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Elvsashagen, T.

Publications and source records attributed to Elvsashagen, T..

10 recordsLinked to original sources

Computational modelling of schizophrenia-associated alterations of ion-channel-encoding gene expression predicts a decrease in delta power

Schizophrenia presents with a wide range of phenotypes that can help to understand the the mechanisms of the disease. Among these, alterations in delta oscillations are especially amenable to experimental investigation, yet the mechanisms underlying these changes remain insufficiently understood. Biophysically detailed computational modeling offers a powerful approach to investigate these phenomena, as it enables multi-scale integration of genetic and electrophysiological data. In this study, we developed a minimal network model composed of biophysically detailed, multicompartmental neurons to replicate experimental data on the effects of pharmacological blockage of gabaergic neurotransmission on delta-band power. We inserted post-mortem RNA expression data from the anterior cingulate and prefrontal cortices of individuals with schizophrenia and matched controls into the model to study the effects of schizophrenia-associated alterations of ion-channel expression on delta-oscillation power. Our simulations revealed a significant reduction in delta-band power in schizophrenia, driven by altered expression of calcium channel genes in pyramidal neurons. These results provide insights into the genetic contributions to oscillatory disruptions observed in schizophrenia, and our modelling framework can help to develop stratification strategies that bridge genetics and in vivo electrophysiology.

neuroscience↗

Computational modelling of novelty detection in the mismatch negativity protocols and its impairments in schizophrenia

The human auditory system rapidly distinguishes between novel and familiar sounds, a process reflected in mismatch negativity (MMN), an EEG-based biomarker of auditory novelty detection. MMN is impaired in psychiatric conditions, most notably schizophrenia (SCZ), yet the neuronal mechanisms underlying this deficit remain unclear. Here, we combined computational modelling and genetic analyses to investigate how SCZ-associated cellular abnormalities affect auditory novelty detection. We developed an integrate-and-fire spiking network model capable of detecting four types of auditory novelty, including stimulus omission. Based on assumptions of short-term depressing synapses between the subpopulations of the network and the existence of neuronal inputs that are phase-locked to the rhythm of the recently experienced stimulus sequence, the model reliably reproduced MMN-like novelty detection and allowed systematic testing of SCZ-related cellular alterations. Simulations revealed that both reduced pyramidal cell excitability, linked to ion-channel dysfunction, and decreased spine density impaired novelty detection, with the latter producing stronger deficits. Our work provides a flexible spiking network model of auditory novelty detection that can link cellular-level abnormalities to measurable MMN deficits, improving their mechanistic interpretation and helping to explain the heterogeneity of SCZ.

neuroscience↗

Thalamic Nuclei Volumes Across Psychiatric and Neurological Disorders: A Multi-Site Magnetic Resonance Imaging Study

The human thalamus is an integrative hub for multiple cortical and subcortical circuits involved in sensory processing and higher cognitive functions. Thalamic volume differences have been reported across multiple psychiatric and neurological disorders, but previous studies have typically relied on small samples, focused on one or a limited number of disorders, or investigated the thalamus as a whole without considering its functional subdivisions. In this multi-site study, we compared thalamic nuclei volumes across mild cognitive impairment (MCI), dementia (DEM), major depressive disorder, schizophrenia spectrum disorder (SCZ), clinical high risk for schizophrenia, bipolar spectrum disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Parkinsons disease, multiple sclerosis (MS), and healthy controls (N > 8 000). Using structural MRI, we segmented 25 bilateral thalamic nuclei, corresponding to six anatomical groups. Linear models revealed that anterior, medial and lateral regions of the thalamus were significantly smaller in several conditions, with largest effects observed for MCI, DEM, SCZ and MS. In contrast, the ventral and intralaminar groups were relatively normal. This pattern of effects largely corresponds to the canonical functional subdivision of the thalamus into higher-order and sensory regions. At the level of individual nuclei, the clinical conditions were associated with distinct patterns of alterations, while left and right lateral geniculate nuclei were implicated in six of the disorders, suggesting a possible relation with circadian and sleep disturbances. Together, the results highlight a role for the higher-order thalamus in common brain disorders and a differential involvement at the nuclei level, refining our understanding of thalamic pathology across common brain disorders.

neuroscience↗

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modelling

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modelling of post-synaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from post-mortem mRNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in anterior cingulate cortex, lead to impaired PKA-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped EEG dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials (VEP) were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.

neuroscience↗

Evidence for widespread alterations in cortical microstructure after 32 hours of sleep deprivation

Cortical microstructure is influenced by circadian rhythm and sleep deprivation, yet the precise underpinnings of these effects remain unclear. The ratio between T1-weighted and T2-weighted magnetic resonance images (T1w/T2w ratio) has been linked to myelin levels and dendrite density and may offer novel insight into the intracortical microstructure of the sleep deprived brain. Here, we examined intracortical T1w/T2w ratio in 41 healthy young adults (26 women) before and after 32 hours of either sleep deprivation (n = 18) or a normal sleep-wake cycle (n = 23). Linear models revealed significant group differences in T1w/T2w ratio change after 32 hours in four clusters, including bilateral effects in the insular, cingulate, and superior temporal cortices, comprising regions involved in attentional, auditory and pain processing. Across clusters, the sleep deprived group showed an increased T1w/T2w ratio, while the normal sleep-wake group exhibited a reduced ratio. These changes were not explained by in-scanner head movement, and 95% of the effects across clusters remained significant after adjusting for cortical thickness and hydration. Compared with a normal sleep-wake cycle, 32 hours of sleep deprivation yields intracortical T1w/T2w ratio increases. While the intracortical changes detected by this study could reflect alterations in myelin or dendritic density, or both, histological analyses are needed to clarify the precise underlying cortical processes.

neuroscience↗

Sleep and sleep deprivation differentially alter white matter microstructure: a mixed model design utilising advanced diffusion modelling

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across 4 time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group x time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.

neuroscience↗

Evidence for reduced long-term potentiation-like visual cortical plasticity in schizophrenia and bipolar disorder

BackgroundSeveral lines of research suggest that impairments in long-term potentiation (LTP)-like synaptic plasticity might be a key pathophysiological mechanism in schizophrenia (SZ) and bipolar disorder type I (BDI) and II (BDII). Using modulations of visually evoked potentials (VEP) of the electroencephalogram, impaired LTP-like visual cortical plasticity has been implicated in patients with BDII, while there has been conflicting evidence in SZ, a lack of research in BDI, and mixed results regarding associations with symptom severity, mood states, and medication. MethodsWe measured the VEP of patients with SZ spectrum disorders (n=31), BDI (n=34), BDII (n=33), and other BD spectrum disorders (n=2), and age-matched healthy control participants (n=200) before and after prolonged visual stimulation. ResultsCompared to healthy controls, modulation of VEP component N1b, but not C1 or P1, was impaired both in patients within the SZ spectrum ({chi}2=35.1, p=3.1x10-9) and BD spectrum ({chi}2=7.0, p=8.2x10-3), including BDI ({chi}2=6.4, p=0.012), but not BDII ({chi}2=2.2, p=0.14). N1b modulation was also more severely impaired in SZ spectrum than BD spectrum patients ({chi}2=14.2, p=1.7x10-4). The reduction in N1b modulation was related to PANSS total scores ({chi}2=10.8, p=1.0x10-3), and nominally to number of psychotic episodes ({chi}2=4.9, p=0.027). Conclusions. These results suggest that LTP-like plasticity is impaired in SZ and BDI, but not BDII, and related to psychotic symptom severity. Adding to previous genetic, pharmacological, and anatomical evidence, these results implicate aberrant synaptic plasticity as a mechanism underlying SZ and BD.

neuroscience↗

Experience-dependent modulation of the visual evoked potential: testing effect sizes, retention over time, and associations with age in 415 healthy individuals

Experience-dependent modulation of the visual evoked potential (VEP) is a promising proxy measure of synaptic plasticity in the cerebral cortex. However, existing studies are limited by small to moderate sample sizes as well as by considerable variability in how VEP modulation is quantified. In the present study, we used a large sample (n = 415) of healthy volunteers to compare different quantifications of VEP modulation with regards to effect sizes and retention of the modulation effect over time. We observed significant modulation for VEP components C1 (Cohens d = 0.53), P1 (d = 0.66), N1 (d = -0.27), N1b (d = -0.66), but not P2 (p = 0.1), and in one time-frequency cluster (~30 Hz and ~70 ms post-stimulus; d = -0.48), 2-4 minutes after 2 Hz prolonged visual stimulation. For components N1 (d = -0.21) and N1b (d = -0.38), as well for the time-frequency cluster (d = -0.33), this effect was retained after 54-56 minutes. Moderate to high correlations ({rho} = [0.39, 0.69]) between modulation at different postintervention blocks revealed a relatively high temporal stability in the modulation effect for each VEP component. However, different VEP components also showed markedly different temporal retention patterns. Finally, P1 modulation correlated positively with age (t = 5.26), and was larger for female participants (t = 3.91), with no effects of either age or sex on N1 and N1b potentiation. These results provide strong support for VEP modulation, and especially N1b modulation, as a robust measure of synaptic plasticity, but underscore the need to differentiate between components, and to control for demographic confounders.

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The genetic architecture of human brainstem structures and their involvement in common brain disorders

Brainstem regions support critical bodily functions, yet their genetic architectures and involvement in brain disorders remain understudied. Here, we examined volumes of brainstem structures using magnetic resonance imaging in 43,353 individuals. In 27,034 genotyped healthy participants, we identified 16 genetic loci associated with whole brainstem volume and 10, 23, 3, and 9 loci associated with volumes of the midbrain, pons, superior cerebellar peduncle, and medulla oblongata, respectively. These loci were mapped to 305 genes, including genes linked to brainstem development and common brain disorders. We detected genetic overlap between the brainstem volumes and eight psychiatric and neurological disorders. Using imaging data from 16,319 additional individuals, we observed differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinsons disease. Together, our results provide new insights into the genetic underpinnings of brainstem structures and support their involvement in common brain disorders.

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Genetics of brain age suggest an overlap with common brain disorders

Numerous genetic and environmental factors contribute to psychiatric disorders and other brain disorders. Common risk factors likely converge on biological pathways regulating the optimization of brain structure and function across the lifespan. Here, using structural magnetic resonance imaging and machine learning, we estimated the gap between brain age and chronological age in 36,891 individuals aged 3 to 96 years, including individuals with different brain disorders. We show that several disorders are associated with accentuated brain aging, with strongest effects in schizophrenia, multiple sclerosis and dementia, and document differential regional patterns of brain age gaps between disorders. In 16,269 healthy adult individuals, we show that brain age gap is heritable with a polygenic architecture overlapping those observed in common brain disorders. Our results identify brain age gap as a genetically modulated trait that offers a window into shared and distinct mechanisms in different brain disorders.

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