Biology subjects

Wengler, K.

Publications and source records attributed to Wengler, K..

6 recordsLinked to original sources

bioRxiv2025

fMRIPrep Lifespan: Extending A Robust Pipeline for Functional MRI Preprocessing to Developmental Neuroimaging

The adoption of a standardized preprocessing workflow is vital for fostering community, sharing, and reproducibility. fMRIPrep has been a critical advancement towards this end, however, it is limited in its capacity to be applied to data across the lifespan, starting from infancy. Here, we introduce fMRIPrep Lifespan, an extension of fMRIPrep that extends the standardized processing from childhood to senescence to include neonatal, infant, and toddler structural and functional MRI data preprocessing. This effort involves a NiPreps integration of 1) a workflow akin to fMRIPrep optimized for MRI data in the first years of life (previously NiBabies) and 2) upstream enhancements to the entire NiPreps suite, including multi-echo data processing, modularization of workflow components, and convergence of processing with other popular workflows (ABCD-BIDS, Human Connectome Project Pipelines). Using data from the Baby Connectome Project (participants 1-43 months of age), we demonstrate that fMRIPrep Lifespan produces high-quality outputs across a wide age range. Moving forward, the scalable, modular infrastructure of fMRIPrep Lifespan will ensure adaptability to data from birth to old age while maintaining robust and reproducible frameworks for functional MRI research across the lifespan.

bioinformatics↗

bioRxiv2024

Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales

Intrinsic neural timescale (INT) is a resting-state fMRI (rs-fMRI) measure that reflects the time window of neural integration within a brain region. Despite the potential relevance of INT to cognition, brain organization, and neuropsychiatric illness, the influences of physiological artifacts on INT have not been systematically considered. Two artifacts, head motion and respiration, pose serious issues in rs-fMRI studies. Here, we described their impact on INT estimation and tested the ability of two denoising strategies for mitigating these artifacts, high-motion frame censoring and global signal regression (GSR). We used a subset of the HCP Young Adult dataset with runs annotated for breathing patterns (Lynch et al., 2020) and at least one "clean" (reference) run that had minimal head motion and no respiration artifacts; other runs from the same participants (n = 46) were labeled as "non-clean." We found that non-clean runs exhibited brain-wide increases in INT compared to their respective clean runs and the magnitude of error in INT between non-clean and clean runs correlated with the amount of head motion. Importantly, effect sizes were comparable to INT effects reported in the clinical literature. GSR and high-motion frame censoring improved the similarity between INT maps from non-clean runs and their respective clean run. Using a pseudo-random frame-censoring approach, there was a relationship between the amount of censored frames and both the mean INT and mean error, suggesting that frame censoring itself biases INT estimation. A group-level correction procedure reduced this bias and improved similarity between non-clean runs and their respective clean run. Based on our findings, we offer recommendations for rs-fMRI INT studies, which include implementing GSR and high-motion frame censoring with Lomb-Scargle interpolation of censored data, and performing group-level correction of the bias introduced by frame censoring.

neuroscience↗

bioRxiv2023

Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer's disease

Alzheimers disease (AD) is a devastating neurodegenerative disease that affects millions of older adults in the US and worldwide. Resting-state functional magnetic resonance imaging (rs-fMRI) has become a widely used neuroimaging tool to study neurophysiology in AD and its prodromal condition, mild cognitive impairment (MCI). The intrinsic neural timescale (INT), which can be estimated through the magnitude of the autocorrelation of intrinsic neural signals using rs-fMRI, is thought to quantify the duration that neural information is stored in a local cortical circuit. The heterogeneity of the timescales is considered to be a basis of the functional hierarchy in the brain. In addition, INT captures an aspect of circuit dynamics relevant to excitation/inhibition (E/I) balance, which is thought to be broadly relevant for cognitive functions. Here we examined its relevance to AD. We used rs-fMRI data of 904 individuals from the Alzheimers Disease Neuroimaging Initiative (ADNI) database. The subjects were divided into 4 groups based on their baseline and end-visit clinical status, which were cognitively normal (CN), stable MCI, Converter, and AD groups. Linear mixed effect model and pairwise comparison were implemented to investigate the large-scale hierarchical organization and local differences. We observed high similarities between AD and Converter groups. Specifically, among the eight identified ROIs with distinct INT alterations in AD, three ROIs (inferior temporal, caudate, pallidum areas) exhibit stable and significant alteration in AD converter. In addition, distinct INT related pathological changes in stable MCI and AD/Converter were found. For AD and Converter groups, neural information is stored for a longer time in lower hierarchical order areas, while higher levels of hierarchy seem to be preferentially impaired in stable MCI leading to a less pronounced hierarchical gradient effect. These results inform that the INT holds great potential as an additional measure for AD prediction, a stable biomarker for clinical diagnosis and an important therapeutic target in AD.

neuroscience↗

bioRxiv2022

Suboptimal foraging decisions and involvement of the ventral tegmental area in human opioid addiction

Addiction is marked by a tendency to exploit sources of reward despite diminishing returns. This behavior is aptly captured by animal patch-foraging models that have recently been extended to humans. Dopamine and norepinephrine centrally mediate addictive behavior and activity in both catecholaminergic systems is proposed to reflect the computations necessary for optimal foraging. However, the specific neural bases of excessive foraging and their role in human addiction are largely unknown. To address this gap, we studied the behavior of people with and without opioid use disorder (OUD) on a patch-foraging task in which they made serial decisions to "harvest" a depleting resource ("patch") for reward or incur a varying cost to "travel" to a replenished patch. In a subset of participants, we used high-resolution neuromelanin-sensitive MRI to image neuromelanin concentration, a proxy for long-term catecholaminergic function, in distinct dopaminergic nuclei (ventral tegmental area, substantia nigra subregions) and the noradrenergic locus coeruleus. While all participants were sensitive to the long-run reward rates of different patch-foraging environments, OUD participants stayed in reward patches longer than optimal--markedly overharvesting a source of reward despite its declining value--and this correlated with more chronic drug use. Overharvesting was selectively associated with lower neuromelanin signal in the ventral tegmental area but not other dopaminergic nuclei, nor the locus coeruleus. Our findings suggest that foraging decisions relevant to addiction involve a ventral-tegmental-area circuit that may signal reward rates in dynamic environments and implicate this circuit in maladaptive reward pursuit in human addiction to opioids. Significance statementPatch-foraging provides a potentially important translational framework for understanding addictive behavior by revealing how maladaptive reward pursuit emerges in more ecologically valid decision contexts. Here, we show that the tendency to exploit sources of reward despite diminishing returns is associated with chronic drug use in people with opioid use disorder, a particularly devastating form of addiction. We further use neuromelanin-sensitive MRI, a neuroimaging measure of the long-term function of dopamine neurons, to reveal that variation in ventral tegmental area neuromelanin signal selectively underlies individual differences in this overharvesting bias. These findings establish a role for specific dopaminergic circuits in patch-foraging decisions and advance understanding of the neurobiology of human addiction to opioids that has so far eluded the field.

neuroscience↗

bioRxiv2020

Distinct Hierarchical Alterations of Intrinsic Neural Timescales Account for Different Manifestations of Psychosis

Hierarchical perceptual-inference models of psychosis may provide a holistic framework for understanding psychosis in schizophrenia including heterogeneity in clinical presentations. Particularly, hypothesized alterations at distinct levels of the perceptual-inference hierarchy may explain why hallucinations and delusions tend to cluster together yet sometimes manifest in isolation. To test this, we used a recently developed resting-state fMRI measure of intrinsic neural timescale (INT), which reflects the time window of neural integration and captures hierarchical brain gradients. In analyses examining extended sensory hierarchies that we first validated, we found distinct hierarchical INT alterations for hallucinations versus delusions in the auditory and somatosensory systems, thus providing support for hierarchical perceptual-inference models of psychosis. Simulations using a large-scale biophysical model suggested local elevations of excitation-inhibition ratio at different hierarchical levels as a potential mechanism. More generally, our work highlights the robustness and utility of INT for studying hierarchical processes relevant to basic and clinical neuroscience.

neuroscience↗

bioRxiv2019

Reproducibility Assessment of Neuromelanin-Sensitive Magnetic Resonance Imaging Protocols for Region-of-Interest and Voxelwise Analyses

Neuromelanin-sensitive MRI (NM-MRI) provides a noninvasive measure of the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). NM-MRI has been validated as a measure of both dopamine neuron loss, with applications in neurodegenerative disease, and dopamine function, with applications in psychiatric disease. Furthermore, a voxelwise-analysis approach has been validated to resolve substructures, such as the ventral tegmental area (VTA), within midbrain dopaminergic nuclei thought to have distinct anatomical targets and functional roles. NM-MRI is thus a promising tool that could have diverse research and clinical applications to noninvasively interrogate in vivo the dopamine system in neuropsychiatric illness. Although a test-retest reliability study by Langley et al. using the standard NM-MRI protocol recently reported high reliability, a systematic and comprehensive investigation of the performance of the method for various acquisition parameters and preprocessing methods has not been conducted. In particular, most previous studies used relatively thick MRI slices ([~]3 mm), compared to the typical in-plane resolution ([~]0.5 mm) and to the height of the SN ([~]15 mm), to overcome technical limitations such as specific absorption rate and signal-to-noise ratio, at the cost of partial-volume effects. Here, we evaluated the effect of various acquisition and preprocessing parameters on the strength and test-retest reliability of the NM-MRI signal to determine optimized protocols for both region-of-interest (including whole SN/VTA-complex and atlas-defined dopaminergic nuclei) and voxelwise measures. Namely, we determined a combination of parameters that optimizes the strength and reliability of the NM-MRI signal, including acquisition time, slice-thickness, spatial-normalization software, and degree of spatial smoothing. Using a newly developed, detailed acquisition protocol, across two scans separated by 13 days on average, we obtained intra-class correlation values indicating excellent reliability and high contrast-to-noise, which could be achieved with a different set of parameters depending on the measures of interest and experimental constraints such as acquisition time. Based on this, we provide detailed guidelines covering acquisition through analysis and recommendations for performing NM-MRI experiments with high quality and reproducibility. This work provides a foundation for the optimization and standardization of NM-MRI, a promising MRI approach with growing applications throughout clinical and basic neuroscience.\n\nHighlightsO_LIA detailed NM-MRI volume placement protocol is described.\nC_LIO_LIGuidelines covering acquisition through analysis for NM-MRI are given.\nC_LIO_LIA test-retest study in 10 healthy subjects shows high reproducibility for region-of-interest (ROI) and voxelwise analyses.\nC_LIO_LI[~]3 minutes of NM-MRI data is needed for high-quality ROI-analysis.\nC_LIO_LI[~]6 minutes of NM-MRI data is needed for high-quality voxelwise-analysis.\nC_LI

neuroscience↗