Biology subjects

Moore, T. M.

Publications and source records attributed to Moore, T. M..

6 recordsLinked to original sources

bioRxiv2018

Cannabis Use in Youth is Associated with Limited Alterations in Brain Structure

Frequent cannabis use during adolescence has been associated with alterations in brain structure. However, studies have featured relatively inconsistent results, predominantly from small samples, and few studies have examined less frequent users to shed light on potential brain structure differences across levels of cannabis use. In this study, high-resolution T1-weighted MRIs were obtained from 781 youth aged 14-21 years who were studied as part of the Philadelphia Neurodevelopmental Cohort. This sample included 147 cannabis users (109 Occasional [[≤]1-2 times per week] and 38 Frequent [[≥] 3 times per week] Users) and 634 cannabis Non-Users. Several structural neuroimaging measures were examined in whole brain analyses, including gray and white matter volumes, cortical thickness, and gray matter density. Established procedures for stringent quality control were conducted, and two automated neuroimaging software processing packages were used to ensure robustness of results. There were no significant differences by cannabis group in global or regional brain volumes, cortical thickness, or gray matter density, and no significant group by age interactions were found. Follow-up analyses indicated that values of structural neuroimaging measures by cannabis group were similar across regions, and any differences among groups were likely of a small magnitude. In sum, structural brain metrics were similar among adolescent and young adult cannabis users and non-users. Our data converge with prior large-scale studies suggesting small or limited associations between cannabis use and structural brain measures in youth. Detailed studies of vulnerability to structural brain alterations and longitudinal studies examining long-term risk are indicated.

neuroscience↗

bioRxiv2018

Optimization of Energy State Transition Trajectory Supports the Development of Executive Function During Youth

Executive function develops rapidly during adolescence, and failures of executive function are associated with both risk-taking behaviors and psychopathology. However, it remains relatively unknown how structural brain networks mature during this critical period to facilitate energetically demanding transitions to activate the frontoparietal system, which is critical for executive function. In a sample of 946 human youths (ages 8-23 yr) who completed diffusion imaging as part of the Philadelphia Neurodevelopment Cohort, we capitalized upon recent advances in network control theory in order to calculate the control energy necessary to activate the frontoparietal system given the existing structural network topology. We found that the control energy required to activate the frontoparietal system declined with development. Moreover, we found that this control energy pattern contains sufficient information to make accurate predictions about individuals brain maturity. Finally, the control energy costs of the cingulate cortex were negatively correlated with executive performance, and partially mediated the development of executive performance with age. These results could not be explained by changes in general network control properties or in network modularity. Taken together, our results reveal a mechanism by which structural networks develop during adolescence to facilitate the instantiation of activation states necessary for executive function.\n\nSIGNIFICANCE STATEMENTExecutive function undergoes protracted development during youth, but it is unknown how structural brain networks mature to facilitate the activation of the frontoparietal cortex that is critical for executive processes. Here, we leverage recent advances in network control theory to establish that structural brain networks evolve in adolescence to lower the energetic cost of activating the frontoparietal system. Our results suggest a new mechanistic framework for understanding how brain network maturation supports cognition, with clear implications for disorders marked by executive dysfunction, such as ADHD and psychosis.

neuroscience↗

bioRxiv2018

Context-dependent architecture of brain state dynamics is explained by white matter connectivity and theories of network control

A diverse white matter network and finely tuned neuronal membrane properties allow the brain to transition seamlessly between cognitive states. However, it remains unclear how static structural connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we deploy an unsupervised machine learning algorithm to define brain states as time point level activity patterns from functional magnetic resonance imaging data acquired during passive visual fixation (rest) and an n-back working memory task. We find that brain states are composed of interdigitated functional networks and exhibit context-dependent dynamics. Using diffusion-weighted imaging acquired from the same subjects, we show that structural connectivity constrains the temporal progression of brain states. We also combine tools from network control theory with geometrically conservative null models to demonstrate that brains are wired to support states of high activity in default mode areas, while requiring relatively low energy. Finally, we show that brain state dynamics change throughout development and explain working memory performance. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics.

neuroscience↗

bioRxiv2018

Brain Iron Mediates the Relationship Between Cognition and Neighborhood Socioeconomic Status in Youth

Non-heme brain iron is a critical metabolic cofactor essential for healthy brain development.1 Iron deficiency is the most common nutritional disorder in the world, with greater prevalence of non-heme iron deficiency among individuals of lower socioeconomic status (SES). However, it remains unknown how brain iron accumulation during development may impact cognition. Brain iron can be measured in vivo using R2* weighted magnetic resonance imaging (MRI); prior work has established that higher R2* is associated with higher iron content.2,3 We hypothesized that more iron in the basal ganglia (BG) regions of the caudate, putamen, and pallidum would be associated with improved cognitive performance and potentially mediate the known relationship between neighborhood-level socioeconomic status (SES) and cognition.4

neuroscience↗

bioRxiv2017

Linked dimensions of psychopathology and connectivity in functional brain networks

Neurobiological abnormalities associated with psychiatric disorders do not map well to existing diagnostic categories. High co-morbidity and overlapping symptom domains suggest dimensional circuit-level abnormalities that cut across clinical diagnoses. Here we sought to identify brain-based dimensions of psychopathology using multivariate sparse canonical correlation analysis (sCCA) in a sample of 663 youths imaged as part of the Philadelphia Neurodevelopmental Cohort. This analysis revealed highly correlated patterns of functional connectivity and psychiatric symptoms. We found that four dimensions of psychopathology -- mood, psychosis, fear, and externalizing behavior -- were highly associated (r=0.68-0.71) with distinct patterns of functional dysconnectivity. Loss of network segregation between the default mode network and executive networks (e.g. fronto-parietal and salience) emerged as a common feature across all dimensions. Connectivity patterns linked to mood and psychosis became more prominent with development, and significant sex differences were present for connectivity patterns related to mood and fear. Critically, findings replicated in an independent dataset (n=336). These results delineate connectivity-guided dimensions of psychopathology that cut across traditional diagnostic categories, which could serve as a foundation for developing network-based biomarkers in psychiatry.

neuroscience↗

bioRxiv2016

What rhythmic perception and amusia can tell us about vocal social communication in schizophrenia

BackgroundPerceiving social intent throughvocal intonation is impaired in schizophrenia; thisdysprosodia partly arisingfrom impaired pitch perception.Individuals with amusia (tone-deafness) are insensitive to pitch change andalso demonstrate prosody deficits. Sensitivity to rhythm is reduced in amusia when tonal sequences contain pitch changes (polytonic), but is normal for monotonic sequences, suggesting perceptual impairment originates at a secondary processing stage where pitch- and time-relatedcues are yoked. Here, we sought to ascertain: 1) whether schizophreniapatients demonstrate rhythmic deficits, 2) whether suchdeficits are restricted to polytonic sequences, and 3) how pitch and rhythm perception relate to prosodic processing.\n\nMethodsSeventy-sixparticipants (33 schizophrenia) completed tasks assessing pitch and prosody perception, as well as monotonic and polytonic rhythmic perception.\n\nResultsIncreasing tone-deafness correlated with pitch-dependent rhythm detection impairments. Pitch and prosody correlated across all participants. Schizophreniapatients displayed basic time and pitch deficits. Correlations and path analyses indicated prosodic processing is an associatedfunction of pitch and pitch-dependent rhythm perception,with pure temporal processing playing an indirect role.In schizophrenia, deficits in monotonic and polytonic rhythmic perception did not contribute to prosodic processing dysfunction, and montonic rhythmic dysfunction and pitch perception did not covary.\n\nConclusionsExploring similarities between amusia and schizophrenia focused our characterization of prosodic processing as the function of sub-processes reflecting pitch and time perception,whichare prerequisite for prosodic processing. The uniqueness of dysprosodia in schizophrenia relative to other illnesses may be measured by idiosyncrasy in the pattern and magnitude of the sub-process task relationships.

neuroscience↗