Biology subjects

Bassett, D.

Publications and source records attributed to Bassett, D..

8 recordsLinked to original sources

bioRxiv2026

Development of the cognitive energy landscape from infancy to adolescence

Brain networks mature in a hierarchical sequence that parallels the emergence of cognitive functions. However, precisely how brain structural maturation supports the ordered development of cognitive functions remains largely unknown. Here, leveraging network control theory and 3712 developmental diffusion magnetic resonance imaging scans, we investigate how the brains structural effort to activate cognitive states -- quantified as control energy -- changes from infancy through adolescence. A total of 100 cognitive states were defined as meta-analytic activation maps from NeuroSynth, prioritized by their frequency in major neurodevelopmental behavioral assessments. We show that the control energy to drive most cognitive tasks decreases during development (for 96 out of 100 cognitive states). Ages to achieve optimal energy efficiency for each state concentrate around school age and late adolescence, whereas social and perceptual functions reach efficiency earlier (mean optimal age = 100.2 months) than higher-order cognitive functions (mean optimal age = 205.5 months). Further, we estimated the influence of molecular-level neurodevelopmental events on control energy by coupling control inputs to each events gene expression profile. We find that such influences vary in both temporal breadth and cognitive scope. Prenatal events (neuron differentiation and migration) exert effects mostly in infancy, while the prolonged process of myelination shapes the energy landscape across all developmental periods and the widest range of cognitive domains. Moreover, the transition energy architecture remains stable across development but becomes progressively modularized, such that transitions within the same category of cognitive states become increasingly favored. Together, these findings provide a comprehensive growth chart of how brain structural maturation supports the hierarchical emergence of cognitive abilities across early life, and establish a normative framework that enables systematic approaches to activate targeted brain circuits and facilitate selective cognitive transitions.

Developmental Biology↗

bioRxiv2025

Neuronal activity and amyloid-beta cause tau seeding in the entorhinal cortex in Alzheimer's disease

The entorhinal cortex is the earliest site of tau pathology in both Alzheimers disease and primary age-related tauopathy, yet the mechanisms underlying this selective vulnerability remain poorly understood. Here, we use a computational model integrating neuronal activity and amyloid-{beta} deposition with interneuronal tau transport to predict regional susceptibility to tau seeding. Using fluorodeoxyglucose PET as a measure of neuronal activity, we show that brain-wide activity patterns drive tau accumulation in the medial temporal lobe, independent of amyloid status. Incorporating amyloid PET, we further show that amyloid-{beta} selectively amplifies tau seeding in the entorhinal cortex, aligning with its early involvement in Alzheimers disease. These predictions are supported by cross-subject correlation analysis, which reveals a significant association between model-derived seeding concentrations and empirical tau deposition. Our findings suggest that neuronal activity patterns shape the early landscape of tau pathology, while amyloid-{beta} deposition creates a unique vulnerability in the entorhinal cortex, potentially triggering the pathological cascade that defines Alzheimers disease.

neuroscience↗

bioRxiv2023

Functional brain networks are associated with both sex and gender in children

Sex and gender are associated with human behavior throughout the lifespan and across health and disease, but whether they are associated with similar or distinct neural phenotypes is unknown. Here, we demonstrate that, in children, sex and gender are uniquely reflected in the intrinsic functional connectivity of the brain. Unimodal networks are more strongly associated with sex while heteromodal networks are more strongly associated with gender. These results suggest sex and gender are irreducible to one another not only in society but also in biology.

neuroscience↗

bioRxiv2020

Genetic program activity delineates risk, relapse, and therapy responsiveness in Multiple Myeloma

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to their previous therapies. Although many therapies exist with diverse mechanisms of action, it is not yet clear how the differences in MM biology across patients impacts the likelihood of success for existing therapies and those in the pipeline. Therefore, we not only need the ability to predict which patients are at high risk for disease progression, but also a means to understand the mechanisms underlying their risk. We hypothesized that knowledge of the biological networks that give rise to MM, specifically the transcriptional regulatory network (TRN) and the mechanisms by which mutations impact gene regulation, would enable improved predictions of disease progression and actionable insights for treatment. Here we present a method to infer TRNs from multi-omics data and apply it to the generation of a MM TRN that links chromosomal abnormalities and somatic mutations to downstream effects on gene expression via perturbation of transcriptional regulators. We find that 141 genetic programs underlie the disease and that the activity profile of these programs fall into one of 25 distinct transcriptional states. These transcriptional signatures prove to be more predictive of outcomes than do mutations and reveal plausible mechanisms for relapse, including the establishment of an immuno-suppressive microenvironment. Moreover, we observe subtype-specific vulnerabilities to interventions with existing drugs and motivate the development of new targeted therapies that appear especially promising for relapsed refractory MM.

systems biology↗

bioRxiv2019

Multiple Myeloma DREAM Challenge Reveals Epigenetic Regulator PHF19 As Marker of Aggressive Disease

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients do not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involve assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post challenge analysis identified a novel expression-based risk marker and histone modifier, PHF19, which featured prominently in several independent models. Lastly, we show that a simple four feature predictor composed of age, International Staging System stage (ISS), and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.\n\nKey pointsO_LIMost comprehensive and unbiased assessment of prognostic biomarkers in MM resulting in a robust and parsimonious model.\nC_LIO_LIIdentification of PHF19 as the expression based biomarker most strongly associated with rapid progression in MM patients.\nC_LI

cancer biology↗

bioRxiv2019

Structural control energy of resting-state functional brain states reveals inefficient brain dynamics in psychosis vulnerability.

How the brains white-matter anatomy constrains brain activity is an open question that might give insights into the mechanisms that underlie mental disorders such as schizophrenia. Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder with an extremely high risk for psychosis providing a test case to study developmental aspects of schizophrenia. In this study, we used principles from network control theory to probe the implications of aberrant structural connectivity for the brains functional dynamics in 22q11DS. We retrieved brain states from resting-state functional magnetic resonance images of 78 patients with 22q11DS and 85 healthy controls. Then, we compared them in terms of persistence control energy; i.e., the control energy that would be required to persist in each of these states based on individual structural connectivity and a dynamic model. Persistence control energy was altered in a broad pattern of brain states including both energetically more demanding and less demanding brain states in 22q11DS. Further, we found a negative relationship between persistence control energy and resting-state activation time, which suggests that the brain reduces energy by spending less time in energetically demanding brain states. In patients with 22q11DS, this behavior was less pronounced, suggesting a dynamic inefficiency of brain function in the disease. In summary, our results provide initial insights into the dynamic implications of altered structural connectivity in 22q11DS, which might improve our understanding of the mechanisms underlying the disease.

neuroscience↗

bioRxiv2019

Space-independent community and hub structure of functional brain networks

Coordinated brain activity reflects underlying cognitive processes and can be modeled as a network of inter-regional functional connections. The most costly connections in the network are long-distance correlations that, in the absence of underlying structural connections, are maintained by sustained energetic inputs. Here, we present a spatial modeling approach that amplifies contributions made by long-distance functional connections to whole-brain network architecture, while simultaneously suppressing contributions made by short-range connections. We use this method to characterize the long-distance architecture of functional networks and to identify aspects of community and hub structure that are driven by long-distance correlations and that, we argue, are of greater functional significance. We find that based only on patterns of long-distance connectivity, primary sensory cortices occupy increasingly central positions and appear more \"hub-like\". Additionally, we show that the community structure of long-distance connections spans multiple topological levels and differs from the community structure detected in networks that include both short-range and long-distance connections. In summary, these findings highlight the complex relationship between the brains physical layout and its functional architecture. The results presented here inform future analyses of community structure and network hubs in health, across development, and in the case of neuropsychiatric disorders.

neuroscience↗

bioRxiv2019

Integrative network modeling reveals mechanisms underlying T cell exhaustion

Failure to clear antigens causes CD8+ T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8+ T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier proliferative/pro-memory (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that druginduced interference with EZH2 function increases the proportion of proliferative/pro-memory cells in the early days post-activation.

systems biology↗