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Response to clozapine in treatment resistant schizophrenia is related to alterations in regional cerebral blood flow.
PET and SPECT studies in treatment-resistant schizophrenia (TRS) have revealed significant alterations in regional cerebral blood flow (CBF) during clozapine treatment, which may vary according to the clinical response. Here, we used the more recent MRI approach of arterial spin labelling (ASL) to evaluate regional CBF in participants with TRS (N = 36) before starting treatment with clozapine compared to in healthy volunteers (N = 16). We then compared CBF in the TRS group, before and after 12 weeks of treatment with clozapine (N = 24); and examined the relationship of those differences against changes in Positive and Negative Syndrome Scale for Schizophrenia (PANSS) scores over the treatment period. We observed widespread reductions in CBF in TRS compared to in healthy volunteers (p
Changes in immunoglobulin levels during clozapine treatment in schizophrenia.
BACKGROUND AND HYPOTHESIS: Use of clozapine in treatment-resistant schizophrenia is often limited due to risk of adverse effects. Cross-sectional associations between clozapine treatment and low immunoglobulin levels have been reported, however prospective studies are required to establish temporal relationships. We tested the hypothesis that reductions in immunoglobulin levels would occur over the first 6 months following initiation of clozapine treatment. Relationships between immunoglobulin levels and symptom severity over the course of clozapine treatment were also explored. DESIGN: This prospective observational study measured immunoglobulin (Ig) levels (A, M and G) in 56 patients with treatment-resistant schizophrenia at 6-, 12- and 24-weeks following initiation with clozapine. Clinical symptoms were also measured at 12 weeks using the positive and negative syndrome scale (PANSS). RESULTS: IgA, IgG and IgM all decreased during clozapine treatment. For IgA and IgG the reduction was significant at 24 weeks (IgA: β = -32.66, 95% CI = -62.38, -2.93, p = 0.03; IgG: β = -63.96, 95% CI = -118.00, -9.31, p = 0.02). For IgM the reduction was significant at 12 and 24 weeks (12 weeks: β = -23.48, 95% CI = -39.56, -7.42, p = 0.004; 24 weeks: β = -33.12, 95 %CI = -50.30, -15.94, p = <0.001). Reductions in IgA and IgG during clozapine treatment were correlated with reductions in PANSS-total over 12 weeks (n = 32, IgA r = 0.59, p = 0.005; IgG r = 0.48, p = 0.03). CONCLUSIONS: The observed reductions in immunoglobulin levels over six months of clozapine treatment add further evidence linking clozapine to secondary antibody deficiency. Associations between Ig reduction and symptom improvement may however indicate that immune mechanisms contribute to both desirable and undesirable effects of clozapine.
BIANCA-MS: An optimized tool for automated multiple sclerosis lesion segmentation.
In this work we present BIANCA-MS, a novel tool for brain white matter lesion segmentation in multiple sclerosis (MS), able to generalize across both the wide spectrum of MRI acquisition protocols and the heterogeneity of manually labeled data. BIANCA-MS is based on the original version of BIANCA and implements two innovative elements: a harmonized setting, tested under different MRI protocols, which avoids the need to further tune algorithm parameters to each dataset; and a cleaning step developed to improve consistency in automated and manual segmentations, thus reducing unwanted variability in output segmentations and validation data. BIANCA-MS was tested on three datasets, acquired with different MRI protocols. First, we compared BIANCA-MS to other widely used tools. Second, we tested how BIANCA-MS performs in separate datasets. Finally, we evaluated BIANCA-MS performance on a pooled dataset where all MRI data were merged. We calculated the overlap using the DICE spatial similarity index (SI) as well as the number of false positive/negative clusters (nFPC/nFNC) in comparison to the manual masks processed with the cleaning step. BIANCA-MS clearly outperformed other available tools in both high- and low-resolution images and provided comparable performance across different scanning protocols, sets of modalities and image resolutions. BIANCA-MS performance on the pooled dataset (SI: 0.72 ± 0.25, nFPC: 13 ± 11, nFNC: 4 ± 8) were comparable to those achieved on each individual dataset (median across datasets SI: 0.72 ± 0.28, nFPC: 14 ± 11, nFNC: 4 ± 8). Our findings suggest that BIANCA-MS is a robust and accurate approach for automated MS lesion segmentation.
The representation of priors and decisions in the human parietal cortex.
Animals actively sample their environment through orienting actions such as saccadic eye movements. Saccadic targets are selected based both on sensory evidence immediately preceding the saccade, and a "salience map" or prior built-up over multiple saccades. In the primate cortex, the selection of each individual saccade depends on competition between target-selective cells that ramp up their firing rate to saccade release. However, it is less clear how a cross-saccade prior might be implemented, either in neural firing or through an activity-silent mechanism such as modification of synaptic weights on sensory inputs. Here, we present evidence from magnetoencephalography for 2 distinct processes underlying the selection of the current saccade, and the representation of the prior, in human parietal cortex. While the classic ramping decision process for each saccade was reflected in neural firing rates (measured in the event-related field), a prior built-up over multiple saccades was implemented via modulation of the gain on sensory inputs from the preferred target, as evidenced by rapid frequency tagging. A cascade of computations over time (initial representation of the prior, followed by evidence accumulation and then an integration of prior and evidence) provides a mechanism by which a salience map may be built up across saccades in parietal cortex. It also provides insight into the apparent contradiction that inactivation of parietal cortex has been shown not to affect performance on single-trials, despite the presence of clear evidence accumulation signals in this region.
Dissociable mechanisms of information sampling in prefrontal cortex and the dopaminergic system
Recently, neuroscientists have become increasingly interested in studying the interactions between information sampling and choice and the mechanisms underlying these. In machine learning, introducing intrinsic rewards for exploration has been found to greatly improve artificial agents’ performance on ‘hard exploration’ problems. There is evidence that humans are intrinsically driven to sample both information that has no direct impact on reward outcome as well as information that reduces uncertainty on upcoming decisions. Recent findings from studies using a range of information sampling tasks suggest a functional dissociation between more posterior and anterior regions of prefrontal cortex (PFC). Specifically, pre-supplementary motor area (pre-SMA) and dorsal anterior cingulate cortex (dACC) are involved in decisions to sample more information to guide upcoming decisions, whereas the more anterior ventromedial prefrontal cortex (vmPFC), encodes the value of upcoming information. We argue that to effectively study information sampling in humans, the behavioral tasks we use must better reflect the large state space available to humans in real life. This, however, is challenging due to the complex model of the world humans have access to when choosing where to sample next.
Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks.
Many studies report atypical responses to sensory information in autistic individuals, yet it is not clear which stages of processing are affected, with little consideration given to decision-making processes. We combined diffusion modelling with high-density EEG to identify which processing stages differ between 50 autistic and 50 typically developing children aged 6-14 years during two visual motion tasks. Our pre-registered hypotheses were that autistic children would show task-dependent differences in sensory evidence accumulation, alongside a more cautious decision-making style and longer non-decision time across tasks. We tested these hypotheses using hierarchical Bayesian diffusion models with a rigorous blind modelling approach, finding no conclusive evidence for our hypotheses. Using a data-driven method, we identified a response-locked centro-parietal component previously linked to the decision-making process. The build-up in this component did not consistently relate to evidence accumulation in autistic children. This suggests that the relationship between the EEG measure and diffusion-modelling is not straightforward in autistic children. Compared to a related study of children with dyslexia, motion processing differences appear less pronounced in autistic children. Exploratory analyses also suggest weak evidence that ADHD symptoms moderate perceptual decision-making in autistic children.
Examining memory reconsolidation as a mechanism of nitrous oxide's antidepressant action.
There is an ongoing need to identify novel pharmacological agents for the effective treatment of depression. One emerging candidate, which has demonstrated rapid-acting antidepressant effects in treatment-resistant groups, is nitrous oxide (N2O)-a gas commonly used for sedation and pain management in clinical settings and with a range of pharmacological effects, including antagonism of NMDA glutamate receptors. A growing body of evidence suggests that subanaesthetic doses of N2O (50%) can interfere with the reconsolidation of maladaptive memories in healthy participants and across a range of disorders. Negative biases in memory play a key role in the onset, maintenance, and recurrence of depressive episodes, and the disruption of affective memory reconsolidation is one plausible mechanism through which N2O exerts its therapeutic effects. Understanding N2O's mechanisms of action may facilitate future treatment development in depression. In this narrative review, we introduce the evidence supporting an antidepressant profile of N2O and evaluate its clinical use compared to other treatments. With a focus on the specific memory processes that are thought to be disrupted in depression, we consider the effects of N2O on memory reconsolidation and propose a memory-based mechanism of N2O antidepressant action.
Disentangling the component processes in complex planning impairments following ventromedial prefrontal lesions
Damage to ventromedial prefrontal cortex (vmPFC) in humans disrupts planning abilities in naturalistic settings. However, it is unknown which components of planning are affected in these patients, including selecting the relevant information, simulating future states, or evaluating between these states. To address this question, we leveraged computational paradigms to investigate the role of vmPFC in planning, using the board game task ‘Four-in-a-Row’ (18 lesion patients, 9 female; 30 healthy control participants, 16 female), and the simpler ‘Two-Step’ task measuring model-based reasoning (49 lesion patients, 27 female; 20 healthy control participants, 13 female). Damage to vmPFC disrupted performance in Four-in-a-Row compared to both control lesion patients and healthy age-matched controls. We leveraged a computational framework to assess different component processes of planning in Four-in-a-Row and found that impairments following vmPFC damage included shallower planning depth, and a tendency to overlook game-relevant features. In the ‘Two-Step’ task, which involves binary choices across a short future horizon, we found little evidence of planning in all groups, and no behavioural differences between groups. Complex yet computationally tractable tasks such as ‘Four-in-a-row’ offer novel opportunities for characterising neuropsychological planning impairments, which in vmPFC patients we find are associated with oversights and reduced planning depth.Significance StatementThe ability to plan in real-world settings is often disrupted after damage to ventromedial prefrontal cortex (vmPFC). However, real-world planning consists of many different cognitive processes, and it is uncertain which processes are disturbed by these lesions. Here we use rich computational models of planning to characterise behaviour in two planning tasks performed by patients with vmPFC damage and controls. VmPFC damage only affected behaviour in the more complex planning task, and behavioural modelling revealed this was associated with planning less far into the future and overlooking important features. These findings shed light on the neural mechanisms supporting complex planning, demonstrating how novel computational methods can strike the balance between task complexity and interpretability.
Probing Autism and ADHD subtypes using cortical signatures of the T1w/T2w-ratio and morphometry.
Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental conditions that share genetic etiology and frequently co-occur. Given this comorbidity and well-established clinical heterogeneity, identifying individuals with similar brain signatures may be valuable for predicting clinical outcomes and tailoring treatment strategies. Cortical myelination is a prominent developmental process, and its disruption is a candidate mechanism for both disorders. Yet, no studies have attempted to identify subtypes using T1w/T2w-ratio, a magnetic resonance imaging (MRI) based proxy for intracortical myelin. Moreover, cortical variability arises from numerous biological pathways, and multimodal approaches can integrate cortical metrics into a single network. We analyzed data from 310 individuals aged 2.6-23.6 years, obtained from the Province of Ontario Neurodevelopmental (POND) Network consisting of individuals diagnosed with ASD (n = 136), ADHD (n = 100), and typically developing (TD) individuals (n = 74). We first tested for differences in T1w/T2w-ratio between diagnostic categories and controls. We then performed unimodal (T1w/T2w-ratio) and multimodal (T1w/T2w-ratio, cortical thickness, and surface area) spectral clustering to identify diagnostic-blind subgroups. Linear models revealed no statistically significant case-control differences in T1w/T2w-ratio. Unimodal clustering mostly isolated single individual- or minority clusters, driven by image quality and intensity outliers. Multimodal clustering suggested three distinct subgroups, which transcended diagnostic boundaries, showing separate cortical patterns but similar clinical and cognitive profiles. T1w/T2w-ratio features were the most relevant for demarcation, followed by surface area. While our analysis revealed no significant case-control differences, multimodal clustering incorporating the T1w/T2w-ratio among cortical features holds promise for identifying biologically similar subsets of individuals with neurodevelopmental conditions.
Left-Right Brain-Wide Asymmetry of Neuroanatomy in the Mouse Brain.
Left-right asymmetry of the human brain is widespread through its anatomy and function. However, limited microscopic understanding of it exists, particularly for anatomical asymmetry where there are few well-established animal models. In humans, most brain regions show subtle, population-average regional asymmetries in thickness or surface area, alongside a macro-scale twisting called the cerebral petalia in which the right hemisphere protrudes anteriorly past the left. Here, we ask whether neuroanatomical asymmetries can be observed in mice, leveraging 6 mouse neuroimaging cohorts from 5 different research groups (∼3,500 animals). We found an anterior-posterior pattern of volume asymmetry with anterior regions larger on the right and posterior regions larger on the left. This pattern appears driven by similar trends in surface area and positional asymmetries, with the results together indicating a small brain-wide twisting pattern, similar to the human cerebral petalia. Furthermore, the results show no apparent relationship to known functional asymmetries in mice, emphasizing the complexity of the structure-function relationship in brain asymmetry. Our results recapitulate and extend previous patterns of asymmetry from two published studies as well as capture well-established, bilateral male-female differences in the mouse brain as a positive control. By establishing a signature of anatomical brain asymmetry in mice, we aim to provide a foundation for future studies to probe the mechanistic underpinnings of brain asymmetry seen in humans - a feature of the brain with extremely limited understanding.
Host genetics maps to behaviour and brain structure in developmental mice.
Gene-environment interactions in the postnatal period have a long-term impact on neurodevelopment. To effectively assess neurodevelopment in the mouse, we developed a behavioural pipeline that incorporates several validated behavioural tests to measure translationally relevant milestones of behaviour in mice. The behavioral phenotype of 1060 wild type and genetically-modified mice was examined followed by structural brain imaging at 4 weeks of age. The influence of genetics, sex, and early life stress on behaviour and neuroanatomy was determined using traditional statistical and machine learning methods. Analytical results demonstrated that neuroanatomical diversity was primarily associated with genotype whereas behavioural phenotypic diversity was observed to be more susceptible to gene-environment variation. We describe a standardized mouse phenotyping pipeline, termed the Developmental Behavioural Milestones (DBM) Pipeline released alongside the 1000 Mouse Developmental Behavioural Milestones (1000 Mouse DBM) database to institute a novel framework for reproducible interventional neuroscience research.
Sex- and brain region-specific alterations in brain volume in germ-free mice.
Several lines of evidence demonstrate that microbiota influence brain development. Using high-resolution ex vivo magnetic resonance imaging (MRI), this study examined the impact of microbiota status on brain volume and revealed microbiota-related differences that were sex and brain region dependent. Cortical and hippocampal regions demonstrate increased sensitivity to microbiota status during the first 5 weeks of postnatal life, effects that were greater in male germ-free mice. Conventionalization of germ-free mice at puberty did not normalize brain volume changes. These data add to the existing literature and highlight the need to focus more attention on early-life microbiota-brain axis mechanisms in order to understand the regulatory role of the microbiome in brain development.
Lithium normalizes ASD-related neuronal, synaptic, and behavioral phenotypes in DYRK1A-knockin mice.
Dyrk1A deficiency is linked to various neurodevelopmental disorders, including developmental delays, intellectual disability (ID) and autism spectrum disorders (ASD). Haploinsufficiency of Dyrk1a in mice reportedly leads to ASD-related phenotypes. However, the key pathological mechanisms remain unclear and human DYRK1A mutations remain uncharacterized in mice. Here, we generated and studied Dyrk1a-knockin mice carrying a human ASD patient mutation (Ile48LysfsX2; Dyrk1a-I48K mice). These mice display severe microcephaly, social and cognitive deficits, dendritic shrinkage, excitatory synaptic deficits, and altered phospho-proteomic patterns enriched for multiple signaling pathways and synaptic proteins. Early chronic lithium treatment of newborn mutant mice rescues the brain volume, behavior, dendritic, synaptic, and signaling/synapse phospho-proteomic phenotypes at juvenile and adult stages. These results suggest that signaling/synaptic alterations contribute to the phenotypic alterations seen in Dyrk1a-I48K mice, and that early correction of these alterations by lithium treatment has long-lasting effects in preventing juvenile and adult-stage phenotypes.
Harmonizing two measures of adaptive functioning using computational approaches: prediction of vineland adaptive behavior scales II (VABS-II) from the adaptive behavior assessment system II (ABAS-II) scores.
BACKGROUND: Very large sample sizes are often needed to capture heterogeneity in autism, necessitating data sharing across multiple studies with diverse assessment instruments. In these cases, data harmonization can be a critical tool for deriving a single dataset for analysis. This can be done through computational approaches that enable the conversion of scores across various instruments. To this end, our study examined the use of analytical approaches for mapping scores on two measures of adaptive functioning, namely predicting the scores on the vineland adaptive behavior scales II (VABS) from the scores on the adaptive behavior assessment system II (ABAS). METHODS: Data from the province of Ontario neurodevelopmental disorders network were used. The dataset included scores VABS and the ABAS for 720 participants (autism n = 547, 433 male, age: 11.31 ± 3.63 years; neurotypical n = 173, 95 male, age: 12.53 ± 4.05 years). Six regression approaches (ordinary least squares (OLS) linear regression, ridge regression, ElasticNet, LASSO, AdaBoost, random forest) were used to predict VABS total scores from the ABAS scores, demographic variables (age, sex), and phenotypic measures (diagnosis; core and co-occurring features; IQ; internalizing and externalizing symptoms). RESULTS: The VABS scores were significantly higher than the ABAS scores in the autism group, but not the neurotypical group (median difference: 8, 95% CI = (7,9)). The difference was negatively associated with age (beta = -1.2 ± 0.12, t = -10.6, p