Biology subjects

Lin, C.-P.

Publications and source records attributed to Lin, C.-P..

At least 19 recordsLinked to original sources

bioRxiv2025

Dynamic evolution of AT-rich isochores shapes the genome of an intertidal fungus Annulohypoxylon annulatoides

Marine and coastal fungi experience intense environmental variability, yet the genomic mechanisms enabling filamentous fungi to tolerate such conditions remain unclear. From 56 fungal isolates collected along the Lailai rocky shore in northern Taiwan, we selected Annulohypoxylon annulatoides for deeper investigation due to its prevalence and distinctive stress response. Phenotypic assays revealed that this strain exhibits distinct growth and recovery dynamics under salinity, temperature, and UV stress compared to conspecific strains isolated from tree bark. To investigate the genomic basis of its adaptation, we generated a high-quality 41.8 Mbp de novo genome assembly with 11,529 predicted proteins. Across Hypoxylaceae genomes, we identified variably sized and dispersed AT-rich isochores, which in A. annulatoides were enriched in repeats and displayed low gene density. Despite differences in AT content, core gene content and Pfam domain profiles remained conserved. These AT-rich isochores exhibit several sequence and structural features consistent with scaffold/matrix attachment regions (S/MARs), raising the possibility that they influence higher-order genome organisation. Comparative analyses suggest they arose through independent repeat insertions or via ancestral repeat amplifications. Together, our findings point to a role for AT-rich isochores in shaping genome architecture and potentially mediating stress-responsive regulation, supporting the broader environmental flexibility observed in Hypoxylaceae, including adaptation to dynamic coastal habitats.

genomics↗

bioRxiv2025

A global synthesis of yeast in microbiomes

Yeasts are widespread members of microbial communities across terrestrial, aquatic, and host-associated environments, yet they remain underrepresented in microbiome studies due to low abundance and methodological biases. By combining a literature review with a meta-analysis of [~]44,000 fungal metabarcoding samples from the GlobalFungi database, we show that yeasts occur in over 90% of samples, confirming their global ubiquity. Basidiomycetous lineages--especially Agaricomycotina--were most frequently detected, whereas Saccharomycotina were more restricted to anthropogenic and aquatic settings. Although yeasts typically comprised only [~]0.1% of fungal reads, their distributions were non-random and reflected distinct habitat preferences across environments. In [~]3% of samples, yeasts exceeded 25% of reads, with genera such as Aureobasidium, Hanseniaspora, and Saccharomyces episodically dominating nutrient-rich or human-influenced environments. Cosmopolitan genera including Vishniacozyma, Solicoccozyma, and Rhodotorula were broadly distributed but remain underreported in microbiome surveys. Shotgun metagenomic data further confirmed yeast presence across diverse microbiomes, though with consistently low coverage, reflecting the "curse of low abundance." Despite their rarity, yeasts likely play disproportionate roles in nutrient cycling, plant growth, and host interactions. We recommend inclusive multi-kingdom approaches--improved primers, long-read sequencing, and quantitative tools--to better integrate yeasts in microbiomes.

microbiology↗

bioRxiv2024

Spatiotemporal dynamics and assembly process differ in fungal communities across contiguous habitats in tropical forests

BackgroundThe variation in fungal community composition within a single habitat space has been extensively studied in forest ecosystems. However, the spatial and temporal distribution of fungi across contiguous habitats, particularly at a local scale and in tropical regions, remains underexplored. In this study, we examined the fungal community composition across multiple habitats proximal to each other over two seasons in seven Fagaceae species in Taiwanese broadleaf forests. We tested how local spatial scale and habitat influence community assembly. ResultsUsing a metabarcoding approach, we sequenced ITS3/ITS4 amplicons from 864 samples collected from four distinct habitats--leaves, twigs, litter, and soil. We identified 11,600 fungal amplicon sequence variants (ASVs), with community composition differing significantly between habitats proximal to each other. Phyllosphere (leaves and twigs) fungi exhibited higher diversity compared to soil. Habitat type and long-term precipitation emerged as the most influential factors driving fungal diversity and composition, with a clear distance-decay relationship observed in leaf and twig but not in soil. Random forest analysis accurately classified habitats based on ASVs relative abundances, with strong predictors were mostly endemic ASVs prevalent in soil. Misclassified samples were due to secondary contact of fungi between adjacent habitats. Co-occurrence network analysis revealed more complex and deterministic networks in leaf and twig habitats, while soil was driven by stochastic processes and contained most endemic ASVs. A Cladosporium sp. emerged as a keystone species, maintaining network stability across forests. ConclusionThis study reveals how local spatial variation and habitat shape distinct fungal communities in tropical forests, with deterministic processes dominating in some habitats and stochasticity playing a key role in others. We show local fungal taxa were strong habitat predictors and drivers of community cohesion. These findings highlight the importance of studying coexisting habitats to gain a deeper understanding of fungal biogeography and ecosystem function.

ecology↗

bioRxiv2024

An overview of GabRat edge disruption and its new extensions for unbiased quantification of disruptive camouflaging patterns using randomization technique

Disruptive colorations are camouflaging patterns that use contrasting colorations to interrupt the continuously of objects edge and disturb the observers visual recognition. The GabRat method has been introduced and widely used to quantify the strength of edge disruption. The original GabRat method requires a composite image where a target object is placed on a particular background. It computes the intensities of frequency components parallel and perpendicular to the edge direction at each edge point using Gabor filters, and summarize the ratios of these two intensities around the perimeter of the shape. However, we found that the original GabRat method has an issue which produces false signals and biases to overestimating the GabRat value depending on the edge angle. Here, we introduce GabRat-R, which can diminish that angle dependency using Gabor filters with randomized base angles. Additionally, we developed GabRat-RR, which iteratively places a target object on a background with random positions and rotation angles to average the effects of the heterogeneity and anisotropy of background. Compared with the original GabRat, our GabRat-R and GabRat-RR programs run more efficiently using multithreading techniques. GabRat-R and GabRat-RR were freely available in Natsumushi 2.0 software of the authors website.

evolutionary biology↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

Evolution of horn length and lifting strength in the Japanese rhinoceros beetle Trypoxylus dichotomus

Rhinoceros beetle (Trypoxylus dichotomus) males have pitchfork-shaped head horns, which they use to pry rival males from the trunks of trees. In the largest males these horns can be three times the length of horns in the two closest sister species. Because this weapon functions as a lever, longer horns should lift with less force than shorter horns (the paradox of the weakening combatant) unless other elements of the weapon system (e.g., input lever length, muscle mass) evolve to compensate. We used next-generation sequencing approaches to consolidate 23 sample locations into 8 genetically distinguishable populations, reconstructing their historical relationships and providing a comprehensive picture of the evolution of this horn lever system. We show that head horns likely increased in length independently in the Northern and Southern lineages. In both instances this resulted in weaker lifting forces, but this mechanical disadvantage was later ameliorated, to some extent and in some locations, by subsequent reductions to horn length, changes in muscle size, or by an increase in input lever length (head height). Our results reveal an exciting geographic mosaic of differences in weapon size, weapon force, and in the extent and nature of mechanical compensation. Reconstructing the evolution of this weapon system offers critical insights towards meaningfully linking mating system dynamics, selection patterns, and diversity in sexually selected traits.

evolutionary biology↗

bioRxiv2023

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome

Major depressive disorder (MDD) is the most burdensome psychiatric disorder characterized by remarkably heterogeneous clinical phenotypes. It remains challenging to delineate the heterogeneity of neurobiological abnormalities underlying the clinical variance and, on this basis, to identify neurophysiological subtypes of MDD patients. Here, using a large multisite resting-state functional MRI data from 1,148 MDD patients and 1,079 healthy controls, we generated lifespan normative models of functional connectivity strengths, mapped the heterogeneity of patients individual deviations, and identified neurobiological MDD subtypes. MDD patients showed positive deviations mainly in the default mode and subcortical areas, and negative deviations widely distributed over the cortex. However, there was a great inter-subject heterogeneity as indicated by that no more than 3.14% of patients deviated from the normative range for any brain region. Two neurophysiological MDD subtypes were identified. Subtype 1 showed severe deviations with positive deviations in the default mode, limbic, and subcortical areas, and negative deviations in the sensorimotor, dorsal and ventral attention areas, while subtype 2 showed a moderate but conversed deviation pattern. The severe-deviation subtype had older age, higher medicated proportion, and higher Suicide item score, while the moderate-deviation subtype showed higher Work and Activities and Depressed Mood item scores. Moreover, the baseline deviations in the severe-deviation subtype were predictive of 6-month antidepressant treatment effects in a subsample. To our knowledge, the current study is the largest multisite analysis of neurophysiological MDD subtyping to date and the findings shed light on our understanding of the biological mechanisms underlying the intersubject heterogeneity of clinical phenotypes, which are informative for the development of personalized treatments for this disorder.

neuroscience↗

bioRxiv2022

Nigral pathology contributes to microstructural integrity of striatal and frontal tracts in Parkinson's disease

BackgroundMotor and cognitive impairment in Parkinsons disease (PD) is associated with dopaminergic dysfunction that stems from substantia nigra (SN) degeneration and concomitant -synuclein accumulation. Diffusion MRI can detect microstructural alterations of the SN and its tracts to (sub)cortical regions, but their pathological sensitivity is still poorly understood. ObjectiveTo unravel the pathological substrate underlying microstructural alterations of the SN, and its tracts to the dorsal striatum and dorsolateral prefrontal cortex (DLPFC) in PD. MethodsCombining post-mortem in-situ MRI and histopathology, T1-weighted and diffusion MRI of 9 PD, 6 PD with dementia (PDD), 5 dementia with Lewy bodies (DLB), and 10 control donors were collected. From MRI, mean diffusivity (MD) and fractional anisotropy (FA) were derived from the SN, and tracts between the SN and caudate nucleus, putamen, and DLPFC. Phosphorylated-Ser129--synuclein and tyrosine hydroxylase immunohistochemistry was included to quantify nigral Lewy pathology and dopaminergic degeneration, respectively. ResultsCompared to controls, PD and PDD/DLB showed increased MD of the SN and SN-DLPFC tract, as well as increased FA of the SN-caudate nucleus tract. Both PD and PDD/DLB showed nigral Lewy pathology and dopaminergic loss compared to controls. Increased FA of the SN and SN-caudate nucleus tract was associated with SN dopaminergic loss, while increased MD of the SN-DLPFC tract was associated with increased SN Lewy neurite load. ConclusionsIn PD and PDD/DLB, diffusion MRI captures microstructural alterations of the SN and tracts to the dorsal striatum and DLPFC, which differentially associates with SN dopaminergic degeneration and Lewy neurite pathology.

neuroscience↗

bioRxiv2022

Cortical distribution of neurofilaments associates with pathological hallmarks and MRI measures of atrophy and diffusivity in Parkinson's disease

Increased neurofilament levels in biofluids, commonly used as a proxy for axonal degeneration in the brain, have been found in Parkinsons disease (PD), PD with dementia (PDD) and dementia with Lewy bodies (DLB), and correlate with MRI biomarkers. The aim of the current study was to unravel the regional distribution of cortical neurofilaments and their association with pathology load and MRI measures of atrophy and diffusivity in the post-mortem brain. Using a within-subject post-mortem MRI-pathology approach, we included 9 PD, 12 PDD/DLB and 18 age-matched control donors. Cortical thickness and mean diffusivity (MD) metrics were extracted respectively from 3DT1 and DTI at 3T in-situ MRI. After autopsy, pSer129 alpha-synuclein (pSer129-Syn), p-tau, and amyloid-beta, together with neurofilament light-chain (NfL) and phosphorylated neurofilament medium- and heavy-chain (p-NfM/H) immunoreactivity were quantified in 7 cortical regions, and studied in detail with confocal-laser scanning microscopy. The correlations between MRI and pathological measures were studied using linear mixed models. Compared to controls, p-NfM/H immunoreactivity was increased in all cortical regions in PD and PDD/DLB, whereas NfL immunoreactivity was mainly increased in the parahippocampal and entorhinal cortex in PDD/DLB. NfL-positive neurons showed degenerative morphological features and axonal fragmentation. Increased p-NfM/H correlated with p-tau load, and NfL correlated with pSer129-Syn but more strongly with p-tau load in PDD/DLB. Lastly, neurofilament immunoreactivity correlated with cortical thinning in PD and with increased cortical MD in PDD/DLB. Taken together, increased neurofilament immunoreactivity suggests underlying axonal injury and neurofilament accumulation in morphologically altered neurons with increasing pathological burden. Importantly, we demonstrate that such neurofilament markers at least partly explain MRI measures that are associated with the neurodegenerative process.

neuroscience↗

bioRxiv2022

TSC2 regulates tumor susceptibility to TRAIL-mediated T cell killing by orchestrating mTOR signaling

Resistance to cancer immunotherapy continues to impair common clinical benefit. Here, we uncover an important role for Tuberous Sclerosis Complex 2 (TSC2) in determining tumor susceptibility to cytotoxic T lymphocytes (CTL) killing, both in vitro and in vivo. TSC2-depleted tumor cells showed disrupted mTOR regulation upon CTL attack, which was associated with enhanced cell death. Tumor cells adapted to CTL attack by shifting their mTOR signaling balance toward increased mTORC2 activity to circumvent apoptosis and necroptosis. TSC2 critically protected tumor cells as its ablation strongly augmented tumor cell sensitivity to CTL attack. Mechanistically, TSC2 inactivation caused elevation of TRAIL receptors expression, cooperating with mTORC1-S6 signaling to induce tumor cell death. Clinically, we found a negative correlation between TSC2 expression and TRAIL signaling in TCGA patient cohorts. Moreover, a lower TSC2 immune response signature was observed in melanomas from patients responding to immune checkpoint blockades. Our study uncovers a pivotal role for TSC2 in the cancer immune response by governing crosstalk between TSC2-mTOR and TRAIL signaling, aiding future therapeutic exploration of this pathway in immuno-oncology.

cancer biology↗

bioRxiv2022

Trophoblast and blood vessel organoid cultures recapitulate the role of WNT2B in promoting intravillous vascularization in human intrauterine and ectopic pregnancy

Tubal ectopic pregnancy (TEP), a pregnancy complication caused by aberrant implantation in fallopian tubes, accounts for 9-13% pregnancy-related deaths. The lack of models for human TEP hampers the understanding of its pathological mechanisms. Here, we employed multiple models to investigate the crosstalk between human trophoblast development and intravillous vascularization. We found that the severity of TEP, the size of placental villi, and the depth of trophoblast invasion are correlated with the extent of intravillous vascularization. We identified a key pro-angiogenic factor secreted by trophoblasts, WNT2B, that promotes villous vasculogenesis, angiogenesis, and vascular network expansion. In an organoid coculture model consisting of trophoblast organoids and blood vessel organoids, knockdown of WNT2B in trophoblast organoids compromises their pro-angiogenic effect on the development of blood vessel organoids. These organoid-based models reveal an important role for WNT-mediated angiogenesis in pregnancies and could be employed to investigate the commutations between trophoblasts and endothelial/endothelial progenitor cells.

cell biology↗

bioRxiv2022

Integrated Diffusion Image Operator (iDIO): A tool for automated configuration and processing of diffusion MRI data

The preprocessing of diffusion magnetic resonance imaging (dMRI) data involves numerous steps, including the corrections for head motion, susceptibility distortion, low signal-to-noise ratio, and signal drifting. Researchers or clinical practitioners often need to configure different preprocessing steps depending on disparate image acquisition schemes, which increases the technical threshold for dMRI analysis for non-expert users. This could cause disparities in data processing approaches and thus hinder the comparability between studies. To make the dMRI data processing steps transparent and adapt to various dMRI acquisition schemes for researchers, we propose a semi-automated pipeline tool for dMRI named integrated Diffusion Image Operator or iDIO. This pipeline integrates features from a wide range of advanced dMRI software tools and targets at providing a one-click solution for dMRI data analysis, via automatic configuration for a set of optimal processing steps based on the image header of the input data. Additionally, the pipeline provides options for post-processing, such as estimation of diffusion tensor metrics and whole-brain tractography-based connectomes reconstruction using common brain atlases. The iDIO pipeline also outputs an easy-to-interpret quality control report to facilitate users to assess the data quality. To keep the transparency of data processing, the execution log and all the intermediate images produced in the iDIOs workflow are accessible. The goal of iDIO is to reduce the barriers for clinical or non-specialist users to adopt the state-of-art dMRI processing steps.

neuroscience↗

bioRxiv2021

Structural (dys)connectivity associates with cholinergic cell density of the nucleus basalis of Meynert in Alzheimer's disease

Cognitive deficits in Alzheimers disease, specifically amnestic (memory dominant) deficits, are associated with cholinergic degeneration in the basal forebrain. The cholinergic nucleus within the basal forebrain, the nucleus basalis of Meynert, exhibits local atrophy and reduced cortical tract integrity on MRI, and reveals amyloid-{beta} and phosphorylated-tau pathology at autopsy. To better understand the pathophysiology of nucleus basalis of Meynert atrophy and its neocortical projections in Alzheimers disease, we utilized a combined post-mortem in-situ MRI and histopathology approach. A total of 19 Alzheimers disease (10 amnestic and 9 non-amnestic) and 9 non-neurological control donors underwent 3T T1-weighted MRI for anatomical delineation and volume assessment of the nucleus basalis of Meynert, and diffusion-weighted imaging for microstructural assessment of the nucleus and its projections. At subsequent brain autopsy, tissue dissection and immunohistochemistry were performed for amyloid-{beta}, phosphorylated-tau and choline acetyltransferase. Compared to controls, we observed an MRI-derived volume reduction and altered microstructural integrity of the nucleus basalis of Meynert in Alzheimers disease donors. Furthermore, decreased cholinergic cell density was associated with reduced integrity of the nucleus and its tracts to the temporal lobe, specifically to the temporal pole of the superior temporal gyrus, and the parahippocampal gyrus. The association between cholinergic cell density and alteration to cortical tracts was specific for amnestic, compared to non-amnestic Alzheimers disease donors. Our study illustrates that the nucleus basalis of Meynert is severely affected in amnestic Alzheimers disease, both in terms of pathology within the nucleus, but also in terms of damage to its cortical projections, specifically to the temporal lobe, which may contribute to the observed cognitive deterioration.

neuroscience↗

bioRxiv2021

Amyloid-beta, p-tau, and reactive microglia load are correlates of MRI cortical atrophy in Alzheimer's disease

INTRODUCTIONThe aim of this study was to identify the histopathological correlates of MRI cortical atrophy in (a)typical Alzheimers disease (AD) donors. METHODS19 AD and 10 control donors underwent post-mortem in-situ 3T-3DT1-MRI, from which cortical thickness was calculated. Upon subsequent autopsy, 21 cortical brain regions were selected and immunostained for amyloid-beta, phosphorylated-tau, and reactive microglia. MRI-pathology associations were assessed using linear mixed models. Post-mortem MRI was compared to ante-mortem MRI when available. RESULTSHigher amyloid-beta load weakly correlated with a higher cortical thickness globally. Phosphorylated-tau strongly correlated with cortical atrophy in temporo-frontal regions. Reactive microglia load strongly correlated with cortical atrophy in the parietal region. Post-mortem scans showed high concordance with ante-mortem scans acquired <1 year before death. DISCUSSIONDistinct histopathological markers differently correlate with cortical atrophy, highlighting their different roles in the neurodegenerative process. This study contributes in understanding the pathological underpinnings of MRI atrophy patterns.

neuroscience↗

bioRxiv2021

Validating Pore Size Estimates in a Complex Microfibre Environment on a Human MRI System

PurposeRecent advances in diffusion-weighted MRI provide restricted diffusion signal fraction and restricting pore size estimates. Materials based on co-electrospun oriented hollow cylinders have been introduced to provide validation for such methods. This study extends this work, exploring accuracy and repeatability using an extended acquisition on a 300 mT/m gradient human MRI scanner, in substrates closely mimicking tissue, i.e., non-circular cross-sections, intra-voxel fibre crossing, intra-voxel distributions of pore-sizes and smaller pore-sizes overall. MethodsIn a single-blind experiment, diffusion-weighted data were collected from a biomimetic phantom on a 3T Connectom system using multiple gradient directions/diffusion times. Repeated scans established short-term and long-term repeatability. The total scan time (54 minutes) matched similar protocols used in human studies. The number of distinct fibre populations was estimated using spherical deconvolution, and median pore size estimated through the combination of CHARMED and AxCaliber3D framework. Diffusion-based estimates were compared with measurements derived from scanning electron microscopy. ResultsThe phantom contained substrates with different orientations, fibre configurations and pore size distributions. Irrespective of one or two populations within the voxel, the pore-size estimates (~5m) and orientation-estimates showed excellent agreement with the median values of pore-size derived from scanning electron microscope and phantom configuration. Measurement repeatability depended on substrate complexity, with lower values seen in samples containing crossing-fibres. Sample-level repeatability was found to be good. ConclusionWhile no phantom mimics tissue completely, this study takes a step closer to validating diffusion microstructure measurements for use in vivo by demonstrating the ability to quantify microgeometry in relatively complex configurations.

biophysics↗

bioRxiv2020

Differential patterns of gyral and sulcal morphological changes during normal aging process

The cerebral cortex is a highly convoluted structure with distinct morphologic features, namely the gyri and sulci, which are associated with the functional segregation or integration in the human brain. During the lifespan, the brain atrophy that is accompanied by cognitive decline is a well-accepted aging phenotype. However, the detailed patterns of cortical folding change during aging, especially the changing trajectories of gyri and sulci, which is essential to brain functioning, remain unclear. In this study, we investigated the morphology of the gyral and sulcal regions from pial and white matter surfaces using MR imaging data of 417 healthy participants across the lifespan (21-92y). To elucidate the age-related changes in the cortical pattern, we fitted cortical thickness and intrinsic curvature of gyri and sulci using the quadratic model to evaluate their trajectories during normal aging. Our findings show that comparing to gyri, the sulcal thinning is the most prominent pattern during the aging process, and the gyrification of pial and white matter surfaces were also affected differently, which implies the vulnerability of functional segregation during aging. Taken together, we propose a morphological model of aging that may provide a framework for understanding the mechanisms underlying the gray matter degeneration.

neuroscience↗

bioRxiv2020

Large-scale Gradient Dysfunction of the Functional Connectome in Major Depression

BackgroundPatients with major depressive disorder (MDD) exhibit concurrent deficits in sensory processing and high-order cognitive functions such as self-awareness and rumination. Connectome mapping studies have suggested a principal primary-to-transmodal gradient in functional brain networks, supporting the spectrum from sensation to cognition. However, whether this principal connectome gradient is disrupted in patients with MDD and how this disruption is associated with gene expression profiles remain unclear. MethodsUsing a large cohort of resting-state functional magnetic resonance imaging data from 2,234 participants (1,150 patients with MDD and 1,084 healthy controls) recruited at 10 sites, we investigated MDD-related alterations in the principal connectome gradient. We further used Neurosynth and postmortem gene expression data to assess the cognitive functions and transcriptional profiles related to the gradient alterations in MDD, respectively. ResultsRelative to controls, patients with MDD exhibited abnormal global topography of the principal primary-to-transmodal gradient, as indicated by reduced explanation ratio, gradient range, and gradient variation (Cohens d = -0.16[~]-0.21). Focal alterations of gradient scores were mostly in the primary systems involved in sensory processing and in the transmodal systems implicated in high-order cognition. The transcriptional profiles explained 53.9% of the spatial variance in the altered gradient patterns, with the most correlated genes enriched in transsynaptic signaling and calcium ion binding. ConclusionsThese results highlight the dysfunction of the core connectome hierarchy in MDD and its linkage with gene expression profiles, providing insights into the neurobiological and molecular genetic underpinnings of sensory-cognitive deficits in this disorder.

neuroscience↗

bioRxiv2020

Alteration of Power Law Scaling of Spontaneous Brain Activity in Schizophrenia

Nonlinear dynamical analysis has been used to quantify the complexity of brain signal at temporal scales. Power law scaling is a well-validated method in physics that has been used to describe the complex nature of a system across different time scales. In this research, we investigated the change of power-law characteristics in a large-scale resting-state fMRI data of schizophrenia (N = 200) and healthy participants (N = 200) derived from Taiwan Aging and Mental Illness cohort. Fourier transform was used to determine the power spectral density (PSD) of resting-state fMRI signal. We estimated the power law scaling of PSD of resting-state fMRI signal by determining the slope of the regression line fitting to the log-log plot of PSD. The power law scaling represents the dynamical properties of resting-state fMRI signal ranging from noisy oscillation (e.g., white noise) to complex fluctuations (e.g., slope approaches -1). Linear regression model was used to assess the statistical difference in power law scaling between schizophrenia and healthy participants. The significant differences in power law scaling were found in six brain regions. Schizophrenia patients has significantly more positive power law scaling (i.e., frequency components become more homogenous) at four brain regions: left precuneus, left medial dorsal nucleus, right inferior frontal gyrus, and right middle temporal gyrus, compared with healthy participants. Additionally, schizophrenia exhibited less positive power law scaling (i.e., frequency components are more dominant at lower frequency range) in bilateral putamen. Significant correlations of power law scaling with the severity of psychosis were found in these identified brain areas in schizophrenia. These findings suggest that schizophrenia has abnormal brain signal complexity toward random patterns, which is linked to psychotic symptoms. The power law scaling analysis may serve as a novel functional brain imaging marker for evaluating patients with mental illness.

neuroscience↗