Federico Turkheimer

The paper investigates how spatial collinearity among PET receptor maps affects multivariate molecular-enriched network estimation and finds that univariate modelling is more reliable.

This study identifies structural brain deviations in post-COVID-19 patients using normative modelling and network analysis, linking them to TMPRSS2 expression and neural circuit disruptions.

This paper identifies altered dynamic brain states in Post-COVID-19 Syndrome using resting-state fMRI, showing reduced attentional states and increased limbic-DMN states linked to cognitive impairment and inflammation.

The paper integrates transcriptome-wide association studies with brain atlases to map polygenic risk onto structural brain changes in psychiatric disorders, finding significant correlations in some disorders but not others.

This study uses multimodal MRI to find altered brain perfusion and oxygen metabolism in PCS, linked to cognitive and emotional symptoms.

The paper uses kriging to show that task-induced brain activity increases can be predicted from activity decreases, revealing topographically determined antagonistic relationships.

DySCo introduces a framework for dynamic functional connectivity analysis, providing a unified theoretical approach and efficient algorithms for processing high-dimensional brain data.

This paper shows how heterogeneous spatial autocorrelation affects brain map comparisons and introduces a Bayesian spatial regression approach for valid statistical inference.

This study examines how anesthesia affects brain dynamics by analyzing ECoG data from monkeys, showing reduced long-range integration and preserved local synchrony under ketamine and propofol.

The paper uses REACT and normative modelling to analyze functional neurocircuits in neuropsychiatric patients, revealing transdiagnostic deviations in neurotransmitter systems and symptom overlaps.

The paper investigates the association between obesity and two brain systems using MRI data from UK Biobank participants, finding distinct structural and genetic relationships.

This paper extends the REACT method to ASL fMRI, showing it can detect molecular-enriched functional connectivity comparable to BOLD fMRI, with complementary information.

The paper assesses how normal cell contamination affects tumour SNP array analysis, showing signal confusion leads to misinterpretation of genotypes.

EiDA is a method for analyzing dynamic functional connectivity in resting-state fMRI data from ageing rats, revealing reduced phase-locking intensity and structural complexity with age.

This study investigates the effects of acute Methylene Blue administration on cerebral blood flow and metabolism in humans and rats, finding dose-dependent reductions in CBF and metabolic rates contrary to initial hypotheses.

This study uses diffusion MRI to detect neuroinflammation in vivo in rats after a lipopolysaccharide challenge, showing diffusivity changes correlate with microglial morphology.

The paper evaluates phase-based dynamic functional connectivity metrics in resting-state fMRI to identify reliable and interpretable measures of brain dynamics and their relationships.

This paper identifies neurotransmission-related functional connectivity biomarkers in chronic pain patients and shows their predictive value for analgesic response to duloxetine.

The paper uses imaging transcriptomics to link neuroimaging markers with transcriptomic and cellular correlates in the human brain, showing robust results across different parcellation methods.

This study examines GABAA and NMDA receptor density changes in MAM-treated rats and their behavioral correlates, finding reduced 5GABAAR and increased NMDA receptor densities linked to schizophrenia-like behaviors.

The paper develops a rat brain age prediction algorithm using MRI and validates it through a healthy lifestyle intervention, showing reduced brain ageing with environmental enrichment and dietary restriction.

This study identifies cortical morphometric similarity remodelling in chronic pain and links it to transcriptomic changes in glial and neuronal genes across multiple pain syndromes.

The paper identifies co-expression patterns between GABA receptor subunits and interneuron markers, linking them to in vivo PET radiotracer binding in human brain data.

The paper investigates serotonergic differences in ASD using fMRI and citalopram, finding a baseline group difference in 5-HTT-enriched response to facial expressions.

The paper introduces an active learning approach to efficiently approximate multiverse analyses in neuroimaging, demonstrating its ability to identify optimal analysis pipelines for predicting participant ages.

This study uses REACT to analyze how methylphenidate affects dopaminergic and noradrenergic circuits in the brain and links these effects to behavioral responses in a reinforcement-learning task.

This study uses dynamic 11C-PiB PET to show reduced cerebrospinal fluid clearance in Alzheimer’s disease and multiple sclerosis compared to healthy controls.