Biology subjects

Ratai, E.-M.

Publications and source records attributed to Ratai, E.-M..

9 recordsLinked to original sources

bioRxiv2026

Cognitive reserve depends on cortical neurochemistry to predict memory after partner-inflicted brain injury

Memory problems are commonplace following brain injury (BI). However, it remains unclear why some report memory problems while others do not, especially following repeated neurotrauma. Cognitive reserve has been widely hypothesized to account for this variation, but testing this account has yielded inconsistent results and proven difficult, likely as it requires a sample spanning a wide range of BI burden with concurrent neuroimaging and cognitive measurement. Here, we combined a wide range of cognitive assessments with measures of neuronal health using magnetic resonance spectroscopy across three brain regions in 62 women who had experienced physical intimate partner violence. Partner-inflicted BI counts ranged from 0 to 420, yet we found that the number of BIs alone did not explain the variance in memory outcomes. Among a small subset with high BI exposure ([≥]10 BIs; n = 11), BI count explained 5% of the variance in delayed recall, the primary memory outcome, whereas cognitive reserve, inferred from a measure of premorbid functioning, explained almost half (unadjusted in-sample associations). In the full cohort, cognitive reserve predicted memory only among the most heavily injured participants. In a separate model, cognitive reserve predicted memory only when creatine-referenced total N-acetylaspartate, a marker of neuronal health, was lower in the posterior cingulate gyrus and dorsolateral prefrontal cortex. Ultimately, our findings provide behavioral and neurochemical evidence consistent with the cognitive reserve hypothesis and shed new light on why, despite a high burden of neurotrauma, memory may remain resilient.

neuroscience↗

bioRxiv2026

A biophysical corticostriatal model predicts learning-dependent 7T fMRI dynamics and individual reward bias in humans

Circuit-level computational models can do more than explain existing data; they can generate novel hypotheses and capture individual differences in human populations. We demonstrate this using a biophysical corticostriatal model, transforming simulated neuronal activity from local field potential (LFP) into functional magnetic resonance imaging (fMRI) signals via the balloon model, and finally generating behavioral outcomes. We then validate the results against those obtained from human subjects. The model generates a counterintuitive yet testable prediction. Although prefrontal-striatal coherence demonstrates an increase at the neural LFP scale during learning, the same circuit-- passed through the hemodynamic transform---predicts a decrease in prefrontal-striatal BOLD correlation, driven by category-selective representations that emerge in cortex but not striatum. This prediction is confirmed in fMRI data optimized for single-subject-level detection sensitivity. The model further enables single-subject fitting of a behavioral outcome, classifying individuals into those differentially responding to positive versus negative reward bias. Established biomarkers, including activation measured by the amplitude of low-frequency fluctuations and dopaminergic effects on hemodynamic latency, are also conserved across LFP and fMRI scales. These findings reposition circuit models as generative tools for human neuroscience, capable of producing mechanistically grounded hypotheses and parsing individual variation in ways inaccessible to data-driven approaches alone.

neuroscience↗

bioRxiv2026

Computational modeling of neurotransmitter cycling predicts human brain glutamate and GABA dynamics in response to administration of exogenous ketones

Administration of ketones is used as a therapeutic option in multiple conditions, including epilepsy, mental health disorders, and brain aging. A proposed mechanism of action involves the modulation of glutamate and GABA, the brains primary excitatory and inhibitory neurotransmitters, which jointly regulate the excitatory-inhibitory balance. However, the precise mechanism by which ketones influence these neurotransmitters remains unclear. In this study, we hypothesize that ketones modulate glutamate and GABA through the pseudomalate-spartate shuttle (PMAS). To test this, we developed a computational model of neurotransmitter cycling centered on the PMAS, simulating the temporal dynamics and steady-state concentrations of glutamate and GABA as functions of ketone metabolism. We then compared the model outputs with MRS data from ketone administration experiments and found agreement with the model predictions, providing quantitative support for the model. Building on this agreement, we performed metabolic control analysis, which identified partial displacement of glucose metabolism through the PMAS as the dominant mechanism underlying the observed reductions in glutamate and GABA and revealed key enzymes that selectively modulate each neurotransmitter. Overall, the model provides researchers and clinicians with a framework for hypothesis testing and treatment optimization, while also serving as a foundation for future model expansions.

neuroscience↗

bioRxiv2025

Fast voxel and structural MRI realignment to mitigate inter-acquisition motion for spectroscopy

Magnetic resonance spectroscopy (MRS) non-invasively measures the biochemical composition within a predefined brain region, enabling quantification of neurochemicals with biological and clinical relevance, such as N-acetylaspartate, creatine, choline, glutamate, and gamma-aminobutyric acid. However, accurate MRS quantification is compromised by subject motion displacing the prescribed location, a common problem during long scans or with motion-prone populations such as children and patients. Furthermore, displacement into bone tissue contaminates MRS data with noisy artifacts, often rendering them unusable. While promising solutions exist to address motion-related issues, many rely on specialized infrastructure and expertise available only at a limited number of research centers. We propose a fast and straightforward method that acquires a head scout (18 s) MRI sequence following potential motion, automatically repositions the prescribed voxel with the scanners built-in AutoAlign function, and realigns the T1-weighted image to the updated position for anatomical segmentation. Using voxels prescribed in the prefrontal cortex, thalamus, and left superior temporal gyrus, we demonstrated that this realignment method successfully restored displaced voxels to their intended locations, eliminating bone contamination while improving voxel targeting through greater overlap with intended regions and more consistent voxel placement across subjects. This solution offers a quick and practical way for correcting subject motion between scans by combining available tools that are readily accessible even to new users, while more sophisticated motion correction technologies continue to develop towards broader adoption.

neuroscience↗

bioRxiv2025

Spatially convergent fMRI signatures of diabetes and male sex identify genetic vulnerabilities to accelerated brain aging

Age-related cognitive decline results from complex interactions between neuroendocrine and neurometabolic processes that undergo lifelong degredation, yet the mechanisms underlying these interactions remain poorly understood. This study examined the effects of diabetes and sex on functional brain networks across aging through analysis of two large cohorts (N=1,621 total) using both 3T and 7T functional MRI, complemented by spatial transcriptomic data from over 14,000 genes from six post-mortem brains. Four networks-- cingulo-opercular, default mode, salience, and lateral somatomotor--exhibited significant functional decline in both individuals with diabetes and independently in males. Gene expression analysis of vulnerable networks revealed significant overexpression of insulin-dependent glucose transporters, dopaminergic and GABAergic synaptic genes, and VEGFA-VEGFR2 pathway components. These findings suggest functionally-specific circuit vulnerability to metabolic and hormonal dysregulation, potentially offering targets for early intervention before irreversible neurodegeneration occurs.

neuroscience↗

bioRxiv2024

Ketosis Elevates Antioxidants and Enhances Neural Function Through Improved Bioenergetics: A 1H MR Spectroscopy Study

Ketosis is known to alter the balance of neuroactive amino acids and enhance neural function when compared to a glycolytic condition. However, its influence on other metabolites, such as antioxidants and neural energy markers, and the mechanisms by which ketosis improves neural function remain unclear. Here, we measure the neurochemical effects of acute ketosis on the human brain using ultra-high-field 1H MR Spectroscopy (MRS) and investigate the subsequent impact on neural function through resting-state functional magnetic resonance imaging (rsfMRI). In a within-subjects design, N = 63 healthy adults from across the lifespan underwent 1H MRS and rsfMRI scans before and after consuming individually weight-dosed and calorically-matched ketone monoester or glucose drinks. Ketone monoester administration, but not glucose, significantly elevated cerebral antioxidants and energy markers while decreasing GABA, glutamate, and glutamine levels in the posterior cingulate cortex (PCC). Notably, increased bioenergetics, specifically an increase in total creatine, correlated with greater improvements in neural function as measured using rsfMRI. Our results integrate metabolic and functional neuroimaging findings, offering a comprehensive understanding of ketosis-induced changes in brain chemistry and functional network dynamics, yielding valuable insights into potential mechanisms by which ketosis imparts its neural benefits.

neuroscience↗

bioRxiv2023

Neuroinflammation in post-acute sequelae of COVID-19 (PASC) as assessed by PBR28 PET correlates with vascular disease measures

The COVID-19 pandemic caused by SARS-CoV-2 has triggered a consequential public health crisis of post-acute sequelae of COVID-19 (PASC), sometimes referred to as long COVID. The mechanisms of the heterogeneous persistent symptoms and signs that comprise PASC are under investigation, and several studies have pointed to the central nervous and vascular systems as being potential sites of dysfunction. In the current study, we recruited individuals with PASC with diverse symptoms, and examined the relationship between neuroinflammation and circulating markers of vascular dysfunction. We used [11C]PBR28 PET neuroimaging, a marker of neuroinflammation, to compare 12 PASC individuals versus 43 normative healthy controls. We found significantly increased neuroinflammation in PASC versus controls across a wide swath of brain regions including midcingulate and anterior cingulate cortex, corpus callosum, thalamus, basal ganglia, and at the boundaries of ventricles. We also collected and analyzed peripheral blood plasma from the PASC individuals and found significant positive correlations between neuroinflammation and several circulating analytes related to vascular dysfunction. These results suggest that an interaction between neuroinflammation and vascular health may contribute to common symptoms of PASC.

neuroscience↗

bioRxiv2020

Ultra-high field (7T) functional magnetic resonance imaging in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of the central nervous system that results in a progressive loss of motor function and ultimately death. It is critical, yet also challenging, to develop non-invasive biomarkers to identify, localize, measure and/or track biological mechanisms implicated in ALS. Such biomarkers may also provide clues to identify potential molecular targets for future therapeutic trials. Herein we report on a pilot study involving twelve participants with ALS and nine age-matched healthy controls who underwent high-resolution resting state functional magnetic resonance imaging at an ultra-high field of 7 Tesla. A group-level whole-brain analysis revealed a disruption in long-range functional connectivity between the superior sensorimotor cortex (in the precentral gyrus) and bilateral cerebellar lobule VI. Post hoc analyses using atlas-derived left and right cerebellar lobule VI revealed decreased functional connectivity in ALS participants that predominantly mapped to bilateral postcentral and precentral gyri. Cerebellar lobule VI is a transition zone between anterior motor networks and posterior non-motor networks in the cerebellum, and is associated with a wide range of key functions including complex motor and cognitive processing tasks. Our observation of the involvement of cerebellar lobule VI adds to the growing number of studies implicating the cerebellum in ALS. Future avenues of scientific investigation should consider how high-resolution imaging at 7T may be leveraged to visualize differences in functional connectivity disturbances in various genotypes and phenotypes of ALS along the ALS-frontotemporal dementia spectrum.

neuroscience↗

bioRxiv2020

Inpainting as a Technique for Estimation of Missing Voxels in Chemical Shift Imaging

Issues with model fitting (i.e. suboptimal standard deviation, linewidth/full-width-at-half-maximum, and/or signal-to-noise ratio) in multi-voxel MRI spectroscopy, or chemical shift imaging (CSI), can result in the significant loss of usable voxels. A potential solution to minimize this problem is to estimate the value of unusable voxels by utilizing information from reliable voxels in the same image. We assessed an image restoration method called inpainting as a tool to restore unusable voxels and compared it with traditional interpolation methods (nearest neighbor, trilinear interpolation and tricubic interpolation). We applied these techniques to N-acetylaspartate (NAA) spectroscopy maps from a CSI dataset. Inpainting exhibited superior performance (lower normalized root-mean-square errors, NRMSE) compared to all other methods considered (ps<0.001). Inpainting maintained its superiority whether the previously unusable voxels were randomly distributed or located in regions most commonly affected by voxel loss in real-world data. Clinical RelevanceThe presence of missing voxels can be problematic, particularly when data are analyzed in standard space, given that only voxels that are contributed to by all participants can be interrogated in these analyses. Inpainting is a promising approach for recovering unusable or missing voxels in voxelwise analyses, particularly in imaging modalities characterized by low SNR such as CSI.

bioengineering↗