On the Nature of Explanations Offered by Network Science: A Perspective From and for Practicing Neuroscientists

Bertolero, Maxwell A.; Bassett, Danielle S.

doi:10.1111/tops.12504

Cited by 31 publications

(14 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Methodological advances are necessary to fully understand how early experiences affect the pace of brain development. The application of network methods to developmental data is still in its infancy, as researchers take on the challenge of describing nodes and edges of brain networks in a biologically accurate and meaningful way 171,172 . Studies have used many different measures of segregation to characterize functional brain networks, and it will be crucial for future research to examine how different measures relate to each other and to SES over development.…”

Section: Future Directions and Conclusionmentioning

confidence: 99%

Environmental influences on the pace of brain development

2021

Self Cite

View full text Add to dashboard Cite

Childhood socio-economic status (SES), a measure of the availability of material and social resources, is one of the strongest predictors of lifelong well-being. Here we review evidence that experiences associated with childhood SES affect not only the outcome but also the pace of brain development. We argue that higher childhood SES is associated with protracted structural brain development and a prolonged trajectory of functional network segregation, ultimately leading to more efficient cortical networks in adulthood. We hypothesize that greater exposure to chronic stress accelerates brain maturation, whereas greater access to novel positive experiences decelerates maturation. We discuss the impact of variation in the pace of brain development on plasticity and learning. We provide a generative theoretical framework to catalyse future basic science and translational research on environmental influences on brain development.

show abstract

Section: Future Directions and Conclusionmentioning

confidence: 99%

Environmental influences on the pace of brain development

2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…As such, these two measures together could provide unique information on network functioning crucial for cognition. 13 Unfortunately, a few studies specifically investigated the cognitive role of cerebellar FC, and even fewer in MS. 14–17…”

Section: Introductionmentioning

confidence: 99%

The cerebellum and its network: Disrupted static and dynamic functional connectivity patterns and cognitive impairment in multiple sclerosis

et al. 2021

View full text Add to dashboard Cite

Background: The impact of cerebellar damage and (dys)function on cognition remains understudied in multiple sclerosis. Objective: To assess the cognitive relevance of cerebellar structural damage and functional connectivity (FC) in relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS). Methods: This study included 149 patients with early RRMS, 81 late RRMS, 48 SPMS and 82 controls. Cerebellar cortical imaging included fractional anisotropy, grey matter volume and resting-state functional magnetic resonance imaging (MRI). Cerebellar FC was assessed with literature-based resting-state networks, using static connectivity (that is, conventional correlations), and dynamic connectivity (that is, fluctuations in FC strength). Measures were compared between groups and related to disability and cognition. Results: Cognitive impairment (CI) and cerebellar damage were worst in SPMS. Only SPMS showed cerebellar connectivity changes, compared to early RRMS and controls. Lower static FC was seen in fronto-parietal and default-mode networks. Higher dynamic FC was seen in dorsal and ventral attention, default-mode and deep grey matter networks. Cerebellar atrophy and higher dynamic FC together explained 32% of disability and 24% of cognitive variance. Higher dynamic FC was related to working and verbal memory and to information processing speed. Conclusion: Cerebellar damage and cerebellar connectivity changes were most prominent in SPMS and related to worse CI.

show abstract

“…For example, the particular form of GLMs that we discuss seeks to measure the statistical variance in system function that is explained by a perturbation. This approach can provide evidence in support of a causal theory [151], but does not itself comprise a causal framework. In contrast, impulse response models and network control models apply an artificial perturbation in silico to predict the effects of a natural perturbation in vivo.…”

Section: Future Directionsmentioning

confidence: 99%

Modeling brain, symptom, and behavior in the winds of change

Lydon‐Staley

Cornblath

Blevins

et al. 2020

Neuropsychopharmacol.

Self Cite

View full text Add to dashboard Cite

Neuropsychopharmacology addresses pressing questions in the study of three intertwined complex systems: the brain, human behavior, and symptoms of illness. The field seeks to understand the perturbations that impinge upon those systems, either driving greater health or illness. In the pursuit of this aim, investigators often perform analyses that make certain assumptions about the nature of the systems that are being perturbed. Those assumptions can be encoded in powerful computational models that serve to bridge the wide gulf between a descriptive analysis and a formal theory of a system’s response. Here we review a set of three such models along a continuum of complexity, moving from a local treatment to a network treatment: one commonly applied form of the general linear model, impulse response models, and network control models. For each, we describe the model’s basic form, review its use in the field, and provide a frank assessment of its relative strengths and weaknesses. The discussion naturally motivates future efforts to interlink data analysis, computational modeling, and formal theory. Our goal is to inspire practitioners to consider the assumptions implicit in their analytical approach, align those assumptions to the complexity of the systems under study, and take advantage of exciting recent advances in modeling the relations between perturbations and system function.

show abstract

On the Nature of Explanations Offered by Network Science: A Perspective From and for Practicing Neuroscientists

Cited by 31 publications

References 74 publications

Environmental influences on the pace of brain development

Environmental influences on the pace of brain development

The cerebellum and its network: Disrupted static and dynamic functional connectivity patterns and cognitive impairment in multiple sclerosis

Modeling brain, symptom, and behavior in the winds of change

Contact Info

Product

Resources

About