Biology subjects

Camilleri, J. A.

Publications and source records attributed to Camilleri, J. A..

4 recordsLinked to original sources

bioRxiv2021

Tract-specific statistics based on diffusion-weighted probabilistic tractography

Diffusion-weighted neuroimaging approaches provide rich evidence with which to estimate the structural integrity of white matter in vivo. Tract-based spatial statistics (TBSS), for instance, allows us to assess the spatial distribution of statistical tests performed on diffusion properties such as fractional anisotropy, which are proposed to reflect the integrity of white matter tracts. However, such methods do not provide a direct assessment of white matter integrity for connections between two specific regions of the brain. Here, we present a novel method for deriving tract-specific diffusion statistics, based upon arbitrarily-defined regions of interest. Our approach makes use of an empirically-derived population distribution based on probabilistic tractography, using the Nathan Kline Institute (NKI) Enhanced Rockland sample. We use a heuristic method to determine the most likely geometry of a path between two regions, if one exists, and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and compute the fraction of diffusion directed along this orientation for each participant. This allows us to obtain participant-wise metrics along the specific tract (tract-specific anisotropy; TSA), which can then be used to perform statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the "default mode" and "what-where" networks), along with more moderate sex differences and age-by-sex interactions in both networks.

neuroscience↗

bioRxiv2020

The Aging Brain and Executive Functions Revisited: Implications from Meta-Analytic and Functional-Connectivity Evidence

Healthy aging is associated with changes in cognitive performance including executive functions (EFs) and their associated brain activation patterns. However, it has remained unclear which EF-related brain regions are affected consistently, because the results of pertinent neuroimaging studies and earlier meta-analyses vary considerably. We, therefore, conducted new rigorous meta-analyses of published age differences in EF-related brain activity. Out of a larger set of regions associated with EFs, only left inferior frontal junction (IFJ) and left anterior cuneus/precuneus (aC/PrC) were found to show consistent age differences. To further characterize these two age-sensitive regions, we performed seed-based resting-state functional connectivity (RS-FC) analyses using fMRI data from a large adult sample with a wide age range. We also assessed associations of the two regions whole-brain RS-FC patterns with age and EF performance. Although functional profiling and RS-FC analyses point towards a domain-general role of left IFJ in EFs, the pattern of individual study contributions to the meta-analytic results suggests process-specific modulations by age. Our analyses further indicate that left aC/PrC is recruited differently by older (compared to younger) adults during EF tasks, potentially reflecting inefficiencies in switching the attentional focus. Overall, our findings question earlier meta-analytic results and suggest a larger heterogeneity of age-related differences in brain activity associated with EFs. Hence, they encourage future research that pays greater attention to replicability, investigates age-related differences in deactivation, and focuses on more narrowly defined EF subprocesses, combining multiple behavioral assessments with multi-modal imaging. Highlights- Healthy aging is linked to deterioration in executive functions (EFs) - ALE meta-analyses examined consistent age differences in brain activity linked to EFs - In a larger set of EF regions, only left IFJ and (pre)cuneus were sensitive to age - Advanced age was linked to weaker functional coupling within EF-related networks - Our findings question earlier meta-analytic findings

neuroscience↗

bioRxiv2020

The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug-related and natural-reward stimuli

BackgroundThe cue-reactivity paradigm is a widely adopted neuroimaging probe engendering brain activity linked with attentional, affective, and reward processes following presentation of appetitive stimuli. Given the multiple mental operations invoked, we sought to decompose cue-related brain activity into constituent components employing emergent meta-analytic techniques when considering drug and natural reward-related cues. MethodsWe conducted multiple coordinate-based meta-analyses delineating common and distinct brain activity convergence across cue-reactivity studies (N=196 articles) involving drug (n=133) or natural reward-related (n=63) visual stimuli. Subsequently, we characterized the connectivity profiles of identified brain regions by using them as seeds in task-independent and task-dependent functional connectivity analyses. Using hierarchical clustering on these connectivity profiles, we grouped cue-related brain regions into subnetworks. Functional decoding was then employed to characterize mental operations linked with each subnetwork. ResultsAcross all studies, pooled activity convergence was observed in the striatum, amygdala, thalamus, cingulate, insula, and multiple frontal, parietal, and occipital regions. Drug-distinct convergence (drug>natural) was observed notably in the posterior cingulate cortex (PCC), dorsolateral prefrontal cortex (dlPFC), and temporal and parietal regions, whereas distinct natural reward convergence (natural>drug) was observed in thalamic, insular, orbitofrontal, and occipital regions. Hierarchical clustering using each regions connectivity profiles identified six subnetworks, involving: 1) occipital and thalamic (lateral geniculate nucleus) regions functionally linked with early visual processing, 2) occipital-temporal regions associated with higher level visual association, 3) parietal-frontal regions linked with cognitive control mechanisms, 4) posterior and ventral insula as well as anterior cingulate cortex (ACC) functionally linked with salient event detection, 5) nucleus accumbens, PCC, precuneus, ACC, and thalamus (mediodorsal) associated with subjective valuation, and 6) bilateral amygdalae, orbitofrontal, and dorsal insula regions linked with affective processes. ConclusionsThese outcomes suggest multifaceted brain activity during the cue-reactivity paradigm can be decomposed into more elemental processes and indicate that while drugs of abuse usurp the brains natural reward processing system, some regions appear distinctly related to drug cue-reactivity (e.g., PCC, dlPFC).

neuroscience↗

bioRxiv2019

PHENOTYPIC AND GENETIC CORRELATION BETWEEN SLEEP, BEHAVIOR, AND MACROSCALE CORTICAL GREY MATTER

Humans need about 7 to 9 hours of sleep per night. Sleep habits are heritable, associated with brain function and structure, and intrinsically related to well-being, mental and physical health. This raises the question whether associations between sleep, mental and physical health can be attributed to a shared macroscale neurobiology.\n\nCombining neuroimaging and behavioral genetic approaches in two independent large-scale datasets (n=1887) we demonstrate phenotypic and genetic correspondence between sleep, intelligence, and BMI. Sleep was associated with local thickness variation in frontal, temporal, and occipital cortices. Using a comprehensive multivariate approach, we identified two robust latent components highlighting the interdigitation of sleep, intelligence, BMI, and depression and their shared relation to regions in unimodal and heteromodal association cortices. Latent relationships were heritable and driven by shared additive genetic factors. These observations provide a system-level perspective on the interrelation of sleep, mental, and physical conditions, anchored in grey-matter neuroanatomy.

neuroscience↗