Biology subjects

Barbour, D. L.

Publications and source records attributed to Barbour, D. L..

3 recordsLinked to original sources

bioRxiv2020

Cognitive Deficits and Altered Functional Brain Network Organization in Pediatric Brain Tumor Patients

Pediatric brain tumor survivors experience significant cognitive sequelae from their diagnosis and treatment. The exact mechanisms of cognitive injury are poorly understood, and validated predictors of long-term cognitive outcome are lacking. Large-scale, distributed brain systems provide a window into brain organization and function that may yield insight into these mechanisms and outcomes. Here, we evaluated functional network architecture, cognitive performance, and brain-behavior relationships in pediatric brain tumor patients. Patients ages 4-18 years old with diagnosis of a brain tumor underwent awake resting state fMRI during regularly scheduled clinical visits and were tested with the NIH Toolbox Cognition Battery. We observed that functional network organization was significantly altered in patients compared to age- and sex-matched healthy controls, with the integrity of the dorsal attention network particularly affected. Moreover, patients demonstrated significant impairments in multiple domains of cognitive performance, including attention. Finally, a significant amount of variance of age-adjusted total composite scores from the Toolbox was explained by changes in segregation between the dorsal attention and default mode networks. Our results suggest that changes in functional network organization may provide insight into long-term changes in cognitive function in pediatric brain tumor patients.

neuroscience↗

bioRxiv2019

Population Responses Represent Vocalization Identity, Intensity, and Signal-to-Noise Ratio in Primary Auditory Cortex

The ability to process speech signals under challenging listening environments is critical for speech perception. Great efforts have been made to reveal the underlying single unit encoding mechanism. However, big variability is usually discovered in single-unit responses, and the population coding mechanism is yet to be revealed. In this study, we are aimed to study how a population of neurons encodes behaviorally relevant signals subjective to change in intensity and signal-noise-ratio (SNR). We recorded single-unit activity from the primary auditory cortex of awake common marmoset monkeys (Callithrix jacchus) while delivering conspecific vocalizations degraded by two different background noises: broadband white noise (WGN) and vocalization babble (Babble). By pooling all single units together, the pseudo-population analysis showed the population neural responses track intra- and inter-trajectory angle evolutions track vocalization identity and intensity/SNR, respectively. The ability of the trajectory to track the vocalizations attribute was degraded to a different degree by different noises. Discrimination of neural populations evaluated by neural response classifiers revealed that a finer optimal temporal resolution and longer time scale of temporal dynamics were needed for vocalizations in noise than vocalizations at multiple different intensities. The ability of population responses to discriminate between different vocalizations were mostly retained above the detection threshold. Significance StatementHow our brain excels in the challenge of precise acoustic signal encoding against noisy environment is of great interest for scientists. Relatively few studies have strived to tackle this mystery from the perspective of neural population responses. Population analysis reveals the underlying neural encoding mechanism of complex acoustic stimuli based upon a pool of single units via vector coding. We suggest the spatial population response vectors as one important way for neurons to integrate multiple attributes of natural acoustic signals, specifically, marmots vocalizations.

neuroscience↗

bioRxiv2018

In Vitro Assay for the Detection of Network Connectivity in Embryonic Stem Cell-Derived Cultures

Stem cell transplantation holds great promise as a repair strategy following spinal cord injury. Embryonic stem cell (ESC) transplantation therapies have elicited encouraging though limited improvement in motor and sensory function with the use of heterogeneous mixtures of spinal cord neural progenitors and ESCs. Recently, transgenic lines of ESCs have been developed to allow for purification of specific candidate populations prior to transplantation, but the functional network connectivity of these populations and its relationship to recovery is difficult to examine with current technological limitations. In this study, we combine an ESC differentiation protocol, multi-electrode arrays (MEAs), and previously developed neuronal connectivity detection algorithms to develop an in vitro high-throughput assay of network connectivity in ESC-derived populations of neurons. Neuronal aggregation results in more consistent detection of individual neuronal activity than dissociated cultures. Both aggregated and dissociated culture types exhibited synchronized bursting behaviors at days 17 and 18 on MEAs, and thousands of statistically significance functional connections were detected in both culture types. Aggregate cultures, however, demonstrate a tight linear relationship between the inter-neuron distance of neuronal pairs and the time delay of the neuronal pair functional connections, whereas dissociated cultures do not. These results suggest that ESC-derived aggregated cultures may reflect some of the spatiotemporal connectivity characteristics of in vivo tissue and prove to be useful models of investigating potentially therapeutic populations of ESC-derived neurons in vitro.\n\nNOVELTY AND SIGNIFICANCEPrevious investigations of stem cell-derived network connectivity on multi-electrode arrays (MEAs) have been limited to characterizations of bursting activity or broad averages of overall temporal network correlations, both of which overlook neuronal level interactions. The use of spike-sorting and short-time cross-correlation histograms along with statistical techniques developed specifically for MEAs allows for the characterization of functional connections between individual stem cell-derived neurons. This high-throughput connectivity assay will open doors for future examinations of the differences in functional network formation between various candidate stem cell-derived populations for spinal cord injury transplantation therapies--a critical inquiry into their therapeutic viability.

bioengineering↗