Biology subjects

Liu, T.-L.

Publications and source records attributed to Liu, T.-L..

7 recordsLinked to original sources

bioRxiv2026

Resting Galvanic Skin Response Reflects Fluctuations in Creativity Potential for Solving Creativity Tasks

Creative performance fluctuates from moment to moment, suggesting that it depends partly on transient internal states present before creative thinking begins. Although such fluctuations have been identified in central neural activity, it remains unclear whether they are also reflected in autonomic physiology. We examined whether cardiac and electrodermal activity during a brief pre-trial resting period was associated with subsequent creative performance. Photoplethysmography, electrocardiography, and electrodermal activity were recorded while 28 participants completed the Alternative Uses Test and Fusion Innovation Test, assessing divergent and convergent creative thinking, respectively. Data from 27 participants was included in the analyses. Heart rate, heart rate variability, tonic skin conductance level, and phasic skin conductance activity were extracted from observation windows ranging from 11 to 30 s within a 30-s pre-trial rest period. Trial-level creativity was evaluated using GPT-based ratings of novelty, feasibility, and goal attainment. Linear mixed-effects models showed that higher pre-trial tonic skin conductance level was consistently associated with better subsequent creative performance across tasks, with overall model fit peaking at a 21-s observation window. Permutation-based feature-importance analysis provided convergent support for the contribution of tonic skin conductance, whereas the cardiac and phasic electrodermal indicators showed no reliable independent associations. However, the model explained only a small proportion of behavioral variance. These findings suggest that tonic sympathetic arousal reflects a momentary physiological state associated with creativity potential, while autonomic signals alone remain insufficient for accurate individual-level prediction.

neuroscience↗

bioRxiv2026

Dynamical Biomarkers of Creative Cognition Across Divergent and Convergent Problem-Solving

Creativity fluctuates markedly from moment to moment, even within the same individual, yet the neural dynamics that determines whether a given attempt produces a highly creative idea remains poorly understood. Prior studies have identified static EEG correlates of creative thinking, but these do not explain how brain activity is dynamically organized before and during successful idea generation. Here, we model creative cognition as trajectories through a neural state space using energy landscape analysis (ELA) of EEG recorded during two complementary problem-solving paradigms: the divergent Alternative Uses Test (AUT) and the convergent, goal-directed Fusion Innovation Test (FIT). Across both tasks, creative success was associated with dissociable dynamical signatures in the resting and ideation stages. Before ideation, greater diversity of resting-state patterns of activity, corresponding to possible attractors, indexed a preparatory substrate of creative potential, showing weak trial-level effects but robust subject-level coupling with performance. During ideation, higher creativity was predicted by how the brain traversed its accessible state space: successful trials were characterized by traversal biased toward sustained exploration within stable attractor basins rather than frequent switching between basins of attraction ({beta} = 0.104, p = 0.004, trial-level). These findings identify a task-invariant, biologically grounded dynamical mechanism of creative cognition and show that creative performance depends not only on which neural states are available, but also on how neural activity traverses that state space.

neuroscience↗

bioRxiv2026

Investigating the skin response of Striped Catfish to acute ammonia stress reveals a potential exosome-based ammonia excretion system

Ammonia can rapidly accumulate in intensive aquaculture and pose serious threats to fish health. Fish skin functions as a vital immune-related organ and a significant surface barrier against ammonia; however, little is known about the skins response and to acute ammonia stress. In this study, Striped catfish were exposed to a half-lethal concentration of ammonia to evaluate skin responses. We found generalized inflammation in the liver, spleen, and skin. However, the skin tissue showed subtle signs of damage, with tissue ammonia concentration accumulating and then decreasing. Further transcriptomic analysis of skin gene function suggested a hypothesized ammonia regulation occurring within cell compartments. Cellular examination by transmission electron microscopy further showed that accumulated exosome-suspecting vesicles near the epithelial surface were associated with ammonia regulation during acute ammonia stress. Using a newly established Striped catfish skin epithelial cell line, along with an exosome inhibitor, confirms the presence of exosome vesicles and their role in ammonia excretion. In conclusion, acute ammonia stress induces inflammation in Striped catfish skin, while active ammonia excretion via exosomes may alleviate ammonia accumulation, thereby maintaining skin tissue integrity. This study explores Striped catfish skin responses to acute ammonia stress and highlights a newly identified mechanism of ammonia regulation in the skin. HighlightsO_LIFish skin can regulate ammonia concentrations and stress. C_LIO_LIExosomal vesicles are involved in the excretion of ammonia from the skin. C_LI

immunology↗

bioRxiv2025

A Shared Neural Marker Predicts Creative Performance Across Distinct Problem-Solving Tasks

Creativity is essential for innovation, yet the brain mechanisms supporting its moment-to-moment variability remain unclear. We hypothesize that creativity depends on dynamic fluctuations in neural flexibility, which determine the potential to generate creative solutions. Here, we identify a shared neural marker of "creativity potential" that predicts upcoming performance across distinct problem-solving tasks. Twenty-eight participants completed the Alternative Uses Test (AUT), a measure of divergent thinking, and the Fusion Innovation Test (FIT), which integrates divergent and convergent thinking. Responses were scored for novelty, feasibility, and goal attainment using validated GPT-based automated evaluation. EEG signals recorded prior to problem onset were used to decode single-trial creativity scores. A decoding model based on coherence features achieved robust performance (r = 0.45, leave-one-trial-out) and generalized across individuals (r = 0.34, leave-one-subject-out). Feature weights revealed a creativity potential network (CPN), characterized by frontal-temporal interactions in beta frequency band. Applying the model to resting-state recordings revealed [~]3-minute cycles of creativity potential, suggesting intrinsic brain dynamics shape readiness for creative problem-solving. These findings establish a shared neural marker of creativity that transcends task boundaries and individuals. Beyond advancing our understanding of creative cognition, this work opens the possibility of monitoring creativity potential in real time, with implications for neurofeedback and creativity enhancement in daily life. Significance statementCreativity allows us to generate novel and useful ideas, yet our ability to be creative fluctuates from moment to moment. Here we identify a neural marker of "creativity potential" that predicts upcoming creative performance across two distinct problem-solving tasks. Using EEG and GPT-based automated evaluation, we show that preparatory brain activity encodes creativity potential, generalizing across tasks and individuals. Furthermore, creativity potential fluctuates in intrinsic [~]3-minute cycles during rest. These results advance our understanding of the neural basis of creativity and provide a foundation for real-time monitoring and neurofeedback applications that may help individuals enhance their creative capacity.

neuroscience↗

bioRxiv2020

ezGeno: An Automatic Model Selection Package for Genomic Data Analysis

To facilitate the process of tailor-making a deep neural network for exploring the dynamics of genomic DNA, we have developed a hands-on package called ezGeno that automates the search process of various parameters and network structure. ezGeno considers three different sets of search spaces, namely, the number of filters, dilation factors, and the connectivity between different layers. ezGeno can be applied to any kind of 1D genomic input such as genomic sequences, histone modifications, DNase feature data and so on. Combinations of multiple abovementioned 1D features are also applicable. Specifically, for the task of predicting TF binding using genomic sequences as the input, ezGeno can consistently return the best performing set of parameters and network structure, as well as highlight the important segments within the original sequences. For the task of predicting tissue-specific enhancer activity using both sequence and DNase feature data as the input, ezGeno also regularly outperforms the hand-designed models. In this study, we demonstrate that ezGeno is superior in efficiency and accuracy when compared to AutoKeras, a general open-source AutoML package. The average AUC of ezGeno is also consistently higher than the result of using a one-layer DeepBind model. With the flexibility of ezGeno, we expect that this package can provide future researchers not only support of model design in their analysis of genomic studies but also more insights into the regulatory landscape. AvailabilityThe ezGeno package can be freely accessed at https://github.com/ailabstw/ezGeno. ContactDr. Chien-Yu Chen, chienyuchen@ntu.edu.tw

bioinformatics↗

bioRxiv2018

Cortical Column and Whole Brain Imaging of Neural Circuits with Molecular Contrast and Nanoscale Resolution

Optical and electron microscopy have made tremendous inroads in understanding the complexity of the brain, but the former offers insufficient resolution to reveal subcellular details and the latter lacks the throughput and molecular contrast to visualize specific molecular constituents over mm-scale or larger dimensions. We combined expansion microscopy and lattice light sheet microscopy to image the nanoscale spatial relationships between proteins across the thickness of the mouse cortex or the entire Drosophila brain, including synaptic proteins at dendritic spines, myelination along axons, and presynaptic densities at dopaminergic neurons in every fly neuropil domain. The technology should enable statistically rich, large scale studies of neural development, sexual dimorphism, degree of stereotypy, and structural correlations to behavior or neural activity, all with molecular contrast.\n\nOne Sentence SummaryCombined expansion and lattice light sheet microscopy enables high speed, nanoscale molecular imaging of neural circuits over large volumes.

neuroscience↗

bioRxiv2017

Lamellar Junctions In The Endolymphatic Sac Act As A Relief Valve To Regulate Inner Ear Pressure

The inner ear is a fluid-filled closed-epithelial structure whose normal function requires maintenance of an internal hydrostatic pressure and fluid composition by unknown mechanisms. The endolymphatic sac (ES) is a dead-end epithelial tube connected to the inner ear. ES defects can cause distended ear tissue, a pathology often seen in hearing and balance disorders. Using live imaging of zebrafish larvae, we reveal that the ES undergoes cycles of slow pressure-driven inflation followed by rapid deflation every 1-3 hours. Using serial-section electron microscopy and adaptive optics lattice light-sheet microscopy, we find a pressure relief valve in the ES comprised of thin overlapping basal lamellae that dynamically extend over neighboring cells before rupturing under pressure leading to ES collapse. The unexpected discovery of a physical relief valve in the ear emphasizes the need for further study into how organs control fluid pressure, volume, flow, and ion homeostasis in development and disease.

developmental biology↗