Biology subjects

Biswal, B.

Publications and source records attributed to Biswal, B..

18 recordsLinked to original sources

bioRxiv2026

LINE-1 Retrotransposon Activation and 5-Gene Dysregulation as a Common Pathological Signature in Post-Traumatic and Status Epilepticus Models of Epilepsy.

The transition from an initial brain insult to chronic epilepsy remains a critical challenge in clinical neuroscience, often involving complex molecular shifts that are difficult to capture through single-gene analysis. This study investigated the existence of a convergent pathway of genomic instability across two distinct etiological models: iron-induced (FeCl3) post-traumatic epilepsy (PTE) and lithium-pilocarpine-induced (LiCl-Pilo) status epilepticus (SE). By integrating Electrophysiology (EEG), {gamma}-oscillation spectral analysis, multi-unit activity (MUA) recordings with behavioural assessments Morris Water Maze (MWM) and Open Field Test (OFT) we validated and established the chronic hyperexcitability and associated cognitive- emotional co-morbidities of these two models. Which further served as a functional backdrop for investigating a targeted 8-gene panel consisting of GABRA2, KCNN2, KCNAB1, GRIK1, BCL11A, BRD7, STX1B, and PNPO. RT-PCR analysis demonstrated a systemic dysregulation of 5 genes out of these 8 genes, mirroring the simultaneous collapse of inhibitory signalling, membrane stability, and neurotransmitter metabolism seen in human phenotypes. While the clinical roles of these genes are well documented, our study demonstrates that these rat models provide a high-fidelity platform for complex multigene studies and gene-level therapeutic exploration. Furthermore, in-silico docking identified Fisetin as a high-affinity ligand for the dysregulated proteins, offering a promising multi-target strategy for stabilizing the epileptic genome.

neuroscience↗

bioRxiv2025

Resting-State fMRI and the Risk of Overinterpretation: Noise, Mechanisms, and a Missing Rosetta Stone

Resting-state fMRI has generated influential insights into large-scale brain organization and contributed to clinically relevant applications, largely through correlation-based measures of cross-regional association in BOLD responses. At the same time, interpreting these statistical associations as reflecting underlying neural interactions requires careful consideration of fundamental methodological constraints. Here, we distinguish two fundamental but often conflated limitations. The first is measurement distortion: the fMRI signal is an indirect and heterogeneous measurement of neural activity, arising from neurovascular coupling, physiology, and measurement-related processes, which can introduce systematic and incompletely characterized biases into estimated correlations. The second is causal non-identifiability: even if correlations perfectly reflected neural synchrony, the resulting correlation structure would not uniquely determine the underlying neural interactions. Using causal reasoning, simulations, and analytic arguments, we distinguish these limitations and examine their consequences for interpretation. Although both apply broadly to fMRI, their implications are particularly important in resting-state analyses, where correlation structure is the primary object of inference in the absence of experimental perturbation. We show that measurement-related biases can distort estimated correlations (e.g., attenuating or in-flating associations and affecting group comparisons) and can produce reproducible patterns that do not necessarily reflect underlying neural relationships, highlighting that statistical reliability does not guarantee biological validity. We further show that graph-theoretic, geometric, and other higher-order representations derived from these correlations do not, by themselves, justify mechanistic interpretation. We argue not against the utility of resting-state fMRI, but for greater precision in interpretation. Our conclusions concern the interpretation of correlation-based analyses rather than their methodological utility. Distinguishing measurement distortion from causal non-identifiability clarifies the inferential boundaries separating descriptive association, predictive utility, and mechanistic interpretation.

neuroscience↗

bioRxiv2024

Connecting the Dots: Approaching a Standardized Nomenclature for Molecular Connectivity Combining Data and Literature

PET-based connectivity computation is a molecular approach that complements fMRI-derived functional connectivity. However, the diversity of methodologies and terms employed in PET connectivity analysis has resulted in ambiguities and confounded interpretations, highlighting the need for a standardized nomenclature. Drawing parallels from other imaging modalities, we propose "molecular connectivity" as an umbrella term to characterize statistical dependencies between PET signals across brain regions at the individual level (within-subject). Like fMRI resting-state functional connectivity, "molecular connectivity" leverages temporal associations in the PET signal to derive brain network associations. Another within-subject approach evaluates regional similarities of tracer kinetics, which are unique in PET imaging, thus referred to as "kinetic connectivity". On the other hand, "molecular covariance" denotes group-level computations of covariance matrices across-subject. Further specification of the terminology can be achieved by including the employed radioligand, such as "metabolic connectivity/covariance" for [18F]FDG as well as "tau/amyloid covariance" for [18F]flutemetamol / [18F]flortaucipir. To augment these distinctions, high-temporal resolution functional [18F]FDG PET scans from 17 healthy participants were analysed with common techniques of molecular connectivity and covariance, allowing for a data-driven support of the above terminology. Our findings demonstrate that temporal band-pass filtering yields structured network organization, whereas other techniques like 3rd order polynomial fitting, spatio-temporal filtering and baseline normalization require further methodological refinement for high-temporal resolution data. Conversely, molecular covariance from across-subject data provided a simple means to estimate brain region interactions through regularized or sparse inverse covariance estimation. A standardized nomenclature in PET-based connectivity research can reduce ambiguity, enhance reproducibility, and facilitate interpretability across radiotracers and imaging modalities. Via a data-driven approach, this work provides a transparent framework for categorizing and comparing PET-derived connectivity and covariance metrics, laying the foundation for future investigations in the field.

neuroscience↗

bioRxiv2024

Brain activation during the N-back working memory task in individuals with spinal cord injury: a functional near-infrared spectroscopy study

Cognitive impairments have frequently been reported in individuals with spinal cord injury (SCI) across different domains such as working memory, attention, and executive function. The mechanism of cognitive impairment after SCI is not well understood due to the heterogeneity of SCI sample populations, and may possibly be due to factors such as cardiovascular dysfunction, concomitant traumatic brain injury (TBI), hypoxia, sleep disorders, and body temperature dysregulation. In this study, we implement the Neuropsychiatric Unit Cognitive Assessment Tool (NUCOG) to assess cognitive differences between individuals with SCI and age-matched able-bodied (AB) controls. We then use an N-back working memory task and functional near-infrared spectroscopy (fNIRS) to elucidate the neurovascular correlates of cognitive function in individuals with SCI. We observed significant differences between the SCI and AB groups on measures of executive function on the NUCOG test. On the N-back task, across the three levels of difficulty: 0-back, 2-back, and 3-back, no significant differences were observed between the SCI and AB group; however, both groups performed worse as the level of difficulty increased. Although there were no significant differences in N-back performance scores between the two groups, functional brain hemodynamic activity differences were observed between the SCI and AB groups, with the SCI group exhibiting higher maximum oxygenated hemoglobin concentration in the right inferior parietal lobe. These findings support the use of fNIRS to study cognitive function in individuals with SCI and may provide a useful tool during rehabilitation to obtain quantitative functional brain activity metrics.

neuroscience↗

bioRxiv2024

Explorations of using a convolutional neural network to understand brain activations during movie watching

Neuroimaging studies increasingly use naturalistic stimuli like video clips to trigger complex brain activations, but the complexity of such stimuli makes it difficult to assign specific functions to the resulting brain activations, particularly for higher-level content like social interactions. To address this challenge, researchers have turned to deep neural networks, e.g., convolutional neural networks (CNNs). CNNs have shown success in image recognition due to their different levels of features enabling high performance. In this study, we used pre-trained VGG-16, a popular CNN model, to analyze video data and extract hierarchical features from low-level shallow layers to high-level deeper layers, linking these activations to different levels of activation of the human brain. We hypothesized that activations in different layers of VGG-16 would be associated with different levels of brain activation and visual processing hierarchy in the brain. We were also curious about which brain regions would be associated with deeper convolutional layers in VGG-16. The study analyzed a functional MRI (fMRI) dataset where participants watched the cartoon movie Partly Cloudy. Frames of the videos were fed into VGG-16, and activation maps from different kernels and layers were extracted. Time series of the average activation patterns for each kernel were created and fed into a voxel-wise model to study brain activations. Results showed that lower convolutional layers (1st convolutional layer) were mostly associated with lower visual regions, but some kernels (6, 19, 24, 42, 55, and 58) surprisingly showed associations with activations in the posterior cingulate cortex, part of the default mode network. Deeper convolutional layers were associated with more anterior and lateral portions of the visual cortex (e.g., the lateral occipital complex) and the supramarginal gyrus. Analyzing activation features associated with different brain regions showed the promise and limitations of using CNNs to link video content to brain functions.

neuroscience↗

bioRxiv2023

Chemical inhibition of histidine biosynthesis curtails M. tuberculosis infection

To overcome the drug resistance crisis and shorten the current duration of human tuberculosis (TB) therapy, new anti-TB molecules is required. In an earlier study, we have shown that Mycobacterium tuberculosis (Mtb), the causative agent of TB, with a fractured de novo histidine biosynthesis fails to mount TB infection in mouse model, emboldening that disrupting the function of this pathway may constitute a novel strategy to curtailing TB infection. In this study, through a target based approach we have designed a number of triazole scaffold molecules specific to imidazole glycerol phosphate dehydratase (IGPD; HisB) of this pathway and have delineated atomic level interactions between the enzyme and inhibitors which pinpointed the specificity and the inhibitory mechanism. Importantly, these molecules exhibited significant potency against free as well as macrophage-internalized wild-type and drug-resistant clinical isolates in culture medium. Notably, a couple of these compounds showed efficacy in reducing the bacterial burden in Mtb-infected mouse model. The chemical inhibition of IGPD induces histidine auxotrophy in Mtb and brings in new prospects to the area of anti-TB drug discovery.

biochemistry↗

bioRxiv2023

Iron chelation by deferoxamine as useful adjunct therapeutics in murine tuberculosis.

Dysregulated iron metabolism is reported in tuberculosis patients; therefore, it represents an opportunity for developing host-directed therapeutics. This study monitored the antimycobacterial properties of an iron chelator, i.e., Deferoxamine (DFO/D), and its impact on the transcript and metabolite levels of Mycobacterium tuberculosis (Mtb) in vitro. For in vivo validation, a group of mice received ferric carboxymaltose to create an iron overload condition, and controls were aerosol-infected with Mtb H37Rv. Mtb-infected mice received isoniazid (INH/H) and rifampicin (RIF/R) in combination with or without DFO before tissue-specific CFU assay, liver metabolite screening and iron quantification using mass spectrometry. DFO showed antimycobacterial properties comparable to INH in vitro. DFO treatment deregulated (log2DFO/control>{+/-}1.0) Mtb transcript (n=137) levels, the majority of which encode for iron-containing proteins and proteins involved in stress response. DFO treatment up-regulated Rv3622c (PE32), Rv2353c (PPE39) and Rv3022A (PE29) genes and conditional knocking down of ABC transporter like irtA by anhydrotetracycline (Atc) inducible CRISPR interference (CRISPRi) approach compromised Mtb growth showing their potential involvement in iron metabolism. Global Mtb metabolite analysis using GC-MS identified a set of 5 deregulated metabolites indicating a perturbed pentose phosphate pathway and inositol phosphate metabolism in the host upon DFO treatment. Iron-overloaded mice exhibited significantly higher tissue mycobacterial burden at two weeks post-infection, and the efficacy of INH and RIF were compromised, corroborating with previous reports. Iron chelation by DFO or combined with/adjunct to RIF and INH significantly reduced the lung/tissue mycobacterial burden at four weeks post-treatment, specifically in the first ([~]0.5 log) and second weeks ([~]0.5 log) of treatment. The intracellular pro-inflammatory cytokine levels in the lung CD4+ T cells of INH and RIF-treated groups with or without DFO were similar, suggesting DFO has a direct role in Mtb survival and metabolism rather than improved infection, and the efficacy of INH and RIF were compromised, corroborating with previous reports. DFO adjunct to RIF and INH treatment significantly altered liver arginine biosynthesis, which directly neutralizes ammonia and is immune-supportive. Conventionally, DFO is used for treating acute iron toxicity that is common in thalassemic patients, and this study demonstrates DFO has potential as adjunct therapeutics for tuberculosis. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/543389v3_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@5066fdorg.highwire.dtl.DTLVardef@99a292org.highwire.dtl.DTLVardef@80426dorg.highwire.dtl.DTLVardef@892436_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Neurovascular reactivity increases across development in the visual and frontal pole networks as revealed by a breath-holding task: a longitudinal fMRI study

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold task is commonly used to understand cerebrovascular reactivity in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal childrens breath-hold dataset from the Nathan Kline Institute (NKI) Rockland Sample (ages 6 to 18 years old at enrollment). A general linear model (GLM) approach was applied to derive cerebrovascular reactivity from breath-hold data. To model both the longitudinal and cross-sectional effects of age on breath-hold response, we used mixed effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased breath-hold BOLD signal in multiple networks across age, in which linear and logarithmic mixed effects models provided the best fit with the lowest Akaike Information Criterion (AIC) scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes which occur with age.

neuroscience↗

bioRxiv2022

ALFF Response Interaction With Learning During Feedback in Individuals With Multiple Sclerosis

Amplitude of low-frequency fluctuations (ALFF) is defined as changes of BOLD signal during resting state (RS) brain activity. Previous studies identified differences in RS activation between healthy and multiple sclerosis (MS) participants. However, no research has investigated the relationship between ALFF and learning in MS. We thus examine this here. Twenty-five MS and 19 healthy participants performed a paired-associate word learning task where participants were presented with extrinsic or intrinsic performance feedback. Compared to healthy participants, MS participants showed higher local brain activation in the right thalamus. We also observed a positive correlation in the MS group between ALFF and extrinsic feedback within the left inferior frontal gyrus, and within the left superior temporal gyrus in association with intrinsic feedback. Healthy participants showed a positive correlation in the right fusiform gyrus between ALFF and extrinsic feedback. Findings suggest that while MS participants do not show a feedback learning impairment compared to the healthy participants, ALFF differences might suggest a general maladaptive pattern of task unrelated thalamic activation and adaptive activation in frontal and temporal regions. Results indicate that ALFF can be successfully used at capturing pathophysiological changes in local brain activation in MS in association with learning through feedback.

neuroscience↗

bioRxiv2022

Assessing functional connectivity differences and work-related fatigue in surviving COVID-negative patients.

The Coronavirus Disease 2019 (COVID-19) has affected all aspects of life around the world. Neuroimaging evidence suggests the novel coronavirus can attack the central nervous system (CNS), causing cerebro-vascular abnormalities in the brain. This can lead to focal changes in cerebral blood flow and metabolic oxygen consumption rate in the brain. However, the extent and spatial locations of brain alterations in COVID-19 survivors are largely unknown. In this study, we have assessed brain functional connectivity (FC) using resting-state functional MRI (RS-fMRI) in 38 (25 males) COVID patients two weeks after hospital discharge, when PCR negative and 31 (24 males) healthy subjects. FC was estimated using independent component analysis (ICA) and dual regression. When compared to the healthy group, the COVID group demonstrated significantly enhanced FC in the basal ganglia and precuneus networks (family wise error (fwe) corrected, pfwe < 0.05), while, on the other hand, reduced FC in the language network (pfwe < 0.05). The COVID group also experienced higher fatigue levels during work, compared to the healthy group (p < 0.001). Moreover, within the precuneus network, we noticed a significant negative correlation between FC and fatigue scores across groups (Spearmans {rho} = - 0.47, p = 0.001, r2 = 0.22). Interestingly, this relationship was found to be significantly stronger among COVID survivors within the left parietal lobe, which is known to be structurally and functionally associated with fatigue in other neurological disorders. Significance StatementEarly neuroimaging studies have mostly focused on structural MRI imaging to report brain abnormalities in acutely ill COVID-19 patients. It is not clear whether functional abnormalities co-exist with structural alterations in patients who have survived the infection and have been discharged from the hospital. A few recent studies have emerged which attempted to address the structural/functional alterations. However, further investigations across different sites are necessary for more conclusive inference. More importantly, fatigue is a highly prevalent symptom among COVID survivors, therefore, the relations of brain imaging abnormalities to fatigue should be investigated. In this study, we try to address these gaps, by collecting imaging data from COVID survivors, now PCR negative, and healthy subjects from a single site - the Indian Institute of Technology (IIT), Delhi, India. Furthermore, this is a continuation of an ongoing study. We have recently shown structural abnormalities and stronger gray matter volume (GMV) correlates of self-reported fatigue in this group of COVID survivors compared to healthy subjects (Hafiz et al., 2022).

neuroscience↗

bioRxiv2021

Common and distinct neurofunctional representations of core and social disgust in the brain: An ALE meta-analysis and MACM characterization

Disgust represents a multifaceted defensive-avoidance response. On the behavioral level, the response includes withdrawal and a disgust-specific facial expression. While both serve the avoidance of pathogens, the latter additionally transmits social-communicative information. Given that common and distinct brain representation of the primary defensive-avoidance response (core disgust) and encoding of the social-communicative signal (social disgust) remain debated, we employed neuroimaging meta-analyses to (1) determine brain systems generally engaged in disgust processing, and (2) segregate common and distinct brain systems for core and social disgust. Disgust processing, in general, engaged a bilateral network encompassing the insula, amygdala, occipital and prefrontal regions. Core disgust evoked stronger reactivity in left-lateralized threat detection and defensive response network including amygdala, occipital and frontal regions while social disgust engaged a right-lateralized superior temporal-frontal network engaged in social cognition. Anterior insula, inferior frontal and fusiform regions were commonly engaged during core and social disgust, suggesting a common neural basis. We demonstrate a common and separable neural basis of primary disgust responses and encoding of associated social-communicative signals.

neuroscience↗

bioRxiv2021

Laminar-specific interhemispheric connectivity mapping with bilateral line-scanning fMRI

Despite extensive studies detecting blood-oxygen-level-dependent (BOLD) fMRI signals across two hemispheres to present cognitive processes in normal and diseased brains, the role of corpus callosum (CC) to mediate interhemispheric functional connectivity remains controversial. Several studies show maintaining low-frequency fluctuation of resting-state (rs)-fMRI signals in homotopic brain areas of acallosal humans and post-callosotomy animals, raising the question: how can we specify the circuit-specific rs-fMRI signal fluctuation from other sources? To address this question, we have developed a bilateral line-scanning fMRI (BiLS) method to detect bilateral laminar BOLD fMRI signals from symmetric cortical regions with high spatial (100 m) and temporal (100 ms) resolution in rodents under anesthesia. In addition to ultra-slow oscillation (0.01-0.02 Hz) patterns across all cortical layers, a layer-specific bilateral coherence pattern was observed with a peak at Layer (L)2/3, where callosal projection neurons are primarily located and reciprocal transcallosal projections are received. In particular, the L2/3-specific coherence pattern showed a peak at 0.05 Hz based on the stimulation paradigm, depending on the interhemispheric CC activation. Meanwhile, the L2/3-specific rs-fMRI coherence was peaked at 0.08-0.1Hz which was independent of the varied ultra-slow oscillation patterns (0.01-0.02 Hz) presumably involved with global neuromodulation. This work provides a unique laminar fMRI mapping scheme to characterize the CC-mediated evoked fMRI and frequency-dependent rs-fMRI responses, presenting crucial evidence to distinguish the circuit-specific fMRI signal fluctuations across two hemispheres. Significance statementLaminar fMRI is a promising method to better understand neuronal circuit contribution to functional connectivity (FC) across cortical layers. Here, we developed a bilateral line-scanning fMRI method, allowing the detection of laminar-specific BOLD-fMRI signals from homologous cortical regions in rodents with high spatial and temporal resolution. Laminar coherence patterns of both evoked and rs-fMRI signals revealed that CC-dependent interhemispheric FC is significantly strong at Layer 2/3, where callosal projection neurons are primarily located. The Layer 2/3-specific rs-fMRI coherence is independent of ultra-slow oscillation based on global neuromodulation, distinguishing the circuit-specific rs-fMRI signal fluctuation from different regulatory sources.

neuroscience↗

bioRxiv2021

Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2

Apart from the canonical fingers, palm and thumb domains, the RNA dependent RNA polymerases (RdRp) from the viral order Nidovirales possess two additional domains. Of these, the function of the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) remains unanswered. The elucidation of the 3D structure of RdRp from the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), provided the first ever insights into the domain organisation and possible functional characteristics of the NiRAN domain. Using in silico tools, we predict that the NiRAN domain assumes a kinase or phosphotransferase like fold and binds nucleoside triphosphates at its proposed active site. Additionally, using molecular docking we have predicted the binding of three widely used kinase inhibitors and five well characterized anti-microbial compounds at the NiRAN domain active site along with their drug-likeliness as well as DFT properties. For the first time ever, using basic biochemical tools, this study shows the presence of a kinase like activity exhibited by the SARS-CoV-2 RdRp. Interestingly, the proposed kinase inhibitors and a few of the predicted nucleotidyl transferase inhibitors significantly inhibited the aforementioned enzymatic activity. In line with the current global COVID-19 pandemic urgency and the emergence of newer strains with significantly higher infectivity, this study provides a new anti-SARS-CoV-2 drug target and potential lead compounds for drug repurposing against SARS-CoV-2.

bioinformatics↗

bioRxiv2020

Molecular basis of the logical evolution of the novel coronavirus SARS-CoV-2: A comparative analysis

A novel disease, COVID-19, is sweeping the world since end of 2019. While in many countries, the first wave is over, but the pandemic is going through its next phase with a significantly higher infectability. COVID-19 is caused by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that seems to be more infectious than any other previous human coronaviruses. To understand any unique traits of the virus that facilitate its entry into the host, we compared the published structures of the viral spike protein of SARS-CoV-2 with other known coronaviruses to determine the possible evolutionary pathway leading to the higher infectivity. The current report presents unique information regarding the amino acid residues that were a) conserved to maintain the binding with ACE2 (Angiotensin-converting enzyme 2), and b) substituted to confer an enhanced binding affinity and conformational flexibility to the SARS-CoV-2 spike protein. The present study provides novel insights into the evolutionary nature and molecular basis of higher infectability and perhaps the virulence of SARS-CoV-2.

evolutionary biology↗

bioRxiv2020

Dynamic Configuration of Coactive Micropatterns in the Default Mode Network during Wakefulness and Sleep

The default mode network (DMN) is a prominent intrinsic network that is observable in many mammalian brains. However, few studies have investigated the temporal dynamics of this network based on direct physiological recordings. Herein, we addressed this issue by characterizing the dynamics of local field potentials (LFPs) from the rat DMN during wakefulness and sleep with an exploratory analysis. We constructed a novel coactive micropattern (CAMP) algorithm to evaluate the configurations of rat DMN dynamics and further revealed the relationship between DMN dynamics with different wakefulness and alertness levels. From the gamma activity (40-80 Hz) in the DMN across wakefulness and sleep, three spatially stable CAMPs were detected: a common low-activity level micropattern (cDMN), an anterior high-activity level micropattern (aDMN) and a posterior high-activity level micropattern (pDMN). A dynamic balance across CAMPs emerged during wakefulness and was disrupted in sleep stages. In the slow-wave sleep (SWS) stage, cDMN became the primary activity pattern, whereas aDMN and pDMN were the major activity patterns in the rapid eye movement sleep (REM) stage. Additionally, further investigation revealed phasic relationships between CAMPs and the up-down states of the slow DMN activity in the SWS stage. Our study revealed that the dynamic configurations of CAMPs were highly associated with different stages of wakefulness and provided a potential three-state model to describe the DMN dynamics for wakefulness and alertness. Impact StatementIn the current study, a novel coactive micropattern method (CAMP) was developed to elucidate fast DMN dynamics during wakefulness and sleep. Our findings demonstrated that the dynamic configurations of DMN activity are specific to different wakefulness stages and provided a three-state DMN CAMP model to depict wakefulness levels, thus revealing a potentially new neurophysiological representation of alertness levels. This work could elucidate the DMN dynamics underlying different stages of wakefulness and have important implications for the theoretical understanding of the neural mechanism of wakefulness and alertness.

bioinformatics↗

bioRxiv2018

Oxytocin modulates the intrinsic dynamics between attention-related large scale networks

Attention and salience processing have been linked to the intrinsic between- and within-network dynamics of large scale networks engaged in internal (default mode network, DN) and external attention allocation (dorsal attention, DAN, salience network, SN). The central oxytocin (OXT) system appears ideally organized to modulate widely distributed neural systems and to regulate the switch between internal attention and salient stimuli in the environment. The current randomized placebo (PLC) controlled between-subject pharmacological resting-state fMRI study in N = 187 (OXT, n = 94; n = 93; single-dose intranasal administration) healthy male and female participants employed an independent component analysis (ICA) approach to determine the modulatory effects of OXT on the within- and between-network dynamics of the DAN-SN-DN triple network system. OXT increased the functional integration between subsystems within SN and DN and increased functional segregation of the DN with the SN and DAN engaged in attentional control. Whereas no sex differences were observed, OXT effects on the DN-SN interaction were modulated by autism traits. Together, the findings suggest that OXT may facilitate efficient attentional allocation towards social cues by modulating the intrinsic functional dynamics between DN components engaged in social processing and large-scale networks involved in external attentional demands (SN, DAN).

neuroscience↗

bioRxiv2018

Functional connectivity mechanisms subserving automatic emotion regulation by implementation intention

Automatic emotion regulation (AER) has received increasing attention. However, the effortless hypothesis of AER has yet to be directly tested and the neural mechanisms supporting AER remain unclear. Here, we addressed these two issues, by simultaneous recording behavioral assessments and functional MRI (fMRI) signals when thirty-one participants were required to watch neutral and disgust pictures in three experimental conditions: Watching, Goal Intention (GI) and Reappraisal by Implementation Intention (RII). RII decreased negative feelings and bilateral amygdala activity without engendering cognitive efforts, evidenced by the reduced self-reported efforts and less prefrontal engagement during RII compared to Watching and GI. These regulation effects should not be explained by emotional habituation, as further experiment did not show significant emotional habituation for the repetition of the same stimuli. Moreover, RII and GI produced similar functional connectivity (FC) of vACC (ventral anterior cingulate cortex) to left insula and right precuneus, corresponding to the common goal pursuit component of both strategies. Furthermore, RII relative to GI exhibited weaker FC in distributed brain networks subserving effortful control (e.g. inferior-superior parietal lobe FC), memory retrieval (e.g. inferior-middle temporal lobes and lingual-putamen FCs), aversive anticipation and emotion-related motor planning (e.g. putamen-operculum and vACC-supramarginal gyrus FCs). These findings suggest that RII downregulates disgust effortlessly, most likely mediated by the reduced online mobilization of neural systems subserving emotion-related coping.

neuroscience↗

bioRxiv2017

Assessment of the impact of shared data on the scientific literature

Data sharing is increasingly recommended as a means of accelerating science by facilitating collaboration, transparency, and reproducibility. While few oppose data sharing philosophically, a range of barriers deter most researchers from implementing it in practice (e.g., workforce and infrastructural demands, sociocultural and privacy concerns, lack of standardization). To justify the significant effort required for sharing data (e.g., organization, curation, distribution), funding agencies, institutions, and investigators need clear evidence of benefit. Here, using the International Neuroimaging Data-sharing Initiative, we present a brain imaging case study that provides direct evidence of the impact of open sharing on data use and resulting publications over a seven-year period (2010-2017). We dispel the myth that scientific findings using shared data cannot be published in high-impact journals and demonstrate rapid growth in the publication of such journal articles, scholarly theses, and conference proceedings. In contrast to commonly used pay to play models, we demonstrate that openly shared data can increase the scale (i.e., sample size) of scientific studies conducted by data contributors, and can recruit scientists from a broader range of disciplines. These findings suggest the transformative power of data sharing for accelerating science and underscore the need for the scientific ecosystem to embrace the challenge of implementing data sharing universally.

bioinformatics↗