A5000578418- Neural dynamics and brain function
- Face Recognition and Perception
- Visual perception and processing mechanisms
- Visual Attention and Saliency Detection
- EEG and Brain-Computer Interfaces
- Gaze Tracking and Assistive Technology
- Neural and Behavioral Psychology Studies
- Spatial Cognition and Navigation
- Neural Networks and Applications
- Functional Brain Connectivity Studies
- Fractal and DNA sequence analysis
- Adipose Tissue and Metabolism
- Multisensory perception and integration
- Facial Nerve Paralysis Treatment and Research
- Cell Image Analysis Techniques
- Categorization, perception, and language
- Mobile Ad Hoc Networks
- Advanced Memory and Neural Computing
- Color Science and Applications
- 2D Materials and Applications
- Image Retrieval and Classification Techniques
- Topic Modeling
- Advanced Graph Neural Networks
- Color perception and design
- Neuroscience and Music Perception
The Ohio State University
2013-2025
East China Normal University
2020
Peng Cheng Laboratory
2020
Sun Yat-sen University
2020
Shanghai Institute of Microsystem and Information Technology
2014
Chinese Academy of Sciences
2014
The University of Texas Health Science Center at San Antonio
2007
In studies of cognitive neuroscience, multivariate pattern analysis (MVPA) is widely used as it offers richer information than traditional univariate analysis. Representational similarity (RSA), one method MVPA, has become an effective decoding based on neural data by calculating the between different representations in brain under conditions. Moreover, RSA suitable for researchers to compare from modalities and even bridge species. However, previous toolboxes have been made fit specific...
Holistic processing has traditionally been regarded as unique to faces, attributed the spatial layout across facial features and their variability individuals. However, whether such can occur in stimuli other than faces remained an open contentious question. Here, we show that novel non-face stimuli, which are designed be differentiated strictly by configural properties, drive holistic effects, while similar non-configural do not generate these effects. Using novel, abstract isolate...
People integrate "what" and "where" information to recognize objects. Even when irrelevant or uninformative, location can influence object identity judgments. When two sequential stationary objects occupy the same location, people are faster more accurate respond (sensitivity effects) likely judge as identical (spatial congruency bias [SCB]). Other paradigms using moving highlight spatiotemporal contiguity's role in processing. To bridge these gaps, we conducted preregistered experiments...
Melatonin is produced not only by the pineal gland but cells of bone marrow. Moreover, melatonin known to promote osteogenic differentiation in several cell line models and multipotential marrow mesenchymal stem cells. Fatty acids have been independently shown direct such acquire phenotype molecular characteristics adipocytes. To examine effect on intracellular triglyceride accumulation, an indicator adipogenic rat osteoblast-like ROS17/2.8 line, were incubated with added oleic acid (100...
Highlights•EEG MVPA provides temporal evidence of facial repetition suppression•Comparisons between brains and DCNNs reveal a fatigue mechanism•Our reverse engineering framework offers tool to investigate neural mechanismsSummaryFacial suppression, well-studied phenomenon characterized by decreased responses repeated faces in visual cortices, remains subject ongoing debate regarding its underlying mechanisms. Our research harnesses advanced multivariate analysis techniques the prowess deep...
Abstract This easy‐to‐follow handbook offers a straightforward guide to electroencephalogram (EEG) analysis using Python, aimed at all EEG researchers in cognitive neuroscience and related fields. It spans from single‐subject data preprocessing advanced multisubject analyses. contains four chapters: Preprocessing Single‐Subject Data, Basic Python Data Operations, Multiple‐Subject Analysis, Advanced Analysis. The chapter provides standardized procedure for preprocessing, primarily the...
Remarkably, human brains have the ability to accurately perceive and process real-world size of objects, despite vast differences in distance perspective. While previous studies delved into this phenomenon, distinguishing from other visual perceptions, like depth, has been challenging. Using THINGS EEG2 dataset with high time-resolution brain recordings more ecologically valid naturalistic stimuli, our study uses an innovative approach disentangle neural representations object retinal...
In contrast to the commonly used chemical vapor deposition growth that leads multilayer graphene formation by carbon segregation from Ni bulk, we designed a Ni-Ge binary system directly grow film on substrate, via with methane and hydrogen gas as precursors. Our fully overcomes fundamental limitations of yields homogenous single layer over large areas. The substrate shows self limiting monolayer can be obtained these substrate.
In an era where neuroscience dances with computational advances, the power to "visualize" one's thoughts at image-level is no longer confined realm of science fiction. This groundbreaking image reconstruction from brain signals (IRBS) techniques, riding wave deep learning and large-scale neuroimaging datasets, offer unprecedented perspective for not only neurocognitive research but also psychiatry. this short commentary, I provide a concise introduction development IRBS technology on its...
Most models in cognitive and computational neuroscience trained on one subject do not generalize to other subjects due individual differences. An ideal individual-to-individual neural converter is expected generate real signals of from those another one, which can overcome the problem differences for models. In this study, we propose a novel EEG converter, called EEG2EEG, inspired by generative computer vision. We applied THINGS EEG2 dataset train test 72 independent EEG2EEG corresponding...
Abstract Our visual systems rapidly perceive and integrate information about object identities locations. There is long-standing debate how we achieve world-centered (spatiotopic) representations across eye movements, with many studies reporting persistent retinotopic (eye-centered) effects even for higher-level object-location binding. But these are generally conducted in fairly static experimental contexts. Might spatiotopic binding only emerge more dynamic saccade contexts? In the present...
Our visual systems rapidly perceive and integrate information about object identities locations. There is long-standing debate if how we achieve world-centered (spatiotopic) representations across eye movements, with many studies reporting persistent retinotopic (eye-centered) effects even for higher level object-location binding. But these are generally conducted in fairly static experimental contexts. Might spatiotopic binding only emerge more dynamic saccade contexts? In the present...
Now published in Brain-X doi: 10.1002/brx2.64 This easy-to-follow handbook offers a straightforward guide to EEG data analysis using Python, aimed at all researchers cognitive neuroscience and related fields. It covers the journey from single-subject preprocessing advanced processing techniques across subjects, with focus on practical application Python libraries such as NumPy, MNE-Python, SciPy, NeuroRA, etc. Designed for easy comprehension, our can serve an essential tool anyone looking...
People have the ability to combine both ‘what’ and ‘where’ information recognize objects. Prior studies revealed several ways location can influence object identity judgments, even when is irrelevant or uninformative. Specifically, in tasks determining whether two sequentially shown objects are same different, types of effects been reported: facilitation (through reaction time priming and/or enhanced sensitivity) “spatial congruency bias” (where people more likely judge as identical)...
Remarkably, human brains have the ability to accurately perceive and process real-world size of objects, despite vast differences in distance perspective. While previous studies delved into this phenomenon, distinguishing from other visual perceptions, like depth, has been challenging. Using THINGS EEG2 dataset with high time-resolution brain recordings more ecologically valid naturalistic stimuli, our study uses an innovative approach disentangle neural representations object retinal...
Deep convolutional neural networks (DCNNs) have demonstrated excellent performance in object recognition and been found to share some similarities with brain visual processing. However, the substantial gap between DCNNs human perception still exists. Functional magnetic resonance imaging (fMRI) as a widely used technique cognitive neuroscience can record activation cortex during process of perception. Can we teach fMRI signals achieve more brain-like model? To answer this question, study...
The advancements of language models (LLMs) have piqued growing interest in developing LLM-based agents to automate scientific discovery end-to-end, which has sparked both excitement and skepticism about the true capabilities such agents. In this work, we argue that for an agent fully discovery, it must be able complete all essential tasks workflow. Thus, call rigorous assessment on individual a workflow before making bold claims end-to-end automation. To end, present ScienceAgentBench, new...
Remarkably, human brains have the ability to accurately perceive and process real-world size of objects, despite vast differences in distance perspective. While previous studies delved into this phenomenon, distinguishing from other visual perceptions, like depth, has been challenging. Using THINGS EEG2 dataset with high time-resolution brain recordings more ecologically valid naturalistic stimuli, our study uses an innovative approach disentangle neural representations object retinal...
Visual working memory (VWM) is a temporary storage system capable of retaining information that can be accessed and manipulated by higher cognitive processes, thereby facilitating wide range functions. Electroencephalography (EEG) used to understand the neural correlates VWM with high temporal precision, one commonly EEG measure an event-related potential called contralateral delay activity (CDA). In landmark study Vogel Machizawa (2004), authors found CDA amplitude increases number items...