Biology subjects

Salman, M.

Publications and source records attributed to Salman, M..

16 recordsLinked to original sources

bioRxiv2026

Hippocampal subfield macrostructure and myelination demonstrate distinct maturational signatures

The hippocampus is essential for learning and memory and undergoes prolonged development throughout childhood and adolescence. Evidence concerning hippocampal maturation is based primarily on volumetric measures. However, macrostructural growth and myelination processes may represent distinct biological processes. Using Hippunfold, we quantified hippocampal subfield volumes and myelin-sensitive tissue concentrations as proxies for tissue maturation using T1w/T2w ratios in 175 community-recruited participants aged 9 months to 21 years. Hippocampal subfield volumes were best described by quadratic developmental trajectories, whereas T1w/T2w ratios increased linearly with age across all subfields. Males exhibited larger hippocampal volumes, and females demonstrated higher and steeper age-related increases in T1w/T2w ratios. Sex-related hippocampal subfield differences were observed despite largely comparable cognitive and behavioural profiles. Hippocampal subfield volumes and myelin follow distinct developmental pathways, revealing sex-specific patterns of development that are not fully captured by morphology alone.

neuroscience↗

bioRxiv2026

Low testosterone promotes anxiety through astrocytic mitochondrial remodelling at the nucleus accumbens blood-brain barrier

Low testosterone is linked to anxiety in men, but its causal role and underlying brain mechanisms remain unknown. Here, using outbred male rats stratified by natural variation in anxiety-like behaviour, we establish its causal endocrine contribution and uncover an astrocytic mitochondrial mechanism at the nucleus accumbens (NAc) blood-brain barrier (BBB). High-anxiety rats showed a NAc-selective increase in BBB permeability, alongside reduced astrocytic endfoot coverage, disrupted endfoot mitochondrial organisation and mitochondria-endoplasmic reticulum contacts, and lower mitofusin 2 (Mfn2). Testosterone suppression increased anxiety in low-anxiety rats, whereas physiological testosterone restoration reduced anxiety, reconfigured astrocytic mitochondrial and BBB-related transcriptional programmes, increased astrocytic endfoot coverage and Mfn2, recovering BBB permeability, with related effects in aged low-testosterone rats. NAc androgen receptor (AR) knockdown blunted behavioural and neurovascular responses, whereas NAc astrocyte-specific Mfn2 overexpression reduced anxiety. Thus, testosterone-AR signalling engages an astrocytic mitochondrial programme at the NAc neurovascular interface linking low testosterone to anxiety vulnerability.

neuroscience↗

bioRxiv2026

Assessing the impact of gamma irradiation on key biological traits of peach fruit fly, Bactrocera zonata (Diptera: Tephritidae) under laboratory conditions

Bactrocera zonata (Saunders) (Diptera: Tephritidae) poses a significant threat to global fruit production due to its high reproductive capacity and broad host range. This study aimed to evaluate the effects of gamma irradiation on key biological parameters of B. zonata. Six-day-old pupae were exposed to irradiation doses of 0, 30, 40, 50, 60, and 70 Gy, and subsequent developmental and reproductive traits were assessed to determine the impact of irradiation. Post-irradiation results revealed a dose-dependent trend. Higher doses ([≥]50 Gy) significantly reduced adult emergence, increased the incidence of partially emerged or deformed adults, and shortened adult longevity. Reproductive potential was significantly impaired in males irradiated at 60 and 70 Gy when mated with un-irradiated females, resulting in a marked decline in both fecundity and egg hatchability. Females irradiated at doses [≥]50 Gy failed to produce eggs when paired with either irradiated or non-irradiated males, indicating a high level of radio-sensitivity in female flies. Additionally, several traits in the F1 generation such as pupal recovery, pupal size, and adult development exhibited significant abnormalities and suggesting that the effects of irradiation may be transmitted to the next generation. Sterility was highest in males irradiated at 60 and 70 Gy, while females exhibited complete sterility at doses exceeding 40 Gy. The findings indicate that a dose of 70 Gy may be optimal for effective sterility induction in B. zonata. However, further detailed studies are required to standardize this dose, incorporating rigorous quality control measures to optimize its application in sterile insect technique (SIT) programs.

zoology↗

bioRxiv2026

Light-driven repair: Photobiomodulation restores blood brain barrier function following hypoxic injury

A functional blood-brain barrier (BBB) is essential for the central nervous system (CNS) homeostasis and its disruption is an early event in acute brain injury and chronic neurodegeneration. Hypoxia triggers BBB breakdown, promoting endothelial dysfunction, oxidative stress, metabolic dysregulation and thrombo-inflammatory responses that compromise barrier integrity. However, strategies that directly restore BBB function remain limited. Here, we investigated whether photobiomodulation (PBM), a non-invasive light therapy, can rescue BBB dysfunction following acute hypoxic stress. Using a multicellular in vitro BBB model comprising immortalised human brain microvascular endothelial cells, pericytes and astrocytes, we induced hypoxic injury (6 h, 1% O2) and applied three PBM treatments during recovery. Hypoxia significantly reduced transendothelial electrical resistance (TEER), whereas PBM restored barrier function in endothelial monocultures and tri-cultures. Endothelial cells showed the strongest hypoxic response, with increased hypoxia-inducible factor-1, plasminogen activator inhibitor-1 and von Willebrand factor (vWF), all attenuated by PBM. Importantly, siRNA-mediated knockdown of vWF partially recapitulated PBM-induced barrier rescue, identifying endothelial vWF as a mediator of recovery. PBM also reduced reactive oxygen species in hypoxic astrocytes and pericytes, indicating coordinated multicellular modulation. These findings demonstrate that PBM restores BBB integrity after hypoxic insult by modulating endothelial thrombo-inflammatory signalling while reducing oxidative stress in glial cells. Rather than acting as a general cytoprotective stimulus, PBM engages defined molecular pathways linked to endothelial activation. This work establishes a mechanistically informed platform for studying BBB repair and supports PBM as a targeted strategy to protect vascular integrity in hypoxia-associated neurological disorders. Key points summaryO_LIHypoxia is a major driver of blood-brain barrier (BBB) dysfunction, yet there are currently no targeted therapies that directly restore barrier integrity. C_LIO_LIPhotobiomodulation (PBM) is a non-invasive low-level light intervention known to facilitate mitochondrial function and cellular stress responses. C_LIO_LIIn a human in vitro BBB model, repeated PBM treatment restored transendothelial electrical resistance (TEER) 24 and 48 hours after hypoxic injury, with endothelial rescue linked to downregulation of von Willebrand factor (vWF). C_LIO_LIPBM modulated oxidative stress, hypoxia signalling, and thrombo-inflammatory pathways across endothelial cells, astrocytes, and pericytes. C_LIO_LIThese findings support light-driven modulation of endothelial signalling as a potential strategy to restore BBB integrity in hypoxia-associated neurological conditions. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/706027v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@987f1corg.highwire.dtl.DTLVardef@1c12d86org.highwire.dtl.DTLVardef@193ea8dorg.highwire.dtl.DTLVardef@bf8d2_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

Membrane curvature association of amphipathic helix 8 drives constitutive GPCR endocytosis

Cellular signaling relies on the activity of transmembrane receptors and their presentation on the cellular surface. Their continuous insertion in the plasma membrane is balanced by constitutive and activity dependent internalization, which is orchestrated by adaptor proteins recognizing semi-specific motifs within the receptors intracellular regions. Here we describe a complementary and evolutionary conserved and refined trafficking mechanism for G-protein coupled receptors (GPCR). This mechanism relies on the insertion of their amphipathic helix 8 into the inner leaflet of lipid membranes, orthogonal to the transmembrane helices. These amphipathic helices dictate subcellular localization of the receptors and autonomously drive their endocytosis by cooperative assembly and association with areas of high membrane curvature. The strength of helix 8 membrane insertion propensity quantitatively predicts the rate of constitutive internalization of GPCRs. This discovery advances our understanding of membrane protein trafficking and highlights a new principle of receptor-lipid interactions that may have broader implications for cellular signaling and therapeutic targeting. One-Sentence SummaryReceptor proteins navigate cellular membranes by interacting with their curvature using an evolutionary conserved mechanism that relies on amphipathic helices and complements direct coupling to the endocytic protein machinery.

cell biology↗

bioRxiv2024

An array of Zymoseptoria tritici effectors suppress plant immune responses

Zymoseptoria tritici is the most economically significant fungal pathogen of wheat in Europe. However, despite the importance of this pathogen, the molecular interactions between pathogen and host during infection are not well understood. Herein, we describe the use of two libraries of cloned Z. tritici effectors that were screened to identify effector candidates with putative pathogen associated molecular pattern (PAMP) triggered immunity (PTI)-suppressing activity. The effectors from each library were transiently expressed in Nicotiana benthamiana, and expressing leaves were treated with bacterial or fungal PAMPs to assess the effectors ability to suppress reactive oxygen species (ROS) production. From these screens, numerous effectors were identified with PTI-suppressing activity. In addition, some effectors were able to suppress cell death responses induced by other Z. tritici secreted proteins. We used structural prediction tools to predict the putative structures of all of the Z. tritici effectors, and used these predictions to examine whether there was enrichment of specific structural signatures among the PTI-suppressing effectors. From among the libraries, multiple members of the killer protein-like 4 (KP4) and killer protein-like 6 (KP6) effector families were identified as PTI-suppressors. This observation is intriguing, as these protein families were previously associated with antimicrobial activity rather than virulence or host manipulation. This data provides mechanistic insight into immune suppression by Z. tritici during infection, and suggests that similar to biotrophic pathogens, this fungus relies on a battery of secreted effectors to suppress host immunity during early phases of colonisation.

plant biology↗

bioRxiv2022

Canonical and Replicable Multi-Scale Intrinsic Connectivity Networks in 100k+ Resting-State fMRI Datasets

Resting-state functional magnetic resonance imaging (rsfMRI) has shown considerable promise for improving our understanding of brain function and characterizing various mental and cognitive states in the healthy and disordered brain. However, the lack of accurate and precise estimations of comparable functional patterns across datasets, individuals, and ever-changing brain states in a way that captures both individual variation and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. We posit that using reliable network templates and advanced group-informed network estimation approaches to accurately and precisely obtain individualized (dynamic) networks that retain cross-subject correspondence while maintaining subject-specific information is one potential solution to overcome the aforementioned barrier when considering cross-study comparability, independence of subject-level estimates, the limited data available in single studies, and the low signal-to-noise ratio (SNR) of rsfMRI. Toward this goal, we first obtained a reliable and replicable network template. We combined rsfMRI data of over 100k individuals across private and public datasets and selected around 58k that meet quality control (QC) criteria. We then applied multi-model-order independent component analysis (ICA) and subsampling to obtain reliable canonical intrinsic connectivity networks (ICNs) across multiple spatial scales. The selected ICNs (i.e., network templates) were also successfully replicated by independently analyzing the data that did not pass the QC criteria, highlighting the robustness of our adaptive template to data quality. We next studied the feasibility of estimating the corresponding subject-specific ICNs using a multivariate-spatially constrained ICA as an example of group-informed network estimation approaches. The results highlight that several factors, including ICNs themselves, data length, and spatial resolution, play key roles in successfully estimating the ICNs at the subject level. Large-scale ICNs, in general, require less data to achieve a specific level of spatial similarity with their templates (as well as within- and between-subject spatial similarity). Moreover, increasing data length can reduce an ICNs subject-level specificity, suggesting longer scans might not always be desirable. We also show spatial smoothing can alter results, and the positive linear relationship we observed between data length and spatial smoothness (we posit that it is at least partially due to averaging over intrinsic dynamics or individual variation) indicates the importance of considering this factor in studies such as those focused on optimizing data length. Finally, the consistency in the spatial similarity between ICNs estimated using the full-length of data and subset of it across different data lengths may suggest that the lower within-subject spatial similarity in shorter data lengths is not necessarily only defined by lower reliability in ICN estimates; rather, it can also be an indication of brain dynamics (i.e., different subsets of data may reflect different ICN dynamics), and as we increase the data length, the result approaches the average (also known as static) ICN pattern, and therefore loses its distinctiveness.

neuroscience↗

bioRxiv2022

Genomic Characterization of Sars-Cov-2 from Islamabad Pakistan by Rapid Nanopore Sequencing

Since the start of COVID-19 pandemic, Pakistan has experienced four waves of pandemic. The fourth wave ended in October, 2021 while the fifth wave of pandemic starts in January, 2022. The data regarding the circulating strains after the fourth wave of pandemic from Pakistan is not available. The current study explore the genomic diversity of SARS-CoV-2 after fourth wave and before fifth wave of pandemic through whole genome sequencing. The results showed the circulation of different strains of SARS-CoV-2 during November-December, 2021. We have Omicron BA.1 (n=4), Lineage A (n=2) and delta AY.27 (n=1) variants of SARS-CoV-2 in the population of Islamabad. All the isolates harbors characteristics mutations of omicron and delta variant in the genome. The lineage A isolate harbors a nine amino acid (68-76) and a ten amino acid (679-688) deletion in the genome. The circulation of omicron in the population before the fifth wave of pandemic and subsequent upsurges of COVID-19 positive cases in Pakistan highlights the importance of genomic surveillance.

molecular biology↗

bioRxiv2021

A Computational Dissection of Spike protein of SARS-CoV-2 Omicron Variant

The emergence of SARS-CoV-2 omicron variant in late November, 2021 and its rapid spread to different countries, warns the health authorities to take initiative to work on containing its spread. The omicron SARS-CoV-2 variant is unusual from the other variants of concerns reported earlier as it harbors many novel mutations in its genome particularly with >30 mutations in the spike glycoprotein alone. The current study investigated the variation in binding mechanism which it carries compared to the wild type. The study also explored the interaction profile of spike-omicron with human ACE2 receptor. The structure of omicron spike glycoprotein was determined though homology modeling. The interaction analysis was performed through docking using HADDOCK followed by binding affinity calculation. Finally, the comparison of interactions were performed among spike-ACE2 complex of wild type, delta and omicron variants. The interaction analysis has revealed the involvement of highly charged and polar residues (H505, Arg498, Ser446, Arg493, and Tyr501) in the interactions. The important novel interactions in the spike-ACE2-omicron complex was observed as S494:H34, S496:D38, R498:Y41, Y501:K353, and H505:R393 and R493:D38. Moreover, the binding affinity of spike-ACE2-omicron complex (-17.6Kcal/mol) is much higher than wild type-ACE2 (-13.2Kcal/mol) and delta-ACE2 complex (-13.3Kcal/mol). These results indicate that the involvement of polar and charged residues in the interactions with ACE2 may have an impact on increased transmissibility of omicron variant.

bioinformatics↗

bioRxiv2021

Exploration of Antibacterial Activities of Berberis royleana Fractions Extracts

ObjectivesPrepare various solvent extracts of Berberis royleana (areal part of plant) to determine the in vitro antibacterial potential of methanolic, ethyl acetate, chloroform, n-hexane and water extracts of B. royleana against various bacterial isolates and Compare the efficacy of outstanding antimicrobial extracts of B. royleana with commonly used antibiotics. Berberis species are medicinally important plants, produce various metabolites and used as treatment for multiple complications. Berberis royleana is a rare specie belongs to genus Berberis. MethodsIn the current study the areal parts of the plant were isolated to explore antibacterial activities. Antibacterial activities were done using standard procedures. The antibacterial activities of different fractions were tested by 100 g methanolic, ethyl acetate, chloroform, n-hexane and water fractions of B. royleana against bacterial isolates Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella Typhi and Proteus spp. The ciprofloxacin (5g) was used as a positive control and DMSO as a negative control. ResultsAll fractions showed zone of inhibition against the growth of tested bacterial isolates. Methanolic fractions have maximum ZI against S. aureus and K. pneumoniae (25.7{+/-}1.5 mm), S. aureus (23{+/-}2.7), Salmonella Typhi (25{+/-}1), water fraction have Klebsiella pneumoniae (24.4 {+/-}2.5), Salmonella Typhi (23 {+/-}1 mm), S. aureus (21{+/-}2.8 mm) and the n-hexane fraction exhibits ZI against K. pneumoniae (24.7{+/-}1.5), Salmonella Typhi (24{+/-}2) S. aureus, ethyl acetate maximum zone against E. coli (16.6{+/-}3.1) and chloroform fraction showed maximum ZI against S. Typhi (21.6{+/-}3.3). ConclusionFrom current report it may be concluded that B. royleana extracts have medicinally effective potentials against drugs resistant bacteria.

microbiology↗

bioRxiv2021

Individualized Spatial Network Predictions Using Siamese Convolutional Neural Networks: A Resting-State fMRI Study of over 11,000 Unaffected Individuals

Individuals can be characterized in a population according to their brain measurements and activity, given the inter-subject variability in brain anatomy, structure-function relationships, or life experience. Many neuroimaging studies have demonstrated the potential of functional network connectivity patterns estimated from resting functional magnetic resonance imaging (fMRI) to discriminate groups and predict information about individual subjects. However, the predictive signal present in the spatial heterogeneity of brain connectivity networks is yet to be extensively studied. In this study, we investigate, for the first time, the use of pairwise-relationships between resting-state independent spatial maps to characterize individuals. To do this, we develop a deep Siamese framework comprising three-dimensional convolution neural networks for contrastive learning based on individual-level spatial maps estimated via a fully automated fMRI independent component analysis approach. The proposed framework evaluates whether pairs of spatial networks (e.g., visual network and auditory network) are capable of subject identification and assesses the spatial variability in different network pairs predictive power in an extensive whole-brain analysis. Our analysis on nearly 12,000 unaffected individuals from the UK Biobank study demonstrates that the proposed approach can discriminate subjects with an accuracy of up to 88% for a single network pair on the test set (best model, after several runs), and 82% average accuracy at the subcortical domain level, notably the highest average domain level accuracy attained. Further investigation of our networks learned features revealed a higher spatial variability in predictive accuracy among younger brains and significantly higher discriminative power among males. In sum, the relationship among spatial networks appears to be both informative and discriminative of individuals and should be studied further as putative brain-based biomarkers.

neuroscience↗

bioRxiv2020

An in-vitro BBB-on-a-chip open model of human blood-brain barrier enabling advanced optical imaging

ABSTRACTWe describe here the design and implementation of an in-vitro BBB-on-a-chip open model system capable of reconstituting the microenvironment of the blood brain barrier. This system allows controlled unidirectional flow of nutrients and biologicals on the lumen of the artificial microvessel. This BBB-on-a-chip is suitable for high resolution electron microscopy and it is amenable for quantitative 3D live fluorescence imaging using spinning confocal disk or lattice light sheet microscopy (LLSM) to follow, for example the transcytosis across the BBB-like barrier of fluorescently-tagged biological, viruses or nanoparticles.Competing Interest StatementG.M. and B.O. are employees and shareholders of Biogen. T.K. is a visiting scientist at Biogen.View Full Text

bioengineering↗

bioRxiv2020

Development Optimization and Validation of RT-LAMP based COVID-19 Facility in Pakistan

The pandemic SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) has created a widespread panic across the globe especially in the developing countries like Pakistan. The lack of resources and technical staff are causing havoc challenges in the detection and prevention of this global outbreak. Therefore, a less expensive and massive screening of suspected individuals for COVID-19 is required. In this study, a user-friendly technique of reverse transcription-loop mediated isothermal amplification (RT-LAMP) was designed and validated to suggest a potential RT-qPCR alternate for rapid testing of COVID-19 suspected individuals. A total of 12 COVID-19 negative and 72 COVID-19 suspected individuals were analyzed. Both RT-qPCR and RT-LAMP assays were performed for all the individuals using open reading frame (ORF 1ab), nucleoprotein (N) and Spike (S) genes. All 12 specimens which were negative using RT-qPCR were also found negative using RT-LAMP assay. Overall 62 out of 72 positive samples (detected using RT-qPCR) were found COVID-19 positive using RT-LAMP assay. Interestingly all samples (45) having Ct values less than 30 showed 100% sensitivity. However, samples with weaker Ct values (i.e., => 35) showed 54% concordance, suggesting potential false negatives or false positives in RT-LAMP or RT-qPCR results, respectively. Overall comparative assessment showed that RT-LAMP assay showed strong sensitivity and specificity and can be used as an alternative strategy for rapid COVID-19 testing. Hence, based on fast processing time, minimal risk of specimens transfer and utilizing available resources, LAMP based detection of COVID-19 is strongly advocated especially for developing countries.

molecular biology↗

bioRxiv2020

Rapid and sensitive direct detection and identification of poliovirus from stool and environmental surveillance samples using nanopore sequencing

Global poliovirus surveillance involves virus isolation from stool and environmental samples, intratypic differential (ITD) by PCR and sequencing of the VP1 region to distinguish vaccine (Sabin), vaccine-derived and wild-type polioviruses and ensure an appropriate response. This cell-culture algorithm takes 2-3 weeks on average between sample receipt and sequencing. Direct detection of viral RNA using PCR allows faster detection but has traditionally faced challenges related to poor sensitivity and difficulties in sequencing common samples containing poliovirus and enterovirus mixtures. We present a nested PCR and nanopore sequencing protocol that allows rapid (<3 days) and sensitive direct detection and sequencing of polioviruses in stool and environmental samples. We developed barcoded primers and a real-time analysis platform that generate accurate VP1 consensus sequences from multiplexed samples. The sensitivity and specificity compared with cell-culture were 90.9% (95% Confidence Interval: 75.7-98.1%) and 99.2% (95.5-100.0%) for wild-type 1 poliovirus, 92.5% (79.6-98.4%) and 98.7% (95.4-99.8%) for vaccine and vaccine-derived serotype 2 poliovirus, and 88.3% (81.2-93.5%) and 93.2% (88.6-96.3%) for Sabin 1 and 3 poliovirus alone or in mixtures when tested on 155 stool samples in Pakistan. Variant analysis of sequencing reads also allowed identification of polioviruses and enteroviruses in artificial mixtures and was able to distinguish complex mixtures of polioviruses in environmental samples. The median identity of consensus nanopore sequences with Sanger or Illumina sequences from the same samples was >99.9%. This novel method shows promise as a faster and safer alternative to cell-culture for the detection and real-time sequencing of polioviruses in stool and environmental samples.

microbiology↗

bioRxiv2020

Hype versus hope: Deep learning encodes more predictive and robust brain imaging representations than standard machine learning

Previous successes of deep learning (DL) approaches on several complex tasks have hugely inflated expectations of their power to learn subtle properties of complex brain imaging data, and scale to large datasets. Perhaps as a reaction to this inflation, recent critical commentaries unfavorably compare DL with standard machine learning (SML) approaches for the analysis of brain imaging data. Yet, their conclusions are based on pre-engineered features which deprives DL of its main advantage: representation learning. Here we evaluate this and show the importance of representation learning for DL performance on brain imaging data. We report our findings from a large-scale systematic comparison of SML approaches versus DL profiled in a ten-way age and gender-based classification task on 12,314 structural MRI images. Results show that DL methods, if implemented and trained following the prevalent DL practices, have the potential to substantially improve compared to SML approaches. We also show that DL approaches scale particularly well presenting a lower asymptotic complexity in relative computational time, despite being more complex. Our analysis reveals that the performance improvement saturates as the training sample size grows, but shows significantly higher performance throughout. We also show evidence that the superior performance of DL is primarily due to the excellent representation learning capabilities and that SML methods can perform equally well when operating on representations produced by the trained DL models. Finally, we demonstrate that DL embeddings span a comprehensible projection spectrum and that DL consistently localizes discriminative brain biomarkers, providing an example of the robustness of prediction relevance estimates. Our findings highlight the presence of non-linearities in brain imaging data that DL frameworks can exploit to generate superior predictive representations for characterizing the human brain, even with currently available data sizes.

neuroscience↗

bioRxiv2019

Parallel Group ICA + ICA: Joint Estimation of Linked Functional Network Variability and Structural Covariation with Application to Schizophrenia

There is growing evidence that rather than using a single brain imaging modality to study its association with physiological or symptomatic features, the field is paying more attention to fusion of multimodal information. However, most current multimodal fusion approaches that incorporate functional magnetic resonance imaging (fMRI) are restricted to second-level 3D features, rather than the original 4D fMRI data. This trade-off is that the valuable temporal information is not utilized during the fusion step. Here we are motivated to propose a novel approach called \"parallel group ICA+ICA\" that incorporates temporal fMRI information from GICA into a parallel ICA framework, aiming to enable direct fusion of first-level fMRI features with other modalities (e.g. structural MRI), which thus can detect linked functional network variability and structural covariations. Simulation results show that the proposed method yields accurate inter-modality linkage detection regardless of whether it is strong or weak. When applied to real data, we identified one pair of significantly associated fMRI-sMRI components that show group difference between schizophrenia and controls in both modalities. Finally, multiple cognitive domain scores can be predicted by the features identified in the linked component pair by our proposed method. We also show these multimodal brain features can predict multiple cognitive scores in an independent cohort. Overall, results demonstrate the ability of parallel GICA+ICA to estimate joint information from 4D and 3D data without discarding much of the available information up front, and the potential for using this approach to identify imaging biomarkers to study brain disorders.

bioinformatics↗