Prospective Validation That Subgenual Connectivity Predicts Antidepressant Efficacy of Transcranial Magnetic Stimulation Sites

Resting EEG source-level connectivity pattern to predict anhedonia improvement with agomelatine treatment in patients with major depression

BACKGROUND

Neuroimaging studies have revealed that dysfunction of reward circuitry in the brain underlies anhedonia, a core symptom of major depressive disorder (MDD) that is related to treatment outcomes. However, the relationship between the brain network at the level of neuronal oscillations and the longitudinal improvement in the severity of anhedonia is still unknown.

METHODS

The study enrolled 84 unmedicated patients with MDD. Anhedonia severity was measured using the Snaith-Hamilton Pleasure Scale (SHAPS). EEG data in the resting state was obtained both at baseline and following an 8-week course of agomelatine 25 mg taken once daily. Whole-brain functional connectivity (FC) of source-level resting-state EEG and FC-derived graph metrics (i.e., global topological properties: global efficiency and local efficiency) were calculated in distinct frequency bands.

RESULTS

SHAPS scores were significantly improved from baseline to 8 weeks. Concurrently, there was a decrease in alpha-1 (8.5-10 Hz) connectivity between the right-hemisphere precuneus (PreC) and the left-hemisphere inferior frontal gyrus (IFG). Reduced alpha-2 (10.5-12 Hz) connectivity between the right-hemisphere transverse temporal gyrus (TTG) and the left-hemisphere superior frontal gyrus (SFG) and middle frontal gyrus (MFG) was observed. Global efficiency in the alpha-1 (p < 0.001) and alpha-2 (p = 0.003) frequency bands and local efficiency in the alpha-1 frequency band (p = 0.003) were reduced. Correlation analyses showed that alpha-1 local efficiency at baseline predicted improvement in SHAPS scores (r = -0.261, p = 0.017).

CONCLUSION

Global topological properties of source-level EEG FC can predict anhedonia improvement during antidepressant treatment, which might help guide treatment decisions and advance precision psychopharmacology.

Reduced mind-wandering and fewer depressive symptoms associated with damage to the medial prefrontal cortex and default mode network

Depressive disorders have been consistently associated with elevated levels of mind-wandering and self-focused negative rumination. Separate tracks of research have implicated brain structures within the default mode network (DMN) in both mind-wandering and depression. In this study, we hypothesized that diminished mind-wandering and fewer depressive symptoms would co-occur in individuals with damage to the DMN. To test this hypothesis, we used a k-means clustering algorithm to identify a target group of patients with reduced mind-wandering and fewer depressive symptoms relative to brain-damaged comparison subjects (n = 37 of 68; ps < .001). The anatomical localization of lesions for this target group was predominantly within the medial prefrontal cortex (mPFC). Structural and functional lesion network mapping results revealed that lesions of the target group had significantly greater connectivity with DMN and limbic regions. Taken together, these results suggest that brain injury affecting the mPFC and DMN is associated with both reduced mind-wandering and fewer depressive symptoms. Further investigation of neuroanatomical substrates that mediate a causal relationship between mind-wandering and mood may facilitate the identification of new therapeutic targets for neuromodulation in patients with disorders characterized by maladaptive mind-wandering, such as rumination.

Network-targeted transcranial magnetic stimulation (TMS) for mild cognitive impairment (MCI)

BACKGROUND

Transcranial magnetic stimulation (TMS) is a promising non-pharmacological intervention for treatment of mild cognitive impairment (MCI) and early Alzheimer's disease (AD). Yet, we know little about precisely where stimulation would be ideal to improve cognitive function.

OBJECTIVE

To examine the network functional connectivity (fc) characteristics of prefrontal and parietal stimulation sites, given that these sites have led to improved cognitive function in TMS studies involving MCI-AD and unimpaired participants.

METHODS

Resting-state functional MRI data were acquired from 32 MCI participants at the baseline visit of an ongoing TMS trial and used to compute connectivity with prefrontal and parietal stimulation locations, selected on the basis of previous TMS studies. The TMS seed maps were examined for extent of spatial overlap with eight canonical networks. After identifying the network most likely to be targeted by TMS, we applied strategies that may provide purer targeting. Finally, we examined network connectivity in relation to participants' behavioral characteristics because of the potential for TMS treatment to be personalized.

RESULTS

The prefrontal TMS seed map overlapped primarily with the salience network. The prefrontal site is also notable for its anti-correlated connectivity with the AD-vulnerable posterior cingulate cortex (PCC). The parietal TMS seed map showed the expected strong positive connectivity with the PCC and other default network regions. Nonetheless, this particular parietal site may simultaneously modulate the fronto-parietal network. Strategies to improve network targeting and to personalize TMS are reported as secondary findings.

CONCLUSION

These results can be applied to network-targeted brain stimulation for MCI and early AD treatment. Greater precision and personalization of TMS offer the promise of achieving better outcomes for individuals with MCI or mild AD dementia.

Real-time optimization to enhance noninvasive cortical excitability assessment in the human dorsolateral prefrontal cortex

OBJECTIVE

We currently lack a robust noninvasive method to measure prefrontal excitability in humans. Concurrent TMS and EEG in the prefrontal cortex is usually confounded by artifacts. Here we asked if real-time optimization could reduce artifacts and enhance a TMS-EEG measure of left prefrontal excitability.

METHODS

This closed-loop optimization procedure adjusts left dlPFC TMS coil location, angle, and intensity in real-time based on the EEG response to TMS. Our outcome measure was the left prefrontal early (20-60 ms) and local TMS-evoked potential (EL-TEP).

RESULTS

In 18 healthy participants, this optimization of coil angle and brain target significantly reduced artifacts by 63 % and, when combined with an increase in intensity, increased EL-TEP magnitude by 75 % compared to a non-optimized approach.

CONCLUSIONS

Real-time optimization of TMS parameters during dlPFC stimulation can enhance the EL-TEP.

SIGNIFICANCE

Enhancing our ability to measure prefrontal excitability is important for monitoring pathological states and treatment response.

Functional Connectivity Patterns Following Mild Traumatic Brain Injury and the Association With Longitudinal Cognitive Function

Functional magnetic resonance imaging (fMRI) has revealed subtle neuroplastic changes in brain networks following mild traumatic brain injury (mTBI), even when standard clinical imaging fails to detect abnormalities. However, prior findings have been inconsistent, in part due to methodological differences and high researcher degrees of freedom in region-based analyses, which often rely on predefined hypotheses and overlook complex, distributed connectivity patterns. Here, we apply an unbiased, data-driven multi-voxel pattern analysis (MVPA) to examine whole-brain functional connectivity differences in a large cohort of individuals with acute mTBI. Unlike conventional statistical approaches, MVPA enables a data-driven analysis of brain-wide connectivity patterns without requiring prior assumptions about the location or nature of abnormalities, allowing for the identification of the most informative features. This approach provides an exploratory characterization of whole-brain functional connectivity patterns and their relationship with cognitive recovery, offering new insights into the neural mechanisms underlying post-injury outcomes. A total of 265 adults (87 women) between 18 and 83 years old with Glasgow Coma Scale (GCS) scores of 13-15 were included in this analysis. Two replicate samples (n = 165, n = 155), with similar demographic characteristics, were also included. Data were collected as part of the prospective multi-center Transforming Research and Clinical Knowledge in TBI (TRACK-TBI). The goal of this study was to assess whole-brain functional connectivity patterns using fc-MVPA and post hoc seed-to-voxel analyses in a large, well-characterized sample to determine if changes in functional connectivity can differentiate subacute mTBI (within 2 weeks of injury) from a matched group of orthopedic control subjects (n = 49). Additionally, we aimed to investigate whether these connectivity patterns were linked to cognitive performance at 2 weeks, 6 months, and 12 months post-injury to better understand cognitive trajectories and recovery over time in individuals with mTBI. Voxel-to-voxel functional connectivity across the entire connectome revealed significant differences between TBI and no TBI in the functional connectivity patterns of 8 clusters (p-voxel < 0.001, FEW cluster-level p < 0.05) (k > 40, Fmax = 15.36), including right occipital cortex, anterior cingulate gyrus, inferior and middle temporal gyrus, right thalamus, left cerebellum, and the bilateral frontal pole. These clusters belong mainly to the visual network (VIS), frontoparietal network (FPN), default mode network (DMN) and limbic network (LIM). Post hoc characterization of each significant cluster revealed by MVPA using seed-to-voxel analysis showed a mixed pattern of connectivity between relevant networks and subcortico-cortical connections. After connectivity characterization, visual-motor skills assessed with Trail Making Test (TMT) A were significantly associated with the increased anticorrelation between the inferior temporal cortex and the bilateral occipital pole (FPN-VIS connectivity), along with decreased anticorrelations between the cerebellum and extensive areas of the somatomotor network (SMN) over 12 months post injury. Additionally, hypoconnectivity between the frontal pole (LIM) and anterior cingulate gyrus (salience network [SAL]) was associated with better executive functions performance measured by TMT-B over 12 months post-mTBI. In our study examining neuroplastic changes following TBI across the entire voxel-to-voxel functional connectome, we identified significant differences in the functional connectivity patterns of several regions known to be particularly vulnerable to injury mechanisms. Our findings highlight the complex and compensatory nature of brain network alterations after mTBI, suggesting both detrimental and adaptive changes in connectivity that affect cognitive functions. Consequently, our study provides novel evidence that specific brain networks and regions are particularly susceptible to functional connectivity changes during the acute stages of mTBI, which are related to cognitive recovery post-injury.

Investigating brain network dynamics in state-dependent stimulation: A concurrent electroencephalography and transcranial magnetic stimulation study using hidden Markov models

BACKGROUND

Systems neuroscience studies have shown that baseline brain activity can be categorized into large-scale networks (resting-state-networks, RNSs), with influence on cognitive abilities and clinical symptoms. These insights have guided millimeter-precise selection of brain stimulation targets based on RSNs. Concurrently, Transcranial Magnetic Stimulation (TMS) studies revealed that baseline brain states, measured by EEG signal power or phase, affect stimulation outcomes. However, EEG dynamics in these studies are mostly limited to single regions or channels, lacking the spatial resolution needed for accurate network-level characterization.

OBJECTIVE

We aim at mapping brain networks with high spatial and temporal precision and to assess whether the occurrence of specific network-level-states impact TMS outcome. To this end, we will identify large-scale brain networks and explore how their dynamics relates to corticospinal excitability.

METHODS

This study leverages Hidden Markov Models to identify large-scale brain states from pre-stimulus source space high-density-EEG data collected during TMS targeting the left primary motor cortex in twenty healthy subjects. The association between states and fMRI-defined RSNs was explored using the Yeo atlas, and the trial-by-trial relation between states and corticospinal excitability was examined.

RESULTS

We extracted fast-dynamic large-scale brain states with unique spatiotemporal and spectral features resembling major RSNs. The engagement of different networks significantly influences corticospinal excitability, with larger motor evoked potentials when baseline activity was dominated by the sensorimotor network.

CONCLUSIONS

These findings represent a step forward towards characterizing brain network in EEG-TMS with both high spatial and temporal resolution and underscore the importance of incorporating large-scale network dynamics into TMS experiments.

Four dimensions of individualization in brain stimulation for psychiatric disorders: context, target, dose, and timing

Non-invasive Brain Stimulation (NIBS) technologies, including transcranial electrical (tES) and magnetic (TMS) stimulation, have emerged as promising interventions for various psychiatric disorders. FDA-approved TMS protocols in depression, OCD and nicotine use disorder provide a meaningful improvement. Treatment efficacy however remains inconsistent across individuals, and one relevant reason is intervention effect variability based on individual factors. There is a growing effort to develop individualized interventions, reinforced recently by FDA approval of a new TMS protocol that includes individualized fMRI-based targeting along with other modifications with higher reported effect size than previous "one size fits all" protocols. This paper discusses the dimensions for individualizing tES/TMS protocols to enhance therapeutic efficacy. We propose a multifaceted approach to personalizing NIBS, considering four levels: (1) context, (2) target, (3) dose, and (4) timing. By addressing inter- and intra-individual variability, we highlight a path toward precision medicine using individualized Brain Stimulation to treat psychiatric diseases. Despite challenges and limitations, this approach encourages broader and more systematic adoption of personalized Brain Stimulation techniques to improve clinical outcomes.

Personalized models of Beam/F3 targeting in transcranial magnetic stimulation for depression: Implications for precision clinical translation

BACKGROUND

Clinical transcranial magnetic stimulation (TMS) for depression routinely relies on the scalp-based Beam/F3 targeting method to identify stimulation targets in the dorsolateral prefrontal cortex (dLPFC). Scalp-based targeting offers a low-cost and easily implemented method for TMS coil placement, enhancing treatment availability. However, limited anatomical and functional specificity of the Beam/F3 method may affect treatment outcomes, motivating assessment of the clinical standard.

METHODS

In a naturalistic clinical trial of TMS conduced at four Veterans Affairs hospitals, the authors evaluate the Beam/F3 method using neuroimaging incorporated before TMS, after five treatment sessions, and after all thirty sessions. Personalized anatomical and electric field (E-field) models were developed to assess target location and network engagement, as well as subsequent effects on clinical outcomes.

RESULTS

Anatomical models demonstrate that the Beam/F3 method produced reliable targets in the dLPFC across individuals and repeated treatment sessions. E-field models revealed that baseline anticorrelation between the stimulation center and the sgACC was associated with antidepressant symptom response after five TMS sessions (p=0.032,r2=0.100,N=46) and at the end of treatment (p=0.042,r2=0.107,N=39). Relatedly, E-field magnitude at the sgACC-anticorrelated peak in the prefrontal cortex correlated with symptom response throughout treatment (early treatment: p=0.001,r2=0.220,N=46; end of treatment: p=0.026,r2=0.127,N=39).

CONCLUSIONS

This work establishes that scalp-based targeting can produce reliable targets in the dLPFC and be successfully evaluated using a combination of neuroimaging and E-field modeling in pragmatic, multisite applications. Importantly, this investigation also found that significant network effects occur early in treatment and that Beam/F3 targets can engage functional mechanisms in TMS.

The Deep Brain Stimulation Response Network in Parkinson's Disease Operates in the High Beta Band

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms in patients with Parkinson's disease. Using functional MRI, optimal DBS response networks have been characterized. However, neural activity associated with Parkinsonian symptoms is magnitudes faster than what can be resolved by this method. While both spatial and temporal domains of these networks appear critical, no single study has yet investigated both domains simultaneously. Here, we aim to close this gap using subthalamic local field potentials that were concurrently recorded alongside whole-brain magnetoencephalography in a multi-center cohort of patients that underwent STN-DBS for the treatment of Parkinson's disease (N = 100 hemispheres). In every cortical vertex, cortico-subthalamic coupling was correlated with stimulation outcomes. This network spatially resembled fMRI-based findings (R = 0.40, P = 0.039) and explained significant amounts of variance in clinical outcomes (β std = 0.30, P = 0.002), while theta-alpha and low beta coupling did not show significant associations with DBS response (theta-alpha: β std = -0.02, P = 0.805; low beta: β std = -0.08, P = 0.426). The 'optimal' high beta coupling map was robust when subjected to various cross-validation designs (10-fold cross-validation: R = 0.29, P = 0.009; split-half design: R = 0.31, P = 0.026) and was able to predict outcomes across DBS centers (R = 0.74; P (1) = 8.9e-5). We identified a DBS response network that i) resembles the previously defined MRI network and ii) operates in the high-beta band. Maximal connectivity to this network was associated with optimal DBS outcomes and was able to cross-predict clinical improvements across DBS surgeons and centers.

Predicting the treatment outcomes of major depressive disorder interventions with baseline resting-state functional connectivity: a meta-analysis

BACKGROUND

Current interventions for major depressive disorder (MDD) demonstrate limited and heterogeneous efficacy, highlighting the need for improving the precision of treatment. Although findings have been mixed, resting-state functional connectivity (rsFC) at baseline shows promise as a predictive biomarker. This meta-analysis evaluates the evidence for baseline rsFC as a predictor of treatment outcomes of MDD interventions.

METHOD

We included MDD literature published between 2012 and 2024 that used antidepressants, non-invasive brain stimulation, and cognitive behavioral therapy. Pearson correlations or their equivalents were analyzed between baseline rsFC and treatment outcome. Nodes were categorized according to the type of brain networks they belong to, and pooled coefficients were generated for rsFC connections reported by more than three studies.

RESULT

Among the 16 included studies and 892 MDD patients, data from nine studies were used to generate pooled coefficients for the rsFC connection between the frontoparietal network (FPN) and default mode network (DMN), and within the DMN (six studies each, with three overlapping studies, involving 534 and 300 patients, respectively). The rsFC between the DMN and FPN had a pooled predictability of -0.060 (p = 0.171, fixed effect model), and the rsFC within the DMN had a pooled predictability of 0.207 (p < 0.001, fixed effect model). The rsFC between the DMN and FPN and the rsFC within the DMN had a larger effect in predicting the outcome of non-invasive brain stimulation (-0.215, p < 0.001, fixed effect model) and antidepressants (0.315, p < 0.001, fixed effect model), respectively. Heterogeneity was observed in both types of rsFC, study design, sample characteristics and data analysis pipeline.

CONCLUSION

Baseline rsFC within the DMN and between the DMN and FPN demonstrated a small but differential predictive effect on the outcome of antidepressants and non-invasive brain stimulation, respectively. The small predictability of rsFC suggested that rsFC between the FPN and DMN and the rsFC within the DMN might not be a good biomarker for predicting treatment outcome. Future research should focus on exploring treatment-specific predictions of baseline rsFC and its predictive utility for other types of MDD interventions.

TRIAL REGISTRATION

The review was pre-registered at PROSPERO CRD42022370235 (33).

Mapping Lesions That Cause Psychosis to a Human Brain Circuit and Proposed Stimulation Target

Importance

Identifying anatomy causally involved in psychosis could inform therapeutic neuromodulation targets for schizophrenia.

Objective

To assess whether lesions that cause secondary psychosis have functional connections to a common brain circuit.

Design, Setting, and Participants

This case-control study mapped functional connections of published cases of lesions causing secondary psychosis compared with control lesions unassociated with psychosis. Published cases of lesion-induced psychosis were analyzed in a computational laboratory. Participants had documented brain lesions associated with new-onset psychotic symptoms without a history of psychosis. Control cases included 1156 patients with lesions not associated with psychosis. Generalizability across lesional datasets was assessed using an independent cohort of 181 patients with brain lesions who subsequently underwent neurobehavioral testing. Data were analyzed from June 2022 to April 2024.

Exposures

Lesions causing secondary psychosis.

Main Outcomes and Measures

Psychosis or no psychosis.

Results

A total of 153 lesions from published cases were determined to be causal of psychosis, 42 of which were described as schizophrenia or schizophrenia-like (71 [46%] patients were male, 82 [54%] female; mean [SD] age, 50.0 [20.8] years). Lesions that caused secondary psychosis mapped to a common brain circuit defined by functional connectivity to the posterior subiculum of the hippocampus (84% functional overlap, family-wise error [FWE] rate corrected P < 5 × 10-5). At a lower statistical threshold (>75% overlap, FWE-corrected P < 5 × 10-4), this circuit included the ventral tegmental area, retrosplenial cortex, lobule IX and dentate nucleus of the cerebellum, and the mediodorsal and midline nuclei of the thalamus. This circuit was consistent when derived from schizophrenia-like cases (spatial r = 0.98). We repeated these analyses after excluding lesions intersecting the hippocampus (n = 47) and found a consistent functional connectivity profile (spatial r = 0.98) with the posterior subiculum remaining the center of connectivity (>75% overlap, FWE-corrected P < 5 × 10-5), demonstrating a circuit-level effect. In an independent observational cohort of patients with penetrating head trauma (n = 181), lesions associated with symptoms of psychosis exhibited significantly similar connectivity profiles to the lesion-derived psychosis circuit (suspiciousness, P = .03; unusual thought content, P = .046). Voxels in the rostromedial prefrontal cortex are highly correlated with this psychosis circuit (spatial r = 0.82), suggesting the rostromedial prefrontal cortex as a promising transcranial magnetic stimulation target for psychosis.

Conclusions and Relevance

Lesions that cause secondary psychosis affect a common brain circuit in the hippocampus. These results can help inform therapeutic neuromodulation targeting.

The Role of the Dorsolateral Prefrontal Cortex in Ego Dissolution and Emotional Arousal During the Psychedelic State

Lysergic acid diethylamide (LSD) is a classic serotonergic psychedelic that induces a profoundly altered conscious state. In conjunction with psychological support, it is currently being explored as a treatment for generalized anxiety disorder and depression. The dorsolateral prefrontal cortex (DLPFC) is a brain region that is known to be involved in mood regulation and disorders; hypofunction in the left DLPFC is associated with depression. This study investigated the role of the DLPFC in the psycho-emotional effects of LSD with functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) data of healthy human participants during the acute LSD experience. In the fMRI data, we measured the correlation between changes in resting-state functional connectivity (RSFC) of the DLPFC and post-scan subjective ratings of positive mood, emotional arousal, and ego dissolution. We found significant, positive correlations between ego dissolution and functional connectivity between the left & right DLPFC, thalamus, and a higher-order visual area, the fusiform face area (FFA). Additionally, emotional arousal was significantly associated with increased connectivity between the right DLPFC, intraparietal sulcus (IPS), and the salience network (SN). A confirmational "reverse" analysis, in which the outputs of the original RSFC analysis were used as input seeds, substantiated the role of the right DLPFC and the aforementioned regions in both ego dissolution and emotional arousal. Subsequently, we measured the effects of LSD on directed functional connectivity in MEG data that was source-localized to the input and output regions of both the original and reverse analyses. The Granger causality (GC) analysis revealed that LSD increased information flow between two nodes of the 'ego dissolution network', the thalamus and the DLPFC, in the theta band, substantiating the hypothesis that disruptions in thalamic gating underlie the experience of ego dissolution. Overall, this multimodal study elucidates a role for the DLPFC in LSD-induced states of consciousness and sheds more light on the brain basis of ego dissolution.

Potential locations for non-invasive brain stimulation in treating ADHD: Results from a cross-dataset validation of functional connectivity analysis

Noninvasive brain stimulation (NIBS) has emerged as a promising therapeutic approach for attention-deficit/hyperactivity disorder (ADHD), yet the inaccurate selection of stimulation sites may constrain its efficacy. This study aimed to identify novel NIBS targets for ADHD by integrating meta-analytic findings with cross-dataset validation of functional connectivity patterns. A meta-analysis including 124 functional magnetic resonance imaging (fMRI) studies was first conducted to delineate critical brain regions associated with ADHD, which were defined as regions of interest (ROIs). Subsequently, functional connectivity (FC) analysis was performed using resting-state fMRI data from two independent databases comprising 116 patients with ADHD. Surface brain regions exhibiting consistent FC patterns with the ADHD-related ROIs across both datasets were identified as candidate NIBS targets. These targets were then translated to scalp-level stimulation sites using the 10-20 system and continuous proportional coordinates (CPC). Key regions mapped to the scalp included the bilateral dorsolateral prefrontal cortex, right inferior frontal gyrus, bilateral inferior parietal lobule, supplementary motor area (SMA), and pre-SMA. These findings propose a set of precise stimulation location for NIBS interventions in ADHD, potentially broadening the scope of neuromodulation strategies for this disorder. The study emphasized the utility of cross-dataset functional connectivity analysis in refining NIBS target selection and highlights novel brain targets that warrant further investigation in clinical trials.

Quantifying and reporting the precision of transcranial magnetic stimulation targeting

The precise positioning of the transcranial magnetic stimulation (TMS) coil on a person's head is crucial for the efficacy and reliability of the delivered stimulation protocol. Sophisticated techniques have been developed to define subject-specific stimulation targets, and advancements in the use of MRI-guided neuronavigation allows for real-time monitoring of the coil location during the TMS session. However, there is a need for TMS users to objectively quantify and report the accuracy of their targeting. Here, we share our technique (open-source scripts) that extracts the location of each TMS pulse delivered in a session from an MRI-guided neuronavigation system and outputs measures of targeting precision. Such measures include the variance in coil location over the duration of a session, detection of 'off-target' pulses, and the distance error relative to the intended cortical target. Reporting these metrics in publications may aid in the replicability of methodology and reproducibility of results of TMS research and clinical treatments. Furthermore, these measures can be used in training TMS operators. We encourage others to adapt our technique to their system(s) and specific needs and to report their targeting precision.

Consensus review and considerations on TMS to treat depression: A comprehensive update endorsed by the National Network of Depression Centers, the Clinical TMS Society, and the International Federation of Clinical Neurophysiology

This article updates the prior 2018 consensus statement by the National Network of Depression Centers (NNDC) on the use of transcranial magnetic stimulation (TMS) in the treatment of depression, incorporating recent research and clinical developments. Publications on TMS and depression between September 2016 and April 2024 were identified using methods informed by PRISMA guidelines. The NNDC Neuromodulation Work Group met monthly between October 2022 and April 2024 to define important clinical topics and review pertinent literature. A modified Delphi method was used to achieve consensus. 2,396 abstracts and manuscripts met inclusion criteria for review. The work group generated consensus statements which include an updated narrative review of TMS safety, efficacy, and clinical features of use for depression. Considerations related to training, roles/responsibilities of providers, and documentation are also discussed. TMS continues to demonstrate broad evidence for safety and efficacy in treating depression. Newer forms of TMS are faster and potentially more effective than conventional repetitive TMS. Further exploration of targeting methods, use in special populations, and accelerated protocols is encouraged. This article provides an updated overview of topics relevant to the administration of TMS for depression and summarizes expert, consensus opinion on the practice of TMS in the United States.

Function-Specific Localization in the Supplementary Motor Area: A Potential Effective Target for Tourette Syndrome

AIMS

Repetitive transcranial magnetic stimulation (rTMS) targeting the supplementary motor area (SMA) may treat Tourette's syndrome (TS) by modulating the function of the globus pallidus internus (GPi) via the cortico-striato-thalamo-cortical circuit.

METHODS

We conducted a randomized longitudinal study to examine circuit functionality and clinical efficacy. The GPi was identified as an "effective region" for TS treatment. Using functional MRI, individualized targets within the SMA were identified. Function-specific targets [left SMA (n = 19), right SMA (n = 16)] were compared with conventional scalp-localized SMA targets (n = 19). Age- and gender-matched typical developmental children (TDC) served as controls (n = 48). TS patients received 50 Hz continuous theta burst stimulation (cTBS) at 70% RMT over five consecutive days (1800 pulses/day). Clinical efficacy was assessed using the Yale Global Tic Severity Scale (YGTSS) at one and two weeks post-cTBS. Functional connectivity (FC) analyses of the GPi evaluated the impact on brain function.

RESULTS

There was an approximately 3 cm Y-axis distance between the function-specific and conventional targets. TS patients exhibited significantly reduced GPi-base FC in bilateral motor areas at baseline compared to TDC. Following cTBS, 4 out of 19 patients in the left SMA group achieved a ≥ 30% reduction in YGTSS scores. cTBS modulated brain function in the left inferior orbital frontal cortex and right Lingual/cerebellum, primarily influenced by the right SMA target, whereas the conventional target showed no effect on YGTSS scores. Changes in GPi-target FC were significantly correlated with reduction in YGTSS total scores (r = 0.638, p = 0.026).

CONCLUSION

These findings suggest that function-specific SMA targets may yield more pronounced modulatory effects, with the left SMA target achieving "Effectiveness" after just one week of cTBS. Combining function-specific SMA-targeted cTBS with standard treatment shows promise in accelerating clinical efficacy for TS treatment, warranting further investigation.

Targeting VMPFC-amygdala circuit with TMS in substance use disorder: A mechanistic framework

The ventromedial prefrontal cortex (VMPFC), located along the medial aspect of the frontal area, plays a critical role in regulating arousal/emotions. Its intricate connections with subcortical structures, including the striatum and amygdala, highlight the VMPFC's importance in the neurocircuitry of addiction. Due to these features, the VMPFC is considered a promising target for transcranial magnetic stimulation (TMS) in substance use disorders (SUD). By the end of 2023, all 21 studies targeting VMPFC for SUD used anatomical landmarks (e.g., Fp1/Fp2 in the EEG system) to define coil location with a fixed orientation. Nevertheless, one-size-fits-all TMS over VMPFC has yielded variable outcomes. Here, we suggested a pipeline based on a tailored TMS targeting framework aimed at optimally modulating the VMPFC-amygdala circuit on an individual basis. We collected MRI data from 60 participants with methamphetamine use disorders (MUDs). We examined the variability in TMS target location based on task-based functional connectivity between VMPFC and amygdala using psychophysiological interaction (PPI) analysis. Electric fields (EF) were calculated for fixed vs. optimized location (Fp1/Fp2 vs. individualized maximal PPI), orientation (AF7/AF8 vs. optimized algorithm) and intensity (constant vs. adjusted) to maximize target engagement. In our pipeline, the left medial amygdala, identified as the brain region with the highest (0.31 ± 0.29) fMRI drug cue reactivity, was selected as the subcortical seed region. The voxel with the most positive amygdala-VMPFC PPI connectivity in each participant was considered the individualized TMS target (MNI-coordinates: [12.6, 64.23, -0.8] ± [13.64, 3.50, 11.01]). This individualized VMPFC-amygdala connectivity significantly correlated with VAS craving after cue exposure (R = 0.27, p = 0.03). Coil orientation was optimized to increase EF strength over the targeted circuit (0.99 ± 0.21 V/m vs. the fixed approach: Fp1: 0.56 ± 0.22 and Fp2: 0.78 ± 0.25 V/m) and TMS intensity was harmonized across the population. This study highlights the potential of an individualized VMPFC targeting framework to enhance treatment outcomes for addiction, specifically modulating the personalized VMPFC-amygdala circuit.

Structurally informed models of directed brain connectivity

Understanding how one brain region exerts influence over another in vivo is profoundly constrained by models used to infer or predict directed connectivity. Although such neural interactions rely on the anatomy of the brain, it remains unclear whether, at the macroscale, structural (or anatomical) connectivity provides useful constraints on models of directed connectivity. Here, we review the current state of research on this question, highlighting a key distinction between inference-based effective connectivity and prediction-based directed functional connectivity. We explore the methods via which structural connectivity has been integrated into directed connectivity models: through prior distributions, fixed parameters in state-space models and inputs to structure learning algorithms. Although the evidence suggests that integrating structural connectivity substantially improves directed connectivity models, assessments of reliability and out-of-sample validity are lacking. We conclude this Review with a strategy for future research that addresses current challenges and identifies opportunities for advancing the integration of structural and directed connectivity to ultimately improve understanding of the brain in health and disease.

Resting fMRI-guided TMS evokes subgenual anterior cingulate response in depression

BACKGROUND

Depression alleviation following treatment with repetitive transcranial magnetic stimulation (rTMS) tends to be more effective when TMS is targeted to cortical areas with high (negative) resting state functional connectivity (rsFC) with the subgenual anterior cingulate cortex (sgACC). However, the relationship between sgACC-cortex rsFC and the TMS-evoked response in the sgACC is still being explored and has not yet been established in depressed patients.

OBJECTIVES

In this study, we investigated the relationship between sgACC-cortical (site of stimulation) rsFC and induced evoked responses in the sgACC in healthy controls and depressed patients.

METHODS

For each participant (N = 115, 34 depressed patients), a peak rsFC cortical 'hotspot' for the sgACC and control targets were identified at baseline. Single pulses of TMS interleaved with fMRI readouts were administered to these targets to evoke downstream fMRI blood-oxygen-level-dependent (BOLD) responses in the sgACC. Generalized estimating equations were used to investigate the association between TMS-evoked BOLD responses in the sgACC and rsFC between the stimulation site and the sgACC.

RESULTS

Stimulations over cortical sites with high rsFC to the sgACC were effective in modulating activity in the sgACC in both healthy controls and depressed patients. Moreover, we found that in depressed patients, sgACC rsFC at the site of stimulation was associated with the induced evoked response amplitude in the sgACC: stronger positive rsFC values leading to stronger evoked responses in the sgACC.

CONCLUSIONS

rsFC-based targeting is a viable strategy to causally modulate the sgACC. Assuming an anti-depressive mechanism working through modulation of the sgACC, the field's exclusive focus on sites anticorrelated with the sgACC for treating depression should be broadened to explore positively-connected sites.

Structural-functional connectomics in major depressive disorder following aiTBS treatment

Major depressive disorder (MDD) has been associated with changes in the structural (SC) and functional connectivity (FC) of the brain. This study investigated the effects of accelerated intermittent theta burst stimulation (aiTBS) on SC-FC coupling and graph theory measures, focusing on the association between baseline SC-FC coupling of the dorsolateral prefrontal cortex (dlPFC) and clinical improvement. In a randomized, sham-controlled, quadruple-blind, crossover study, aiTBS was delivered to the left dlPFC of depressed patients with MDD, and diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rsfMRI) data were acquired. In 77 MDD patients, significantly increased whole-brain SC-FC coupling was observed, primarily driven by default mode network (DMN) SC-FC coupling, along with increased somatomotor network FC, and decreased FC between the DMN hubs and limbic regions after active aiTBS. Furthermore, significant increases were observed in structural global and local efficiency measures that were not specific to the stimulation condition (active/sham aiTBS). However, these changes did not significantly correlate with clinical improvement. Notably, baseline SC-FC coupling of the left dlPFC was a significant predictor of clinical improvement. Our findings highlight the potential of left dlPFC SC-FC coupling as a predictor of aiTBS treatment outcomes, as well as the effect of aiTBS in enhancing SC-FC coupling.

Repetitive transcranial magnetic stimulation enhanced by neuronavigation in the treatment of depressive disorder and schizophrenia

This editorial assesses the advancements in neuronavigation enhanced repetitive transcranial magnetic stimulation for depressive disorder and schizophrenia treatment. Conventional repetitive transcranial magnetic stimulation faces challenges due to the intricacies of brain anatomy and patient variability. Neuronavigation offers innovative solutions by integrating neuroimaging with three-dimensional localization to pinpoint brain regions and refine therapeutic targeting. This systematic review of recent literature underscores the enhanced efficacy of neuronavigation in improving treatment outcomes for these disorders. This editorial highlights the pivotal role of neuronavigation in advancing psychiatric care.

Reproducible routes: reliably navigating the connectome to enrich personalized brain stimulation strategies

Non-invasive brain stimulation (NIBS) technologies, such as repetitive transcranial magnetic stimulation (rTMS), offer significant therapeutic potential for a growing number of neuropsychiatric conditions. Concurrent with the expansion of this field is the swift evolution of rTMS methodologies, including approaches to optimize stimulation site planning. Traditional targeting methods, foundational to early successes in the field and still widely employed today, include using scalp-based heuristics or integrating structural MRI co-registration to align the transcranial magnetic stimulation (TMS) coil with anatomical landmarks. Recent evidence, however, supports refining and personalizing stimulation sites based on the target's structural and/or functional connectivity profile. These connectomic approaches harness the network-wide neuromodulatory effects of rTMS to reach deeper brain structures while also enabling a greater degree of personalization by accounting for heterogenous network topology. In this study, we acquired baseline multimodal magnetic resonance (MRI) at two time points to evaluate the reliability and reproducibility of distinct connectome-based strategies for stimulation site planning. Specifically, we compared the intra-individual difference between the optimal stimulation sites generated at each time point for (1) functional connectivity (FC) guided targets derived from resting-state functional MRI and (2) structural connectivity (SC) guided targets derived from diffusion tensor imaging. Our findings suggest superior reproducibility of SC-guided targets. We emphasize the necessity for further research to validate these findings across diverse patient populations, thereby advancing the personalization of rTMS treatments.

Repetitive Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations in Schizophrenia: A Randomized Clinical Trial

IMPORTANCE

Auditory verbal hallucinations (AVH) are a common symptom of schizophrenia, increasing the patient's risks of suicide and violence. Repetitive transcranial magnetic stimulation (rTMS) is a potential treatment for AVH.

OBJECTIVE

To investigate the effect of imaging-navigated rTMS on AVH in patients with schizophrenia.

DESIGN, SETTING, AND PARTICIPANTS

This 6-week, double-blind, sham-controlled, randomized clinical trial was performed at the Anhui Mental Health Center, Hefei, China, from September 1, 2016, to August 31, 2021. Participants included 66 patients with AVH and schizophrenia. Data were analyzed from May 1, 2022, to March 31, 2023.

INTERVENTIONS

Participants were randomly assigned 1:1 to either imaging-navigated active or sham rTMS over the left temporoparietal junction for 2 weeks.

MAIN OUTCOMES AND MEASURES

The primary outcome measured improvements in AVH from baseline to week 2 and week 6 using the Auditory Hallucination Rating Scale (AHRS) scores. In addition, the TMS-induced electric field strength was used to estimate improvements in AVH as a secondary outcome.

RESULTS

A total of 62 participants (33 women [53%]; mean [SD] age, 27.4 [9.2] years) completed the 2-week treatments. Of these, 32 were randomized to the active rTMS group (18 women [56%]; mean [SD] age, 26.9 [9.2] years) and 30 to the sham treatment group (15 women [50%]; mean [SD] age, 27.8 [9.4] years). In the intention-to-treat analyses, patients receiving active rTMS showed a significantly greater reduction in AHRS scores compared with those receiving sham treatment at week 2 (difference, 5.96 [95% CI, 3.42-8.50]; t = 4.61; P < .001; Cohen d, 1.17 [95% CI, 0.62-1.71]). These clinical effects were sustained at week 6. Additionally, a stronger TMS-induced electric field within a predefined AVH brain network was associated with greater reductions in AHRS scores (B = 3.12; t = 3.58; P = .002). No serious adverse event was observed.

CONCLUSIONS AND RELEVANCE

The findings of this randomized clinical trial suggest that imaging-navigated rTMS may effectively and safely alleviate AVH in patients with schizophrenia. Findings also suggest that the electric field strength in the individualized AVH network is a vital parameter for optimizing the efficacy of the rTMS protocol.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02863094.

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

What can neuroimaging of neuromodulation reveal about the basis of circuit therapies for psychiatry?

Neuromodulation is increasingly becoming a therapeutic option for treatment resistant psychiatric disorders. These non-invasive and invasive therapies are still being refined but are clinically effective and, in some cases, provide sustained symptom reduction. Neuromodulation relies on changing activity within a specific brain region or circuit, but the precise mechanisms of action of these therapies, is unclear. Here we review work in both humans and animals that has provided insight into how therapies such as deep brain and transcranial magnetic stimulation alter neural activity across the brain. We focus on studies that have combined neuromodulation with neuroimaging such as PET and MRI as these measures provide detailed information about the distributed networks that are modulated and thus insight into both the mechanisms of action of neuromodulation but also potentially the basis of psychiatric disorders. Further we highlight work in nonhuman primates that has revealed how neuromodulation changes neural activity at different scales from single neuron activity to functional connectivity, providing key insight into how neuromodulation influences the brain. Ultimately, these studies highlight the value of combining neuromodulation with neuroimaging to reveal the mechanisms through which these treatments influence the brain, knowledge vital for refining targeted neuromodulation therapies for psychiatric disorders.

Contribution of resting-state functional connectivity of the subgenual anterior cingulate to prediction of antidepressant efficacy in patients with major depressive disorder

This study investigated how resting-state functional connectivity (rsFC) of the subgenual anterior cingulate cortex (sgACC) predicts antidepressant response in patients with major depressive disorder (MDD). Eighty-seven medication-free MDD patients underwent baseline resting-state functional MRI scans. After 12 weeks of escitalopram treatment, patients were classified into remission depression (RD, n = 42) and nonremission depression (NRD, n = 45) groups. We conducted two analyses: a voxel-wise rsFC analysis using sgACC as a seed to identify group differences, and a prediction model based on the sgACC rsFC map to predict treatment efficacy. Haufe transformation was used to interpret the predictive rsFC features. The RD group showed significantly higher rsFC between the sgACC and regions in the fronto-parietal network (FPN), including the bilateral dorsolateral prefrontal cortex (DLPFC) and bilateral inferior parietal lobule (IPL), compared to the NRD group. These sgACC rsFC measures correlated positively with symptom improvement. Baseline sgACC rsFC also significantly predicted treatment response after 12 weeks, with a mean accuracy of 72.64% (p < 0.001), mean area under the curve of 0.74 (p < 0.001), mean specificity of 0.82, and mean sensitivity of 0.70 in 10-fold cross-validation. The predictive voxels were mainly within the FPN. The rsFC between the sgACC and FPN is a valuable predictor of antidepressant response in MDD patients. These findings enhance our understanding of the neurobiological mechanisms underlying treatment response and could help inform personalized treatment strategies for MDD.

Brain Circuit-Derived Biotypes for Treatment Selection in Mood Disorders: A Critical Review and Illustration of a Functional Neuroimaging Tool for Clinical Translation

Although the lifetime burden due to major depressive disorder is increasing, we lack tools for selecting the most effective treatments for each patient. One-third to one-half of patients with major depressive disorder do not respond to treatment, and we lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry. We begin by summarizing the current landscape of how functional neuroimaging-derived circuit predictors can forecast treatment outcomes in depression. Then, we outline the opportunities and challenges in integrating circuit predictors into clinical practice. We highlight one standardized and reproducible approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation. We conclude by evaluating the prospects and practicality of employing neuroimaging tools, such as the one that we propose, in routine clinical practice.

Precision Network Modeling of Transcranial Magnetic Stimulation Across Individuals Suggests Therapeutic Targets and Potential for Improvement

Higher-order cognitive and affective functions are supported by large-scale networks in the brain. Dysfunction in different networks is proposed to associate with distinct symptoms in neuropsychiatric disorders. However, the specific networks targeted by current clinical transcranial magnetic stimulation (TMS) approaches are unclear. While standard-of-care TMS relies on scalp-based landmarks, recent FDA-approved TMS protocols use individualized functional connectivity with the subgenual anterior cingulate cortex (sgACC) to optimize TMS targeting. Leveraging previous work on precision network estimation and recent advances in network-level TMS targeting, we demonstrate that clinical TMS approaches target different functional networks between individuals. Homotopic scalp positions (left F3 and right F4) target different networks within and across individuals, and right F4 generally favors a right-lateralized control network. We also modeled the impact of targeting the dorsolateral prefrontal cortex (dlPFC) zone anticorrelated with the sgACC and found that the individual-specific anticorrelated region variably targets a network coupled to reward circuitry. Combining individualized, precision network mapping and electric field (E-field) modeling, we further illustrate how modeling can be deployed to prospectively target distinct closely localized association networks in the dlPFC with meaningful spatial selectivity and E-field intensity and retrospectively assess network engagement. Critically, we demonstrate the feasibility and reliability of this approach in an independent cohort of participants (including those with Major Depressive Disorder) who underwent repeated sessions of TMS to distinct networks, with precise targeting derived from a low-burden single session of data. Lastly, our findings emphasize differences between selectivity and maximal intensity, highlighting the need to consider both metrics in precision TMS efforts.

Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample

BACKGROUND

Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample.

METHODS

We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes.

RESULTS

The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation.

CONCLUSIONS

Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.

The effect of repetitive transcranial magnetic stimulation on the Hamilton Depression Rating Scale-17 criterion in patients with major depressive disorder without psychotic features: a systematic review and meta-analysis of intervention studies

AIM

In line with the publication of clinical information related to the therapeutic process of repetitive transcranial magnetic stimulation (rTMS) and the updating of relevant treatment guidelines, the present meta-analysis study was designed and conducted to determine the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features.

METHODS

In this study, a systematic search was conducted in electronic databases such as PubMed [Medline], Scopus, Web of Science, Embase, Ovid, Cochrane Library, and ClinicalTrials. gov using relevant keywords. The search period in this study was from January 2000 to January 2022, which was updated until May 2023. Randomized controlled trials (RCTs) that determined the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features were included in the analysis. The quality of the included RCTs was assessed using the Cochrane Risk of Bias checklist. Statistical analyses were performed using STATA (Version 16) and RevMan (Version 5).

RESULTS

Following the combination of results from 16 clinical trial studies in the present meta-analysis, it was found that the mean Hamilton Depression Rating Scale-17 (HDRS-17) in patients with major depressive disorder (MDD) decreases by an average of 1.46 units (SMD: -1.46; % 95 CI: -1.65, -1.27, I square: 45.74%; P heterogeneity: 0.56). Subgroup analysis results indicated that the standardized mean difference of Hamilton Depression Rating Scale-17 (HDRS-17) varied based on the number of treatment sessions: patients receiving 10 or fewer repetitive transcranial magnetic stimulation (rTMS) sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 2.60 units (SMD: -2.60; % 95 CI: -2.86, -2.33, I square: 55.12%; P heterogeneity: 0.55), while those receiving 11 to 20 sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 0.28 units (SMD: -0.28; % 95 CI: -0.65, -0.09, I square: 39.91%; P heterogeneity: 0.89).

CONCLUSION

In conclusion, our meta-analysis demonstrates the efficacy of repetitive transcranial magnetic stimulation (rTMS) in reducing depressive symptoms in major depressive disorder (MDD) patients. The complex results of subgroup analysis revealed insight on the possible benefits of a more focused strategy with fewer sessions, as well as the impact of treatment session frequency. These findings add to our understanding of repetitive transcranial magnetic stimulation (rTMS) as a therapeutic intervention for the treatment of major depressive illnesses.

Chronometric TMS-fMRI of personalized left dorsolateral prefrontal target reveals state-dependency of subgenual anterior cingulate cortex effects

Transcranial magnetic stimulation (TMS) applied to a left dorsolateral prefrontal cortex (DLPFC) area with a specific connectivity profile to the subgenual anterior cingulate cortex (sgACC) has emerged as a highly effective non-invasive treatment option for depression. However, antidepressant outcomes demonstrate significant variability among therapy plans and individuals. One overlooked contributing factor is the individual brain state at the time of treatment. In this study we used interleaved TMS-fMRI to investigate the influence of brain state on acute TMS effects, both locally and remotely. TMS was performed during rest and during different phases of cognitive task processing. Twenty healthy participants were included in this study. In the first session, imaging data for TMS targeting were acquired, allowing for identification of individualized targets in the left DLPFC based on highest anti-correlation with the sgACC. The second session involved chronometric interleaved TMS-fMRI measurements, with 10 Hz triplets of TMS administered during rest and at distinct timings during an N-back task. Consistent with prior findings, interleaved TMS-fMRI revealed significant BOLD activation changes in the targeted network. The precise timing of TMS relative to the cognitive states during the task demonstrated distinct BOLD response in clinically relevant brain regions, including the sgACC. Employing a standardized timing approach for TMS using a task revealed more consistent modulation of the sgACC at the group level compared to stimulation during rest. In conclusion, our findings strongly suggest that acute local and remote effects of TMS are influenced by brain state during stimulation. This study establishes a basis for considering brain state as a significant factor in designing treatment protocols, possibly improving TMS treatment outcomes.

A comparative study of the dorsolateral prefrontal cortex targeting approaches for transcranial magnetic stimulation treatment: Insights from the healthy control data

Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (DLPFC) is an established treatment for medication-resistant depression. Several targeting methods for the left DLPFC have been proposed including identification with resting-state functional magnetic resonance imaging (rs-fMRI) neuronavigation, stimulus coordinates based on structural MRI, or electroencephalography (EEG) F3 site by Beam F3 method. To date, neuroanatomical and neurofunctional differences among those approaches have not been investigated on healthy subjects, which are structurally and functionally unaffected by psychiatric disorders. This study aimed to compare the mean location, its dispersion, and its functional connectivity with the subgenual cingulate cortex (SGC), which is known to be associated with the therapeutic outcome in depression, of various approaches to target the DLPFC in healthy subjects. Fifty-seven healthy subjects underwent MRI scans to identify the stimulation site based on their resting-state functional connectivity and were measured their head size for targeting with Beam F3 method. In addition, we included two fixed stimulus coordinates over the DLPFC in the analysis, as recommended in previous studies. From the results, the rs-fMRI method had, as expected, more dispersed target sites across subjects and the greatest anticorrelation with the SGC, reflecting the known fact that personalized neuronavigation yields the greatest antidepressant effect. In contrast, the targets located by the other methods were relatively close together with less dispersion, and did not differ in anticorrelation with the SGC, implying their limitation of the therapeutic efficacy and possible interchangeability of them.

Neuromodulatory transcranial magnetic stimulation (TMS) changes functional connectivity proportional to the electric-field induced by the TMS pulse

OBJECTIVE

Transcranial magnetic stimulation (TMS) can efficiently and robustly modulate synaptic plasticity, but little is known about how TMS affects functional connectivity (rs-fMRI). Accordingly, this project characterized TMS-induced rsFC changes in depressed patients who received 3 days of left prefrontal intermittent theta burst stimulation (iTBS).

METHODS

rs-fMRI was collected from 16 subjects before and after iTBS. Correlation matrices were constructed from the cleaned rs-fMRI data. Electric-field models were conducted and used to predict pre-post changes in rs-fMRI. Site by orientation heatmaps were created for vectors centered on the stimulation site and a control site (contralateral motor cortex).

RESULTS

For the stimulation site, there was a clear relationship between both site and coil orientation, and connectivity changes. As distance from the stimulation site increased, prediction accuracy decreased. Similarly, as eccentricity from the optimal orientation increased, prediction accuracy decreased. The systematic effects described above were not apparent in the heatmap centered on the control site.

CONCLUSIONS

These results suggest that rs-fMRI following iTBS changes systematically as a function of the distribution of electrical energy delivered from the TMS pulse, as represented by the e-field model.

SIGNIFICANCE

This finding lays the groundwork for future studies to individualize TMS targeting based on how predicted rs-fMRI changes might impact psychiatric symptoms.

Dose-Dependent Target Engagement of a Clinical Intermittent Theta Burst Stimulation Protocol: An Interleaved Transcranial Magnetic Stimulation-Functional Magnetic Resonance Imaging Study in Healthy People

BACKGROUND

Intermittent theta burst stimulation (iTBS) of the dorsolateral prefrontal cortex (DLPFC) is widely applied as a therapeutic intervention in mental health; however, the understanding of its mechanisms is still incomplete. Prior magnetic resonance imaging (MRI) studies have mainly used offline iTBS or short sequences in concurrent transcranial magnetic stimulation (TMS)-functional MRI (fMRI). This study investigated a full 600-stimuli iTBS protocol using interleaved TMS-fMRI in comparison with 2 control conditions in healthy subjects.

METHODS

In a crossover design, 18 participants underwent 3 sessions of interleaved iTBS-fMRI: 1) the left DLPFC at 40% resting motor threshold (rMT) intensity, 2) the left DLPFC at 80% rMT intensity, and 3) the left primary motor cortex (M1) at 80% rMT intensity. We compared immediate blood oxygen level-dependent (BOLD) responses during interleaved iTBS-fMRI across these conditions including correlations between individual fMRI BOLD activation and iTBS-induced electric field strength at the target sites.

RESULTS

Whole-brain analysis showed increased activation in several regions following iTBS. Specifically, the left DLPFC, as well as the bilateral M1, anterior cingulate cortex, and insula, showed increased activation during 80% rMT left DLPFC stimulation. Increased BOLD activity in the left DLPFC was observed with neither 40% rMT left DLPFC stimulation nor left M1 80% rMT iTBS, whereas activation in other regions was found to overlap between conditions. Of note, BOLD activation and electric field intensities were only correlated for M1 stimulation and not for the DLPFC conditions.

CONCLUSIONS

This interleaved TMS-fMRI study showed dosage- and target-specific BOLD activation during a 600-stimuli iTBS protocol in healthy individuals. Future studies may use our approach for investigating target engagement in clinical samples.

Theta-burst direct electrical stimulation remodels human brain networks

Theta-burst stimulation (TBS), a patterned brain stimulation technique that mimics rhythmic bursts of 3-8 Hz endogenous brain rhythms, has emerged as a promising therapeutic approach for treating a wide range of brain disorders, though the neural mechanism of TBS action remains poorly understood. We investigated the neural effects of TBS using intracranial EEG (iEEG) in 10 pre-surgical epilepsy participants undergoing intracranial monitoring. Here we show that individual bursts of direct electrical TBS at 29 frontal and temporal sites evoked strong neural responses spanning broad cortical regions. These responses exhibited dynamic local field potential voltage changes over the course of stimulation presentations, including either increasing or decreasing responses, suggestive of short-term plasticity. Stronger stimulation augmented the mean TBS response amplitude and spread with more recording sites demonstrating short-term plasticity. TBS responses were stimulation site-specific with stronger TBS responses observed in regions with strong baseline stimulation effective (cortico-cortical evoked potentials) and functional (low frequency phase locking) connectivity. Further, we could use these measures to predict stable and varying (e.g. short-term plasticity) TBS response locations. Future work may integrate pre-treatment connectivity alongside other biophysical factors to personalize stimulation parameters, thereby optimizing induction of neuroplasticity within disease-relevant brain networks.

Status and trends of TMS research in depressive disorder: a bibliometric and visual analysis

Background

Depression is a chronic psychiatric condition that places significant burdens on individuals, families, and societies. The rapid evolution of non-invasive brain stimulation techniques has facilitated the extensive clinical use of Transcranial Magnetic Stimulation (TMS) for depression treatment. In light of the substantial recent increase in related research, this study aims to employ bibliometric methods to systematically review the global research status and trends of TMS in depression, providing a reference and guiding future studies in this field.

Methods

We retrieved literature on TMS and depression published between 1999 and 2023 from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) databases within the Web of Science Core Collection (WoSCC). Bibliometric analysis was performed using VOSviewer and CiteSpace software to analyze data on countries, institutions, authors, journals, keywords, citations, and to generate visual maps.

Results

A total of 5,046 publications were extracted covering the period from 1999 to 2023 in the field of TMS and depression. The publication output exhibited an overall exponential growth trend. These articles were published across 804 different journals, BRAIN STIMULATION is the platform that receives the most articles in this area. The literature involved contributions from over 16,000 authors affiliated with 4,573 institutions across 77 countries. The United States contributed the largest number of publications, with the University of Toronto and Daskalakis ZJ leading as the most prolific institution and author, respectively. Keywords such as "Default Mode Network," "Functional Connectivity," and "Theta Burst" have recently garnered significant attention. Research in this field primarily focuses on TMS stimulation patterns, their therapeutic efficacy and safety, brain region and network mechanisms under combined brain imaging technologies, and the modulation effects of TMS on brain-derived neurotrophic factor (BDNF) and neurotransmitter levels.

Conclusion

In recent years, TMS therapy has demonstrated extensive potential applications and significant implications for the treatment of depression. Research in the field of TMS for depression has achieved notable progress. Particularly, the development of novel TMS stimulation patterns and the integration of TMS therapy with multimodal techniques and machine learning algorithms for precision treatment and investigation of brain network mechanisms have emerged as current research hotspots.

Effect of Low-Intensity Transcranial Focused Ultrasound Stimulation in Patients With Major Depressive Disorder: A Randomized, Double-Blind, Sham-Controlled Clinical Trial

OBJECTIVE

Low-intensity transcranial focused ultrasound (tFUS) has emerged as a promising non-invasive brain stimulation modality with high spatial selectivity and the ability to reach deep brain areas. The present study aimed to investigate the safety and effectiveness of low-intensity tFUS in treating major depressive disorder.

METHODS

Participants were recruited in an outpatient clinic and randomly assigned to either the verum tFUS or sham stimulation group. The intervention group received six sessions of tFUS stimulation to the left dorsolateral prefrontal cortex over two weeks. Neuropsychological assessments were conducted before and after the sessions. Resting-state functional magnetic resonance imaging (rsfMRI) was also performed to evaluate changes in functional connectivity (FC). The primary outcome measure was the change in depressive symptoms, assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS).

RESULTS

The tFUS stimulation sessions were well tolerated without any undesirable side effects. The analysis revealed a significant main effect of session sequence on the MADRS scores and significant interactions between the session sequences and groups. The rsfMRI analysis showed a higher FC correlation between the right superior part of the subgenual anterior cingulate cortex (sgACC) and several other brain regions in the verum group compared with the sham group.

CONCLUSION

Our results reveal that tFUS stimulation clinically improved MADRS scores with network-level modulation of a sgACC subregion. This randomized, sham-controlled clinical trial, the first study of its kind, demonstrated the safety and probable efficacy of tFUS stimulation for the treatment of depression.

A cognitive neural circuit biotype of depression showing functional and behavioral improvement after transcranial magnetic stimulation in the B-SMART-fMRI trial

We previously identified a cognitive biotype of depression characterized by treatment resistance, impaired cognitive control behavioral performance and dysfunction in the cognitive control circuit, comprising the dorsolateral prefrontal cortex (dLPFC) and dorsal anterior cingulate cortex (dACC). Therapeutic transcranial magnetic stimulation (TMS) to the left dLPFC is a promising option for individuals whose depression does not respond to pharmacotherapy. Here, 43 veterans with treatment-resistant depression were assessed before TMS, after early TMS and post-TMS using functional magnetic resonance imaging during a Go-NoGo paradigm, behavioral cognitive control tests and symptom questionnaires. Stratifying veterans at baseline based on task-evoked dLPFC-dACC connectivity, we demonstrate that TMS-related improvement in cognitive control circuit connectivity and behavioral performance is specific to individuals with reduced connectivity at baseline (cognitive biotype +), whereas individuals with intact connectivity at baseline (cognitive biotype -) did not demonstrate significant changes. Our findings show that dLPFC-dACC connectivity during cognitive control is both a promising diagnostic biomarker for a cognitive biotype of depression and a response biomarker for cognitive improvement after TMS applied to the dLPFC.

Mapping cortical excitability in the human dorsolateral prefrontal cortex

BACKGROUND

Transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (dlPFC) is an effective treatment for depression, but the neural effects after TMS remains unclear. TMS paired with electroencephalography (TMS-EEG) can causally probe these neural effects. Nonetheless, variability in single pulse TMS-evoked potentials (TEPs) across dlPFC subregions, and potential artifact induced by muscle activation, necessitate detailed mapping for accurate treatment monitoring.

OBJECTIVE

To characterize early TEPs anatomically and temporally (20-50 ms) close to the TMS pulse (EL-TEPs), as well as associated muscle artifacts (<20 ms), across the dlPFC. We hypothesized that TMS location and angle influence EL-TEPs, and specifically that conditions with larger muscle artifact may exhibit lower observed EL-TEPs due to over-rejection during preprocessing. Additionally, we sought to determine an optimal group-level TMS target and angle, while investigating the potential benefits of a personalized approach.

METHODS

In 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses.

RESULTS

Stimulation location significantly influenced observed EL-TEPs, with posterior and medial targets yielding larger EL-TEPs. Regions with high EL-TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger EL-TEP responses compared to other dlPFC targets. Optimal dlPFC target differed across subjects, suggesting that a personalized targeting approach might boost the EL-TEP by an additional 36%.

SIGNIFICANCE

EL-TEPs can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. The identification of an optimal group-level target and the potential for further refinement through personalized targeting hold significant implications for optimizing depression treatment protocols.

In Search for a Pathogenesis of Major Depression and Suicide-A Joint Investigation of Dopamine and Fiber Tract Anatomy Focusing on the Human Ventral Mesencephalic Tegmentum: Description of a Workflow

Major depressive disorder (MDD) is prevalent with a high subjective and socio-economic burden. Despite the effectiveness of classical treatment methods, 20-30% of patients stay treatment-resistant. Deep Brain Stimulation of the superolateral branch of the medial forebrain bundle is emerging as a clinical treatment. The stimulation region (ventral tegmental area, VTA), supported by experimental data, points to the role of dopaminergic (DA) transmission in disease pathology. This work sets out to develop a workflow that will allow the performance of analyses on midbrain DA-ergic neurons and projections in subjects who have committed suicide. Human midbrains were retrieved during autopsy, formalin-fixed, and scanned in a Bruker MRI scanner (7T). Sections were sliced, stained for tyrosine hydroxylase (TH), digitized, and integrated into the Montreal Neurological Institute (MNI) brain space together with a high-resolution fiber tract atlas. Subnuclei of the VTA region were identified. TH-positive neurons and fibers were semi-quantitatively evaluated. The study established a rigorous protocol allowing for parallel histological assessments and fiber tractographic analysis in a common space. Semi-quantitative readings are feasible and allow the detection of cell loss in VTA subnuclei. This work describes the intricate workflow and first results of an investigation of DA anatomy in VTA subnuclei in a growing naturalistic database.

Increased anti-correlation between the left dorsolateral prefrontal cortex and the default mode network following Stanford Neuromodulation Therapy (SNT): analysis of a double-blinded, randomized, sham-controlled trial

SNT is a high-dose accelerated intermittent theta-burst stimulation (iTBS) protocol coupled with functional-connectivity-guided targeting that is an efficacious and rapid-acting therapy for treatment-resistant depression (TRD). We used resting-state functional MRI (fMRI) data from a double-blinded sham-controlled randomized controlled trial1 to reveal the neural correlates of SNT-based symptom improvement. Neurobehavioral data were acquired at baseline, post-treatment, and 1-month follow-up. Our primary analytic objective was to investigate changes in seed-based functional connectivity (FC) following SNT and hypothesized that FC changes between the treatment target and the sgACC, DMN, and CEN would ensue following active SNT but not sham. We also investigated the durability of post-treatment observed FC changes at a 1-month follow-up. Study participants included transcranial magnetic stimulation (TMS)-naive adults with a primary diagnosis of moderate-to-severe TRD. Fifty-four participants were screened, 32 were randomized, and 29 received active or sham SNT. An additional 5 participants were excluded due to imaging artifacts, resulting in 12 participants per group (Sham: 5F; SNT: 5F). Although we did not observe any significant group × time effects on the FC between the individualized stimulation target (L-DLPFC) and the CEN or sgACC, we report an increased magnitude of negative FC between the target site and the DMN post-treatment in the active as compared to sham SNT group. This change in FC was sustained at the 1-month follow-up. Further, the degree of change in FC was correlated with improvements in depressive symptoms. Our results provide initial evidence for the putative changes in the functional organization of the brain post-SNT.

Reduced dorsal fronto-striatal connectivity at rest in anorexia nervosa

BACKGROUND

Anorexia nervosa (AN) is a serious psychiatric illness that remains difficult to treat. Elucidating the neural mechanisms of AN is necessary to identify novel treatment targets and improve outcomes. A growing body of literature points to a role for dorsal fronto-striatal circuitry in the pathophysiology of AN, with increasing evidence of abnormal task-based fMRI activation within this network among patients with AN. Whether these abnormalities are present at rest and reflect fundamental differences in brain organization is unclear.

METHODS

The current study combined resting-state fMRI data from patients with AN (n = 89) and healthy controls (HC; n = 92) across four studies, removing site effects using ComBat harmonization. First, the a priori hypothesis that dorsal fronto-striatal connectivity strength - specifically between the anterior caudate and dlPFC - differed between patients and HC was tested using seed-based functional connectivity analysis with small-volume correction. To assess specificity of effects, exploratory analyses examined anterior caudate whole-brain connectivity, amplitude of low-frequency fluctuations (ALFF), and node centrality.

RESULTS

Compared to HC, patients showed significantly reduced right, but not left, anterior caudate-dlPFC connectivity (p = 0.002) in small-volume corrected analyses. Whole-brain analyses also identified reduced connectivity between the right anterior caudate and left superior frontal and middle frontal gyri (p = 0.028) and increased connectivity between the right anterior caudate and right occipital cortex (p = 0.038). No group differences were found in analyses of anterior caudate ALFF and node centrality.

CONCLUSIONS

Decreased coupling of dorsal fronto-striatal regions indicates that circuit-based abnormalities persist at rest and suggests this network may be a potential treatment target.

Cognitive enhancing effect of rTMS combined with tDCS in patients with major depressive disorder: a double-blind, randomized, sham-controlled study

BACKGROUND

Cognitive dysfunction is one of the common symptoms in patients with major depressive disorder (MDD). Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) have been studied separately in the treatment of cognitive dysfunction in MDD patients. We aimed to investigate the effectiveness and safety of rTMS combined with tDCS as a new therapy to improve neurocognitive impairment in MDD patients.

METHODS

In this brief 2-week, double-blind, randomized, and sham-controlled trial, a total of 550 patients were screened, and 240 MDD inpatients were randomized into four groups (active rTMS + active tDCS, active rTMS + sham tDCS, sham rTMS + active tDCS, sham rTMS + sham tDCS). Finally, 203 patients completed the study and received 10 treatment sessions over a 2-week period. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was performed to assess patients' cognitive function at baseline and week 2. Also, we applied the 24-item Hamilton Depression Rating Scale (HDRS-24) to assess patients' depressive symptoms at baseline and week 2.

RESULTS

After 10 sessions of treatment, the rTMS combined with the tDCS group showed more significant improvements in the RBANS total score, immediate memory, and visuospatial/constructional index score (all p < 0.05). Moreover, post hoc tests revealed a significant increase in the RBANS total score and Visuospatial/Constructional in the combined treatment group compared to the other three groups but in the immediate memory, the combined treatment group only showed a better improvement than the sham group. The results also showed the RBANS total score increased significantly higher in the active rTMS group compared with the sham group. However, rTMS or tDCS alone was not superior to the sham group in terms of other cognitive performance. In addition, the rTMS combined with the tDCS group showed a greater reduction in HDRS-24 total score and a better depression response rate than the other three groups.

CONCLUSIONS

rTMS combined with tDCS treatment is more effective than any single intervention in treating cognitive dysfunction and depressive symptoms in MDD patients.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (ChiCTR2100052122).

Real-time optimization to enhance noninvasive cortical excitability assessment in the human dorsolateral prefrontal cortex

Objective

We currently lack a robust noninvasive method to measure prefrontal excitability in humans. Concurrent TMS and EEG in the prefrontal cortex is usually confounded by artifacts. Here we asked if real-time optimization could reduce artifacts and enhance a TMS-EEG measure of left prefrontal excitability.

Methods

This closed-loop optimization procedure adjusts left dlPFC TMS coil location, angle, and intensity in real-time based on the EEG response to TMS. Our outcome measure was the left prefrontal early (20-60 ms) and local TMS-evoked potential (EL-TEP).

Results

In 18 healthy participants, this optimization of coil angle and brain target significantly reduced artifacts by 63% and, when combined with an increase in intensity, increased EL-TEP magnitude by 75% compared to a non-optimized approach.

Conclusions

Real-time optimization of TMS parameters during dlPFC stimulation can enhance the EL-TEP.

Significance

Enhancing our ability to measure prefrontal excitability is important for monitoring pathological states and treatment response.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Neural response during prefrontal theta burst stimulation: Interleaved TMS-fMRI of full iTBS protocols

BACKGROUND

Left prefrontal intermittent theta-burst stimulation (iTBS) has emerged as a safe and effective transcranial magnetic stimulation (TMS) treatment protocol in depression. Though network effects after iTBS have been widely studied, the deeper mechanistic understanding of target engagement is still at its beginning. Here, we investigate the feasibility of a novel integrated TMS-fMRI setup and accelerated echo planar imaging protocol to directly observe the immediate effects of full iTBS treatment sessions.

OBJECTIVE/HYPOTHESIS

In our effort to explore interleaved iTBS-fMRI feasibility, we hypothesize that TMS will induce acute BOLD signal changes in both the stimulated area and interconnected neural regions.

METHODS

Concurrent TMS-fMRI with full sessions of neuronavigated iTBS (i.e. 600 pulses) of the left dorsolateral prefrontal cortex (DLPFC) was investigated in 18 healthy participants. In addition, we conducted four TMS-fMRI sessions in a single patient on long-term maintenance iTBS for bipolar depression to test the transfer to clinical cases.

RESULTS

Concurrent TMS-fMRI was feasible for iTBS sequences with 600 pulses. During interleaved iTBS-fMRI, an increase of the BOLD signal was observed in a network including bilateral DLPFC regions. In the clinical case, a reduced BOLD response was found in the left DLPFC and the subgenual anterior cingulate cortex, with high variability across individual sessions.

CONCLUSIONS

Full iTBS sessions as applied for the treatment of depressive disorders can be established in the interleaved iTBS-fMRI paradigm. In the future, this experimental approach could be valuable in clinical samples, for demonstrating target engagement by iTBS protocols and investigating their mechanisms of therapeutic action.

Structural Brain Connectivity and Treatment Improvement in Mood Disorder

Background: The treatment of depressive episodes is well established, with clearly demonstrated effectiveness of antidepressants and psychotherapies. However, more than one-third of depressed patients do not respond to treatment. Identifying the brain structural basis of treatment-resistant depression could prevent useless pharmacological prescriptions, adverse events, and lost therapeutic opportunities. Methods: Using diffusion magnetic resonance imaging, we performed structural connectivity analyses on a cohort of 154 patients with mood disorder (MD) and 77 sex- and age-matched healthy control (HC) participants. To assess illness improvement, the patients with MD went through two clinical interviews at baseline and at 6-month follow-up and were classified based on the Clinical Global Impression-Improvement score into improved or not-improved (NI). First, the threshold-free network-based statistics (NBS) was conducted to measure the differences in regional network architecture. Second, nonparametric permutations tests were performed on topological metrics based on graph theory to examine differences in connectome organization. Results: The threshold-free NBS revealed impaired connections involving regions of the basal ganglia in patients with MD compared with HC. Significant increase of local efficiency and clustering coefficient was found in the lingual gyrus, insula, and amygdala in the MD group. Compared with the NI, the improved displayed significantly reduced network integration and segregation, predominately in the default-mode regions, including the precuneus, middle temporal lobe, and rostral anterior cingulate. Conclusions: This study highlights the involvement of regions belonging to the basal ganglia, the fronto-limbic network, and the default mode network, leading to a better understanding of MD disease and its unfavorable outcome.

A precision functional atlas of personalized network topography and probabilities

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.