Biology subjects

Pham, T. Q.

Publications and source records attributed to Pham, T. Q..

5 recordsLinked to original sources

bioRxiv2026

Multi-modal Ensemble Approach for Decoding Player Intentions in Table Tennis

This study aims to predict human intentions during intense sports activities, specifically in table tennis. Using a publicly available Real World Table Tennis dataset containing simultaneous EEG and video recordings, we developed a series of subject-specific classifiers for nine players (7 males and 2 females; age range 18-30), based on pose features and EEG signals. The pose-based classifier used a stochastic gradient descent model with logistic loss, whereas the EEG-based classifier employed a modified convolutional neural network architecture (EEGNet). Both classifiers successfully predicted left-right attack intentions from the time windows preceding racket-ball impact, with optimal decoding occurring at -100 ms for pose features and -500 ms for EEG signals. Although EEG-based decoding achieved comparable performance to pose-based decoding, a multi-modal ensemble further improved prediction significantly, reaching a mean macro F1 score of 0.563 (bootstrapped 95% CI: 0.523-0.603), corresponding to gains of +0.03 over pose-only and +0.02 over EEG-only classifiers. Because each classifier is trained independently, the ensemble can be feasibly extended to incorporate additional modalities in the future. These results suggest potential relevance of this framework as neurofeedback tools for sports training and neural prosthetic systems in future work.

neuroscience↗

bioRxiv2026

Cross Domain Consistency of Aesthetic Preference-driven Social Behavior

Aesthetic preference is a primary driver of social behavior in the digital era, yet the extent to which these preferences remain consistent across disparate domains remains poorly understood. We hypothesize that aesthetic judgment is governed by a domain-invariant latent structure, such that individuals who exhibit similar preferences in one category will demonstrate comparable alignment in seemingly unrelated domains. To test this, we recruited 37 participants to evaluate stimuli across three distinct aesthetic domains: art, faces (male and female), and scenes. We developed a novel computational framework that reformulates cross-domain preference as a user-based collaborative filtering problem, encoding individual profiles through inter-subject similarity matrices. Our model successfully predicted participant responses in a target domain based on their similarity to the cohort in a separate source domain. These results demonstrate robust cross-domain consistency, suggesting that aesthetic evaluation is mediated by an abstract, domain-general mechanism rather than being purely stimulus-dependent. We propose that this consistency is rooted in a shared neurophysiological pathway, likely involving the orbitofrontal cortex (OFC) and the Default Mode Network (DMN), and discuss how these findings provide a foundation for more sophisticated, cross-modal recommendation systems and the study of individual social identity.

neuroscience↗

bioRxiv2021

On co-activation pattern analysis and non- stationarity of resting brain activity

The non-stationarity of resting-state brain activity has received increasing attention in recent years. Functional connectivity (FC) analysis with short sliding windows and coactivation pattern (CAP) analysis are two widely used methods for assessing the dynamic characteristics of brain activity observed with functional magnetic resonance imaging (fMRI). However, the statistical nature of the dynamics captured by these techniques needs to be verified. In this study, we found that the results of CAP analysis were similar for real fMRI data and simulated stationary data with matching covariance structures and spectral contents. We also found that, for both the real and simulated data, CAPs were clustered into spatially heterogeneous modules. Moreover, for each of the modules in the real data, a spatially similar module was found in the simulated data. The present results suggest that care needs to be taken when interpreting observations drawn from CAP analysis as it does not necessarily reflect non-stationarity or a mixture of states in resting brain activity. HighlightsO_LICAP was conducted for real fMRI data and a stationary null model. C_LIO_LIThe results of CAP analysis were similar for the real and simulated data. C_LIO_LISimilar results for real and simulated data in both ROI- and voxel-based analyses. C_LIO_LIResults of CAP analysis may not reflect non-stationarity of resting brain activity. C_LI

neuroscience↗

bioRxiv2021

Vision-to-value transformations in artificial network and human brains

Humans and now computers can derive subjective valuations from sensory events although such transformation process is essentially unknown. In this study, we elucidated unknown neural mechanisms by comparing convolutional neural networks (CNNs) to their corresponding representations in humans. Specifically, we optimized CNNs to predict aesthetic valuations of paintings and examined the relationship between the CNN representations and brain activity via multivoxel pattern analysis. Primary visual cortex and higher association cortex activities were similar to computations in shallow CNN layers and deeper layers, respectively. The vision-to-value transformation is hence proved to be a hierarchical process which is consistent with the principal gradient that connects unimodal to transmodal brain regions (i.e. default mode network). The activity of the frontal and parietal cortices was approximated by goal-driven CNN. Consequently, representations of the hidden layers of CNNs can be understood and visualized by their correspondence with brain activity-facilitating parallels between artificial intelligence and neuroscience.

neuroscience↗

bioRxiv2019

HDAC6 promotes self-renewal and migration/invasion of rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a devastating pediatric sarcoma. The survival outcomes remain poor for patients with relapsed or metastatic disease. Effective targeted therapy is lacking due to our limited knowledge of the underlying cellular and molecular mechanisms leading to disease progression. In this study, we used functional assays in vitro and in vivo (zebrafish and xenograft mouse models) to demonstrate the crucial role of HDAC6, a cytoplasmic histone deacetylase, in driving RMS tumor growth, self-renewal and migration/invasion. Treatment with the HDAC6-selective inhibitor, Tubastatin A, recapitulates the HDAC6 loss-of-function phenotypes. HDAC6 regulates cytoskeletal dynamics to promote tumor cell migration and invasion. RAC1, a Rho family GTPase, is an essential mediator of HDAC6 function, and is necessary and sufficient for RMS cell migration and invasion. High expression of RAC1 correlates with poor clinical prognosis in RMS patients. Targeting the HDAC6-RAC1 axis represents a promising therapeutic option for improving survival outcomes of RMS patients.

cancer biology↗