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Siebenhühner, F.

Publications and source records attributed to Siebenhühner, F..

4 recordsLinked to original sources

Low-dimensional brain-symptom associations delineate depression phenotypes with distinct connectivity biomarkers and symptom profiles

Depression is neurobiologically and clinically heterogeneous. New approaches using resting-state functional MRI (rs-fMRI) functional connectivity (FC) data have modeled the neural basis of depression heterogeneity and revealed unique neural phenotypes. Yet, no studies have identified depression phenotypes from electrophysiological magnetoencephalography (MEG) data although MEG measures human brain dynamics at millisecond precision. We demonstrate here unique depression phenotypes based on MEG-oscillation FC. We collected resting-state MEG, MRI, and clinical symptom data from 263 patients with unipolar depression and 75 healthy controls. We assessed MEG-FC with two oscillatory coupling-mode measures that are fundamental for information processing. To define normative phenotypes, we computed their latent-space low-dimensional brain-symptom associations, and used these components to identify phenotypes using unsupervised machine learning. We identified five stable depression phenotypes that were characterized by unique symptom profiles and distinct spectral patterns. Our results demonstrate new neural underpinnings of depression heterogeneity and reveal unique neural phenotypes with potential personalized diagnostic value.

neuroscience↗

Sleep-Modulated Cross-Frequency Coupling Between δ Phase and β-γ Bistability: A System-Level Modulation of Epileptic Activity

ObjectiveWhile slow waves in {delta} (0.5-4 Hz) characterize NREM sleep, in patients with sleep-related epilepsy, seizures most frequently emerge during NREM stage 2, known to be promoted by {delta}-band instability. Meanwhile, the epileptogenic zone (EZ) shows localized bistability in {beta}-{gamma} band (15-200 Hz) neuronal oscillations--indicating a catastrophic shift toward seizure. We aim to clarify the mechanistic link between {delta}-band synchrony and {beta}-{gamma} band bistability in epilepsy. MethodsWe studied a cohort of fourteen patients with Sleep Hypermotor Epilepsy (22.3 {+/-} 10.8 years old; 7 males). 7-9-hour stereo-EEG sleep recordings were segmented into 10-minute of uninterrupted, interictal N2 and N3 epochs, and phase synchrony, phase-amplitude coupling (PAC), and bistability were assessed. Canonical correlation was examined to answer whether PAC links {delta}-phase to {beta}-{gamma} bistability. ResultsCompared to non-EZ, the EZ exhibited larger 15-200 Hz bistability along with stronger 2-8 Hz and 15-100 Hz synchrony throughout N2 and N3. Compared to N3, N2 showed stronger PAC between 2-30 Hz phases in the non-EZ and 5-150 Hz amplitudes in the EZ. Canonical correlations between {delta}-phase modulated PAC and both bistability and synchrony were identified during N2 (r = 0.86 and 0.82) and N3 (r = 0.84 and 0.80), with the strongest contributors being 2-4 Hz synchrony and bistability in 2-4 Hz and 15-200 Hz bands. Correlations between interictal spikes and canonical covariates of bistability and PAC (r2 = 0.62 for N2 and 0.56 for N3) validated their relevance to epileptogenicity. Significance{delta}-band synchrony and {beta}-{gamma} band bistability are not isolated epileptogenic mechanisms but likely act synergistically, playing a pivotal role in seizure generation through the coupling of {delta} phases and {beta}-{gamma} amplitudes across large networks, with significant contributions from non-epileptogenic tissues. Key pointsO_LIStrong {beta}-{gamma} bistability in neuronal oscillations localizes the EZ throughout N2 and N3 sleep. C_LIO_LIElevated {delta}-band phase synchrony characterizes the EZ and its functional neighbors throughout N2 and N3 sleep. C_LIO_LIa-band synchrony modulates local {beta}-{gamma} bistability through PAC, with significant contributions from non-EZ tissues. C_LI

neuroscience↗

Critical-like bistable dynamics in the resting-state human brain

Brain activity exhibits scale-free avalanche dynamics and power-law long-range temporal correlations (LRTCs) across the nervous system. This has been thought to reflect "brain criticality", i.e., brains operating near a critical phase transition between disorder and excessive order. Neuronal activity is, however, metabolically costly and may be constrained by activity-limiting mechanisms and resource depletion, which could make the phase transition discontinuous and bistable. Observations of bistability in awake human brain activity have nonetheless remained scarce and its functional significance unclear. First, using computational modelling where bistable synchronization dynamics emerged through local positive feedback, we found bistability to occur exclusively in a regime of critical-like dynamics. We then assessed bistability in vivo with resting-state magnetoencephalography and stereo-encephalography. Bistability was a robust characteristic of cortical oscillations throughout frequency bands from {delta} (3-7 Hz) to high-{gamma} (100-225 Hz). As predicted by modelling, bistability and LRTCs were positively correlated. Importantly, while moderate levels of bistability were positively correlated with executive functioning, excessive bistability was associated with epileptic pathophysiology and predictive of local epileptogenicity. Critical bistability is thus a salient feature of spontaneous human brain dynamics in awake resting-state and is both functionally and clinically significant. These findings expand the framework of brain criticality and show that critical-like neuronal dynamics in vivo involves both continuous and discontinuous phase transitions in a frequency-, neuroanatomy-, and state-dependent manner.

neuroscience↗

Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations

Neuronal oscillations, their inter-areal synchronization, and scale-free dynamics constitute fundamental mechanisms for cognition by regulating communication in neuronal networks. These oscillatory dynamics have large inter-individual variability that is partly heritable. However, the genetic underpinnings of oscillatory dynamics have remained poorly understood. We recorded resting-state magnetoencephalography (MEG) from 82 healthy participants and investigated whether oscillation dynamics were influenced by genetic polymorphisms in Catechol-O-methyltransferase (COMT) Val158Met and brain-derived neurotrophic factor (BDNF) Val66Met. Both COMT and BDNF polymorphisms influenced local oscillation amplitudes and their long-range temporal correlations (LRTCs), while only BDNF polymorphism affected the strength of large-scale synchronization. Our findings demonstrate that COMT and BDNF genetic polymorphisms contribute to inter-individual variability in local and large-scale synchronization dynamics of neuronal oscillations. Comparison of these results to computational modelling of near-critical synchronization dynamics further suggested that COMT and BDNF polymorphisms influenced local oscillations by modulating the excitation-inhibition balance according to the brain criticality framework.

neuroscience↗