Alexander Li Cohen

Diffuse midline gliomas (DMGs) are near-universally lethal tumours of the childhood central nervous system ^1,2 . In animal models, DMGs form brain-wide integrated networks through neuron-to-glioma synapses ^3–6 and glioma-to-glioma gap junctional coupling ³ . This extensive connectivity robustly promotes the growth and invasion of DMG ^3–9 and other glial malignancies ^10–12 through paracrine mechanisms and direct neuron-to-glioma synapses. However, the organization and clinical implications of these connections in the living human brain remain to be elucidated. Here, we develop tumour network mapping to compute the brain-wide connectivity profile of DMG, defining a conserved brain network across pontine and thalamic DMG associated with patient short-term survival (DMG network). Tumour functional connectivity with the DMG network was independently predictive of patient overall survival across two external validation cohorts. Tumour growth mapped to DMG network-specific trajectories and peak in-network neurometabolic changes across development spatiotemporally aligned with the peak age incidence of DMG. Analyses of single-nucleus RNA sequencing data confirmed diverse synaptic gene enrichment in high-connectivity DMG. Strikingly, incidental surgical resection of high-connectivity thalamic DMG tissue conferred a significant survival advantage. Collectively, these data define a conserved and prognostically important brain network in children with DMG, consistent with the hypothesis that DMGs exploit otherwise healthy brain circuits to promote tumour growth.

Task-based “localizer” neuroimaging protocols are often used to identify specific functional areas in individual participants. Conventionally, these tasks can be unengaging, leading to increased motion and scan fatigue, especially for populations which may struggle with lengthy scans. Dynamic, naturalistic stimuli, like entertaining movies, offer a potential alternative with higher participant engagement and improved data quality. Here, we evaluated whether a short Pixar movie, Partly Cloudy, could serve as a reasonable and useful replacement for a traditional fusiform face area (FFA) localizer in a group of adolescents with and without autism spectrum disorder (ASD). We found that individualized FFA localizations derived from a Pixar movie, Partly Cloudy, were largely consistent with those produced by a traditional localizer. Peak activation locations showed no difference between localizer types; measures of activation pattern and magnitude were also largely the same, except that the occipital face area (OFA) demonstrated more task than movie activation and the parahippocampal place area (PPA) demonstrated more movie than task activation. However, applying these FFA individualized ROIs (iROIs) to independent task data revealed that traditional localizer iROIs still produce more face-selective activations. We also demonstrated that the movie viewing helps to reduce motion levels in both adolescents with and without autism relative to the traditional localizer task. Hence, while they may not localize face-selective regions of the FFA as robustly as traditional task-based localizers, movie localizers may be an appropriate, or even preferable, choice for fMRI studies in populations which struggle to tolerate lengthy scans, such as individuals with autism, and in paradigms that must rapidly localize multiple functional regions.

Lesion network mapping (LNM) and related techniques have been used in over 200 studies, primarily to test whether anatomically distributed lesions that cause the same symptom fall within a common brain network. A recent article ¹ challenges the specificity and validity of this technique, suggesting that lesion network maps primarily reflect intrinsic properties of the normative connectome rather than lesion–symptom relationships. However, the data and procedures in van den Heuvel et al. do not reflect those used in most LNM studies. Further, the main conclusions were based on similarity between maps, but similarity does not imply the absence of meaningful differences. In contrast, LNM provides evidence for meaningful differences using specificity testing. Exemplary analyses of 1090 lesion locations from 34 prior LNM studies do not support van den Heuvel’s concerns and confirm the lesion-deficit specificity of LNM. While we encourage further methodological investigation, the analyses of van den Heuvel et al. do not invalidate prior LNM findings or future applications.

Aggressive behaviour is prevalent across neurodevelopmental and neuropsychiatric conditions and is related to poor outcomes. Yet, despite extensive neuroimaging studies, a consistent set of brain networks where dysfunction is consistently related to aggressive behaviour remains unclear. Many studies are correlational in nature, while causal studies, such a lesion-location-based studies, are often limited to injury of the frontal lobes. Here, we analyse 61 focal brain lesions, identified in the current medical literature, that are associated with new-onset aggression and related behaviours. Lesions were traced onto a standardized brain atlas and used as seeds for a functional connectivity analysis, leveraging resting-state data from 1000 healthy individuals. These maps, representing likely pre-injury connectivity, were grouped using a data-driven hierarchical clustering approach. Then, the lesion networks of the identified clusters were separately compared with the connectivity of 716 lesions causing other symptoms. This data-driven approach identified two distinct lesion subgroups that both appear to manifest aggression through the co-occurrence of disrupted functional connectivity to networks involved in emotional expression and cognitive control. Both ‘aggression networks’ demonstrated sensitivity and specificity when compared with lesions causing a wide variety of other neuropsychiatric symptoms. The first subgroup network involved connectivity to the anterior cingulate cortex and was correlated with the connectivity of lesions causing akinetic mutism. The second subgroup network involved connectivity to the ventromedial prefrontal cortex and contained a notable subset of cases (n = 25) that had reported criminal behaviour, supporting a role of self-control in this subgroup and implying separable influences towards criminality within our identified aggression networks. Alterations within the first group aligned with motivation networks, while the second group aligned with disinhibition networks, indicating these as the potential underlying factors in aggression in the two subgroups, respectively. This characterization was supported by previous work on the atrophy network mapping of behavioural variant frontotemporal dementia. Overall, this study suggests that aggressive behaviour may be more likely after injury to distinct brain networks, which may be related to distinct behavioural factors, and has implications for potential targeted therapeutic interventions such as focused neuromodulation.

Neuroimaging research depends on registration, the alignment of patients’ brains to a template or standard space, to enable accurate comparisons across individuals. Decades of work have advanced our ability to accurately register typical brains, but registering atypical brains, such as those with injury or highly distorted anatomy, remains a challenge. In particular, registration of perinatal stroke imaging is often complicated by delayed injury identification, which results in imaging obtained during the chronic stage where secondary structural impacts are evident. While analyses in native space can be valuable for subject-specific investigations, group-level studies require registration to a common template space, which enables between-subject comparisons of lesion locations and their network correlates. Although many registration algorithms exist, as do various compensation techniques for focal lesions, it is unclear how effective they are when applied to the highly distorted anatomy often present in this chronic perinatal stroke imaging. Here, we quantitatively and qualitatively compared the performance of three registration algorithms (FNIRT, ANTs, EasyReg) in registering eleven variably distorted brains with perinatal stroke to a standard template using their default lesion-compensation techniques. We also assessed the impact of “brain grafting”, that is, inserting a healthy tissue mask in place of the defined lesion area prior to registration. Our findings show that ANTs and EasyReg are significantly more accurate than FNIRT for chronic perinatal stroke imaging, although all three software packages have marked difficulty with large lesions. Notably, brain grafting significantly improved the lesion mask normalization performance of FNIRT. In light of these comparisons, the recently released EasyReg appears to be an appropriate starting point for registering cohorts with chronic perinatal strokes, but we still emphasize the necessity of consistent visual inspection of registered brains.

Objective: This study was undertaken to develop a fully automated algorithm for tuber segmentation and quantification of tuber volume that performs similarly to the gold standard human neuroradiologist. Methods: We used brain magnetic resonance imaging (MRI) from patients with tuberous sclerosis complex (TSC) to train and validate a convolutional neural network (CNN), which was evaluated on segmentation with the Dice–Sørensen similarity coefficient (DSSC) and on tuber burden quantification with Spearman correlation coefficient against a neuroradiologist's gold standard in the test set. Results: We collected 263 MRIs from 196 patients (57% males) with median (25th percentile–75th percentile) age of 4.3 (3.0–10.1) years: 176 MRIs in the train set, 39 in the validation set, and 48 in the test set. The final model achieved in the test set a DSSC of .820 (95% confidence interval [CI] = .799–.840) in the whole brain and in the different lobes the following: .831 (95% CI = .804–.850) in left frontal, .827 (95% CI = .799–.853) in right frontal, .817 (95% CI = .779–.842) in left temporal, .834 (95% CI = .812–.849) in right temporal, .821 (95% CI = .783–.856) in left parietal, .840 (95% CI = .810–.865) in right parietal, .832 (95% CI = .808–.851) in left occipital, and .856 (95% CI = .838–.871) in right occipital. CNN tuber volume quantification nearly perfectly correlated (Spearman correlation coefficient) with the neuroradiologist's across the whole brain (.984, 95% CI = .971–.991) and in the different lobes: .966 (95% CI = .940–.981) in left frontal, .973 (95% CI = .952–.985) in right frontal, .936 (95% CI = .888–.964) in left temporal, .967 (95% CI = .942–.982) in right temporal, .989 (95% CI = .980–.994) in left parietal, .983 (95% CI = .970–.990) in right parietal, .992 (95% CI = .985–.995) in left occipital, and .982 (95% CI = .968–.990) in right occipital (all p < .00001). Significance: We generated, trained, validated, and made publicly available a CNN that achieves a near‐perfect correlation with a neuroradiologist gold standard quantification of tuber burden, allows for objective tuber segmentation, and increases rigor and reproducibility in TSC research across institutions.

Sensory processing as a neurological construct is the perception and interpretation of sensory information from both the body and the environment. Disruptions to sensory processing adversely impact daily functioning. One type of disruption that is particularly interesting is altered sensory modulation, leading to hypersensitivity or hyposensitivity, which are common in many neurodevelopmental and psychiatric conditions such as autism spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer’s, and schizophrenia. Here we aim to identify modality-specific and cross-modality brain networks involved in altered auditory and somatosensory processing. A systematic review identified 61 patients with new-onset sensory alterations following focal brain injury. Lesions were traced and combined with resting-state data from 1000 healthy controls to generate normative lesion connectivity maps. The specificity of our cohort’s lesion-connectivity compared to lesions associated with 22 other neuropsychiatric symptoms was assessed with voxel-wise two-sample t-tests performed with the FSL Permutation Analysis of Linear Models tool (family-wise error P < 0.05). A conjunction analysis against lesions associated with hallucination was conducted by binarizing and multiplying one-sample T-test maps to identify common lesion-connections between the conditions. Modality-specific networks were connected to their unimodal cortices and the cerebellum. Overall, lesions associated with cross-modality sensitivity changes had convergent connections to the substantia nigra, medial orbitofrontal cortex, and cerebellum (Lobule V, medial Lobule VIIIa). Subgroup analysis by direction revealed that lesions causing decreased sensitivity were connected to lobule X, in addition to the aforementioned cerebellar regions, while those causing increased sensitivity were only connected to medial V and bilateral V. Regardless of directionality, 90% of lesions exhibited connections to bilateral Lobule V. Conjunction analysis with hallucinations revealed common lesion-connections to cerebellar vermis and frontal pole. Our analysis identified significant lesion-connections to the substantia nigra, medial orbitofrontal cortex, and cerebellum—highlighting these key regions in cross-modality sensory processing. These findings emphasize the role of higher cognitive functions in sensory integration and suggest potential targets for neuromodulation to improve sensory processing.

Structural brain imaging is increasingly introduced as evidence in criminal trials. A key imaging abnormality identified in criminal populations is alteration to the right uncinate fasciculus but it remains unclear whether these changes play a causal role in criminal behavior. Lesion studies of acquired criminality offer the opportunity to assess the causal role of focal disruption of specific white matter connections in criminal behavior. We studied lesion locations of focal brain damage associated with new onset criminal behavior compared to lesions associated with 21 diverse neuropsychiatric symptoms. First, we analyzed the intersection of lesion locations with an atlas-based right uncinate fasciculus. Second, we assessed the intersection of lesion locations with all white matter tracts from this atlas. Third, we performed a connectome-based analysis of all possible white matter connections with each lesion location, without a priori assumptions regarding specific tracts. We repeated all analyses limited to subjects who committed violent crimes. Lesions associated with criminality intersected the right uncinate more than lesions associated with other neuropsychiatric symptoms (p = 4.78 × 10⁻⁸). Compared to other tracts, the right uncinate fasciculus was the tract most strongly associated with lesion-induced criminality followed by the forceps minor. An unbiased connectome-based analysis confirmed these findings. Among subjects who committed violent crimes the right uncinate was the key tract identified. Lesions associated with criminality intersect the right uncinate fasciculus more than other lesions and more than other white matter tracts. Damage to the right uncinate may play a causal role in criminal behavior, especially violent crime.

Background: Visual mental imagery, the ability to volitionally form perceptual representations without corresponding external stimuli, allows reliving of past events, solving problems and imagining the future. The absence of visual mental imagery, called aphantasia, has recently been recognized to occur in about 1% of the general population but the cause is uncertain. By studying rare cases of acquired aphantasia we can identify regions that when injured cause loss of visual mental imagery. Methods: We analyzed aphantasia lesions, identified from case reports by systematic review, and previously studied control lesions causing other neuropsychiatric symptoms (n=887). The network of brain regions connected to each lesion location was computed using resting-state functional connectivity from healthy subjects (n=1000). First, we tested the connectivity of aphantasia lesions and controls to the fusiform imagery node , a region in the ventral visual pathway which is active during visual mental imagery tasks. Then, we performed a data-driven analysis assessing whole brain lesion connectivity that was sensitive (100% overlap) and specific (family-wise error pfusiform imagery node . Connectivity to this region was both sensitive (100% overlap) and specific (family-wise error pfusiform imagery node is a key brain region involved in visual mental imagery and offers clinical insight into which locations of brain injury are likely to cause aphantasia.