Biology subjects

Poudel, G. R.

Publications and source records attributed to Poudel, G. R..

3 recordsLinked to original sources

bioRxiv2021

Network diffusion model predicts neurodegeneration in limb-onset amyotrophic lateral sclerosis

The trans-neural propagation of phosphorylated 43-kDa transactive response DNA-binding protein (pTDP-43) contributes to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS). We investigated whether Network Diffusion Model (NDM), a biophysical model of spread of pathology via the brain connectome, could capture the severity and progression of neurodegeneration (atrophy) in ALS. We measured degeneration in limb-onset ALS patients (n=14 at baseline, 12 at 6-months, and 9 at 12 months) and controls (n=12 at baseline) using FreeSurfer analysis on the structural T1-weighted Magnetic Resonance Imaging (MRI) data. The NDM was simulated on the canonical structural connectome from the IIT Human Brain Atlas. To determine whether NDM could predict the atrophy pattern in ALS, the accumulation of pathology modelled by NDM was correlated against atrophy measured using MRI. The cross-sectional analyses revealed that the network diffusion seeded from the inferior frontal gyrus (pars triangularis and pars orbitalis) significantly predicts the atrophy pattern in ALS compared to controls. Whereas, atrophy over time with-in the ALS group was best predicted by seeding the network diffusion process from the inferior temporal gyrus at 6-month and caudal middle frontal gyrus at 12-month. Our findings suggest the involvement of extra-motor regions in seeding the spread of pathology in ALS. Importantly, NDM was able to recapitulate the dynamics of pathological progression in ALS. Understanding the spatial shifts in the seeds of degeneration over time can potentially inform further research in the design of disease modifying therapeutic interventions in ALS.

neuroscience↗

bioRxiv2020

Perceptual Degradation Affects Stop-Signal Performance in Normal Healthy Adults

During stop-signal task performance, little is known how the quality of visual information of the go stimuli may indirectly affect the interplay between the go and stop processes. In this study, we assessed how perceptual degradation of the visual go stimuli affect response inhibition. Twenty-six healthy individuals (mean age 33.34 {+/-} 9.61) completed a modified 12-minute stop-signal task, where V and Y letters were used as visual go stimuli. The stimuli were subjected to four levels of perceptual degradation using Gaussian smoothing, to parametrically manipulate stop difficulty across low, intermediate-1, intermediate-2 and high difficulty conditions. On 33% of trials, the stop-signal (50ms audio tone) followed a go stimulus after a stop-signal delay, which was individually adjusted for each participant. As predicted, we found that with increased level of stop difficulty (little perceptual degradation), reaction times on go trials and the proportion of successful behavioural inhibitions on stop trials (P(i)) decreased in normal healthy adults. Contrary to our predictions, there was no effect of increased stop difficulty on the number of correct responses on go trials and reaction times on stop trials. Overall, manipulation of the completion time of the go process via perceptual degradation has been partially successful, whereby increased stop difficulty differentially affected P(i) and SSRT. These findings have implications for the relationship between the go and stop processes and the horse-race model, which may be limited in explaining the role of various cortico-basal ganglia loops in modulation of response inhibition. HighlightsO_LIManipulation of the completion time of the go process is partially successful C_LIO_LIPerceptual degradation differentially affects stop-signal performance C_LIO_LIIncreased stop difficulty (easy go) results in lower P(i) C_LIO_LIIncreased stop difficulty (easy go) has no effect on SSRT C_LIO_LIHorse-race model does not fully explain basal ganglia involvement in inhibition C_LI

neuroscience↗

bioRxiv2020

Sleeping While Awake: The Intrusion of Neural Activity Associated with Sleep Onset in the Awake Human Brain

Sleep can intrude into the awake human brain when sleep deprived or fatigued, even while performing cognitive tasks. However, how the brain activity associated with sleep onset can co-exist with the activity associated with cognition in the awake humans remains unexplored. Here, we used simultaneous fMRI and EEG to generate fMRI activity maps associated with EEG theta (4-7 Hz) activity associated with sleep onset. We implemented a method to track these fMRI activity maps in individuals performing a cognitive task after well-rested and sleep-deprived nights. We found frequent intrusions of the fMRI maps associated with sleep-onset in the task-related fMRI data. These sleep events elicited a pattern of transient fMRI activity, which was spatially distinct from the task-related activity in the frontal and parietal areas of the brain. They were concomitant with reduced arousal as indicated by decreased pupil size and increased response time. Graph theoretical modelling showed that the activity associated with sleep onset emerges from the basal forebrain and spreads anterior-posteriorly via the brains structural connectome. We replicated the key findings in an independent dataset, which suggests that the approach can be reliably used in understanding the neuro-behavioural consequences of sleep and circadian disturbances in humans.

neuroscience↗