Biology subjects

Nour, M. M.

Publications and source records attributed to Nour, M. M..

3 recordsLinked to original sources

bioRxiv2026

Convergent Multimodal Evidence of Cortical Excitation-Inhibition Imbalance in Psychosis

Psychosis is increasingly understood as a disorder of disrupted cortical excitation-inhibition balance, yet robust non-invasive translational biomarkers remain lacking. The resting-state fMRI Hurst exponent (HE) and EEG aperiodic spectral exponent are promising complementary biomarkers, with lower values in each proposed to reflect a shift towards cortical hyperexcitability, but they have not been jointly examined in psychosis, and the spatial and molecular architecture of HE alterations remains poorly defined. We therefore tested for convergent systems-level signatures across independent cohorts and modalities, using resting-state fMRI (107 patients, 53 controls) and EEG (547 patients, 363 controls). Whole-brain and regional HE were estimated using wavelet methods, and EEG aperiodic exponents were quantified using spectral parameterisation. Compared with healthy controls, individuals with psychosis showed reduced whole-brain HE and widespread regional reductions. Regional HE case-control differences were associated with cortical gene-expression patterns, with enrichment for potassium channel and GABA receptor pathways, and correlated with noradrenergic, muscarinic, serotonergic, glutamatergic and dopaminergic receptor density maps, but not with cortical thickness or symptom or cognitive measures. In the independent EEG cohort, psychosis was similarly associated with a reduced aperiodic spectral exponent. Together, these findings provide cross-modal evidence for altered cortical resting-state dynamics in psychosis, consistent with a shift towards cortical hyperexcitability. Integration with receptor-density and transcriptomic maps implicates biologically plausible molecular pathways and supports HE and EEG aperiodic activity as scalable translational biomarkers in psychosis.

neuroscience↗

bioRxiv2025

Dopamine drives a positive reward bias on human reinforcement learning

Formal theories of reinforcement learning (RL) prescribe a clearly defined function for dopamine, namely modulating learning via reward prediction errors (RPEs). Yet, empirical evidence in humans remains scarce, and recent advances introducing noisy RL cast doubt on a simple one-to-one mapping between neurotransmitters and computational mechanisms. Here, we detail a double-blind, placebo-controlled, randomised pharmacological study using the dopamine precursor L-DOPA, while healthy volunteers performed a volatile two-armed bandit task. Behaviourally, L-DOPA decreased switching behaviour following below-average rewards. Algorithmic RL modelling of human behaviour supported a dual effect of L-DOPA on the rate and precision of learning. By leveraging recurrent neural networks (RNNs) as implementational models of RL, we explain this dual effect through a single inference-time modulation, whereby L-DOPA triggers a positive reward bias at the input of the recurrent layer that implements RL. Our findings highlight a unifying mechanism at the implementation level that explain seemingly disparate algorithmic effects of dopamine.

neuroscience↗

bioRxiv2024

The relationship between brain activation and mitochondrial complex I protein levels during cognitive function in healthy humans: an BCPP-EF PET and functional MRI study of task switching

Mitochondrial complex I is the largest enzyme complex in the respiratory chain and can be non-invasively measured using [18F]BCPP-EF positron emission tomography (PET). Neurological conditions associated with mitochondria complex I pathology are also associated with altered blood oxygen level dependent (BOLD) response and impairments in cognition. To evaluate the link between mitochondrial complex I, cognition and associated neural activity, 23 cognitively healthy adults underwent a [18F]BCPP-EF PET scan and a functional magnetic resonance imaging (fMRI) scan during which they performed a task switching exercise. We found significant positive associations between [18F]BCPP-EF volume of distribution (VT), which measures mitochondrial complex I levels and the task switching fMRI response (Partial Least Squares (PLS) Canonical Analysis (CA), first component r=0.51, p=0.03). Exploratory Pearsons correlations showed significant positive associations between mitochondrial complex I levels and the fMRI response in regions including the dorsolateral prefrontal cortex (r=0.61, p=0.0019), insula (r=0.46, p=0.0264) parietal-precuneus (r=0.51, p=0.0139) and anterior cingulate cortex (r=0.45, p=0.0293). Mitochondrial complex I levels across task-relevant regions were also predictive of task switching accuracy (PLS-Regression (PLS-R), R2=0.48, RMSE=0.154, p=0.011) and of switch cost (PLS-R, R^2=0.38, RMSE=0.07, p=0.048). Our findings suggest that higher mitochondrial complex I levels may underlie an individuals ability to exhibit a stronger BOLD response during task switching and are predictive of better task switching performance. This provides the first evidence linking the BOLD response with mitochondrial complex I and suggests a possible biological mechanism for aberrant BOLD response in conditions associated with mitochondrial complex I dysfunction, that should be tested in future studies.

neuroscience↗