Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology.

BACKGROUND: Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Population modelling, often referred to as normative modelling, provides a unified framework for studying age-specific and sex-specific divergences in brain development. METHODS: Here we used population modelling and a large, multi-site neuroimaging dataset (N = 4255 after quality control) to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of average brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD). RESULTS: We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume, that was localised to the superior temporal cortex, whereas individuals with ADHD showed more global increases in cortical thickness, but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only. CONCLUSIONS: These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

Brain tumour microstructure is associated with post-surgical cognition.

Brain tumour microstructure is potentially predictive of changes following treatment to cognitive functions subserved by the functional networks in which they are embedded. To test this hypothesis, intra-tumoural microstructure was quantified from diffusion-weighted MRI to identify which tumour subregions (if any) had a greater impact on participants' cognitive recovery after surgical resection. Additionally, we studied the role of tumour microstructure in the functional interaction between the tumour and the rest of the brain. Sixteen patients (22-56 years, 7 females) with brain tumours located in or near speech-eloquent areas of the brain were included in the analyses. Two different approaches were adopted for tumour segmentation from a multishell diffusion MRI acquisition: the first used a two-dimensional four group partition of feature space, whilst the second used data-driven clustering with Gaussian mixture modelling. For each approach, we assessed the capability of tumour microstructure to predict participants' cognitive outcomes after surgery and the strength of association between the BOLD signal of individual tumour subregions and the global BOLD signal. With both methodologies, the volumes of partially overlapped subregions within the tumour significantly predicted cognitive decline in verbal skills after surgery. We also found that these particular subregions were among those that showed greater functional interaction with the unaffected cortex. Our results indicate that tumour microstructure measured by MRI multishell diffusion is associated with cognitive recovery after surgery.

Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis.

Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study used sulcal patterns from structural images of the brain as the basis for classifying patients with schizophrenia from unaffected controls. Statistical, machine learning and deep learning techniques were sequentially applied as a demonstration of how a CAD system might be comprehensively evaluated in the absence of prior empirical work or extant literature to guide development, and the availability of only small sample datasets. Sulcal features of the entire cerebral cortex were derived from 58 schizophrenia patients and 56 healthy controls. No similar CAD systems has been reported that uses sulcal features from the entire cortex. We considered all the stages in a CAD system workflow: preprocessing, feature selection and extraction, and classification. The explainable AI techniques Local Interpretable Model-agnostic Explanations and SHapley Additive exPlanations were applied to detect the relevance of features to classification. At each stage, alternatives were compared in terms of their performance in the context of a small sample. Differentiating sulcal patterns were located in temporal and precentral areas, as well as the collateral fissure. We also verified the benefits of applying dimensionality reduction techniques and validation methods, such as resubstitution with upper bound correction, to optimize performance.

Tumour-infiltrated cortex participates in large-scale cognitive circuits.

The extent to which tumour-infiltrated brain tissue contributes to cognitive function remains unclear. We tested the hypothesis that cortical tissue infiltrated by diffuse gliomas participates in large-scale cognitive circuits using a unique combination of intracranial electrocorticography (ECoG) and resting-state functional magnetic resonance (fMRI) imaging in four patients. We also assessed the relationship between functional connectivity with tumour-infiltrated tissue and long-term cognitive outcomes in a larger, overlapping cohort of 17 patients. We observed significant task-related high gamma (70-250 Hz) power modulations in tumour-infiltrated cortex in response to increased cognitive effort (i.e., switch counting compared to simple counting), implying preserved functionality of neoplastic tissue for complex tasks probing executive function. We found that tumour locations corresponding to task-responsive electrodes exhibited functional connectivity patterns that significantly co-localised with canonical brain networks implicated in executive function. Specifically, we discovered that tumour-infiltrated cortex with larger task-related high gamma power modulations tended to be more functionally connected to the dorsal attention network (DAN). Finally, we demonstrated that tumour-DAN connectivity is evident across a larger cohort of patients with gliomas and that it relates to long-term postsurgical outcomes in goal-directed attention. Overall, this study contributes convergent fMRI-ECoG evidence that tumour-infiltrated cortex participates in large-scale neurocognitive circuits that support executive function in health. These findings underscore the potential clinical utility of mapping large-scale connectivity of tumour-infiltrated tissue in the care of patients with diffuse gliomas.

Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology.

Background: Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development. Methods: Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD). Results: We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only. Conclusions: These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

Insight, grey matter and cognitive function in first-onset psychosis

BACKGROUND: Several studies have suggested that neuropsychological and structural brain deficits are implicated in poor insight. Few insight studies however have combined neurocognitive and structural neuroanatomical measures. AIMS: Focusing on the ability to relabel psychotic symptoms as pathological, we examined insight, brain structure and neurocognition in first-onset psychosis.METHOD: Voxel-based magnetic resonance imaging data were acquired from 82 individuals with psychosis and 91 controls assessed with a brief neuropsychological test battery. Insight was measured using the Schedule for the Assessment of Insight. RESULTS: The principal analysis showed reduced general neuropsychological function was linked to poor symptom relabelling ability. A subsequent between-psychosis group analysis found those with no symptom relabelling ability had significant global and regional grey matter deficits primarily located at the posterior cingulate gyrus and right precuneus/cuneus. CONCLUSIONS: The cingulate gyrus (as part of a midline cortical system) along with right hemisphere regions may be involved in illness and symptom self-appraisal in first-onset psychosis.

Grey matter abnormalities in first-episode schizophrenia and affective psychosis.

BACKGROUND: Grey matter and other structural brain abnormalities are consistently reported in first-onset schizophrenia, but less is known about the extent of neuroanatomical changes in first-onset affective psychosis. AIMS: To determine which brain abnormalities are specific to (a) schizophrenia and (b) affective psychosis. METHOD: We obtained dual-echo (proton density/T2-weighted) magnetic resonance images and carried out voxel-based analysis on the images of 73 patients with first-episode psychosis (schizophrenia n=44, affective psychosis n=29) and 58 healthy controls. RESULTS: Both patients with schizophrenia and patients with affective psychosis had enlarged lateral and third ventricle volumes. Regional cortical grey matter reductions (including bilateral anterior cingulate gyrus, left insula and left fusiform gyrus) were evident in affective psychosis but not in schizophrenia, although patients with schizophrenia displayed decreased hippocampal grey matter and increased striatal grey matter at a more liberal statistical threshold. CONCLUSIONS: Both schizophrenia and affective psychosis are associated with volumetric abnormalities at the onset of frank psychosis, with some of these evident in common brain areas.

Different effects of typical and atypical antipsychotics on grey matter in first episode psychosis: the AESOP study

Typical antipsychotic drugs act on the dopaminergic system, blocking the dopamine type 2 (D2) receptors. Atypical antipsychotics have lower affinity and occupancy for the dopaminergic receptors, and a high degree of occupancy of the serotoninergic receptors 5-HT2A. Whether these different pharmacological actions produce different effects on brain structure remains unclear. We explored the effects of different types of antipsychotic treatment on brain structure in an epidemiologically based, nonrandomized sample of patients at the first psychotic episode. Subjects were recruited as part of a large epidemiological study (’SOP: aetiology and ethnicity in schizophrenia and other psychoses). We evaluated 22 drug-free patients, 32 on treatment with typical antipsychotics and 30 with atypical antipsychotics. We used high-resolution MRI and voxel-based methods of image analysis. The MRI analysis suggested that both typical and atypical antipsychotics are associated with brain changes. However, typicals seem to affect more extensively the basal ganglia (enlargement of the putamen) and cortical areas (reductions of lobulus paracentralis, anterior cingulate gyrus, superior and medial frontal gyri, superior and middle temporal gyri, insula, and precuneus), while atypical antipsychotics seem particularly associated with enlargement of the thalami. These changes are likely to reflect the effect of antipsychotics on the brain, as there were no differences in duration of illness, total symptoms scores, and length of treatment among the groups. In conclusion, we would like to suggest that even after short-term treatment, typical and atypical antipsychotics may affect brain structure differently.

The structural brain correlates of neurological soft signs in AESOP first-episode psychoses study

Patients with schizophrenia and related psychoses have an excess of minor neurological abnormalities (neurological soft signs of unclear neuropathological origin. These include poor motor coordination, sensory perceptual difficulties and difficulties in sequencing complex motor tasks. Neurological soft signs seem not to reflect primary tract or nuclear pathology. It still has to be established whether neurological soft signs result from specific or diffuse brain structural abnormalities. Studying their anatomical correlates can provide not only a better understanding of the aetiopathogenesis of soft signs, but also of the pathophysiology of schizophrenia. Suprisingly few studies have investigated the brain correlates of neurological soft signs. In the present study, we investigated the relationship between brain structure and neurological soft signs in an epidemiologically based sample of 77 first-episode psychosis patients. We used the Neurological Evaluation Scale for neurological assessment and high-resolution MRI and voxel based methods of image analysis to investigate brain structure. Higher rates of soft neurological signs (both motor and sensory) were associated with a reduction of grey matter volume of subcortical structures (putamen, globus pallidus and thalamus). Signs of sensory integration deficits were additionally associated with volume reduction in the cerebral cortex, including the precentral, superior and middle temporal, and lingual gyri. Neurological soft signs and their associated brain changes were independent of antipsychotic exposure. We conclude that neurological soft signs are associated with regional grey matter volume changes and that they may represent a clinical sign of the perturbed cortical-subcortical connectivity that putatively underlies psychotic disorders(AU)