Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation

Topographical anatomy of the septum verum and its white matter connections

The human septum verum represents a small but clinically important region of the brain. Based on the results of animal experiments, the stimulation of its medial part was recently proposed with various indications like epilepsy or cognitive impairment after traumatic brain injury. The aim of our study was to present the anatomical relationships of the human septum verum using fiber dissection and histological analysis to support its research and provide essential information for future deep brain stimulation therapies. 16 human cadaveric brains were dissected according to Klingler's method. To validate our macroscopical findings, 12 samples obtained from the dissected brains and 2 additional specimens from unfrozen brains were prepared for histological examinations. We identified the following white matter connections of the septum verum: (1) the precommissural fibers of the fornix; (2) the inferior fascicle of the septum pellucidum; (3) the cingulum; (4) the medial olfactory stria; (5) the ventral amygdalofugal pathway; (6) the stria medullaris of the thalamus and (7) the stria terminalis. Moreover, we could distinguish a less-known fiber bundle connecting the postcommissural column of the fornix to the stria medullaris of the thalamus and the anterior thalamic nuclei. In this study we present valuable anatomical information about this region to promote safe and effective deep brain stimulation therapies in the future.

A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response

By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.

Emerging Outlook on Personalized Neuromodulation for Depression: Insights From Tractography-Based Targeting

BACKGROUND

Deep brain stimulation has shown promise in treating individual patients with treatment-resistant depression, but larger-scale trials have been less successful. Here, we created what is, to our knowledge, the largest meta-analysis with individual patient data to date to explore whether the use of tractography enhances the efficacy of deep brain stimulation for treatment-resistant depression.

METHODS

We systematically reviewed 1823 articles, selecting 32 that contributed data from 366 patients. We stratified the individual patient data based on stimulation target and use of tractography. Using 2-way type III analysis of variance, Welch's 2-sample t tests, and mixed-effects linear regression models, we evaluated changes in depression severity 1 year (9-15 months) postoperatively and at last follow-up (4 weeks to 8 years) as assessed by depression scales.

RESULTS

Tractography was used for medial forebrain bundle (MFB) (n = 17 tractography/32 total), subcallosal cingulate (SCC) (n = 39 tractography/241 total), and ventral capsule/ventral striatum (n = 3 tractography/41 total) targets; it was not used for bed nucleus of stria terminalis (n = 11), lateral habenula (n = 10), and inferior thalamic peduncle (n = 1). Across all patients, tractography significantly improved mean depression scores at 1 year (p < .001) and last follow-up (p = .009). Within the target cohorts, tractography improved depression scores at 1 year for both MFB and SCC, though significance was met only at the α = 0.1 level (SCC: β = 15.8%, p = .09; MFB: β = 52.4%, p = .10). Within the tractography cohort, patients with MFB tractography showed greater improvement than patients with SCC tractography (72.42 ± 7.17% vs. 54.78 ± 4.08%) at 1 year (p = .044).

CONCLUSIONS

Our findings underscore the promise of tractography in deep brain stimulation for treatment-resistant depression as a method for personalization of therapy, supporting its inclusion in future trials.

Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation

Subcallosal cingulate (SCC) deep brain stimulation (DBS) is an emerging therapy for refractory depression. Good clinical outcomes are associated with the activation of white matter adjacent to the SCC. This activation produces a signature cortical evoked potential (EP), but it is unclear which of the many pathways in the vicinity of SCC is responsible for driving this response. Individualized biophysical models were built to achieve selective engagement of two target bundles: either the forceps minor (FM) or cingulum bundle (CB). Unilateral 2 Hz stimulation was performed in seven patients with treatment-resistant depression who responded to SCC DBS, and EPs were recorded using 256-sensor scalp electroencephalography. Two distinct EPs were observed: a 120 ms symmetric response spanning both hemispheres and a 60 ms asymmetrical EP. Activation of FM correlated with the symmetrical EPs, while activation of CB was correlated with the asymmetrical EPs. These results support prior model predictions that these two pathways are predominantly activated by clinical SCC DBS and provide first evidence of a link between cortical EPs and selective fiber bundle activation.

The potential predictors for treatment-resistance depression after selective serotonin reuptake inhibitors therapy in Han Chinese: A resting-state functional magnetic resonance imaging study

AIM

Selective serotonin reuptake inhibitors (SSRIs) are among the most important antidepressants. However, there is limited research on predicting the occurrence of treatment-resistant depression (TRD) after 5 years. Examining the predictive effect of TRD occurrence using resting-state fMRI in patients initiating SSRIs treatment at the onset of major depressive disorder (MDD) could potentially enhance TRD management.

METHODS

A total of 60 first-episode drug-naive MDD patients who met the criteria, along with 41 healthy controls of Han Chinese ethnicity, were recruited. All MDD patients received SSRIs as the initial treatment for relieving depressive symptoms. Resting-state fMRI scans were conducted for all subjects. Follow-up assessments were conducted over a period of five years, during which MDD patients were categorized into treatment-resistant depression (TRD) and non-treatment-resistant depression (NRD) groups based on disease progression. Amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and Regional Homogeneity (ReHo) values were calculated and compared among the three groups. Additionally, receiver operating characteristic (ROC) curves were employed to identify potential predictors.

RESULTS

After 5 years of follow-up, it was found that 43 MDD patients were classified as NRD, while 17 were classified as TRD. In comparison to TRD, NRD exhibited decreased ALFF in the left middle cingulum gyrus (MCG.L) and in the right middle frontal gyrus (MFG.R), as well as decreased ReHo in MCG.L. Furthermore, NRD showed increased fALFF in the left precuneus (PCUN.L). The area under the curve (AUC) values were as follows: 0.724 (MCG.L by ALFF), 0.732 (MFG.R), 0.767 (PCUN.L), 0.774 (MCG.L by ReHo), 0.878 (combined), 0.547 (HAMD), and 0.408 (HAMA) respectively.

CONCLUSION

The findings suggest that PCUN.L, MFG.R, MCG.L, and the combined measures may indicate the possibility of developing TRD after 5 years when SSRIs are used as the initial therapy for relieving depressive symptoms in MDD patients.

Aperiodic neural activity is a biomarker for depression severity

A reliable physiological biomarker for Major Depressive Disorder (MDD) is necessary to improve treatment success rates by shoring up variability in outcome measures. In this study, we establish a passive biomarker that tracks with changes in mood on the order of minutes to hours. We record from intracranial electrodes implanted deep in the brain - a surgical setting providing exquisite temporal and spatial sensitivity to detect this relationship in a difficult-to-measure brain area, the ventromedial prefrontal cortex (VMPFC). The aperiodic slope of the power spectral density captures the balance of activity across all frequency bands and is construed as a putative proxy for excitatory/inhibitory balance in the brain. This study demonstrates how shifts in aperiodic slope correlate with depression severity in a clinical trial of deep brain stimulation for treatment-resistant depression (TRD). The correlation between depression severity scores and aperiodic slope is significant in N=5 subjects, indicating that flatter (less negative) slopes correspond to reduced depression severity, especially in the ventromedial prefrontal cortex. This biomarker offers a new way to track patient response to MDD treatment, facilitating individualized therapies in both intracranial and non-invasive monitoring scenarios.

Cingulate dynamics track depression recovery with deep brain stimulation

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD)1. However, achieving stable recovery is unpredictable2, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting3. We currently lack objective brain-based biomarkers to guide clinical decisions by distinguishing natural transient mood fluctuations from situations requiring intervention. To address this gap, we used a new device enabling electrophysiology recording to deliver SCC DBS to ten TRD participants (ClinicalTrials.gov identifier NCT01984710). At the study endpoint of 24 weeks, 90% of participants demonstrated robust clinical response, and 70% achieved remission. Using SCC local field potentials available from six participants, we deployed an explainable artificial intelligence approach to identify SCC local field potential changes indicating the patient's current clinical state. This biomarker is distinct from transient stimulation effects, sensitive to therapeutic adjustments and accurate at capturing individual recovery states. Variable recovery trajectories are predicted by the degree of preoperative damage to the structural integrity and functional connectivity within the targeted white matter treatment network, and are matched by objective facial expression changes detected using data-driven video analysis. Our results demonstrate the utility of objective biomarkers in the management of personalized SCC DBS and provide new insight into the relationship between multifaceted (functional, anatomical and behavioural) features of TRD pathology, motivating further research into causes of variability in depression treatment.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome.

OBJECTIVE/HYPOTHESIS

We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort.

METHODS

Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures.

RESULTS

PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047).

CONCLUSION(S)

These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Orientation selective stimulation with tetrahedral electrodes of the rat infralimbic cortex to indirectly target the amygdala

Introduction

Deep brain stimulation (DBS) is a rapidly developing therapeutic intervention with constantly expanding neurological and psychiatric indications. A major challenge for the approach is the precise targeting and limitation of the effect on the desired neural pathways. We have introduced a new approach, orientation selective stimulation (OSS) that allows free rotation of the induced electric field on a plane when using a probe with three parallel electrodes forming an equilateral triangle at the tip. Here, we expand the technique by introducing a tetrahedral stimulation probe that enables adjustment of the primary electric field direction freely at any angle in a 3D space around the stimulating probe. OSS in 3D will enable better targeting of the electric field according to the local brain anatomy. We tested its utility in a rat model of DBS for treatment-resistant depression. The stimulation directed to the subgenual anterior cingulate cortex (sgACC) has yielded dramatic improvement in individual patients suffering from therapy resistant depression, but no consistent benefit in larger series. This failure has been ascribed to the challenging anatomy of sgACC with several crossing neural tracts and individual differences in the local anatomy.

Methods

We stimulated infralimbic cortex (IL), the rat analog of sgACC, and recorded local electrical responses in amygdala (AMG) that is monosynaptically connected to IL and plays a central role in emotional states. We further traced AMG-IL connections using a viral vector and tractography using diffusion magnetic resonance imaging (MRI). Finally, we mimicked the clinical situation by delivering sustained 130 Hz stimulation at IL at the most effective field orientation and followed changes in resting-state functional connectivity with IL using functional MRI. To help interpretation of responses in functional connectivity, we stimulated only the left IL, which we did not expect to evoke measurable changes in the rat behavior.

Results

The AMG evoked responses depended systematically on the IL stimulation field orientation and yielded the maximum response in near vertical field orientation in accordance with tractography. Sustained 130 Hz stimulation at a field orientation yielding the strongest AMG evoked responses increased functional connectivity between IL and AMG on the stimulation side.

Conclusion

These findings suggest that OSS in 3D provides a new approach to optimize the DBS for every individual patient with a single stimulation probe implantation.

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.

Mitigating Mismatch Compression in Differential Local Field Potentials

Deep brain stimulation (DBS) devices capable of measuring differential local field potentials ( ∂ LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂ LFP that we introduce as mismatch compression (MC). Using in vivo, in silico, and in vitro models of MC, we showed that impedance mismatches in the two recording electrodes can yield incomplete rejection of stimulation artifact and subsequent gain compression that distorts oscillatory power. We then developed and validated an opensource mitigation pipeline that mitigates the distortions arising from MC. This work enables more reliable oscillatory readouts for adaptive DBS applications.

White Matter Microstructure Associated with the Antidepressant Effects of Deep Brain Stimulation in Treatment-Resistant Depression: A Review of Diffusion Tensor Imaging Studies

Treatment-resistant depression (TRD) is a severe disorder characterized by high relapse rates and decreased quality of life. An effective strategy in the management of TRD is deep brain stimulation (DBS), a technique consisting of the implantation of electrodes that receive a stimulation via a pacemaker-like stimulator into specific brain areas, detected through neuroimaging investigations, which include the subgenual cingulate cortex (sgCC), basal ganglia, and forebrain bundles. In this context, to improve our understanding of the mechanism underlying the antidepressant effects of DBS in TRD, we collected the results of diffusion tensor imaging (DTI) studies exploring how WM microstructure is associated with the therapeutic effects of DBS in TRD. A search on PubMed, Web of Science, and Scopus identified 11 investigations assessing WM microstructure in responders and non-responders to DBS. Altered WM microstructure, particularly in the sgCC, medial forebrain bundle, cingulum bundle, forceps minor, and uncinate fasciculus, was associated with the antidepressant effect of DBS in TRD. Overall, the results show that DBS targeting selective brain regions, including the sgCC, forebrain bundle, cingulum bundle, rectus gyrus, anterior limb of the internal capsule, forceps minor, and uncinate fasciculus, seem to be effective for the treatment of TRD.

Linking profiles of pathway activation with clinical motor improvements - A retrospective computational study

BACKGROUND

Deep brain stimulation (DBS) is an established therapy for patients with Parkinson's disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity.

OBJECTIVE

The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement.

METHODS

We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson's Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways.

RESULTS

The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort.

CONCLUSION

Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson's patients treated with DBS.

Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate

Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering. We examined these spectral features—evoked power and phase clustering—in a sample of TRD patients (n = 8) with implanted SCC stimulators. Electroencephalogram (EEG) was recorded during wakeful rest. Location of electrical stimulation in the SCC target region was the experimental manipulation. EEG was analyzed at the surface level with an average reference for a cluster of frontal sensors and at a time window identified by prior study (50–150 ms). Morlet wavelets generated indices of evoked power and inter-trial phase clustering. Enhanced phase clustering at theta frequency (4–7 Hz) was observed in every subject and was significantly correlated with SCC-EP magnitude, but only during left SCC stimulation. Stimulation to dorsal SCC evinced stronger phase clustering than ventral SCC. There was a weak correlation between phase clustering and white matter density. An increase in evoked delta power (2–4 Hz) was also coincident with SCC-EP, but was less consistent across participants. DBS evoked time-frequency features index mm-scale changes to the location of stimulation in the SCC target region and correlate with structural characteristics implicated in treatment optimization. Results also imply a shared generative mechanism (inter-trial phase clustering) between evoked potentials evinced by electrical stimulation and evoked potentials evinced by auditory/visual stimuli and behavioral tasks. Understanding how current injection impacts downstream cortical activity is essential to building new technologies that adapt treatment parameters to individual differences in neurophysiology.

Lawrence K, Théberge J, Hicks JW, Finger E, Palaniyappan L, Anazodo UC. The functional and structural associations of aberrant microglial activity in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a debilitating mental illness that has been linked to increases in markers of inflammation, as well as to changes in brain functional and structural connectivity, particularly between the insula and the subgenual anterior cingulate cortex (sgACC). In this study, we directly related inflammation and dysconnectivity in treatment-resistant MDD by concurrently measuring the following: microglial activity with [¹⁸F]N-2-(fluoroethoxyl)benzyl-N-(4phenoxypyridin-3-yl)acetamide ([¹⁸F]FEPPA) positron emission tomography (PET); the severity of MDD; and functional or structural connectivity among insula or sgACC nodes.

METHODS

Twelve patients with treatment-resistant MDD (8 female, 4 male; mean age ± standard deviation 54.9 ± 4.5 years and 23 healthy controls (11 female, 12 male; 60.3 ± 8.5 years) completed a hybrid [¹⁸F]FEPPA PET and MRI acquisition. From these, we extracted relative standardized uptake values for [¹⁸F]FEPPA activity and Pearson r-to-z scores representing functional connectivity from our regions of interest. We extracted diffusion tensor imaging metrics from the cingulum bundle, a key white matter bundle in MDD. We performed regressions to relate microglial activity with functional connectivity, structural connectivity and scores on the 17-item Hamilton Depression Rating Scale.

RESULTS

We found significantly increased [¹⁸F]FEPPA uptake in the left sgACC in patients with treatment-resistant MDD compared to healthy controls. Patients with MDD also had a reduction in connectivity between the sgACC and the insula. The [¹⁸F]FEPPA uptake in the left sgACC was significantly related to functional connectivity with the insula, and to the structural connectivity of the cingulum bundle. [¹⁸F]FEPPA uptake also predicted scores on the Hamilton Depression Rating Scale.Limitations: A relatively small sample size, lack of functional task data and concomitant medication use may have affected our findings.

CONCLUSION

We present preliminary evidence linking a network-level dysfunction relevant to the pathophysiology of depression and related to increased microglial activity in MDD.

White Matter Tracts Associated With Deep Brain Stimulation Targets in Major Depressive Disorder: A Systematic Review

Background

Deep brain stimulation (DBS) has been proposed as a last-resort treatment for major depressive disorder (MDD) and has shown potential antidepressant effects in multiple clinical trials. However, the clinical effects of DBS for MDD are inconsistent and suboptimal, with 30-70% responder rates. The currently used DBS targets for MDD are not individualized, which may account for suboptimal effect.

Objective

We aim to review and summarize currently used DBS targets for MDD and relevant diffusion tensor imaging (DTI) studies.

Methods

A literature search of the currently used DBS targets for MDD, including clinical trials, case reports and anatomy, was performed. We also performed a literature search on DTI studies in MDD.

Results

A total of 95 studies are eligible for our review, including 51 DBS studies, and 44 DTI studies. There are 7 brain structures targeted for MDD DBS, and 9 white matter tracts with microstructural abnormalities reported in MDD. These DBS targets modulate different brain regions implicated in distinguished dysfunctional brain circuits, consistent with DTI findings in MDD.

Conclusions

In this review, we propose a taxonomy of DBS targets for MDD. These results imply that clinical characteristics and white matter tracts abnormalities may serve as valuable supplements in future personalized DBS for MDD.

Causal mapping of human brain function

Mapping human brain function is a long-standing goal of neuroscience that promises to inform the development of new treatments for brain disorders. Early maps of human brain function were based on locations of brain damage or brain stimulation that caused a functional change. Over time, this approach was largely replaced by technologies such as functional neuroimaging, which identify brain regions in which activity is correlated with behaviours or symptoms. Despite their advantages, these technologies reveal correlations, not causation. This creates challenges for interpreting the data generated from these tools and using them to develop treatments for brain disorders. A return to causal mapping of human brain function based on brain lesions and brain stimulation is underway. New approaches can combine these causal sources of information with modern neuroimaging and electrophysiology techniques to gain new insights into the functions of specific brain areas. In this Review, we provide a definition of causality for translational research, propose a continuum along which to assess the relative strength of causal information from human brain mapping studies and discuss recent advances in causal brain mapping and their relevance for developing treatments.

Subcallosal Cingulate Cortex Deep Brain Stimulation for Treatment-Resistant Depression: A Systematic Review

Background

Deep brain stimulation (DBS) is considered a relatively new and still experimental therapeutic modality for treatment-resistant depression (TRD). There is clinical evidence to suggest that stimulation of the subcallosal cingulate cortex (SCC) involved in the pathogenesis of TRD may exert an antidepressant effect.

Aims

To conduct a systematic review of current studies, such as randomized clinical trials (RCTs), open-label trials, and placebo-controlled trials, examining SCC DBS for TRD in human participants.

Method

A formal review of the academic literature was performed using the Medical Literature, Analysis, and Retrieval System Online (MEDLINE) and Cochrane Central Register of Controlled Trials (CENTRAL) databases. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Suitable studies were screened and assessed based on patient characteristics, clinical outcomes, adverse events related to DBS, and the stereotactic technique used to guide the implantation of DBS electrodes.

Results

The literature search identified 14 clinical studies that enrolled a total of 230 patients with TRD who underwent SCC DBS. The average duration of follow-up was 14 months (range 6–24 months). The response and remission rates at the last available follow-up visit ranged between 23–92% and 27–66.7%, respectively.

Conclusion

The current results of SCC DBS are limited by the relatively small number of patients treated worldwide. Nevertheless, studies to date suggest that SCC can be a promising and efficacious target for DBS, considering the high response and remission rates among patients with TRD. The adverse events of SCC DBS are usually transient and stimulation-induced.

Dynamic Oscillations Evoked by Subcallosal Cingulate Deep Brain Stimulation

Deep brain stimulation (DBS) of subcallosal cingulate white matter (SCCwm) alleviates symptoms of depression, but its mechanistic effects on brain dynamics remain unclear. In this study we used novel intracranial recordings (LFP) in n = 6 depressed patients stimulated with DBS around the SCCwm target, observing a novel dynamic oscillation (DOs). We confirm that DOs in the LFP are of neural origin and consistently evoked within certain patients. We then characterize the frequency and dynamics of DOs, observing significant variability in DO behavior across patients. Under the hypothesis that LFP-DOs reflect network engagement, we characterize the white matter tracts associated with LFP-DO observations and report a preliminary observation of DO-like activity measured in a single patient's electroencephalography (dEEG). These results support further study of DOs as an objective signal for mechanistic study and connectomics guided DBS.

Circuit-Targeted Neuromodulation for Anhedonia

Despite the prevalence of anhedonia across multiple psychiatric disorders, its relevance to treatment selection and prognostication can be unclear (Davey et al., Psychol Med 42(10):2071-81, 2012). Given the challenges in pharmacological and psychosocial treatment, there has been increasing attention devoted to neuroanatomically-targeted treatments. This chapter will present a brief introduction to circuit-targeted therapeutics in psychiatry (Sect. 1), an overview of brain mapping as it relates to anhedonia (Sect. 2), a review of existing studies on brain stimulation for anhedonia (Sect. 3), and a description of emerging approaches to circuit-based neuromodulation for anhedonia (Sect. 4).

3 T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation

Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS), a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While SCC-DBS drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 Tesla functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of twelve patients with fully implanted SCC-DBS devices. Four additional SCC-DBS patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n=78 acquisitions overall) during i) inactive DBS; ii) clinically optimal active DBS; iii) suboptimal active DBS. All scans were acquired within a single MRI session, each separated by a 5-minute washout period. Analysis of the amplitude of low frequency fluctuations (ALFF) in each sequence indicated that clinically optimal SCC-DBS reduced spontaneous brain activity in several areas, including bilateral dorsal anterior cingulate cortex (dACC), posterior cingulate cortex (PCC), precuneus, and left inferior parietal lobule (pBonferroni<0.0001). Stimulation-induced dACC signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings, and related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dACC, PCC, and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated ALFF changes in these three areas (along with pre-operative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally all three brain areas exhibited significant changes in functional connectivity between active and inactive DBS states (pBonferroni<0.01). These results provide insight into the network-level mechanisms of SCC-DBS and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.

Validating Patient-Specific Finite Element Models of Direct Electrocortical Stimulation

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications.

Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression

Subcallosal cingulate deep brain stimulation (SCC-DBS) produces long-term clinical improvement in approximately half of patients with severe treatment-resistant depression (TRD). We hypothesized that both structural and functional brain attributes may be important in determining responsiveness to this therapy. In a TRD SCC-DBS cohort, we retrospectively examined baseline and longitudinal differences in MRI-derived brain volume (n = 65) and 18F-fluorodeoxyglucose-PET glucose metabolism (n = 21) between responders and non-responders. Support-vector machines (SVMs) were subsequently trained to classify patients' response status based on extracted baseline imaging features. A machine learning model incorporating pre-operative frontopolar, precentral/frontal opercular, and orbitofrontal local volume values classified binary response status (12 months) with 83% accuracy (leave-one-out cross-validation (LOOCV): 80% accuracy) and explained 32% of the variance in continuous clinical improvement. It was also predictive in an out-of-sample SCC-DBS cohort (n = 21) with differing primary indications (bipolar disorder/anorexia nervosa) (76% accuracy). Adding pre-operative glucose metabolism information from rostral anterior cingulate cortex and temporal pole improved model performance, enabling it to predict response status in the TRD cohort with 86% accuracy (LOOCV: 81% accuracy) and explain 67% of clinical variance. Response-related patterns of metabolic and structural post-DBS change were also observed, especially in anterior cingulate cortex and neighbouring white matter. Areas where responders differed from non-responders - both at baseline and longitudinally - largely overlapped with depression-implicated white matter tracts, namely uncinate fasciculus, cingulum bundle, and forceps minor/rostrum of corpus callosum. The extent of patient-specific engagement of these same tracts (according to electrode location and stimulation parameters) also served as a predictor of TRD response status (72% accuracy; LOOCV: 70% accuracy) and augmented performance of the volume-based (88% accuracy; LOOCV: 82% accuracy) and combined volume/metabolism-based SVMs (100% accuracy; LOOCV: 94% accuracy). Taken together, these results indicate that responders and non-responders to SCC-DBS exhibit differences in brain volume and metabolism, both pre- and post-surgery. Baseline imaging features moreover predict response to treatment (particularly when combined with information about local tract engagement) and could inform future patient selection and other clinical decisions.

White Matter Microstructure Alterations Associated With Paroxetine Treatment Response in Major Depression

More than one-third of depressive patients do not achieve remission after the first antidepressant treatment. The "watch and wait" approach used to find the most effective antidepressant leads to an increased personal, social, and economic burden in society. In order to overcome this challenge, there has been a focus on studying neural biomarkers associated with antidepressant response. Diffusion tensor imaging measures have shown a promising role as predictors of antidepressant response by pointing to pretreatment differences in the white matter microstructural integrity between future responders and non-responders to different pharmacotherapies. Therefore, the aim of the present study was to explore whether response to paroxetine treatment was associated with differences in the white matter microstructure at baseline. Twenty drug-naive patients diagnosed with major depressive disorder followed a 6- to 12-week treatment with paroxetine. All patients completed magnetic resonance brain imaging and a clinical assessment at baseline and 6-12 weeks after treatment. Whole-brain tract-based spatial statistics was used to explore differences in white matter microstructural properties estimated from diffusion magnetic resonance imaging. Voxel-wise statistical analysis revealed a significant increase in fractional anisotropy and a decrease in radial diffusivity in forceps minor and superior longitudinal fasciculus in responders compared to non-responders. Thus, alterations in white matter integrity, specifically in forceps minor and the superior longitudinal fasciculus, are associated with paroxetine treatment response. These findings pave the way for personalized treatment strategies in major depression.

Advanced Imaging in Psychiatric Neurosurgery: Toward Personalized Treatment

OBJECTIVES

Our aim is to review several recent landmark studies discussing the application of advanced neuroimaging to guide target selection in deep brain stimulation (DBS) for psychiatric disorders.

MATERIALS AND METHODS

We performed a PubMed literature search of articles related to psychiatric neurosurgery, DBS, diffusion tensor imaging, probabilistic tractography, functional magnetic resonance imaging (MRI), and blood oxygen level-dependent activation. Relevant articles were included in the review.

RESULTS

Recent advances in neuroimaging, namely the use of diffusion tensor imaging, probabilistic tractography, functional MRI, and Positron emission tomography have provided higher resolution depictions of structural and functional connectivity between regions of interest. Applying these imaging modalities to DBS has increased understanding of the mechanism of action of DBS from the single structure to network level, allowed for new DBS targets to be discovered, and allowed for individualized DBS targeting for psychiatric indications.

CONCLUSIONS

Advanced neuroimaging techniques may be especially important to guide personalized DBS targeting in psychiatric disorders such as treatment-resistant depression and obsessive-compulsive disorder where symptom profiles and underlying disordered circuitry are more heterogeneous. These articles suggest that advanced imaging can help to further individualize and optimize DBS, a promising next step in improving its efficacy.

Image-based biophysical modeling predicts cortical potentials evoked with subthalamic deep brain stimulation

BACKGROUND

Subthalamic deep brain stimulation (DBS) is an effective surgical treatment for Parkinson's disease and continues to advance technologically with an enormous parameter space. As such, in-silico DBS modeling systems have become common tools for research and development, but their underlying methods have yet to be standardized and validated.

OBJECTIVE

Evaluate the accuracy of patient-specific estimates of neural pathway activations in the subthalamic region against intracranial, cortical evoked potential (EP) recordings.

METHODS

Pathway activations were modeled in eleven patients using the latest advances in connectomic modeling of subthalamic DBS, focusing on the hyperdirect pathway (HDP) and corticospinal/bulbar tract (CSBT) for their relevance in human research studies. Correlations between pathway activations and respective EP amplitudes were quantified.

RESULTS

Good model performance required accurate lead localization and image fusions, as well as appropriate selection of fiber diameter in the biophysical model. While optimal model parameters varied across patients, good performance could be achieved using a global set of parameters that explained 60% and 73% of electrophysiologic activations of CSBT and HDP, respectively. Moreover, restricted models fit to only EP amplitudes of eight standard (monopolar and bipolar) electrode configurations were able to extrapolate variation in EP amplitudes across other directional electrode configurations and stimulation parameters, with no significant reduction in model performance across the cohort.

CONCLUSIONS

Our findings demonstrate that connectomic models of DBS with sufficient anatomical and electrical details can predict recruitment dynamics of white matter. These results will help to define connectomic modeling standards for preoperative surgical targeting and postoperative patient programming applications.

7T MRI and Computational Modeling Supports a Critical Role of Lead Location in Determining Outcomes for Deep Brain Stimulation: A Case Report

Subthalamic nucleus (STN) deep brain stimulation (DBS) is an established therapy for Parkinson’s disease motor symptoms. The ideal site for implantation within STN, however, remains controversial. While many argue that placement of a DBS lead within the sensorimotor territory of the STN yields better motor outcomes, others report similar effects with leads placed in the associative or motor territory of the STN, while still others assert that placing a DBS lead “anywhere within a 6-mm-diameter cylinder centered at the presumed middle of the STN (based on stereotactic atlas coordinates) produces similar clinical efficacy.” These discrepancies likely result from methodological differences including targeting preferences, imaging acquisition and the use of brain atlases that do not account for patient-specific anatomic variability. We present a first-in-kind within-patient demonstration of severe mood side effects and minimal motor improvement in a Parkinson’s disease patient following placement of a DBS lead in the limbic/associative territory of the STN who experienced marked improvement in motor benefit and resolution of mood side effects following repositioning the lead within the STN sensorimotor territory. 7 Tesla (7 T) magnetic resonance imaging (MRI) data were used to generate a patient-specific anatomical model of the STN with parcellation into distinct functional territories and computational modeling to assess the relative degree of activation of motor, associative and limbic territories.

Variability of white matter anatomy in the subcallosal cingulate area

The subcallosal cingulate (SCC) area is a putative hub in the brain network underlying depression. Deep brain stimulation (DBS) targeting a particular subregion of SCC, identified as the intersection of forceps minor (FM), uncinate fasciculus (UCF), cingulum and fronto-striatal fiber bundles, may be critical to a therapeutic response in patients with severe, treatment-resistant forms of major depressive disorder (MDD). The pattern and variability of the white matter anatomy and organization within SCC has not been extensively characterized across individuals. The goal of this study is to investigate the variability of white matter bundles within the SCC that structurally connect this region with critical nodes in the depression network. Structural and diffusion data from 100 healthy subjects from the Human Connectome Project database were analyzed. Anatomically defined SCC regions were used as seeds to perform probabilistic tractography and to estimate the connectivity from the SCC to subject-specific target areas believed to be involved in the pathology of MDD including ventral striatum (VS), UCF, anterior cingulate cortex (ACC), and medial prefrontal cortex (mPFC). Four distinct areas of connectivity were identified within SCC across subjects: (a) postero-lateral SCC connectivity to medial temporal regions via UCF, (b) postero-medial connectivity to VS, (c) superior-medial connectivity to ACC via cingulum bundle, and (d) antero-lateral connectivity to mPFC regions via forceps minor. Assuming white matter connectivity is critical to therapeutic response, the improved anatomic understanding of SCC as well as an appreciation of the intersubject variability are critical to developing optimized therapeutic targeting for SCC DBS.

Clinical Evaluation of Cingulum Bundle Connectivity for Neurosurgical Hypothesis Development

BACKGROUND

The cingulum bundle (CB) has long been a target for psychiatric neurosurgical procedures, but with limited understanding of the brain networks being impacted. Recent advances in human tractography could provide a foundation to better understand the effects of neurosurgical interventions on the CB; however, the reliability of tractography remains in question.

OBJECTIVE

To evaluate the ability of different tractography techniques, derived from typical, human diffusion-weighted imaging (DWI) data, to characterize CB connectivity described in animal models. This will help validate the clinical applicability of tractography, and generate insight on current and future neurosurgical targets for psychiatric disorders.

METHODS

Connectivity of the CB in 15 healthy human subjects was evaluated using DWI-based tractography, and compared to tract-tracing findings from nonhuman primates. Brain regions of interest were defined to coincide with the animal model. Tractography was performed using 3 techniques (FSL probabilistic, Camino probabilistic, and Camino deterministic). Differences in connectivity were assessed, and the CB segment with the greatest connectivity was determined.

RESULTS

Each tractography technique successfully reproduced the animal tracing model with a mean accuracy of 72% (68-75%, P < .05). Additionally, one region of the CB, the rostral dorsal segment, had significantly greater connectivity to associated brain structures than all other CB segments (P < .05).

CONCLUSION

Noninvasive, in vivo human analysis of the CB, using clinically available DWI for tractography, consistently reproduced the results of an animal tract-tracing model. This suggests that tractography of the CB can be used for clinical applications, which may aid in neurosurgical targeting for psychiatric disorders.

A Decade of Progress in Deep Brain Stimulation of the Subcallosal Cingulate for the Treatment of Depression

Major depression contributes significantly to the global disability burden. Since the first clinical study of deep brain stimulation (DBS), over 446 patients with depression have now undergone this neuromodulation therapy, and 29 animal studies have investigated the efficacy of subgenual cingulate DBS for depression. In this review, we aim to provide a comprehensive overview of the progress of DBS of the subcallosal cingulate in humans and the medial prefrontal cortex, its rodent homolog. For preclinical animal studies, we discuss the various antidepressant-like behaviors induced by medial prefrontal cortex DBS and examine the possible mechanisms including neuroplasticity-dependent/independent cellular and molecular changes. Interestingly, the response rate of subcallosal cingulate Deep brain stimulation marks a milestone in the treatment of depression. DBS achieved response and remission rates of 64–76% and 37–63%, respectively, from clinical studies monitoring patients from 6–24 months. Although some studies showed its stimulation efficacy was limited, it still holds great promise as a therapy for patients with treatment-resistant depression. Overall, further research is still needed, including more credible clinical research, preclinical mechanistic studies, precise selection of patients, and customized electrical stimulation paradigms.

Deep Brain Stimulation Is Effective for Treatment-Resistant Depression: A Meta-Analysis and Meta-Regression

Major depressive disorder (MDD) is a leading cause of disability and a significant cause of mortality worldwide. Approximately 30–40% of patients fail to achieve clinical remission with available pharmacological treatments, a clinical course termed treatment-resistant depression (TRD). Numerous studies have investigated deep brain stimulation (DBS) as a therapy for TRD. We performed a meta-analysis to determine efficacy and a meta-regression to compare stimulation targets. We identified and screened 1397 studies. We included 125 citations in the qualitative review and considered 26 for quantitative analysis. Only blinded studies that compared active DBS to sham stimulation (k = 12) were included in the meta-analysis. The random-effects model supported the efficacy of DBS for TRD (standardized mean difference = −0.75, <0 favors active stimulation; p = 0.0001). The meta-regression did not demonstrate a statistically significant difference between stimulation targets (p = 0.45). While enthusiasm for DBS treatment of TRD has been tempered by recent randomized trials, this meta-analysis reveals a significant effect of DBS for the treatment of TRD. Additionally, the majority of trials have demonstrated the safety and efficacy of DBS for this indication. Further trials are required to determine the optimal stimulation parameters and patient populations for which DBS would be effective. Particular attention to factors including electrode placement technique, patient selection, and long-term follow-up is essential for future trial design.

Tract-based analysis of target engagement by subcallosal cingulate deep brain stimulation for treatment resistant depression

BACKGROUND

Deep brain stimulation (DBS) of subcallosal cingulate cortex (SCC) is a promising investigational therapy for treatment-resistant depression (TRD). However, outcomes vary, likely due to suboptimal DBS placement. Ideal placement is proposed to stimulate 4 SCC white matter bundles; however, no quantitative data have linked activation of these target tracts to response.

OBJECTIVE

Here we used the volume of tissue activated (VTA) and probabilistic diffusion tensor imaging (DTI) to quantify tract activation relating to response.

METHODS

DTI was performed in 19 TRD patients who received SCC-DBS. We defined clinical response as >48% reduction from baseline in the Hamilton Depression Rating Scale. Bilateral VTAs were generated based on subject-specific stimulation parameters. Patient-specific tract maps emanating from the VTAs were calculated using whole-brain probabilistic DTI. The four target tracts were isolated using tract-specific quantification and examined for overlap with DBS activated tissue.

RESULTS

Medial frontal and temporal projections were stimulated in all responders at 6 and 12 months. Individual tract-based generalized linear mixed model analysis revealed a significant tract-by-response interaction at both 6 (F(1,135) = 3.828, p = 0.001) and 12 (F(1,135) = 5.688, p < 0.001) months, with post hoc tests revealing a response-related increase in cingulum activation at 6 months (t(135) = 2.418, p = 0.017) and decrease in forceps minor activation at 12 months (t(135) = -2.802, p = 0.006).

CONCLUSIONS

A wider profile of white matter tracts, particularly to the medial frontal, was associated with DBS response. Cingulum bundle stimulation may promote early response and excess stimulation of the forceps minor might be detrimental. Our work supports prospective patient-specific targeting to inform personalized DBS.

Connectivity-based identification of a potential neurosurgical target for mood disorders

OBJECTIVE

Stereotactic ablation (cingulotomy) and subcallosal cingulate deep brain stimulation (SCC DBS) of different regions of the cingulum bundle (CB) have been successfully used to treat psychiatric disorders, such as depression and bipolar disorder. They are hypothesized to work by disrupting white matter pathways involved in the clinical manifestation of these disorders. This study aims to compare the connectivity of different CB subregions using tractography to evaluate stereotactic targets for the treatment of mood disorders.

METHODS

Fourteen healthy volunteers underwent 3T-MR imaging followed by connectivity analysis using probabilistic tractography. Twenty-one anatomic regions of interest were defined for each subject: 10 CB subregions (including the classical cingulotomy and SCC DBS targets) and 11 cortical/subcortical structures implicated in mood disorders. Connectivity results were compared using Friedman and Bonferroni-corrected post-hoc Wilcoxon tests.

RESULTS

CB connectivity showed a high degree of regional specificity. Both of the traditional stereotactic targets had widespread connectivity with discrete topology. The cingulotomy target connected primarily to the dorsomedial frontal, dorsal anterior cingulate, and posterior cingulate cortices, whereas the SCC DBS target connected mostly to the subgenual anterior cingulate and medial/central orbitofrontal cortices. However, a region of the rostral dorsal CB, lying between these surgical targets, encompassed statistically equivalent connections to all five cortical regions.

CONCLUSIONS

The CB is associated with brain structures involved in affective disorders, and the rostral dorsal CB demonstrates connectivity that is comparable to the combined connectivity of cingulotomy and SCC DBS neurosurgical interventions. The rostral dorsal CB represents a surgical target worthy of clinical exploration for mood disorders.

Electrical stimulation of cranial nerves in cognition and disease

The cranial nerves are the pathways through which environmental information (sensation) is directly communicated to the brain, leading to perception, and giving rise to higher cognition. Because cranial nerves determine and modulate brain function, invasive and non-invasive cranial nerve electrical stimulation methods have applications in the clinical, behavioral, and cognitive domains. Among other neuromodulation approaches such as peripheral, transcranial and deep brain stimulation, cranial nerve stimulation is unique in allowing axon pathway-specific engagement of brain circuits, including thalamo-cortical networks. In this review we amalgamate relevant knowledge of 1) cranial nerve anatomy and biophysics; 2) evidence of the modulatory effects of cranial nerves on cognition; 3) clinical and behavioral outcomes of cranial nerve stimulation; and 4) biomarkers of nerve target engagement including physiology, electroencephalography, neuroimaging, and behavioral metrics. Existing non-invasive stimulation methods cannot feasibly activate the axons of only individual cranial nerves. Even with invasive stimulation methods, selective targeting of one nerve fiber type requires nuance since each nerve is composed of functionally distinct axon-types that differentially branch and can anastomose onto other nerves. None-the-less, precisely controlling stimulation parameters can aid in affecting distinct sets of axons, thus supporting specific actions on cognition and behavior. To this end, a rubric for reproducible dose-response stimulation parameters is defined here. Given that afferent cranial nerve axons project directly to the brain, targeting structures (e.g. thalamus, cortex) that are critical nodes in higher order brain networks, potent effects on cognition are plausible. We propose an intervention design framework based on driving cranial nerve pathways in targeted brain circuits, which are in turn linked to specific higher cognitive processes. State-of-the-art current flow models that are used to explain and design cranial-nerve-activating stimulation technology require multi-scale detail that includes: gross anatomy; skull foramina and superficial tissue layers; and precise nerve morphology. Detailed simulations also predict that some non-invasive electrical or magnetic stimulation approaches that do not intend to modulate cranial nerves per se, such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), may also modulate activity of specific cranial nerves. Much prior cranial nerve stimulation work was conceptually limited to the production of sensory perception, with individual titration of intensity based on the level of perception and tolerability. However, disregarding sensory emulation allows consideration of temporal stimulation patterns (axon recruitment) that modulate the tone of cortical networks independent of sensory cortices, without necessarily titrating perception. For example, leveraging the role of the thalamus as a gatekeeper for information to the cerebral cortex, preventing or enhancing the passage of specific information depending on the behavioral state. We show that properly parameterized computational models at multiple scales are needed to rationally optimize neuromodulation that target sets of cranial nerves, determining which and how specific brain circuitries are modulated, which can in turn influence cognition in a designed manner.

A Population Model of Deep Brain Stimulation in Movement Disorders From Circuits to Cells

For more than 30 years, deep brain stimulation (DBS) has been used to target the symptoms of a number of neurological disorders and in particular movement disorders such as Parkinson’s disease (PD) and essential tremor (ET). It is known that the loss of dopaminergic neurons in the substantia nigra leads to PD, while the exact impact of this on the brain dynamics is not fully understood, the presence of beta-band oscillatory activity is thought to be pathological. The cause of ET, however, remains uncertain, however pathological oscillations in the thalamocortical-cerebellar network have been linked to tremor. Both of these movement disorders are treated with DBS, which entails the surgical implantation of electrodes into a patient’s brain. While DBS leads to an improvement in symptoms for many patients, the mechanisms underlying this improvement is not clearly understood, and computational modeling has been used extensively to improve this. Many of the models used to study DBS and its effect on the human brain have mainly utilized single neuron and single axon biophysical models. We have previously shown in separate models however, that the use of population models can shed much light on the mechanisms of the underlying pathological neural activity in PD and ET in turn, and on the mechanisms underlying DBS. Together, this work suggested that the dynamics of the cerebellar-basal ganglia thalamocortical network support oscillations at frequency range relevant to movement disorders. Here, we propose a new combined model of this network and present new results that demonstrate that both Parkinsonian oscillations in the beta band and oscillations in the tremor frequency range arise from the dynamics of such a network. We find regions in the parameter space demonstrating the different dynamics and go on to examine the transition from one oscillatory regime to another as well as the impact of DBS on these different types of pathological activity. This work will allow us to better understand the changes in brain activity induced by DBS, and allow us to optimize this clinical therapy, particularly in terms of target selection and parameter setting.

Bio-Heat Model of Kilohertz-Frequency Deep Brain Stimulation Increases Brain Tissue Temperature

OBJECTIVES

Early clinical trials suggest that deep brain stimulation at kilohertz frequencies (10 kHz-DBS) may be effective in improving motor symptoms in patients with movement disorders. The 10 kHz-DBS can deliver significantly more power in tissue compared to conventional frequency DBS, reflecting increased pulse compression (duty cycle). We hypothesize that 10 kHz-DBS modulates neuronal function through moderate local tissue heating, analogous to kilohertz spinal cord stimulation (10 kHz-SCS). To establish the role of tissue heating in 10 kHz-DBS (30 μs, 10 kHz, at intensities of 3-7 mA_peak ), a decisive first step is to characterize the range of temperature changes during clinical kHz-DBS protocols.

MATERIALS AND METHODS

We developed a high-resolution magnetic resonance imaging-derived DBS model incorporating joule-heat coupled bio-heat multi-physics to establish the role of tissue heating. Volume of tissue activated (VTA) under assumptions of activating function (for 130 Hz) or heating (for 10 kHz) based neuromodulation are contrasted.

RESULTS

DBS waveform power (waveform RMS) determined joule heating at the deep brain tissues. Peak heating was supralinearly dependent on stimulation RMS. The 10 kHz-DBS stimulation with 2.3 to 5.4 mA_RMS (corresponding to 3 to 7 mA_peak ) produced 0.10 to 1.38°C heating at the subthalamic nucleus (STN) target under standard tissue parameters. Maximum temperature increases were predicted inside the electrode encapsulation layer (enCAP) with 2.3 to 5.4 mA_RMS producing 0.13 to 1.87°C under standard tissue parameters. Tissue parameter analysis predicted STN heating was especially sensitive (ranging from 0.44 to 1.35°C at 3.8 mA_RMS ) to decreasing enCAP electrical conductivity and decreasing STN thermal conductivity.

CONCLUSIONS

Subject to validation with in vivo measurements, neuromodulation through a heating mechanism of action by 10 kHz-DBS can indicate novel therapeutic pathways and strategies for dose optimization.

Field potential 1/f activity in the subcallosal cingulate region as a candidate signal for monitoring deep brain stimulation for treatment-resistant depression

Subcallosal cingulate cortex deep brain stimulation (SCC-DBS) is an experimental therapy for treatment-resistant depression (TRD). Refinement and optimization of SCC-DBS will benefit from increased study of SCC electrophysiology in context of ongoing high-frequency SCC-DBS therapy. The study objective was a 7-mo observation of frequency-domain 1/f slope in off-stimulation local field potentials (SCC-LFPs) alongside standardized measurements of depression severity in 4 patients undergoing SCC-DBS. SCC was implanted bilaterally with a combined neurostimulation-LFP recording system. Following a 1-mo off-stimulation postoperative phase with multiple daily recordings, patients received bilateral SCC-DBS therapy (130 Hz, 90 μs) and weekly resting-state SCC-LFP recordings over a 6-mo treatment phase. 1/f slopes for each time point were estimated via linear regression of log-transformed Welch periodograms. General linear mixed-effects models were constructed to estimate pretreatment sources of 1/f slope variance, and 95% bootstrap confidence intervals were constructed to estimate treatment phase 1/f slope association with treatment response (50% decrease in preimplantation symptom severity). Results show the time of recording was a prominent source of pretreatment 1/f slope variance bilaterally, with increased 1/f slope magnitude observed during night hours (2300-0659). Increase in right 1/f slope was observed in the setting of treatment response, with bootstrap analysis supporting this observation in 3 of 4 subjects. We conclude that 1/f slope can be measured longitudinally in a combined SCC-DBS/LFP recording system and likely conforms to known 1/f circadian variability. The preliminary evidence of 1/f slope increase during treatment response suggests a potential utility as a candidate biomarker for ongoing development of adaptive TRD-neuromodulation strategies.NEW & NOTEWORTHY In four patients with treatment-resistant depression undergoing therapeutic deep brain stimulation (DBS), we present the first longitudinal observations of local field potentials (LFP) from the subcallosal cingulate region outside the postoperative period. Specifically, our results demonstrate that frequency-domain 1/f activity is measurable in a combined DBS-LFP recording system and that right hemisphere recordings appear sensitive to mood state, thus suggesting a potential readout suitable for consideration in ongoing efforts to develop adaptive DBS delivery systems.

White matter architecture in major depression with anxious distress symptoms

BACKGROUND

Comorbid anxious distress is common in Major Depressive Disorder (MDD), and associated with significantly worse clinical course and treatment response. While DSM-5 recently introduced the Anxious Distress (AD) specifier as a potentially useful symptom-based subtyping scheme for MDD, its neurobiological underpinnings remain unclear. The current study hence uniquely probed whether MDD with co-occurring AD (MDD/AD+) relates to distinct perturbations in frontolimbic white matter (WM) pathways tentatively theorized in MDD/AD+ pathophysiology.

METHODS

Tract-based spatial statistics (TBSS) was therefore used to analyze diffusion tensor imaging data on WM microstructure, in MDD/AD+ patients (N = 20) relative to MDD patients without AD (MDD/AD-; N = 29) and healthy controls (HC; N = 39). Using TBSS, we probed fractional anisotropy and axial/radial/mean diffusivity as proxies for WM integrity. Categorical (between-groups) and dimensional (within-patients) analyses subsequently assessed how Anxious Distress in MDD impacts frontolimbic WM connectivity. Receiver-Operating Characteristics additionally assessed classification capabilities of between-groups WM effects.

RESULTS

Compared to MDD/AD- and HC participants, MDD/AD+ patients exhibited diminished integrity within the anterior thalamic radiation (ATR). Higher AD specifier scores within MDD patients additionally related to diminished integrity of the uncinate fasciculus and cingulum pathways. These effects were not confounded by key clinical (e.g., comorbid anxiety disorder) and sociodemographic (e.g., age/sex) factors, with altered ATR integrity moreover successfully classifying MDD/AD+ patients from MDD/AD- and HC participants (90% sensitivity | 73% specificity | 77% accuracy).

CONCLUSIONS

These findings collectively link MDD/AD+ to distinct WM anomalies in frontolimbic tracts important to adaptive emotional functioning, and may as such provide relevant, yet preliminary, clues on MDD/AD+ pathophysiology.

Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is an emerging experimental therapy for treatment-resistant depression. New developments in SCC DBS surgical targeting are focused on identifying specific axonal pathways for stimulation that are estimated from patient-specific computational models. This connectomic-based biophysical modeling strategy has proven successful in improving the clinical response to SCC DBS therapy, but the DBS models used to date have been relatively simplistic, limiting the precision of the pathway activation estimates. Therefore, we used the most detailed patient-specific foundation for DBS modeling currently available (i.e., field-cable modeling) to evaluate SCC DBS in our most recent cohort of six subjects, all of which were responders to the therapy. We quantified activation of four major pathways in the SCC region: forceps minor (FM), cingulum bundle (CB), uncinate fasciculus (UF), and subcortical connections between the frontal pole and the thalamus or ventral striatum (FP). We then used the percentage of activated axons in each pathway as regressors in a linear model to predict the time it took patients to reach a stable response, or TSR. Our analysis suggests that stimulation of the left and right CBs, as well as FM are the most likely therapeutic targets for SCC DBS. In addition, the right CB alone predicted 84% of the variation in the TSR, and the correlation was positive, suggesting that activation of the right CB beyond a critical percentage may actually protract the recovery process.