlighting the clinical translational potential of the methods.

A collaborative resource platform for non-human primate neuroimaging.

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field .

Pypreclin: An automatic pipeline for macaque functional MRI preprocessing.

Non-human primate functional MRI (fMRI) is a growing field in neuroscience. However, there is no standardized method for monkey fMRI data analysis, specifically for data preprocessing. The preprocessing of monkey fMRI data is challenged by several technical and experimental specificities of the monkey research such as artifacts related to body movements or to intracranial leads. Here we propose to address these challenges by developing a new versatile pipeline for macaque fMRI preprocessing. We developed a Python module, Pypreclin, to process raw images using state of the art algorithms embedded in a fully automatic pipeline. To evaluate its robustness, we applied Pypreclin to fMRI data acquired at 3T in both awake and anesthetized macaques, with or without iron oxide contrast agent, using single loop or multichannel phased-array coils, combined or not with intracranial implanted electrodes. We performed both resting-state and auditory evoked fMRI and compared the results of Pypreclin to a previously employed preprocessing pipeline. Pypreclin successfully achieved the registration of the fMRI data to the macaque brain template in all the experimental conditions. Moreover, Pypreclin enables more accurate locations of auditory evoked activations in relation to the gray matter at corrected level in the awake fMRI condition. Finally, using the Primate neuroimaging Data-Exchange open access platform, we could further validate Pypreclin for monkey fMRI images that were acquired at ultra-high fields, from other institutions and using different protocols. Pypreclin is a validated preprocessing tool that adapts to diverse experimental and technical situations of monkey fMRI. Pypreclin code is available on open source data sharing platform.

Resting-state Dynamics as a Cortical Signature of Anesthesia in Monkeys.

WHAT WE ALREADY KNOW ABOUT THIS TOPIC: WHAT THIS ARTICLE TELLS US THAT IS NEW: BACKGROUND:: The mechanism by which anesthetics induce a loss of consciousness remains a puzzling problem. We hypothesized that a cortical signature of anesthesia could be found in an increase in similarity between the matrix of resting-state functional correlations and the anatomical connectivity matrix of the brain, resulting in an increased function-structure similarity. METHODS: We acquired resting-state functional magnetic resonance images in macaque monkeys during wakefulness (n = 3) or anesthesia with propofol (n = 3), ketamine (n = 3), or sevoflurane (n = 3). We used the k-means algorithm to cluster dynamic resting-state data into independent functional brain states. For each condition, we performed a regression analysis to quantify function-structure similarity and the repertoire of functional brain states. RESULTS: Seven functional brain states were clustered and ranked according to their similarity to structural connectivity, with higher ranks corresponding to higher function-structure similarity and lower ranks corresponding to lower correlation between brain function and brain anatomy. Anesthesia shifted the brain state composition from a low rank (rounded rank [mean ± SD]) in the awake condition (awake rank = 4 [3.58 ± 1.03]) to high ranks in the different anesthetic conditions (ketamine rank = 6 [6.10 ± 0.32]; moderate propofol rank = 6 [6.15 ± 0.76]; deep propofol rank = 6 [6.16 ± 0.46]; moderate sevoflurane rank = 5 [5.10 ± 0.81]; deep sevoflurane rank = 6 [5.81 ± 1.11]; P < 0.0001). CONCLUSIONS: Whatever the molecular mechanism, anesthesia led to a massive reconfiguration of the repertoire of functional brain states that became predominantly shaped by brain anatomy (high function-structure similarity), giving rise to a well-defined cortical signature of anesthesia-induced loss of consciousness.