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Dagher, A.

Publications and source records attributed to Dagher, A..

At least 19 recordsLinked to original sources

NEURAL CORRELATES OF SUBJECTIVE FOOD VALUATION IN THE CONTEXT OF BARIATRIC SURGERY

Objective: To examine changes in the neural valuation of high- versus low-calorie stimuli following bariatric surgery and determine whether these changes relate to weight loss at 24 months. Methods: Adults undergoing bariatric surgery completed fMRI scans before surgery and at 4, 12 and 24 months post-surgery while performing the Becker-DeGroot-Marschak auction task to assess willingness-to-pay (WTP) for food stimuli. Linear mixed-effect models tested longitudinal changes in WTP-related blood oxygen level-dependent (BOLD) associations and their interactions with total weight loss at 24 months. Results: WTP for high-calorie foods decreased significantly after surgery, whereas valuation of low-calorie foods remained stable. At 4 months, WTP-BOLD associations for high- versus low-calorie stimuli were enhanced within the frontoparietal control network and right lateral orbitofrontal cortex relative to pre-surgery. These early postoperative changes did not correlate with 24-month weight loss. Instead, greater 24-month weight loss correlated with both pre-surgical and long-term changes (24 months versus pre-surgery) in WTP-BOLD associations within the precuneus, inferior parietal cortex and visual cortex. Conclusion: Bariatric surgery induces early reductions in the valuation of high-calorie foods, potentially through enhanced cognitive control and aversive processing. However, long-term weight-loss success appears more strongly related to trait-like neural differences in self-referential and attentional processing.

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Cerebral vasculature shapes the spatial patterning of brain metastases

Primary cancer cells that originate in diverse tissues in the body can spread to the brain through various physiological pathways and form metastatic tumors. The spatial patterning of brain metastases is highly stereotyped across individuals, but the physiological factors that confer regional vulnerability to tumor colonization are poorly understood. Here we map the brain metastases associated with primary breast cancer, lung cancer, and malignant melanoma to the multiscale organization of the brain. We analyze structural magnetic resonance imaging (MRI) data from more than 2, 300 cancer patients with approximately 10, 000 brain metastases to estimate metastatic frequency maps. We then examine whether transcriptional (microarray profiling), functional (functional MRI), and vascular (arterial spin labeling) features can predict the spatial pattern of each brain metastasis type. Our analyses highlight vascular anatomy as an integral determinant of metastatic patterning, particularly in breast and lung cancers. We find arterial border-zones as sites of elevated vulnerability to metastatic invasion. These areas, characterized by slow flow and small-caliber vessels, create a hemodynamic environment that favors the arrest and extravasation of circulating tumor cells. Together, these results provide quantitative support for the long-standing hypothesis that vascular architecture and its biomechanical properties constrain metastatic seeding in the brain. Identifying vascular topology as a key determinant of metastatic patterning suggests that systemic vascular and metabolic factors may contribute to metastatic risk.

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Music-to-My-Brain: Modulation of Reward System Activity via Musical Neurofeedback

Music robustly engages the human reward system, yet whether this engagement can be harnessed for volitional self-neuromodulation remains unknown. We developed a musical neurofeedback approach that enables individuals to control a validated, fMRI-informed EEG marker of ventral striatal activity. Personalized pleasurable music served as feedback, becoming increasingly rewarding through acoustic manipulation as regulation improved, thereby creating a positive feedback loop. Across three double-blind, sham-controlled studies (N=80; two with repeated training), contingent neurofeedback enabled participants to upregulate this EEG signal reflecting ventral striatal activity; in studies with repeated training, this learning generalized to no-feedback contexts. In the neurofeedback (but not sham) group, regulation success correlated with self-reported hedonic capacity, indicating behavioral relevance. Pre-post fMRI further showed that improvements in ventral striatal BOLD self-regulation were associated with EEG-based regulation performance, supporting the EEG measure as a marker of ventral striatal modulation. Mechanistically, neurofeedback training enhanced functional connectivity between right auditory cortex and ventral striatum during listening to trained music, with stronger effects in the neurofeedback than in the sham group, demonstrating experience-dependent modification of auditory-reward pathways. Together, these findings reveal a mechanism for music-based reward self-regulation and offer a potential scalable, personalized approach for targeting reward dysfunction such as anhedonia.

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Comparative lifespan trajectories of brain energy metabolism in human and macaque

The brains extraordinary energy demands are met by a suite of metabolic pathways that selectively appropriate glucose across development, yet how this metabolic strategy changes across the lifespan and whether it is conserved across species remains incompletely understood. We previously mapped five core energy metabolism pathways across the human cortex and lifespan, revealing a fundamental dichotomy between anabolic and energy-producing pathway expression: the pentose phosphate pathway, which contributes to biomass, peaks prenatally, while glycolysis, the TCA cycle, and oxidative phosphorylation rise postnatally. Here, we extend the analysis to the rhesus macaque and show that the prenatal-to-postnatal transition is similar across the two species. Using the MitoCarta3.0 annotation framework, we further identify two consistent mitochondria-specific programs: a progressive decline in mitochondrial genome maintenance pathways, and a postnatal rise in mitochondrial energy production and substrate utilization, replicated across human and macaque. Extending to mouse, rat, and chicken, we find this shifting metabolic strategy is a conserved feature of vertebrate brain development. Finally, we map the cortical expression of mitochondria-localized pathway genes in the adult human cortex, finding that the anabolic-oxidative dichotomy follows in the mature brain. Together, these findings provide a comparative transcriptomic framework for studying brain energy metabolism across the lifespan.

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Spatial organization of AQP4 channels in the human brain: links with perfusion, edema, and disease vulnerability

Aquaporin-4 (AQP4) water channels support the glymphatic system, a brain-wide pathway that clears cerebral waste products. Despite its importance, the whole-brain organization of this system in humans remains underexplored. Here we use AQP4 gene expression as a molecular anchor to reconstruct a whole-brain glymphatic-related topography and link it to vascular physiology, edema, and neurode-generative vulnerability. We find that AQP4 expression is highly organized across the brain, peaking in subcortical, ventral, and periventricular territories, consistent with a clearance axis near cerebrospinal fluid reservoirs and perivascular interfaces. Linking AQP4 expression to vascular organization, we find that AQP4-enriched regions show lower normative blood perfusion and lower vein density, suggesting that this axis is not simply explained by vascular supply or large-vessel anatomy. Turning to neurodegeneration, we find that atrophy patterns across multiple neurodegenerative diseases co-localize with AQP4 expression--most strongly for tau and TDP-43 proteinopathies--and high-atrophy regions lie close to AQP4 hotspots in both anatomical space and structural connectome space. Furthermore, incorporating normative PET markers of neuroinflammation typically strengthens the spatial alignment between AQP4 expression and disease atrophy, suggesting that inflammatory tone and glymphatic-related architecture jointly shape vulnerability. Finally, we show that peritumoral edema is most frequent in AQP4-enriched regions and is further shaped by regional inflammatory tone. Collectively, this work highlights a whole-brain glymphatic organization that relates to diverse aspects of brain physiology and vulnerability.

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Joint multi-omics profiling of brain and body health in aging

The human brain and peripheral systems undergo coordinated changes throughout the lifespan, yet studies of aging have traditionally examined these systems as separate entities. Here we ask how brain health relates to peripheral biomarkers of bodily health including body mass index, blood pressure, and blood biochemistry results. We use partial least squares analysis to identify generalizable patterns of covariance between multi-modal neuroimaging data (structural, functional, diffusion, and arterial spin labeling MRI), demographic, and peripheral physiological markers in two large-scale deeply phenotyped datasets: the Human Connectome Project-Aging and UK Biobank. This data-driven pattern learning approach identifies two principal axes of brain-body associations in both biological sex groups. The first axis is driven by the dominant contribution of age. Across multiple brain measures, aging is associated with loss of brain structural integrity and cerebral vascular dysfunction. The second axis is driven by metabolic features, characterized by low high-density lipoprotein cholesterol, elevated body mass index, blood pressure, glycosylated hemoglobin, insulin, glucose, and alanine aminotransferase, and reduced cerebral blood perfusion. Finally, we show that deviations from a healthy metabolic profile are linked to cognitive deficits, particularly in females. Our study contributes to development of comprehensive translatable biomarkers for brain health assessment, and highlights the importance of metabolic health as a determinant of brain health.

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In vivo and in silico alpha-synuclein propagation dynamics: The role of genotype, epicentre, and connectivity

Neurodegeneration observed in synucleinopathies, like Parkinsons disease (PD), are hypothesized to be a consequence of the progressive accumulation and spread of misfolded alpha-synuclein (aSyn) throughout the brain. Here, we study the generalizability of this hypothesis across multiple biologically-relevant factors including genotype, aSyn species, and regional vulnerability (i.e.: does the introduction of aSyn into different brain regions have a similar impact) using a detailed longitudinal brain (using magnetic resonance imaging; [MRI]) and behavioural approaches. We first examined wild-type and M83 A53T hemizygous transgenic (engineered to over-express human aSyn) C57BL/6 x C3H mice receiving striatal inoculation with human or mouse preformed fibrils (PFFs) (n=89 mice at the last time point; n=687 MRI). Longitudinal analyses demonstrated a time-dependent increase in network-like atrophy and motor deficits, generalized across genotype and PFF species. We further derived latent dimensions relating brain-behaviour relationships revealing a pattern of sex- and genotype-relevant atrophy. Overall, atrophy was most prominent in M83 mice with mouse PFFs, while human PFFs or wild-type hosts showed attenuated effects. Changing the inoculation site to the hippocampus, a major connectivity hub, revealed differential regional vulnerability in the form of localized atrophy. Computational models previously validated in clinical PD further indicated regional vulnerability with increased predictive ability for atrophy patterns associated with striatal compared to hippocampal inoculation. Our findings reveal atrophy resulting from aSyn spreading is generalizable across genotype and PFF species, but not disease epicentres, emphasizing the role of regional vulnerability in disease progression.

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Genomic structural equation modeling of impulsivity and risk-taking traits reveals three latent factors distinctly associated with brain structure and development

BackgroundImpulsivity is a multifaceted transdiagnostic trait that emerges in childhood. Research has identified genetic loci and brain systems associated with different facets of impulsivity and risk-taking. However, how these genetic underpinnings overlap across different facets, and how they are associated with brain development during childhood remain unknown. MethodsUsing genomic structural equation modeling on 17 impulsivity and risk-taking traits, we identified latent factors capturing overlapping genetic architecture. We then calculated polygenic scores for these factors using Adolescent Brain Cognitive Development Study data (N = 4,142) and examined their associations with brain structure, development, and behavior in children aged 9-14 years. Finally, we tested whether socioeconomic status modulated the associations between latent polygenic scores and brain structures. ResultsWe identified three distinct genetic latent factors, which we label lack of self-control, reward drive, and sensation seeking. In children, polygenic scores for the three factors showed associations with distinct brain patterns: lack of self-control associated with reduced prefrontal cortical thickness, reward drive with increased subcortical cellular density, and sensation seeking with increased cortical surface area and white matter integrity. Longitudinally, lack of self-control predicted slower white matter development. The association between polygenetic score for lack of self-control and white matter mean diffusivity was modulated by socioeconomic status. ConclusionsWe identified three genetically distinct dimensions of impulsivity and risk-taking with separable neurodevelopmental origins. These genetic predispositions manifested as distinct brain patterns as early as ages 9-10. Environmental experience modulated some of the genetic effects on brain development.

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Brain network dynamics determine tau presence while regional vulnerability governs tau load in Alzheimer's disease

In Alzheimers disease (AD), tau pathology accumulates gradually throughout the brain, with clinical decline reflecting tau progression. A comprehensive understanding of, first, whether tau propagation is predominantly governed by connectome-based diffusion, regional vulnerability, or an interplay of both, and second, which types of brain connectivity or regional factors best explain tau propagation, remains crucial for advancing our understanding of AD progression. Here, we apply multi-scale, biologically informed disease progression simulations to human data, to disentangle the influence of local mechanisms on global tau progression patterns in AD. We find that whether tau reaches a brain region (presence) and how much tau accumulates there (load) are governed by different mechanisms. Tau presence patterns are highly consistent across the population, and can be largely explained through synaptic spread through white-matter networks and excitatory-inhibitory dynamics. Meanwhile tau load differs across people, and is driven by a combination of synaptic spread and intrinsic or extrinsic regional properties, including regional {beta}-amyloid load, MAPT gene expression and regional blood flow. Finally, while distinct tau patterns in the population could each be explained by established AD mechanisms, our models highlight a role of distinct brain networks (parietal networks in MTL-sparing AD tau subtype) and neurotransmitter systems (cholinergic system in posterior subtype). Together, this work suggests that network dynamics likely determine the sequence of regional tau progression, while individual-specific tissue-vulnerability factors influence regional tau load.

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Mapping energy metabolism systems in the human brain

Energy metabolism involves a network of biochemical reactions that generate ATP, utilizing substrates such as glucose and oxygen supplied via cerebral blood flow. Energy substrates are metabolized in multiple interrelated pathways that are cell- and organelle-specific. These pathways not only generate energy but are also fundamental to the production of essential biomolecules required for neuronal function and survival. How these complex biochemical processes are distributed over the cortex is integral to understanding the structure and function of the brain. Here, using curated gene sets and whole-brain transcriptomics, we generate maps of five fundamental energy metabolic pathways: glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, oxidative phosphorylation and lactate metabolism. We find consistent divergence between primarily energy-producing pathways and anabolic pathways, particularly in unimodal sensory cortices. We then explore the spatial alignment of these maps with multi-scale structural and functional attributes, including metabolic uptake, neurophysiological oscillations, cell type composition, laminar organization and macro-scale connectivity. Finally, we show that metabolic pathways exhibit unique developmental trajectories from the fetal stage to adulthood. The primary energy-producing pathways peak in late childhood, while the anabolic pentose phosphate pathway shows pronounced expression in the fetal stage and declines throughout life. Together, these results highlight the rich biochemical complexity of energy metabolism organization in the brain.

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Cell type transcriptomics reveal shared genetic mechanisms in Alzheimer's and Parkinson's disease

Historically, Alzheimers disease (AD) and Parkinsons disease (PD) have been investigated as two distinct disorders of the brain. However, a few similarities in neuropathology and clinical symptoms have been documented over the years. Traditional single gene-centric genetic studies, including GWAS and differential gene expression analyses, have struggled to unravel the molecular links between AD and PD. To address this, we tailor a pattern-learning framework to analyze synchronous gene co-expression at sub-cell-type resolution. Utilizing recently published single-nucleus AD (70,634 nuclei) and PD (340,902 nuclei) datasets from postmortem human brains, we systematically extract and juxtapose disease-critical gene modules. Our findings reveal extensive molecular similarities between AD and PD gene cliques. In neurons, disrupted cytoskeletal dynamics and mitochondrial stress highlight convergence in key processes; glial modules share roles in T-cell activation, myelin synthesis, and synapse pruning. This multi-module sub-cell-type approach offers insights into the molecular basis of shared neuropathology in AD and PD.

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Cerebral blood perfusion across biological systems and the human lifespan

Blood perfusion delivers oxygen and nutrients to all cells, making it a fundamental feature of brain organization. How cerebral blood perfusion maps onto micro-, meso- and macro-scale brain structure and function is therefore a key question in neuroscience. Here we analyze pseudo-continuous arterial spin labeling (ASL) data from 1 305 healthy individuals in the HCP Lifespan studies (5-100 years) to reconstruct a high-resolution normative cerebral blood perfusion map. At the cellular and molecular level, cerebral blood perfusion co-localizes with granular layer IV, biological pathways for maintenance of cellular relaxation potential and mitochondrial organization, and with neurotransmitter and neuropeptide receptors involved in vasomodulation. At the regional level, blood perfusion aligns with cortical arealization and is greatest in regions with high metabolic demand and resting-state functional hubs. Looking across individuals, blood perfusion is dynamic throughout the lifespan, follows microarchitectural changes in development, and maps onto individual differences in physiological changes in aging. In addition, we find that cortical atrophy in multiple neurodegenerative diseases (late-onset Alzheimers disease, TDP-43C, and dementia with Lewy bodies) is most pronounced in regions with lower perfusion, highlighting the utility of perfusion topography as an indicator of transdiagnostic vulnerability. Finally, we show that ASL-derived perfusion can be used to delineate arterial territories in a data-driven manner, providing insights into how the vascular system is linked to human brain function. Collectively, this work highlights how cerebral blood perfusion is central to, and interlinked with, multiple structural and functional systems in the brain.

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Mapping neuropeptide sigaling in the human brain

Neuropeptides are functionally diverse signaling molecules in the brain, regulating a wide range of basal bodily and cognitive processes. Despite their importance, the distribution and function of neu-ropeptides in the human brain remains underexplored. Here we comprehensively map the organization of human whole-brain neuropeptide receptors across multiple levels of description; from molecular and cellular embedding to mesoscale connectivity and macroscale cognitive specialization. Using gene transcription as a proxy, we reconstruct a topographic cortical and subcortical atlas of neuropeptide receptors for 38 neuropeptide receptors, across 14 different neuropeptide families. We find that most neuropeptide receptors are highly expressed either in cortex or subcortex, delineating an anatomical cortical-subcortical gradient. Neuropeptides preferentially co-localize with metabotropic neurotrans-mitters, suggesting a system-wide correspondence between slow-acting molecular signaling mechanisms. Mapping neuropeptide receptors and their cognate ligands onto white-matter connectomes, we demonstrate that specific neuropeptides families shape electrophysiological and haemodynamic interregional connectivity. To investigate the behavioural consequences of distributed neuropeptide systems, we apply meta-analytic decoding to neuropeptide maps and show a gradient of functions, from sensory-cognitive to reward and bodily functions. Finally, evolutionary analysis indicates extended positive selection for neuropeptides in early mammals, suggesting that refinement of neuropeptides coincides with the emergence of neocortex and higher cognitive function. Collectively, these results show that the neuropeptide receptors are highly organized across the human brain and closely intertwined with multiple features of brain structure and function.

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Right posterior theta reflects human parahippocampal phase resetting by salient cues during goal-directed navigation

Animal and computational work indicate that phase resetting of theta oscillations (4-12 Hz) in the parahippocampal gyrus (PHG) by salient events (e.g., reward, landmarks) facilitates the encoding of goal-oriented information during navigation. Although well-studied in animals, this mechanism has not been empirically substantiated in humans. In the present article, we present data from two studies (Study 1: asynchronous EEG-MEG | Study 2: simultaneous EEG-fMRI) to investigate theta phase resetting and its relationship to PHG BOLD activation in healthy adults (aged 18-34 years old) navigating a virtual T-maze to find rewards. In the first experiment, both EEG and MEG data revealed a burst of theta power over right-posterior scalp locations following feedback onset (termed right-posterior theta, RPT), and RPT power and measures of phase resetting were sensitive to the subjects spatial trajectory. In Experiment 2, we used probabilistic tractography data from the human connectome project to segment the anterior and posterior PHG based on differential connectivity profiles to other brain regions. This analysis resulted in a PHG subdivision consisting of four distinct anterior and two posterior PHG clusters. Next, a series of linear mixed effects models based on simultaneous EEG-fMRI data revealed that single-trial RPT peak power significantly predicted single-trial hemodynamic responses in two clusters within the posterior PHG and one in the anterior PHG. This coupling between RPT power and PHG BOLD was exclusive to trials performed during maze navigation, and not during a similar task devoid of the spatial context of the maze. These findings highlight a role of PHG theta phase resetting for the purpose of encoding salient information during goal-directed spatial navigation. Taken together, RPT during virtual navigation integrates experimental, computational, and theoretical research of PHG function in animals with human cognitive electrophysiology studies and clinical research on memory-related disorders such as Alzheimers disease.

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Network Spreading and Local Biological Vulnerability in Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease that predominantly targets the motor system. Spread of pathology is thought to be driven by both local vulnerability and network architecture. Namely, molecular and cellular features may confer vulnerability to specific neuronal populations, while synaptic contacts may also increase exposure to pathology in connected neuronal populations. However, these principles are typically studied in isolation and it remains unknown how local vulnerability and network spreading interact to shape cortical atrophy. Here we investigate how network structure and local biological features jointly shape the spatial patterning of atrophy in ALS. We analyze the Canadian ALS Neuroimaging Consortium (CALSNIC) dataset and estimate cortical atrophy using deformation-based morphometry (DBM). We find that structural connectivity closely aligns with the course of atrophy. Atrophy is also more likely to occur in regions that share similar transcriptomic, neurotransmitter receptor and metabolic profiles. We identify disease epicenters in motor cortex. Epicenter probability maps show transcriptomic enrichment for biological pathways involved in mitochondrial function as well as support cells, including endothelial cells and pericytes. Finally, individual differences in epicenter location correspond to individual differences in clinical and cognitive symptoms, and differentiate patient subtypes.

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Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation

Reward processing is essential for our mental-health and well-being. Here, we present the development and validation of a scalable fMRI-informed EEG model related to reward processing in the ventral-striatum (VS); a central reward circuit node. Simultaneous EEG/fMRI data were acquired from 17 healthy individuals listening to pleasurable music, and used to construct a one-class regression model for predicting the reward-related VS-BOLD signal using spectro-temporal features from the EEG. Validation analyses, applied on EEG/fMRI data from a different group (N=14), revealed that the EEG model predicted VS-BOLD activation from the simultaneous EEG to a greater extent than a model derived from another anatomical region. The VS-EEG-model was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating it functional relevance. These findings provide compelling evidence for the use of a scalable yet precise EEG-only probe of VS-originated reward processing, which could serve for process specific neruo-monitoring and -modulation.

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Interpretable brain decoding from sensations to cognition to action: graph neural networks reveal the representational hierarchy of human cognition

Inter-subject modeling of cognitive processes has been a challenging task due to large individual variability in brain structure and function. Graph neural networks (GNNs) provide a potential way to project subject-specific neural responses onto a common representational space by effectively combining local and distributed brain activity through connectome-based constraints. Here we provide in-depth interpretations of biologically-constrained GNNs (BGNNs) that reach state-of-the-art performance in several decoding tasks and reveal inter-subject aligned neural representations underpinning cognitive processes. Specifically, the model not only segregates brain responses at different stages of cognitive tasks, e.g. motor preparation and motor execution, but also uncovers functional gradients in neural representations, e.g. a gradual progression of visual working memory (VWM) from sensory processing to cognitive control and towards behavioral abstraction. Moreover, the multilevel representations of VWM exhibit better inter-subject alignment in brain responses, higher decoding of cognitive states, and strong phenotypic and genetic correlations with individual behavioral performance. Our work demonstrates that biologically constrained deep-learning models have the potential towards both cognitive and biological fidelity in cognitive modeling, and open new avenues to interpretable functional gradients of brain cognition in a wide range of cognitive neuroscience questions. HighlightsO_LIBGNN improves inter-subject alignment in task-evoked responses and promotes brain decoding C_LIO_LIBGNN captures functional gradients of brain cognition, transforming from sensory processing to cognition to representational abstraction. C_LIO_LIBGNNs with diffusion or functional connectome constraints better predict human behaviors compared to other graph architectures C_LI Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/510241v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@1b34a13org.highwire.dtl.DTLVardef@1c45ca2org.highwire.dtl.DTLVardef@9db47dorg.highwire.dtl.DTLVardef@1b4916d_HPS_FORMAT_FIGEXP M_FIG C_FIG Multilevel representational learning of cognitive processes using BGNN

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Cerebellar and cortico-striatal-midbrain contributions to reward-cognition processes and apathy within the psychosis continuum

Negative symptoms in the psychosis continuum are linked to impairments in reward processing and cognitive function. Processes at the interface of reward processing and cognition and their relation to negative symptoms remain little studied, despite evidence suggestive of integration in mechanisms and neural circuitry. Here, we investigated brain activation during reward-dependent modulation of working memory (WM) and their relationship to negative symptoms in subclinical and early stages of the psychosis continuum. We included 27 persons with high schizotypal personality traits and 23 patients with first episode psychosis as well as 27 healthy controls. Participants underwent functional magnetic resonance imaging while performing an established 2-back WM task with two reward levels (5 CHF vs. no reward), which allowed us to assess common reward-cognition regions through whole-brain conjunction analyses and to investigate relations with clinical scores of negative symptoms. As expected for behavior, reward facilitated performance while cognitive load diminished it. At the neural level, the conjunction of high reward and high cognitive load contrasts across the psychosis continuum showed increased hemodynamic activity in the thalamus and the cerebellar vermis. During high cognitive load, more severe apathy but not diminished expression in the psychosis continuum was associated with reduced activity in right lateral orbitofrontal cortex, midbrain, posterior vermal cerebellum, caudate and lateral parietal cortex. Our results suggest that hypoactivity in the cerebellar vermis and the cortical-striatal-midbrain-circuitry in the psychosis continuum relates to apathy possibly via impaired flexible cognitive resource allocation for effective goal pursuit.

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