Biology subjects

Argyelan, M.

Publications and source records attributed to Argyelan, M..

5 recordsLinked to original sources

bioRxiv2023

Effects of phase encoding direction on test-retest reliability of human functional connectome

The majority of human connectome studies in the literature based on functional magnetic resonance imaging (fMRI) data use either an anterior-to-posterior (AP) or a posterior-to-anterior (PA) phase encoding direction. However, whether and how phase encoding direction would affect test-retest reliability of functional connectome is unclear. Here, in a sample of healthy subjects with two sessions of fMRI scans separated by 12 weeks (two runs per session, one with AP, the other with PA), we tested the influence of phase encoding direction on global and nodal connectivity in the constructed brain networks. All data underwent the state-of-the-art Human Connectome Project (HCP) pipeline to correct for phase-encoding-related distortions before entering analysis. We found that at the global level, the PA scans showed significantly higher intraclass correlation coefficients (ICCs) for global connectivity compared with AP scans, which was particularly prominent when using the Seitzman-300 atlas (versus the CAB-NP-718 atlas). At the nodal level, regions most strongly affected by phase encoding direction were consistently mapped to the cingulate cortex and temporal lobe, with significantly higher ICCs during PA scans compared with AP scans, regardless of atlas. Further, we demonstrated that the observed reliability differences between phase encoding directions may relate to a similar effect on the reliability of temporal signal-to-noise ratio (tSNR) in the same regions (that PA scans were associated with higher reliability of tSNR than AP scans). Averaging the connectivity outcome from the AP and PA scans could slightly, but overall have limited value to boost the ICCs. These results were largely replicated in an independent, public dataset from the HCP-Early Psychosis (HCP-EP) study with a similar design but a much shorter scan session interval. Our findings suggest that phase encoding direction has significant effects on the reliability of connectomic estimates in fMRI studies. We urge that these effects need to be carefully considered in future neuroimaging designs, especially in longitudinal studies such as those related to neurodevelopment or clinical intervention.

neuroscience↗

bioRxiv2022

Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after Personalized Intrinsic Network Topography

BackgroundSpatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls using individualized connectivity profiles. MethodsWe utilized resting state and anatomical MRI data from n=406 participants (n = 203 SSD, n = 203 healthy controls) from four cohorts. For each participant, functional timeseries were extracted from 80 cortical regions of interest, representing 6 intrinsic networks using 1) a volume-based approach 2) a surface-based group atlas approach, and 3) Personalized Intrinsic Network Topography (PINT), a personalized surface-based approach (Dickie et al., 2018). Timeseries were also extracted from previously defined intrinsic network subregions of the striatum (Choi et al 2011), thalamus (Ji et al 2019), and cerebellum (Buckner et al 2011). ResultsCompared to a volume-based approach, the correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohens D volume vs surface 0.27-1.00, all p<10^-6) and further increased after PINT (Cohens D surface vs PINT 0.18-0.96, all p <10^-4). In SSD vs HC comparisons, controlling for age, sex, scanner and in-scanner motion, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 357, surface: 562, PINT: 630, FDR corrected). These patterns were found from four different cortical networks - frontal-parietal, sensory-motor, visual, and default mode -- to subcortical regions. ConclusionOur results indicate that individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models (Murray et al 2019). Our results also change our understanding of the specific network-network functional connectivity alterations in people with SSDs, and the extent of those alterations. Future work will examine these new patterns of dysconnectivity with behaviour using dimensional models. Highlights- We evaluated the impact of cortical mapping method (volume-based, surface-based, vs surface personalized: PINT) on resting-state fMRI results in Schizophrenia Spectrum Disorders (SSD). - The use of surface-based approaches and PINT increased the connectivity of cortical networks with the expected subregions of the striatum, thalamus and cerebellum, in comparison to a volume-based approach - whole-brain case-control differences in functional connectivity were more pronounced after surface-based approach and PINT, in comparison to a volume-based approach

neuroscience↗

bioRxiv2021

Neural excitation/inhibition imbalance and the treatment of severe depression

An influential hypothesis holds that depression is related to a neural excitation/inhibition imbalance, but its role in the treatment of depression remains unclear. Here, we show that unmedicated patients with severe depression demonstrated reduced inhibition of brain-wide resting-state networks relative to healthy controls. Patients using antidepressants showed inhibition that was higher than unmedicated patients and comparable to controls, but they still suffered from severe depression. Subsequent treatment with electroconvulsive therapy (ECT) reduced depressive symptoms, but its effectiveness did not depend on changes in network inhibition. Concomitant pharmacotherapy increased the effectiveness of ECT, but only when the strength of neural inhibition before ECT was within the normal range and not when inhibition was excessive. These findings suggest that reversing the excitation/inhibition imbalance may not be sufficient nor necessary for the effective treatment of severe depression, and that brain-state informed pharmacotherapy management may enhance the effectiveness of ECT.

neuroscience↗

bioRxiv2020

Adaptive current-flow models of ECT: Explaining individual static impedance, dynamic impedance, and brain current delivery

BackgroundImprovements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patients head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes. ObjectiveHowever, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice. MethodsWe developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These "adaptive" models simulate ECT both during therapeutic stimulation using high (~1 A) current and when dynamic impedance is measured, as well as prior to stimulation when low (~1 mA) current is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject specific maximum [Formula], and a deep scalp layer with a subject-specific fixed conductivity ({sigma}DS). ResultsWe demonstrate that variation in these scalp parameters explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrate that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models. ConclusionsOur predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and current delivery to the brain, are themselves subject to assumptions about tissue properties. Broadly, our novel pipeline for tES models is important in ongoing efforts to optimize devices, personalize interventions, and explain clinical findings.

bioengineering↗

bioRxiv2018

Striatal volume and functional connectivity predict weight gain in early-phase psychosis

BackgroundSecond-generation antipsychotic drugs (SGAs) are essential in the treatment of psychotic disorders, but are well-known for inducing substantial weight gain and obesity. Critically, weight gain may reduce life expectancy for up to 20-30 years in patients with psychotic disorders, and prognostic bio-markers are generally lacking. The dorsal striatum, rich in dopamine D2 receptors which are antagonized by antipsychotic medications, plays a key role in the human reward system and in appetite regulation, suggesting that altered dopamine activity in the striatal reward circuitry may be responsible for increased food craving and resultant weight gain.\n\nMethodsHere, we measured striatal volume and striatal resting state functional connectivity at baseline, and weight gain over the course of 12 weeks of antipsychotic treatment in 81 patients with early-phase psychosis. We also included a sample of 58 healthy controls. Weight measurements were completed at baseline, and then weekly for 4 weeks, and every 2 weeks until week 12. We used linear mixed models to compute individual weight gain trajectories. Striatal volume and whole-brain striatal connectivity were then calculated for each subject, and used to assess the relationship between striatal structure and function and individual weight gain in multiple regression models.\n\nOutcomesPatients had similar baseline weights and body mass indices (BMI) compared to healthy controls. There was no evidence that prior drug exposure or duration of untreated psychosis correlated with baseline BMI. Higher left putamen volume and lower frontopolar connectivity predicted magnitude of weight gain in patients, and these effects multiplied when the structure-function interaction was considered.\n\nInterpretationThese results provide evidence for a synergistic effect of striatal structure and function on antipsychotics-induced weight gain. Lower fronto-striatal connectivity, implicated in less optimal long-term decision making, was associated with more weight gain, and this relationship was stronger for higher compared to lower left putamen volumes.\n\nFundingSupported by NIMH grant P50MH080173 to Dr. Malhotra, grant R01MH060004 to Dr. Robinson, grant R01MH076995 to Dr. Szeszko and R21MH101746 to Drs. Robinson and Szeszko.

neuroscience↗