Biology subjects

Powell, M.

Publications and source records attributed to Powell, M..

18 recordsLinked to original sources

bioRxiv2026

Cervical spinal cord stimulation disrupts proprioception yet improves voluntary arm reaching

Whether proprioception is necessary for upper-limb motor control has been debated for decades. Classic studies in deafferented animals and humans suggested that proprioception may be dispensable for rapid, goal-directed movements. However, chronic sensory loss conflates the absence of proprioceptive input with years of compensatory adaptation. As a result, the field has lacked a strong causal test of proprioceptions contribution to motor control. Here, we leveraged a clinical trial of cervical spinal cord stimulation (SCS) in individuals with chronic post-stroke hemiparesis to study if electrical stimulation of sensory afferents causally perturbs proprioception and affects arm reaching. We found that turning SCS ON causally impaired proprioceptive perception and postural stabilization in response to force perturbations, and enhanced adaptation to visual errors during implicit learning. Yet visually and non-visually rapid, goal-directed reaching improved in smoothness, straightness and spatial accuracy. These findings provide strong causal evidence that proprioception is not required for rapid, goal-directed action, helping resolve a decades-long debate regarding its necessity for effective movement.

bioengineering↗

bioRxiv2026

Machine learning-based image analysis of Parkinson's disease iPS-derived neurons predicts genotype and reveals mitochondria-lysosome abnormalities

Mitochondrial and lysosomal dysfunction are central features of Parkinsons disease (PD) across major genetic forms including PRKN, SNCA, and LRRK2. We applied cell morphomics, a machine-learning-based framework combining high-content imaging with quantitative feature extraction, to analyse mitochondrial and lysosomal morphology at single-cell resolution in iPS cell-derived cortical neurons from PD patients and healthy controls (13 lines total). Supervised machine-learning models distinguished PD neurons from controls with high accuracy (AUC = 0.87) and reliably separated individual genotypes. Feature importance and attribution analysis revealed genotype-specific organelle biases, with mitochondrial features dominating classification in PRKN neurons, balanced mitochondrial and lysosomal contributions in SNCA neurons, and a greater lysosomal contribution in LRRK2 neurons. Multi-class models retained strong performance, and findings were reproduced across two independent laboratories using different dyes and imaging conditions. These results demonstrate that morphomics provides a robust and scalable framework to quantify genotype-specific organelle abnormalities in PD neurons and supports its application for cellular stratification and biomarker discovery.

neuroscience↗

bioRxiv2025

Targeting the COP9 signalosome overcomes platinum resistance in ovarian cancer through two distinct genome stability mechanisms

Tubo-ovarian high-grade serous carcinoma (HGSC) is a leading cause of gynecologic cancer mortality, largely due to the emergence of platinum resistance, which serves as the mainstay of chemotherapy. Here, we identify COPS5 as a therapeutic target and use an available small molecule inhibitor to overcome platinum resistance. A genetic screen for platinum-induced DNA damage in a platinum resistant ovarian cancer model identified COPS5 and COPS6, two components of the COP9 signalosome. Consistently, high COPS5 expression correlated with poor clinical outcomes in patients with HGSC. In both in vitro and in vivo experiments, COPS5 depletion sensitized ovarian cancer cells to carboplatin. A small molecule COPS5 inhibitor, CSN5i-3, synergized with carboplatin in homologous recombination-deficient and -proficient cells. This combination was also effective in xenografts and in a syngeneic mouse model of carboplatin-resistant HGSC. Importantly, we demonstrate that CSN5i-3 is selective for cancer cells, with patient-derived HGSC cells exhibiting up to 50-fold greater sensitivity to CSN5i-3 than benign cells. Finally, we show that genetic or small molecule inhibition of COPS5 impaired both nucleotide excision repair (NER) and interstrand crosslink (ICL) repair, leading to increased DNA platinum adducts. Mechanistically, this was due to increased ubiquitination and degradation of DNA-specific DNA binding protein 1 (DDB1) and other key NER and ICL repair proteins, consistent with the role of COPS5 in the regulation of these factors. Our findings highlight the importance of NER and ICL regulation in chemotherapy response and indicate that targeting COPS5 can enhance the efficacy of platinum-based chemotherapy in HGSC. One Sentence SummaryCOPS5 depletion or inhibition using a small molecule COPS5 inhibitor CSN5i-3 sensitizes high-grade serous carcinoma to platinum chemotherapy through downregulation of nucleotide excision repair and interstrand crosslink repair.

cancer biology↗

bioRxiv2024

Replication stress marker phospho-RPA2 predicts response to platinum and PARP inhibitors in homologous recombination-proficient ovarian cancer

BackgroundOvarian cancer treatment includes cytoreductive surgery, platinum-based chemotherapy, and often poly (ADP-ribose) polymerase (PARP) inhibitors. Homologous recombination (HR)-deficiency is a well-established predictor of therapy sensitivity. However, over 50% of HR-proficient tumors also exhibit sensitivity to standard-of-care treatments. Currently, there are no biomarkers to identify which HR-proficient tumors will be sensitive to standard-of-care therapy. Replication stress may serve as a key determinant of response. MethodsWe evaluated phospho-RPA2-T21 (pRPA2) foci via immunofluorescence as a potential biomarker of replication stress in formalin-fixed, paraffin-embedded tumor samples collected at diagnosis from patients treated with platinum chemotherapy (discovery cohort: n = 31, validation cohort: n = 244) or PARP inhibitors (n = 87). Recurrent tumors (n = 37) were also analyzed. pRPA2 scores were calculated using automated imaging analysis. Samples were defined as pRPA2-High if > 16% of cells had [≥] 2 pRPA2 foci. ResultsIn the discovery cohort, HR-proficient, pRPA2-High tumors demonstrated significantly higher rates of pathologic complete response to platinum chemotherapy than HR-proficient, pRPA2-Low tumors. In the validation cohort, patients with HR-proficient, pRPA2-High tumors had significantly longer survival after platinum treatment than those with HR-proficient, pRPA2-Low tumors. Additionally, the pRPA2 assay effectively predicted survival outcomes in patients treated with PARP inhibitors and in recurrent tumor samples. ConclusionOur study underscores the importance of considering replication stress markers alongside HR status in therapeutic planning. Our work suggest that this assay could be used throughout a patients treatment course to expand the number of patients receiving effective therapy while reducing unnecessary toxicity.

cancer biology↗

bioRxiv2024

Intrauterine Growth-Restricted Pregnant Rats, from Hypertensive Placental Ischemic Dams Display Preeclamptic-like Symptoms: A New Rodent Model of Preeclampsia

Preeclampsia (PE) is characterized by de novo hypertension (HTN) and is one of the primary causes of intrauterine growth restriction (IUGR). PE is associated with placental ischemia, decreased nitric oxide (NO) bioavailability, oxidative stress (OS), and organ damage in the kidneys and brain. This study aims to characterize a new model of PE using IUGR rats from hypertensive placental ischemic dams. It is hypothesized that pregnant IUGR rats from hypertensive placental ischemic dams will have elevated blood pressure (BP), OS, and organ damage. MethodsPregnant Sprague Dawley rats are divided into 2 groups: normal pregnant (NP) and reduced uterine perfusion pressure (RUPP) hypertensive placental ischemic dams. Offspring from NP and RUPP dams were mated at 10 weeks of age to generate pregnant IUGR (IUGR Preg; n=3-8) and pregnant CON (CON Preg; n=3-6) rats. BP and other markers of PE were evaluated during late gestation. ResultsPregnant IUGR rats had elevated BP and systemic OS, as demonstrated by higher trending 8-isoprostanes and lower circulating antioxidant capacity. Maternal body weight of pregnant IUGR rats and their pups weights were decreased, while the brains were enlarged. Brain OS was elevated, with a rise in hydrogen peroxide (H2O2) and heat shock protein 1 (HSP- 1), along with lower Manganese Superoxide Dismutase (MnSOD) and antioxidant capacity. ConclusionPregnant IUGR rats, born from hypertensive placental ischemic dams, have HTN and increased systemic and brain OS, with larger brain sizes and smaller pups. Pregnant IUGR rats exhibit an preeclamptic-like phenotype, which suggests a new epigenetic model of PE.

physiology↗

bioRxiv2023

An AAV capsid reprogrammed to bind human Transferrin Receptor mediates brain-wide gene delivery

Developing vehicles that efficiently deliver genes throughout the human central nervous system (CNS) will broaden the range of treatable genetic diseases. We engineered an AAV capsid, BI-hTFR1, that binds human Transferrin Receptor (TfR1), a protein expressed on the blood-brain barrier (BBB). BI-hTFR1 was actively transported across a human brain endothelial cell layer and, relative to AAV9, provided 40-50 times greater reporter expression in the CNS of human TFRC knock-in mice. The enhanced tropism was CNS-specific and absent in wild type mice. When used to deliver GBA1, mutations of which cause Gaucher disease and are linked to Parkinsons disease, BI-hTFR1 substantially increased brain and cerebrospinal fluid glucocerebrosidase activity compared to AAV9. These findings establish BI-hTFR1 as a promising vector for human CNS gene therapy.

neuroscience↗

bioRxiv2023

Human Connectomes Are Heritable

A complete understanding of human behavior and disease depends upon our ability to parse genetic and environmental influences in the human brain. The heritability of a trait quantifies the degree of its variability due to genetic influences. Classical approach for quantifying heritability operate on simple traits, and sometimes do not properly control for other potential sources of variation, such as age or sex. We therefore develop Causal Heritability of Networks (CHaiN) to rigorously quantify heritability of human brain networks (i.e., connectomes). We applied CHaiN to 1024 anatomical connectomes derived from the Human Connectome Project. Connectomes appeared to be heritable, but heritability was insignificant once we addressed variability within networks. These results suggest that previous conclusions on connectome heritability may be driven by the shared network structures, and highlights the importance of modeling networks and other sources of variability when studying heritability of connectomes.

neuroscience↗

bioRxiv2022

Systematic multi-trait AAV capsid engineering for efficient gene delivery

Broadening gene therapy applications requires manufacturable vectors that efficiently transduce target cells in humans and preclinical models. Conventional selections of adeno-associated virus (AAV) capsid libraries are inefficient at searching the vast sequence space for the small fraction of vectors possessing multiple traits essential for clinical translation. Here, we present Fit4Function, a generalizable machine learning (ML) approach for systematically engineering multi-trait AAV capsids. By leveraging a capsid library that evenly samples the manufacturable sequence space, reproducible screening data are generated to train accurate sequence-to-function models. Combining six models, we designed a multi-trait (liver-targeted, manufacturable) capsid library and validated 89% of library variants on all six predetermined criteria. Furthermore, the models, trained only on mouse in vivo and human in vitro Fit4Function data, accurately predicted AAV capsid variant biodistribution in macaque. Top candidates exhibited high production yields, efficient murine liver transduction, up to 1000-fold greater human hepatocyte transduction, and increased enrichment, relative to AAV9, in a screen for liver transduction in macaques. The Fit4Function strategy ultimately makes it possible to predict cross-species traits of peptide-modified AAV capsids and is a critical step toward assembling an ML atlas that predicts AAV capsid performance across dozens of traits.

synthetic biology↗

bioRxiv2022

Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome

Comparing connectomes can help explain how neural connectivity is related to genetics, disease, development, learning, and behavior. However, making statistical inferences about the significance and nature of differences between two networks is an open problem, and such analysis has not been extensively applied to nanoscale connectomes. Here, we investigate this problem via a case study on the bilateral symmetry of a larval Drosophila brain connectome. We translate notions of "bilateral symmetry" to generative models of the network structure of the left and right hemispheres, allowing us to test and refine our understanding of symmetry. We find significant differences in connection probabilities both across the entire left and right networks and between specific cell types. By rescaling connection probabilities or removing certain edges based on weight, we also present adjusted definitions of bilateral symmetry exhibited by this connectome. This work shows how statistical inferences from networks can inform the study of connectomes, facilitating future comparisons of neural structures.

neuroscience↗

bioRxiv2022

Impact of cellular prion protein expression on disease progression and pathology in two mouse models of Alzheimer's disease

The aggregation of amyloid-{beta} (A{beta}) monomers increases their neurotoxicity, and these oligomeric species are thought to be central to the pathogenesis of Alzheimers disease. Unsurprisingly for such a complex disease, current Alzheimers disease mouse models fail to fully mimic the clinical disease in humans. Moreover, results obtained in a given mouse model are not always reproducible in a different model. Cellular prion protein (PrPC) is now an established receptor for A{beta} oligomers. However, different groups studying the A{beta}-PrPC interaction in vivo using a variety of mouse models have obtained contradictory results. Here we performed a longitudinal study in two commonly used AD mouse models using a range of biochemical, histological and behavioural techniques and found similar contradictory results and a possible explanation for the discrepancy. We propose that these two mouse models produce A{beta} oligomers with different conformations. Therefore, binding to PrPC and the subsequent activation of toxic signalling cascade will occur only when the A{beta} oligomer species with appropriate conformation are present. Hence, it is crucial to select the appropriate model producing the appropriate species of A{beta} oligomers to study specific aspects of {beta}-amyloidosis and its downstream pathways. Further conformational characterisation of A{beta} oligomers and their binding to PrPC is required to better understand A{beta} neurotoxicity.

neuroscience↗

bioRxiv2022

Saving the Devils is in the details: Tasmanian Devil facial tumor disease can be eliminated with interventions

AO_SCPLOWBSTRACTC_SCPLOWTasmanian Devils facial tumor disease is severely impacting the population of this wild animal. We developed a computational model of the population of Tasmanian Devils, and the change induced by DFTD. We use this model to test possible intervention strategies Tasmanian conservationists could do. We investigate bait drop vaccination programs, diseased animal removals programs, and evolution of natural immunity. We conclude that a combination of intervention strategies gives the most favorable outcome. An additional goal of this paper is for reproducibility of our results. Our StochSS software platform features the ability to share and reproduce the computational notebooks that created all of the results in the paper. We endeavor that all readers should be able to reproduce our results with minimum effort.

ecology↗

bioRxiv2022

A hierarchical genotyping framework using DNA melting temperatures applied to adenovirus species typing

Known genetic variation for a pathogen, in conjunction with post-PCR melting curve analysis, can be leveraged to provide increased taxonomic detail for pathogen identification in commercial molecular diagnostic tests. The increased taxonomic detail may be used by clinicians and public health decision makers to observe circulation patterns, monitor for outbreaks, and inform local testing practices. We propose a method for expanding the taxonomic resolution of PCR diagnostic systems by incorporating a priori knowledge of the assay design and publicly available sequence information into a genotyping classification model. For multiplexed PCR systems, this framework is generalized to incorporate information from multiple assays that react with different gene targets of the same pathogen to increase classification accuracy. To illustrate the method, a hierarchical classification model is developed for the BioFire(R) Respiratory 2.1 Panel and the BioFire(R) Respiratory 2 Panel (collectively the BioFire Respiratory Panels - highly multiplexed PCR diagnostic tests) to predict the species of human adenovirus (HAdV) from Adenovirus Detected test results. Performance of the classification model was characterized via a 10-fold cross-validation on a labeled dataset and exhibited 95% {+/-} 4% accuracy. The model was then applied to the BioFire(R) Syndromic Trends dataset, which contains deidentified patient test data from BioFire Respiratory Panels collected at over 100 sites across the globe since 2015. Adenovirus Detected test results in BioFire Syndromic Trends were classified to produce predicted prevalence of each HAdV species within the United States from 2018 through 2021. These results show a marked change in both the predicted prevalence for HAdV and the species makeup with the onset of the COVID-19 pandemic. In particular, HAdV-B decreased from a pre-pandemic predicted prevalence of up to 40% to less than 5% in 2021, while HAdV-A and HAdV-F species both increased in predicted prevalence. Author SummaryIn the diagnosis of infectious disease there is often a trade-off between time to result, cost, and the amount of information gained about the pathogen. We develop a method that can provide increased genotypic information about a pathogen in a test result, with no additional time or cost. Our method is applied to the BioFire Respiratory(R) 2.1 Panel and the BioFire Respiratory(R) 2 Panel to speciate positive test results for adenovirus. The method shows robust performance in correctly identifying the adenovirus species from the test results. We estimate the prevalence of each adenovirus species in the United States by applying this method to adenovirus positive test results in the BioFire Syndromic Trends network. This information can be used in near real-time to augment the Centers for Disease Control and Prevention efforts to monitor adenovirus species circulation. Our mathematical framework can be generalized to other genotyping applications.

molecular biology↗

bioRxiv2021

Batch Effects are Causal Effects: Applications in Human Connectomics

Batch effects, undesirable sources of variability across multiple experiments, present significant challenges for scientific and clinical discoveries. Batch effects can (i) produce spurious signals and/or (ii) obscure genuine signals, contributing to the ongoing reproducibility crisis. Because batch effects are typically modeled as classical statistical effects, they often cannot differentiate between sources of variability due to confounding biases, which may lead them to erroneously conclude batch effects are present (or not). We formalize batch effects as causal effects, and introduce algorithms leveraging causal machinery, to address these concerns. Simulations illustrate that when non-causal methods provide the wrong answer, our methods either produce more accurate answers or "no answer", meaning they assert the data are an inadequate to confidently conclude on the presence of a batch effect. Applying our causal methods to 27 neuroimaging datasets yields qualitatively similar results: in situations where it is unclear whether batch effects are present, non-causal methods confidently identify (or fail to identify) batch effects, whereas our causal methods assert that it is unclear whether there are batch effects or not. In instances where batch effects should be discernable, our techniques produce different results from prior art, each of which produce results more qualitatively similar to not applying any batch effect correction to the data at all. This work therefore provides a causal framework for understanding the potential capabilities and limitations of analysis of multi-site data.

neuroscience↗

bioRxiv2021

Target Enrichment Enhances the Sensitivity of Sanger Sequencing for BRAF V600 Mutation Detection

BRAF is a serine/threonine protein kinase whose mutations lead to unregulated cell growth and cause different types of cancers. Since V600E is a major BRAF mutation and V600E detection as a companion diagnostic test (CDx) is stipulated in the labeling of the BRAF V600 inhibitors. Traditional Sanger sequencing cannot accurately detect mutations lower than 15% variant allele frequency (VAF) due to its limited sensitivity. Here we applied our patented XNA molecular clamping technology to modify Sanger sequencing template preparation by enriching the mutation population. We found that the use of our mutation-enriched template enhanced the analytical sensitivity of Sanger sequencing to 0.04% VAF. The method is verified to detect V600E, V600K, and V600R mutants and is validated for the known BRAF mutation status in clinical samples. Our streamlined protocol can be used for easy validation of the highly sensitive target-enrichment method for detecting BRAF V600 mutations using Sanger sequencing in clinical labs. In addition to BRAF V600 mutations, this method can be extended to the detection of other clinically important actionable mutations for cancer diagnostics.

molecular biology↗

bioRxiv2021

Natural variation in the irld gene family affects insulin/IGF signaling and starvation resistance

Starvation resistance is important to disease and fitness, but the genetic basis of its natural variation is unknown. We developed a synthetic-population (re)sequencing approach using molecular inversion probes (MIP-seq) to measure relative fitness during and after larval starvation in C. elegans. We applied this competitive assay to 100 genetically diverse, sequenced, wild strains, revealing natural variation in starvation resistance. We confirmed that the most starvation-resistant strains survive and recover from starvation better than the most starvation-sensitive strain, MY2147, using standard assays. We performed genome-wide association with the MIP-seq trait data and identified three quantitative trait loci (QTL) for starvation resistance. These QTL contain several members of the Insulin/EGF Receptor-L Domain (irld) family with sequence variation associated with variation in starvation resistance. We used genome editing to show that individual modification of four irld genes increases starvation resistance of MY2147. Modification of irld-39 and irld-52 together increases starvation resistance of the laboratory-reference strain N2. Increased starvation resistance of the irld-39; irld-52 double mutant depends on daf-16/FoxO, and these worms also show increased nuclear localization of DAF-16 during starvation. DAF-16/FoxO is a widely conserved transcriptional effector of insulin/IGF signaling (IIS), and these results suggest that IRLD proteins modify IIS. This work demonstrates efficacy of using MIP-seq to dissect a complex trait, identifies irld genes as natural modifiers of starvation resistance in C. elegans, and suggests that an expanded gene family affects a deeply conserved signaling pathway to alter a fitness-proximal trait.

genetics↗

bioRxiv2020

Pericytes Directly Communicate with Emerging Endothelial Cells During Vasculogenesis

SummaryPericytes (PCs), cells that extend along capillaries to contribute stability and other critical functions to established vasculature, are attracting attention from various fields involving vascular-related pathologies. Here, we demonstrate primary evidence of PC communication with endothelial cells (ECs) prior to tube coalescence. Observations of apparent PCs during early embryogenesis urged development of a mouse embryonic stem cell line (DR-ESCs), enabling unique dual-reporter investigations into earliest PC-EC interactions. Live imaging of differentiating DR-ESCs corroborated emergence of a PC lineage, which preceded EC differentiation, and further revealed highly dynamic PC-EC interactions during coordinated vessel formation. We show direct PC-EC communication via cell microinjection and dye-transfer, and RNA-seq analysis indicates a PC-EC coupling mechanism via gap junction Connexin43 (Cx43), exclusively up-regulated throughout DR-ESC differentiation. High resolution imaging of embryonic and postnatal mouse vasculature substantiates Cx43 plaques at PC-EC borders. These findings indicate a new role for PCs during vasculogenesis via Cx43-mediated communication with ECs.Competing Interest StatementThe authors have declared no competing interest.View Full Text

developmental biology↗

bioRxiv2020

A Novel Xenonucleic Acid Mediated Molecular Clamping Technology for Early Colorectal Cancer Screening

BackgroundColorectal cancer (CRC) is one of the leading causes of cancer-related death. Early detection is critical to reduce CRC morbidity and mortality. In order to meet this need, we developed a molecular clamping assay called the ColoScape for early colorectal cancer diagnostics. MethodsNineteen mutations in four genes APC, KRAS, BRAF and CTNNB1 associated with early events in CRC pathogenesis are targeted in the ColoScape assay. Xenonucleic Acid (XNA) mediated qPCR clamping technology was applied to minimize the wild-type background amplification in order to improve assay sensitivity of CRC mutation detection. The assay analytical performance was verified and validated, cfDNA and FFPE CRC patient samples were evaluated, and a ROC cure was applied to evaluate its performance. ResultsThe data showed that the assay analytical sensitivity is 0.5% Variant Allele Frequency, corresponding to ~7-8 copies of mutant DNA with 5ng total DNA input per test. This assay is highly reproducible with intra-assay CV <3% and inter-assay <5%. We have investigated 380 clinical samples including plasma cfDNA and FFPE samples from patients with precancerous and different stages of CRC. The preliminary assay clinical specificity and sensitivity for CRC cfDNA were 100% (95% CI, 80.3-97.5%) and 92.2% (95% CI, 94.7-100%) respectively with AUC being about 0.96; and 96% (95% CI, 77.6-99.7%) specificity and 92% (95% CI, 86.1-95.6%) sensitivity with AUC 0.94 for CRC FFPE; and 95% specificity (95% CI, 82.5%-99.1%) and 62.5% sensitivity (95% CI, 35.8%-83.7%) with AUC 0.79 for precancerous lesions cfDNA. ConclusionsXNA mediated molecular clamping assay is a rapid, precise, and sensitive assay for the detection of precancerous lesions cfDNA and CRC cfDNA or FFPE samples.

cancer biology↗

bioRxiv2017

Local Connectome Phenotypes Predict Social, Health, and Cognitive Factors

The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N=841) of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP) maps that could reliably predict a subset of subject attributes measured, including demographic, health and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions.\n\nAuthor SummaryThe local connectome is the pattern of fiber systems (i.e., number of fibers, orientation, and size) within a voxel and reflects the proximal characteristics of white matter fascicles distributed throughout the brain. Here we show how variability in the local connectome is correlated in a principled way across individuals. This inter-subject correlation is reliable enough that unique phenotype maps can be learned to predict between-subject variability in a range of social, health, and cognitive attributes. This work shows, for the first time, how shared variability across individuals is reflected in the local connectome.

neuroscience↗