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Psychiatric disorders share neurobiology and frequently co-occur. This neurobiological and clinical overlap highlights opportunities for transdiagnostic treatments. In this study, we used coordinate and lesion network mapping to test for a shared brain network across psychiatric disorders. In our meta-analysis of 193 studies, atrophy coordinates across six psychiatric disorders mapped to a common brain network defined by positive connectivity to anterior cingulate and insula, and by negative connectivity to posterior parietal and lateral occipital cortex. This network was robust to leave-one-diagnosis-out cross-validation and specific to atrophy coordinates from psychiatric versus neurodegenerative disorders (72 studies). In 194 patients with penetrating head trauma, lesion damage to this network correlated with the number of post-lesion psychiatric diagnoses. Neurosurgical ablation targets for psychiatric illness (four targets) also aligned with the network. This convergent brain network for psychiatric illness may partially explain high rates of psychiatric comorbidity and could highlight neuromodulation targets for patients with more than one psychiatric disorder. The authors use morphometric and brain lesion data to identify a convergent brain network shared by psychiatric disorders.

Disorders of consciousness are characterized by severe impairments in arousal and awareness. Deep brain stimulation is a potential treatment, but outcomes vary—possibly due to differences in patient characteristics, electrode placement, or the specific brain network engaged. We describe 40 patients with disorders of consciousness undergoing deep brain stimulation targeting the thalamic centromedian-parafascicular complex. Improvements in consciousness are associated with better-preserved gray matter, particularly in the striatum. Electric field modeling reveals that stimulation is most effective when it extends below the centromedian nucleus, engaging the inferior parafascicular nucleus and the adjacent ventral tegmental tract—a pathway that connects the brainstem and hypothalamus and runs along the midbrain-thalamus border. External validation analyses show that effective stimulation engages a brain network overlapping with disrupted patterns of brain activity observed in two independent cohorts with impaired consciousness: one with arousal-impairing stroke lesions and the other with awareness-impairing seizures. Together, these findings advance the field by informing patient selection, refining stimulation targets, and identifying a brain network linked to recovery that may have broader therapeutic relevance across consciousness-impairing conditions. In people with severe brain injuries, stimulation restored consciousness by engaging a deep brain circuit for wakefulness—revealing a target that may also guide treatment in stroke and epilepsy.

Damage to specific brain circuits can cause specific neuropsychiatric symptoms. Therapeutic stimulation to these same circuits may modulate these symptoms. To determine whether these circuits converge, we studied depression severity after brain lesions ( n  = 461, five datasets), transcranial magnetic stimulation ( n  = 151, four datasets) and deep brain stimulation ( n  = 101, five datasets). Lesions and stimulation sites most associated with depression severity were connected to a similar brain circuit across all 14 datasets ( P  < 0.001). Circuits derived from lesions, deep brain stimulation and transcranial magnetic stimulation were similar ( P  < 0.0005), as were circuits derived from patients with major depression versus other diagnoses ( P  < 0.001). Connectivity to this circuit predicted out-of-sample antidepressant efficacy of transcranial magnetic stimulation and deep brain stimulation sites ( P  < 0.0001). In an independent analysis, 29 lesions and 95 stimulation sites converged on a distinct circuit for motor symptoms of Parkinson’s disease ( P  < 0.05). We conclude that lesions, transcranial magnetic stimulation and DBS converge on common brain circuitry that may represent improved neurostimulation targets for depression and other disorders. Which brain circuits are causally involved in depression? Using the human connectome as a wiring diagram, Siddiqi et al. combine data from lesions, deep brain stimulation and transcranial magnetic stimulation studies to show that these three methods converge in identifying a single depression circuit.

Structural brain lesions are the most common cause of adult‐onset epilepsy. The lesion location may contribute to the risk for epileptogenesis, but whether specific lesion locations are associated with a risk for secondary seizure generalization from focal to bilateral tonic–clonic seizures, is unknown. We identified patients with a diagnosis of adult‐onset epilepsy caused by an ischemic stroke or a tumor diagnosed at the Turku University Hospital in 2004–2017. Lesion locations were segmented on patient‐specific MR imaging and transformed to a common brain atlas (MNI space). Both region‐of‐interest analyses (intersection with the cortex, hemisphere, and lobes) and voxel‐wise analyses were conducted to identify the lesion locations associated with focal to bilateral tonic–clonic compared to focal seizures. We included 170 patients with lesion‐induced epilepsy (94 tumors, 76 strokes). Lesions predominantly localized in the cerebral cortex (OR 2.50, 95% C.I. 1.21–5.15, p = .01) and right hemisphere (OR 2.22, 95% C.I. 1.17–4.20, p = .01) were independently associated with focal to bilateral tonic–clonic seizures. At the lobar‐level, focal to bilateral tonic–clonic seizures were associated with lesions in the right frontal cortex (OR 4.41, 95% C.I. 1.44–13.5, p = .009). No single voxels were significantly associated with seizure type. These effects were independent of lesion etiology. Our results demonstrate that lesion location is associated with the risk for secondary generalization of epileptic seizures. These findings may contribute to identifying patients at risk for focal to bilateral tonic–clonic seizures. Structural brain lesions are the most common cause of adult‐onset epilepsy. The lesion location may contribute to the risk for epileptogenesis, but whether specific lesion locations are associated with a risk for secondary seizure generalization from focal to bilateral tonic‐clonic seizures, is unknown. Our results demonstrate that lesion location is associated with the risk for secondary generalization of epileptic seizures independent of lesion etiology.

Abstract BACKGROUND Deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) can improve seizure control for patients with drug-resistant epilepsy (DRE). Yet, one cannot overlook the high discrepancy in efficacy among patients, possibly resulting from differences in stimulation site. OBJECTIVE To test the hypothesis that stimulation at the junction of the ANT and mammillothalamic tract (ANT-MTT junction) increases seizure control. METHODS The relationship between seizure control and the location of the active contacts to the ANT-MTT junction was investigated in 20 patients treated with ANT-DBS for DRE. Coordinates and Euclidean distance of the active contacts relative to the ANT-MTT junction were calculated and related to seizure control. Stimulation sites were mapped by modelling the volume of tissue activation (VTA) and generating stimulation heat maps. RESULTS After 1 yr of stimulation, patients had a median 46% reduction in total seizure frequency, 50% were responders, and 20% of patients were seizure-free. The Euclidean distance of the active contacts to the ANT-MTT junction correlates to change in seizure frequency (r2 = 0.24, P = .01) and is ∼30% smaller (P = .015) in responders than in non-responders. VTA models and stimulation heat maps indicate a hot-spot at the ANT-MTT junction for responders, whereas non-responders had no evident hot-spot. CONCLUSION Stimulation at the ANT-MTT junction correlates to increased seizure control. Our findings suggest a relationship between the stimulation site and therapy response in ANT-DBS for epilepsy with a potential role for the MTT. DBS directed at white matter merits further exploration for the treatment of epilepsy. Graphical Abstract Graphical Abstract

Objective To systematically evaluate which lesion‐based imaging features and methods allow for the best statistical prediction of poststroke deficits across independent datasets. Methods We utilized imaging and clinical data from three independent datasets of patients experiencing acute stroke (N1 = 109, N2 = 638, N3 = 794) to statistically predict acute stroke severity (NIHSS) based on lesion volume, lesion location, and structural and functional disconnection with the lesion location using normative connectomes. Results We found that prediction models trained on small single‐center datasets could perform well using within‐dataset cross‐validation, but results did not generalize to independent datasets (median R2N1 = 0.2%). Performance across independent datasets improved using large single‐center training data (R2N2 = 15.8%) and improved further using multicenter training data (R2N3 = 24.4%). These results were consistent across lesion attributes and prediction models. Including either structural or functional disconnection in the models outperformed prediction based on volume or location alone (P < 0.001, FDR‐corrected). Interpretation We conclude that (1) prediction performance in independent datasets of patients with acute stroke cannot be inferred from cross‐validated results within a dataset, as performance results obtained via these two methods differed consistently, (2) prediction performance can be improved by training on large and, importantly, multicenter datasets, and (3) structural and functional disconnection allow for improved prediction of acute stroke severity.

•ANT connect distinct higher-order association cortex wider than the Papez circuit.•ANT evoked electrical activity flows along intrinsic functional network architecture.•This study highlights the neural basis of RSFC at the level of thalamocortical circuit. Characterizing human thalamocortical network is fundamental for understanding a vast array of human behaviors since the thalamus plays a central role in cortico-subcortical communication. Over the past few decades, advances in functional magnetic resonance imaging have allowed for spatial mapping of intrinsic resting-state functional connectivity (RSFC) between both cortical regions and in cortico-subcortical networks. Despite these advances, identifying the electrophysiological basis of human thalamocortical network architecture remains challenging. By leveraging stereoelectroencephalography electrodes temporarily implanted into distributed cortical regions and the anterior nucleus of the thalamus (ANT) of 10 patients with refractory focal epilepsy, we tested whether ANT stimulation evoked cortical potentials align with RSFC from the stimulation site, derived from a normative functional connectome (n = 1000). Our study identifies spatial convergence of ANT stimulation evoked cortical potentials and normative RSFC. Other than connections to the Papez circuit, the ANT was found to be closely connected to several distinct higher-order association cortices, including the precuneus, angular gyrus, dorsal lateral prefrontal cortex, and anterior insula. Remarkably, we found that the spatial distribution and magnitude of cortical-evoked responses to single-pulse electrical stimulation of the ANT aligned with the spatial pattern and strength of normative RSFC of the stimulation site. The present study provides electrophysiological evidence that stimulation evoked electrical activity flows along intrinsic brain networks connected on a thalamocortical level.

•Sleep spindles were measured in human anterior thalamus and on the scalp.•Both fast and slow spindles occurred in the anterior thalamus.•> 25% of spindles spanned multiple channels in thalamus and cortex.•A novel statistical approach confirmed that spindle co-occurrences were not random.•Cortical spindle patterns depended on thalamic involvement and spindle frequency. Sleep spindles (8 - 16 Hz) are transient electrophysiological events during non-rapid eye movement sleep. While sleep spindles are routinely observed in the cortex using scalp electroencephalography (EEG), recordings of their thalamic counterparts have not been widely studied in humans. Based on a few existing studies, it has been hypothesized that spindles occur as largely local phenomena. We investigated intra-thalamic and thalamocortical spindle co-occurrence, which may underlie thalamocortical communication. We obtained scalp EEG and thalamic recordings from 7 patients that received bilateral deep brain stimulation (DBS) electrodes to the anterior thalamus for the treatment of drug resistant focal epilepsy. Spindles were categorized into subtypes based on their main frequency (i.e., slow (10±2 Hz) or fast (14±2 Hz)) and their level of thalamic involvement (spanning one channel, or spreading uni- or bilaterally within the thalamus). For the first time, we contrasted observed spindle patterns with permuted data to estimate random spindle co-occurrence. We found that multichannel spindle patterns were systematically coordinated at the thalamic and thalamocortical level. Importantly, distinct topographical patterns of thalamocortical spindle overlap were associated with slow and fast subtypes of spindles. These observations provide further evidence for coordinated spindle activity in thalamocortical networks.

Idiopathic generalized epilepsy (IGE) is a brain network disease, but the location of this network and its relevance for treatment remain unclear. We combine the locations of brain abnormalities in IGE (131 coordinates from 21 studies) with the human connectome to identify an IGE network. We validate this network by showing alignment with structural brain abnormalities previously identified in IGE and brain areas activated by generalized epileptiform discharges in simultaneous electroencephalogram-functional magnetic resonance imaging. The topography of the IGE network aligns with brain networks involved in motor control and loss of consciousness consistent with generalized seizure semiology. To investigate therapeutic relevance, we analyze data from 21 patients with IGE treated with deep brain stimulation (DBS) for generalized seizures. Seizure frequency reduced a median 90% after DBS and stimulation sites intersect an IGE network peak in the centromedian nucleus of the thalamus. Together, this study helps unify prior findings in IGE and identify a brain network target that can be tested in clinical trials of brain stimulation to control generalized seizures. Ji et al. identify an idiopathic generalised epilepsy network that links heterogeneously distributed brain abnormalities to a common brain network and deep brain stimulation sites which reduce generalised seizures.