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Janes, A.

Publications and source records attributed to Janes, A..

4 recordsLinked to original sources

Human striatal population state dynamics

Animal models reveal that striatal projection neurons (SPNs) fluctuate between discrete electrophysiological states with distinct levels of cortical interaction. These dynamics and their behavioral relevance remain uncharacterized in humans. Leveraging neurobiologically informed modeling of over 3 billion voxel-frame-wise striatal coactivation profiles with cortex in functional magnetic resonance imaging (fMRI), we identified population-level striatal states in humans resembling canonical SPN states that reorganized systematically with task demands, arousal and behavior. A background of low- and moderate-coactivation "down-like" and "up-like" striatal rest states with high transition reciprocity modulated task reaction times and reward reactivity. Meanwhile, sparse, disproportionately high-magnitude bursts of striatal coactivation with cortex, which emerged preferentially from the up-like rest state and whose cortical input composition varied with task context, tracked task engagement and arousal level. Findings bring a critical feature of corticostriatal neurobiology into systems-level view in humans and reveal a subthreshold state architecture whose balance encodes behaviorally relevant information.

neuroscience↗

Brain morphological pattern is associated with the presence, severity, and transition of transdiagnostic psychiatric disorders in preadolescents

Cognitive function, psychological processes, mental states, and behaviors are key dimensions of human subjective experience that separately relate to mental disorders across diagnostic categories. However, whether these dimensions are linked to common or distinct brain morphological patterns that convey risk or resilience for psychiatric disorders remains unclear. The current study is a longitudinal investigation on 11,875 youths from the Adolescent Brain Cognitive Development (ABCD) Study aged 9-10 years at baseline. A machine learning approach based on canonical correlation analysis was used to identify latent dimensional associations of cortical morphology (4 metrics: surface area, cortical and subcortical volume, cortical thickness, and sulcal/gyral depth) with multidomain behavioral assessments including cognitive scores and psychological measures indexing motivation, impulse control, mental states, and behaviors across a normative continuum from healthy to pathological. Across morphological measures, we identified a robust latent brain structural variate that correlated positively with cognitive performance and negatively with psychological measures indexing greater psychology. Notably, higher scores on this brain variate reflected larger cortical surface area and cortical volume--especially in the temporal gyri--together with a posterior-anterior gradient in cortical thickness, showing relatively greater thickness in occipital, parietal, and temporal cortices and lower thickness in cingulate and frontal regions. This brain variate and the related cognitive-psychological-behavioral variate remained stable at the 2-year follow-up, demonstrating temporal consistency. Importantly, the brain variate showed a dose-dependent relationship with the cumulative number of psychiatric diagnoses assessed concurrently and at 2-year follow-up, with lower brain variate scores being associated with higher numbers of comorbid diagnoses. In addition, the brain scores were associated with longitudinal transitions between healthy and diagnosed states over the 2-year study period, in which lower scores at baseline were associated with persistent psychiatric diagnoses whereas higher scores at baseline were associated with persistent healthy states, suggesting that the brain scores capture a vulnerability- resilience continuum for psychopathology. By revealing shared brain structural substrates across conventional diagnostic boundaries, these findings advance the neurodevelopmental understanding of psychiatric disorders and highlight the potential utility of morphology-informed approaches for early screening and intervention in youth.

developmental biology↗

Physiological Arousal as a Predominant Source of Individual Differences in Functional Brain Networks

Individual differences in brain network function and organization are promising targets for fMRI-based biomarkers in precision psychiatry, yet the sources of individual variability remain poorly understood. We show that arousal, assessed by systemic low-frequency oscillation (sLFO) amplitude in the fMRI signal, accounts for a substantial portion of variance in brain network properties (e.g.: R= 0.70 for default mode network (DMN)-dorsal attention connectivity; R= -0.63 for DMN dynamics). These relationships replicated across sessions, across independent samples, and when assessed with traditional arousal indices. Critically, associations persisted after sLFO denoising, indicating a genuine brain-physiology relationship rather than hemodynamic artifact. Pharmacological manipulation showed that drug-induced sLFO-assessed arousal changes were accompanied by corresponding shifts in network connectivity and dynamics. This work identifies arousal as a prominent determinant of variability in functional brain networks, providing a new perspective on brain-based individual differences while offering an approach to measure arousal directly from fMRI data.

neuroscience↗

Maturation of Dorsal Association Tracts during Preadolescence Links to Concurrent and Future Cognitive Performance and Transdiagnostic Psychopathology

Many psychiatric disorders begin during adolescence, coinciding with the rapid development of brain white matter (WM). However, it remains unclear whether deviations from normal WM maturation during this age period contribute to the development of psychopathology. In this study, we developed and validated normative models of brain age based on specific WM tracts using three large-scale developmental datasets (a total of [~]10,000 subjects). We found that tract-specific deviations in WM development of association and limbic/subcortical systems were linked to concurrent cognition and psychopathology. The spatial pattern of the association system aligned closely with distributions of high-order brain networks, and with mitochondrial content and respiratory capacity. The maturation of the association system contributed significantly to better cognitive performance assessed two or three years later. Importantly, delayed WM development especially in dorsal association tracts predicted psychiatric disorders across diagnoses and disorder onset over a 2-year follow-up. By identifying tract-specific WM development during preadolescence as a predictor of cognitive capacity and psychiatric disorder risks, this study provides a valuable framework for tracking individualized brain maturation and understanding the neurobiological underpinnings of cognitive performance and transdiagnostic psychopathology.

neuroscience↗