Michael J Breakspear

This paper identifies EEG factors linked to FDG-PET dementia phenotypes, showing slowing and rhythm changes correlate with specific neurodegenerative subtypes.

This study shows that dopamine compensates for amyloid-induced dysfunction in the default mode network to support learning in preclinical Alzheimer's disease.

This paper shows that excitability gradients in the hippocampus generate travelling waves and influence their interaction with the cortex, revealing directional asymmetry in communication.

This paper introduces BiSCA to detect nonlinearity in EEG data and finds that narrowband oscillations like Alpha and Mu rhythms exhibit significant nonlinear behavior, while broadband activity is linear and Gaussian.

The paper surveys neuroimaging researchers on definitions, usage, and evaluation of generative models, revealing both agreement and disagreement on criteria and methods.

This paper introduces a framework for geometry-constrained coupling between neural manifolds, showing how inter-manifold interactions reorganize dynamics and produce critical transitions in brain activity.

The paper investigates how heart rate influences large-scale brain network dynamics using EEG, fMRI, and HR data during emotional stimuli, finding both direct and obscured neural-cardiac links.

This study examines how FTLD and AD differentially affect cognitive mechanisms underlying creative idea generation, finding distinct patterns in semantic retrieval, memory, and context-dependent creativity.

This paper develops a geometrically constrained framework to map brain regions across species and shows geometry influences regional organization through patterning molecules.

This paper introduces eigenstrapping, a method to generate surrogate brain maps that preserve spatial autocorrelation while breaking map correlations, improving false positive control in brain map analysis.

This study identifies and addresses spurious correlations in surface-based fMRI data caused by uneven vertex spacing in processing pipelines.

The paper responds to criticisms of a previous study showing that geometric eigenmodes of the human cortex better reconstruct fMRI activity maps than connectome-derived eigenmodes.

The paper shows that multiscale neuronal activity patterns are preserved across species and scales, reconciling scale-dependent theories of brain function through self-similar scaling.

This paper introduces mode-based morphometry (MBM), a multiscale method for analyzing neuroanatomical variability, showing it is as valid or more reliable than traditional techniques for cortical thickness maps.

The paper analyzes brain-muscle networks during gait to show age-related reductions in neuromuscular connectivity and compensatory changes in individuals with impaired foot tactile sensitivity.

The paper addresses concerns about eigenmode reconstructions in a previous study, demonstrating how specificity is achieved through appropriate benchmarks.

This paper shows that brain function can be understood through geometric resonant modes rather than connectivity, revealing brain-wide dynamics in task-evoked activity.

The paper investigates how metabolic demands of the posteromedial default mode network (DMN) are influenced by task-positive networks during attention-demanding tasks.

The paper quantifies dynamic facial expressions under naturalistic conditions and identifies distinct spatiotemporal states that vary between individuals with melancholic depression.

This study shows that neuroimaging studies in clinical populations require hundreds, not thousands, of participants to achieve reproducible results due to larger effect sizes.

This paper introduces a method to detect cross-frequency coupling between brain areas using phase-linearity measurements, demonstrating its effectiveness on both simulated and real MEG data.

The paper examines cognitive and brain morphology changes from mid-life to older adulthood, finding age-related shifts in cognitive domains and sulcal width patterns.

This paper identifies critical-like bistable dynamics in the resting-state human brain, showing their functional and clinical significance across frequency bands.

The paper uses fMRI and computational modeling to show the anterior insula gates the interaction between motor planning and mirror systems during intentional versus incidental imitation.

This study investigates reduced brain flexibility in Parkinson's disease using magnetoencephalography, finding stereotyped dynamics and beta-band hypersynchronization linked to symptom severity.

The paper reveals the topographic organization of the human subcortex using resting-state fMRI data from 1000 adults, identifying four scales of organization and 27 new regions, and introduces a new subcortical atlas.

This study analyzes facial thermal responses to an emotional movie, finding significant correlations between thermal signals and emotional content, and introducing a novel analysis approach for facial IRI data.

The paper uses intracranial EEG to show that the temporal pole drives amygdala activity in response to emotional stimuli through theta-alpha oscillations modulating high gamma responses.

This paper develops a method to track functional brain age in preterm infants using EEG, showing it correlates strongly with postmenstrual age and predicts neurodevelopmental outcomes.

The paper demonstrates that each individual's brain has a converging optimal working point in The Virtual Brain model that predicts fMRI and EEG features, with inter-individual differences driven by structural connectivity.