Biology subjects

Muncy, N. M.

Publications and source records attributed to Muncy, N. M..

5 recordsLinked to original sources

bioRxiv2026

Concussion decreases brain signal variability

Sports-related concussion represents a major public health concern, with millions of cases diagnosed annually. Despite significant methodological advances in functional brain imaging, a clinically meaningful neuroimaging biomarker of concussion has yet to be established. This may be due in part to a reliance on traditional measures. For example, approaches examining mean activation across trials reduce responses to a single measure of central tendency and therefore fail to capture important individual differences. In contrast, blood oxygenation level dependent (BOLD) variability offers a promising new approach to measuring brain function, Specifically, it captures individual differences in the temporal variability in the BOLD signal over time. Further, it is sensitive to neural, vascular, and neurovascular coupling changes that accompany concussion. We collected baseline (prior to injury) and post-concussion (within 48 hours of injury) neuroimaging data in 56 collegiate athletes. Within this longitudinal dataset, we investigated changes in BOLD variability across multiple spatial scales. In addition, we examined their relationships with self-reported symptoms and cognitive performance. As expected, symptoms increased following concussion while computerized cognitive performance declined. BOLD variability decreased from baseline to post-concussion, particularly in the somatomotor and language networks. Moreover, changes in BOLD variability were related to changes in symptom reporting and cognitive performance. Together, these findings advance our understanding of how concussion affects brain function and highlight BOLD signal variability as a promising biomarker to aid ongoing efforts to improve the diagnosis and treatment of sports-related concussion.

neuroscience↗

bioRxiv2026

The Relationship between Institutional Prestige, Journal Impact Factor, and Sample Size in fMRI Studies of Memory: A Systematic Review

Low statistical power remains a persistent concern in functional magnetic resonance imaging (fMRI) research, largely due to small sample sizes. Although prior work has documented gradual increases in sample size over time, it remains unclear whether structural factors in the publication process are associated with study design characteristics such as sample size. This review addresses this gap by analyzing a large sample of fMRI studies to assess how institutional prestige, journal impact factor, and journal review practices are associated with sample size. We analyzed articles published in 2021-2024 reporting new fMRI data collection in adult humans and including a measure of memory. We found studies with specialized populations, such as patient populations, had smaller sample sizes, as did studies with task-based designs compared to resting-state designs. We also found larger sample sizes were associated with journals with a double-blind review process. Institutional prestige was positively associated with sample size such that more highly ranked institutions tended to have larger samples, but there was no interaction between review type (single-vs. double-blind) and prestige, indicating this difference is not likely due to reviewer bias. Journal impact factor was not associated with sample size, however institutional prestige score predicted journal impact factor. These results suggest structural factors at the institutional level likely have a stronger influence on published study sample size than reviewer practices or biases.

neuroscience↗

bioRxiv2026

Decoding of arousal and valence from fMRI data obtained during emotion inductions

Arousal and valence are fundamental dimensions of affective experience signifying levels of activation and pleasantness, respectively. These dimensions play a crucial role in shaping emotional responses and behaviors, with significant implications for psychopathology. Previous machine learning studies had some success decoding these states from brain activation patterns observed during task-based functional magnetic resonance imaging (fMRI), but the results have varied across studies. Moreover, prior studies have often been limited by small sample sizes, weak decoding performance, and non-whole-brain analyses, leaving the neural representations of arousal and valence largely unresolved. Here we successfully decoded arousal and valence from whole-brain task-fMRI data collected from 132 participants during exposure to 300 unique emotional stimuli, including 150 movie clips and 150 text scenarios that reliably induced a wide range of arousal and valence states. Mass univariate general linear models identified block-level activation (emotion stimuli > washout) from all gray matter voxels. Multivariate regression analysis predicted arousal and valence ratings based on these gray matter activations. Patterns in the fMRI data underlying arousal and valence were robust, as they were successfully decoded across both induction modalities using five different linear multivariate regression models. Although significant, decoding from scenarios was less successful than from movies, likely due to their more imaginative nature. In particular, decoding arousal from scenarios only showed low predictive utility. Representations of arousal and valence were widespread throughout the brain, and we reveal cerebellar and brainstem contributions that have largely been absent in past fMRI decoding studies. These findings clarify the distributed neural basis of arousal and valence and provide a foundation for future clinical research on the role of these constructs in affective dysregulation.

neuroscience↗

bioRxiv2025

Representational Similarity and Pattern Classification of Fifteen Emotional States Induced by Movie Clips and Text Scenarios

How do different emotional states relate to each other and how are they represented in the human brain? These are important questions in the field of affective neuroscience, with profound scientific and vast clinical implications. Different theories of emotion tend to emphasize the relative importance of distinct psychological constructs, for example categorical labels (e.g., fear, joy, or sadness) versus dimensional ratings (e.g., valence and arousal), for understanding human emotions. To investigate whether categorical or dimensional constructs correspond better to patterns of brain activity associated with human affective experiences, we experimentally induced 15 emotions (spanning positive, negative, and neutral valence) in 136 participants using 150 short movie clips and 150 one- or two-sentence text scenarios, while their blood oxygenation-level dependent activity was recorded in a magnetic resonance imaging scanner. Results from our representational similarity analyses suggest participants brain activity significantly correlated with their categorical labeling of, but not their dimensional rating of, the movie clips and text scenarios. Subsequently, we were also able to decode the categorical labels of these emotional stimuli using whole-brain multi-voxel pattern classification, with important voxels found in many cortical, limbic, subcortical, cerebellar, and brainstem regions. Finally, we found similar clusters of emotions through exploratory hierarchical clustering analyses of participants categorical labeling of and brain responses to these stimuli. Taken together, these findings greatly advance our understanding of how a large set of human emotions are related to each other both in terms of the participants self-report and their brain activity. Significance StatementWe successfully decoded fifteen emotional states induced by movie clips and text scenarios based on participants brain responses (blood oxygenation-level dependent signals) to these stimuli using multi-voxel pattern classification (a supervised machine learning approach). We also found that participants brain responses correlated with their self-reported emotional experience, i.e. which emotion they felt while they were presented with these stimuli, using representative similarity analysis (an unsupervised approach). Finally, we found that these emotions are organized in very similar ways both in terms of participants categorical labeling and their brain responses to these stimuli. Together, these data-driven and computational modeling-based findings greatly advance our understanding of how a large set of emotions are organized and represented in the human brain.

neuroscience↗

bioRxiv2020

Differences in Chemo-signaling Compound-Evoked Brain Activity in Male and Female Young Adults: A Pilot Study in the Role of Sexual Dimorphism in Olfactory Chemo-Signaling

IntroductionPrevious studies have shown that putative pheromones 4,16-androstadien-3-one (AND) and estra-1,3,5(10),16-tetraen-3-ol (EST) cause activation in the preoptic area/anterior hypothalamus in men and women. Sex differences in neural activation patterns have been demonstrated when participants are subject to pheromone stimulation; however, whether other compounds give rise to similar neural activity has not been completely investigated. MethodsTwenty-nine young adults [16 female (21.3+/-0.54; mean yrs+/-SE), 13 male (22.85+/-0.42)] participated in a 3-block design, where participants were exposed to a scent (lavender), a synthetic male pheromone (4,16-androstadien-3b-ol; ALD), and a synthetic female pheromone (1,3,5(10),16-Estratetraen-3-ol; EST) via an automated olfactometer. Whole-brain, high-resolution (1.8mm3) functional MRI data from a Siemens Trio 3T MRI scanner were collected during all blocks. Five adults were excluded due to excessive movement. MANOVA analysis, a 2 x 3 multivariate model and analysis of 2x2 effects between sex and subsets of stimuli was done for activation over the whole brain and small volumes involved in olfaction. ResultsExploratory analysis of 2x2 effects between sex and subsets of stimuli exhibited significant interactions when assessing activations over the whole brain, and small volumes involved in olfaction. The left and right frontal poles (LFP, RFP) shows significant interaction when assessing sex with lavender and EST for whole brain analysis. For small volume analysis, the right orbitofrontal cortex (ROFC) exhibited a sex with lavender and ALD interaction, and a sex with lavender and EST interaction was observed in the left inferior frontal gyrus (LIFG). Main effects of sex, stimulus, or interaction show no differences analyzed using a 2 x 3 multivariate model. ConclusionThe study shows there is a sexually dimorphic response in the olfactory system to pheromones not previously studied. Scents like lavender do not have this same response. These distinct functional differences in activation patterns may be a result of neural development and maturation differences between sexes. Future studies should expand this pilot study and involve a younger demographic to accurately determine the age at which the olfactory response differentiates between males and females.

neuroscience↗