Biology subjects

Medina, M. C.

Publications and source records attributed to Medina, M. C..

4 recordsLinked to original sources

bioRxiv2026

Evaluating Approaches for Inference Testing of Whole-Brain Densely Sampled Single-Subject Task fMRI Data

Task-based precision mapping has become a promising technique in functional MRI (fMRI) to robustly characterize and map an individuals unique activity patterns. These experiments consist of acquiring extensive imaging data in one participant, ultimately improving the sensitivity and specificity of individual-specific functional localization. Despite its advantages, studies have primarily focused on understanding individual-specific cortical activation, preventing a holistic view of a systems-level functional response, and to date, best approaches for the statistical analysis of controlled task-based, densely sampled, whole-brain data have not yet been fully established. Therefore, in this study, we collected whole-brain (i.e. covering cortex, cerebellum, and brainstem) multi-echo densely sampled data of the auditory system, a system with major subcortical components, and evaluated activation sensitivity as well as activation stability across data subsets of commonly-used whole-brain and region-specific inference testing approaches. The whole-brain approaches involved standard voxel-level and cluster-level inference schemes with varying statistical thresholds and a non-parametric permutation inference approach. The region-specific approaches involved an exploratory top % t-statistics methods and non-parametric permutation inference approaches. We found that a whole-brain voxel-level approach with a false discovery rate (FDR) correction (p<0.05) presented highest sensitivity across regions and subjects as well as most consistent detection of expected auditory regions, even with lower scan duration. In addition, we found that a region-specific top % t-statistic approach may be a useful exploratory functional localization tool and a complementary method to standard inference testing approaches.

bioengineering↗

bioRxiv2026

Stretch-Evoked Motor Responses in the Brainstem are Modulated by Task Instructions

Reliable noninvasive measurement of human brainstem activity during motor control remains challenging due to small anatomical structures and physiological noise, yet it is essential for understanding descending contributions to rapid feedback control. We used brainstem-optimized whole brain functional magnetic resonance imaging (fMRI) to examine whether task-dependent modulation of stretch-evoked motor responses in humans are associated with changes in activation within reticulospinal regions of the human brainstem. A behavioral validation experiment (N=10), in which participants were instructed to resist or yield to brief wrist perturbations, confirmed task-dependent modulation of long-latency responses (LLRs). In a separate imaging cohort (N=26), participants performed the same tasks during fMRI using an MRI-compatible robotic device and a multi-echo acquisition with physiological noise compensation. Imaging analyses revealed greater blood-oxygen-level-dependent signal during Resist compared to Yield while controlling for background contraction and proprioceptive input, with activation distributed bilaterally across the pons and medulla in regions consistent with major reticulospinal nuclei. Laterality analyses demonstrated a rostrocaudal gradient, with relatively ipsilateral-biased activation in the medulla shifting toward more contralateral patterns in the pons. These findings indicate that instruction-dependent modulation of stretch-evoked motor responses is associated with measurable changes in human brainstem activation, providing evidence that reticulospinal regions contribute to task-dependent feedback control.

neuroscience↗

bioRxiv2025

Mapping Whole-Brain Auditory Activation with 3T Multi-Echo fMRI at the Group and Individual-Subject Level

Magnetic resonance imaging (MRI) is a powerful and established tool to non-invasively probe the human auditory system. Varied blood oxygen level-dependent functional MRI (BOLD fMRI) acquisitions have been used to examine the functional roles of this system, but these acquisitions have substantial limitations, such as the need for specialized hardware and long acquisition times, and they typically rely on group averaging of activation patterns. In recent years, whole-brain multi-echo (ME) fMRI techniques have been used to reduce artifacts and scan times, map entire sensory systems, and improve sensitivity to neural activity in both resting-state and task fMRI data acquired at 3T. Combined with dense-sampling strategies, these ME techniques have facilitated "precision mapping" of neural activity in individual subjects. Thus, in this technical note we propose the use of a commonly available ME wholebrain acquisition and ME denoising approaches to examine the auditory system in both group and densely sampled single-subject datasets. Whole-brain and region-specific analyses were performed to identify auditory regions of activation. At the group level, auditory activation was identified bilaterally in cortical regions and unilaterally in cerebellar lobules VIIb/VIIIa with both analyses. Additionally, the region-specific analysis successfully identified unilateral activation in thalamic and brainstem regions. At the individual subject-level, precision mapping combined with ME denoising methods enhanced sensitivity, yielding bilateral activation in cortical, cerebellar, thalamic, and brainstem regions with both analyses. Lastly, we demonstrate the benefits of using multi-echo methods and a whole-brain precision mapping approach to better align an individuals functional response to their specific anatomy.

bioengineering↗

bioRxiv2025

Impact of multi-echo ICA modeling decisions on motor-task fMRI analysis

Multi-echo independent component analysis (ME-ICA) has been demonstrated to improve sensitivity and reliability of task functional magnetic resonance imaging (fMRI) data and, in particular, motor-task data with inherent task-correlated head motion. However, previous work has shown that an overly aggressive ME-ICA denoising approach may unintentionally remove task-related signal, while a more conservative approach may not effectively mitigate noise. While the effects of varied implementations of ME-ICA on signal and noise characteristics have been tested thoroughly in breath-hold data, the effects of similar modeling decisions have not been studied in motor-task data, which present with a more localized neural response. Here, we tested and compared the impacts of three analysis methods using rejected ME-ICA components as regressors in subject-level modeling: Aggressive (simple inclusion of ME-ICA regressors), Moderate (excluding task-correlated ME-ICA regressors from the model), and Conservative (orthogonalization of ME-ICA regressors to the core model and accepted ME-ICA components). We applied these methods to data from healthy and multiple sclerosis populations that included performance of hand-grasp, shoulder-abduction, and ankle-flexion tasks. We found that when the amount of head motion and its correlation with the task was high and the expected task-evoked signal was relatively low, the Conservative method led to significantly higher activation, t-statistics, and test-retest similarity in motor regions compared to the Aggressive method. Future motor-task studies may wish to implement similar models to prevent loss of motor signal, while still mitigating the effects of task-correlated head motion.

bioengineering↗