Biology subjects

Marek, S.

Publications and source records attributed to Marek, S..

24 records · Page 2Linked to original sources

bioRxiv2021

Precision Diffusion Imaging

Diffusion tensor imaging (DTI) aims to non-invasively characterize the anatomy and integrity of the brains white matter fibers. To establish individual-specific precision approaches for DTI, we defined its reliability and accuracy as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). DTI methods that allow for crossing fibers (BedpostX [BPX], Q-Ball Imaging [QBI]) estimated excess fibers when insufficient data was present and when the data did not match the model priors. To reduce such overfitting, we developed a novel crossing-fiber diffusion imaging method, Bayesian Multi-tensor Model-selection (BaMM), that is designed for high-quality repeated sampling data sets. BaMM was robust to overfitting, showing high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, the choice of diffusion imaging analysis method is important for the success of individual-specific diffusion imaging. Importantly, for potential clinical applications of individual-specific precision DTI, such as deep brain stimulation (DBS), other forms of neuromodulation or neurosurgical planning, the data quantities required to achieve DTI reliability are lower than for functional MRI measures.

neuroscience↗

bioRxiv2020

Parallel Hippocampal-Parietal Circuits for Self- and Goal-oriented Processing

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. The human hippocampus has been thought of as being solely functionally connected to a set of neocortical regions known as the default mode network (DMN), which supports self-referential cognition. Using individual-specific precision functional mapping of resting state fMRI data, we found the anterior hippocampus (head and body) to be preferentially connected to the DMN as expected. The hippocampal tail, however, was strongly preferentially connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This resting state functional connectivity (RSFC) anterior-posterior dichotomy was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the head and body of the hippocampus (DMN), relatively sparing the tail (PMN). Anterior and posterior hippocampal connectivity was network-specific even though the DMN and PMN are interdigitated in medial parietal cortex. The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel, but distinct circuits between the hippocampus and medial parietal cortex for self vs. goal-oriented processing.

neuroscience↗

bioRxiv2020

Cingulo-Opercular Control Network Supports Disused Motor Circuits in Standby Mode

Whole-brain resting-state functional MRI (rs-fMRI) during two weeks of limb constraint revealed that disused motor regions became more strongly connected to the cingulo-opercular network (CON), an executive control network that includes regions of the dorsal anterior cingulate cortex (dACC) and insula (1). Disuse-driven increases in functional connectivity (FC) were specific to the CON and somatomotor networks and did not involve any other networks, such as the salience, frontoparietal, or default mode networks. Censoring and modeling analyses showed that FC increases during casting were mediated by large, spontaneous activity pulses that appeared in the disused motor regions and CON control regions. During limb constraint, disused motor circuits appear to enter a standby mode characterized by spontaneous activity pulses and strengthened connectivity to CON executive control regions. SignificanceMany studies have examined plasticity in the primary somatosensory and motor cortex during disuse, but little is known about how disuse impacts the brain outside of primary cortical areas. We leveraged the whole-brain coverage of resting-state functional MRI (rs-fMRI) to discover that disuse drives plasticity of distant executive control regions in the cingulo-opercular network (CON). Two complementary analyses, pulse censoring and pulse addition, demonstrated that increased functional connectivity between the CON and disused motor regions was driven by large, spontaneous pulses of activity in the CON and disused motor regions. These results point to a previously unknown role for the CON in supporting motor plasticity and reveal spontaneous activity pulses as a novel mechanism for reorganizing the brains functional connections.

neuroscience↗

bioRxiv2020

Towards Reproducible Brain-Wide Association Studies

Magnetic resonance imaging (MRI) continues to drive many important neuroscientific advances. However, progress in uncovering reproducible associations between individual differences in brain structure/function and behavioral phenotypes (e.g., cognition, mental health) may have been undermined by typical neuroimaging sample sizes (median N=25)1,2. Leveraging the Adolescent Brain Cognitive Development (ABCD) Study3 (N=11,878), we estimated the effect sizes and reproducibility of these brain-wide associations studies (BWAS) as a function of sample size. The very largest, replicable brain-wide associations for univariate and multivariate methods were r=0.14 and r=0.34, respectively. In smaller samples, typical for brain-wide association studies (BWAS), irreproducible, inflated effect sizes were ubiquitous, no matter the method (univariate, multivariate). Until sample sizes started to approach consortium-levels, BWAS were underpowered and statistical errors assured. Multiple factors contribute to replication failures4-6; here, we show that the pairing of small brain-behavioral phenotype effect sizes with sampling variability is a key element in wide-spread BWAS replication failure. Brain-behavioral phenotype associations stabilize and become more reproducible with sample sizes of N{gap}2,000. While investigator-initiated brain-behavior research continues to generate hypotheses and propel innovation, large consortia are needed to usher in a new era of reproducible human brain-wide association studies.

neuroscience↗

bioRxiv2020

Shared and unique brain network features predict cognition, personality and mental health in childhood

The manner through which individual differences in brain network organization track population-level behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, the focus of most studies on single behavioral traits has come at the expense of capturing broader relationships across behaviors. Here, we utilized a large-scale dataset of 1858 typically developing children to estimate whole-brain functional network organization that is predictive of individual differences in cognition, impulsivity-related personality, and mental health during rest and task states. Predictive network features were distinct across the broad behavioral domains: cognition, personality and mental health. On the other hand, traits within each behavioral domain were predicted by highly similar network features. This is surprising given decades of research emphasizing that distinct brain networks support different mental processes. Although tasks are known to modulate the functional connectome, we found that predictive network features were similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood, yet are unique to different behavioral domains.

neuroscience↗

bioRxiv2018

A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum

An important aspect of network-based analysis is robust node definition. This issue is critical for functional brain network analyses, as poor node choice can lead to spurious findings and misleading inferences about functional brain organization. Two sets of functional brain nodes from our group are well represented in the literature: (1) 264 volumetric regions of interest (ROIs) reported in Power et al., 2011 and (2) 333 cortical surface parcels reported in Gordon et al., 2016. However, subcortical and cerebellar structures are either incompletely captured or missing from these ROI sets. Therefore, properties of functional network organization involving the subcortex and cerebellum may be underappreciated thus far. Here, we apply a winner-take-all partitioning method to resting-state fMRI data to generate novel functionally-constrained ROIs in the thalamus, basal ganglia, amygdala, hippocampus, and cerebellum. We validate these ROIs in three datasets using several criteria, including agreement with existing literature and anatomical atlases. Further, we demonstrate that combining these ROIs with established cortical ROIs recapitulates and extends previously described functional network organization. This new set of ROIs is made publicly available for general use, including a full list of MNI coordinates and functional network labels.

neuroscience↗