Identifying the anatomy of circuits causal of psychosis could inform treatment targets for schizophrenia. We identified 155 published case reports of brain lesions that caused new-onset psychosis. We mapped connectivity of these lesions using a normative human fMRI connectome. Lesions causing psychosis mapped to a common brain circuit defined by functional connectivity to the posterior subiculum of the hippocampus. This circuit was consistent both across individual symptoms of psychosis (delusions, hallucinations, and thought disorders), and when excluding lesions that touched the hippocampus. In an independent observational study (n=181), lesions connected to this circuit were preferentially associated with psychotic symptoms. A location in the rostromedial prefrontal cortex with high connectivity to this psychosis circuit was identified as a potential target for transcranial magnetic stimulation. Based on these results, we conclude that lesions that cause psychosis have common functional connections to the posterior subiculum of the hippocampus.

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 x 10(-5)). At a lower statistical threshold (>75% overlap, FWE-corrected P < 5 x 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 x 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.

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 analyzed 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.

BACKGROUND:Aggression exacts a significant toll on human societies and is highly prevalent among neuropsychiatric patients. The neural mechanisms of aggression are unclear and treatment options are limited. METHODS:Using a recently validated lesion network mapping technique, we derived an aggression-associated network by analyzing data from 182 patients who had experienced penetrating head injuries during their service in the Vietnam War. To test whether damage to this lesion-derived network would increase the risk of aggression-related neuropsychiatric symptoms, we used the Harvard Lesion Repository (N = 852). To explore potential therapeutic relevance of this network, we used an independent deep brain stimulation dataset of 25 patients with epilepsy, in which irritability and aggression are known potential side effects. RESULTS:We found that lesions associated with aggression occurred in many different brain locations but were characterized by a specific brain network defined by functional connectivity to a hub region in the right prefrontal cortex. This network involves positive connectivity to the ventromedial prefrontal cortex, dorsolateral prefrontal cortex, frontal pole, posterior cingulate cortex, anterior cingulate cortex, temporal-parietal junction, and lateral temporal lobe and negative connectivity to the amygdala, hippocampus, insula, and visual cortex. Among all 24 neuropsychiatric symptoms included in the Harvard Lesion Repository, criminality demonstrated the most alignment with our aggression-associated network. Deep brain stimulation site connectivity to this same network was associated with increased irritability. CONCLUSIONS:We conclude that brain lesions associated with aggression map to a specific human brain circuit, and the functionally connected regions in this circuit provide testable targets for therapeutic neuromodulation.

Gene expression shapes the brain's functional connectome, yet it is unclear whether genes linked to the same disorder converge on shared networks. We introduce gene network mapping-a framework combining spatial transcriptomics with normative functional connectivity to identify networks associated with gene expression. By generating gene-network maps, we captured distributed connectivity patterns for individual genes. Aggregating these across genes implicated in the same disorder yielded disease-network maps that captured the cumulative genetic impact on brain networks. We validated these maps by comparing them to lesion-derived networks and testing whether modulation of these networks predicted outcomes in deep brain stimulation (DBS) cohorts. This framework offers a novel tool to study the molecular architecture of brain disorders and supports the network-informed diagnostics and therapeutics in precision medicine.

Abstract Therapeutic brain stimulation targets are typically designed to treat specific psychiatric or neurological symptoms.1–4 This approach presents a dilemma when treating patients with comorbidities, atypical symptom profiles, or overlapping symptoms. Identifying targets that modulate groups of behavioral or cognitive symptoms across diagnoses may provide alternative treatment options and outcomes. Here, we use causal brain mapping and clustering methods to identify two distinct brain networks, based on common patterns of connectivity to lesions that selectively modify behaviors and symptoms. Due to the behavioral items in each cluster, we hypothesize that these networks are related to positive and negative affect, respectively. Across ten different datasets of patients receiving transcranial magnetic stimulation (TMS) or deep brain stimulation (DBS),1,5,6 stimulation site connectivity to each of our two brain networks independently predicted improvement in depressive symptoms. Thus, we defined two networks which are independently and causally involved in depression symptoms.

To test whether lesions causing takotsubo cardiomyopathy map to a common brain network.

Religious fundamentalism, characterized by rigid adherence to a set of beliefs putatively revealing inerrant truths, is ubiquitous across cultures and has a global impact on society. Understanding the psychological and neurobiological processes producing religious fundamentalism may inform a variety of scientific, sociological, and cultural questions. Research indicates that brain damage can alter religious fundamentalism. However, the precise brain regions involved with these changes remain unknown. Here, we analyzed brain lesions associated with varying levels of religious fundamentalism in two large datasets from independent laboratories. Lesions associated with greater fundamentalism were connected to a specific brain network with nodes in the right orbitofrontal, dorsolateral prefrontal, and inferior parietal lobe. This fundamentalism network was strongly right hemisphere lateralized and highly reproducible across the independent datasets ( r = 0.82) with cross-validations between datasets. To explore the relationship of this network to lesions previously studied by our group, we tested for similarities to twenty-one lesion-associated conditions. Lesions associated with confabulation and criminal behavior showed a similar connectivity pattern as lesions associated with greater fundamentalism. Moreover, lesions associated with poststroke pain showed a similar connectivity pattern as lesions associated with lower fundamentalism. These findings are consistent with the current understanding of hemispheric specializations for reasoning and lend insight into previously observed epidemiological associations with fundamentalism, such as cognitive rigidity and outgroup hostility.

To begin expanding on previous lesion network mapping of delusions.

AbstractObjectiveTo systematically evaluate which lesion‐based imaging features and methods allow for the best statistical prediction of poststroke deficits across independent datasets.MethodsWe 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.ResultsWe 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).InterpretationWe 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.

To identify the brain regions and networks involved in lesion induced cerebral achromatopsia.

Importance:Drug-resistant temporal lobe epilepsy (TLE) has been associated with hippocampal pathology. Most surgical treatment strategies, including resection and responsive neurostimulation (RNS), focus on this disease epicenter; however, imaging alterations distant from the hippocampus, as well as emerging data from responsive neurostimulation trials, suggest conceptualizing TLE as a network disorder. Objective:To assess whether brain networks connected to areas of atrophy in the hippocampus align with the topography of distant neuroimaging alterations and RNS response. Design, Setting, and Participants:This retrospective case-control study was conducted between July 2009 and June 2022. Data collection for this multicenter, population-based study took place across 4 tertiary referral centers in Montréal, Canada; Querétaro, México; Nanjing, China; and Salt Lake City, Utah. Eligible patients were diagnosed with TLE according to International League Against Epilepsy criteria and received either neuroimaging or neuroimaging and RNS to the hippocampus. Patients with encephalitis, traumatic brain injury, or bilateral TLE were excluded. Main Outcomes and Measures:Spatial alignment between brain network topographies. Results:Of the 110 eligible patients, 94 individuals diagnosed with TLE were analyzed (51 [54%] female; mean [SD] age, 31.3 [10.9] years). Hippocampal thickness maps in TLE were compared to 120 healthy control individuals (66 [55%] female; mean [SD] age, 29.8 [9.5] years), and areas of atrophy were identified. Using an atlas of normative connectivity (n = 1000), 2 brain networks were identified that were functionally connected to areas of hippocampal atrophy. The first network was defined by positive correlations to temporolimbic, medial prefrontal, and parietal regions, whereas the second network by negative correlations to frontoparietal regions. White matter changes colocalized to the positive network (t93 = -3.82; P = 2.44 × 10-4). In contrast, cortical atrophy localized to the negative network (t93 = 3.54; P = 6.29 × 10-3). In an additional 38 patients (20 [53%] female; mean [SD] age, 35.8 [11.3] years) treated with RNS, connectivity between the stimulation site and atrophied regions within the negative network was associated with seizure reduction (t212 = -2.74; P = .007). Conclusions and Relevance:The findings in this study indicate that distributed pathology in TLE may occur in brain networks connected to the hippocampal epicenter. Connectivity to these same networks was associated with improvement following RNS. A network approach to TLE may reveal therapeutic targets outside the traditional target in the hippocampus.