Research Database
Curated neuroscience and AI research papers
Showing 20 of 100 papers
Explainable AI for forensic speech authentication within cognitive and computational neuroscience.
Cheng, Zhe; Yang, Haitao; Xiong, Yingzhuo; Hu, Xuran
The proliferation of deepfake technologies presents serious challenges for forensic speech authentication. We propose a deep learning framework combining Convolutional Neural Networks (CNNs) and Long...
Deep learning on independent spatial EEG activity patterns delineates time windows relevant for response inhibition.
Gholamipourbarogh, Negin; Vahid, Amirali; Mückschel, Moritz; Beste, Christian
Inhibitory control processes are an important aspect of executive functions and goal-directed behavior. However, the mostly correlative nature of neurophysiological studies was not able to provide...
Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.
Scheinost, Dustin; Pollatou, Angeliki; Dufford, Alexander J; Jiang, Rongtao; Farruggia, Michael C et al.
Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of these models have been developed...
Deep learning techniques for automated Alzheimer's and mild cognitive impairment disease using EEG signals: A comprehensive review of the last decade (2013 - 2024).
Acharya, Madhav; Deo, Ravinesh C; Tao, Xiaohui; Barua, Prabal Datta; Devi, Aruna et al.
Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) are progressive neurological disorders that significantly impair the cognitive functions, memory, and daily activities. They affect...
An in-depth survey on Deep Learning-based Motor Imagery Electroencephalogram (EEG) classification.
Wang, Xianheng; Liesaputra, Veronica; Liu, Zhaobin; Wang, Yi; Huang, Zhiyi
Electroencephalogram (EEG)-based Brain-Computer Interfaces (BCIs) build a communication path between human brain and external devices. Among EEG-based BCI paradigms, the most commonly used one is...
FMRI Data Analysis Preserving Map Variability Via Unsupervised Object-Centric Learning.
Jin, Rui; Kim, Seung-Jun
A novel data-driven functional magnetic resonance imaging (fMRI) data analysis method is proposed using a deep object-centric learning paradigm. The method can faithfully estimate the variabilities...
Simultaneous EEG-fMRI.
Ritter, Petra; Villringer, Arno
Acquisition of electroencephalogram (EEG) during functional magnetic resonance imaging (fMRI) provides an additional monitoring tool for the analysis of brain state fluctuations. The exploration of...
Neural activation signatures in individuals with subclinical depression: A task-fMRI meta-analysis.
Lyu, Cui; Lyu, Xinyue; Gong, Qiyong; Gao, Bo; Wang, Yiming
Previous task-related functional magnetic resonance imaging (task-fMRI) investigations have documented abnormal brain activation associated with subclinical depression (SD), defined as a clinically...
Brain-Computer Interface-Based Humanoid Control: A Review.
Chamola, Vinay; Vineet, Ankur; Nayyar, Anand; Hossain, Eklas
A Brain-Computer Interface (BCI) acts as a communication mechanism using brain signals to control external devices. The generation of such signals is sometimes independent of the nervous system, such...
Brain Neuroplasticity Leveraging Virtual Reality and Brain-Computer Interface Technologies.
Drigas, Athanasios; Sideraki, Angeliki
This study explores neuroplasticity through the use of virtual reality (VR) and brain-computer interfaces (BCIs). Neuroplasticity is the brain's ability to reorganize itself by forming new neural...
Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity.
Yin, Tao; Ma, Peihong; Tian, Zilei; Xie, Kunnan; He, Zhaoxuan et al.
The effects of acupuncture facilitating neural plasticity for treating diseases have been identified by clinical and experimental studies. In the last two decades, the application of neuroimaging...
Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks.
Pulvermüller, Friedemann
Neural networks are successfully used to imitate and model cognitive processes. However, to provide clues about the neurobiological mechanisms enabling human cognition, these models need to mimic the...
Convolutional neural networks for cytoarchitectonic brain mapping at large scale.
Schiffer, Christian; Spitzer, Hannah; Kiwitz, Kai; Unger, Nina; Wagstyl, Konrad et al.
Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic principle of the...
Spine dynamics in the brain, mental disorders and artificial neural networks.
Kasai, Haruo; Ziv, Noam E; Okazaki, Hitoshi; Yagishita, Sho; Toyoizumi, Taro
In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also...
Neuroscience-Inspired Artificial Intelligence.
Hassabis, Demis; Kumaran, Dharshan; Summerfield, Christopher; Botvinick, Matthew
The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less...
Embracing deepfakes and AI-generated images in neuroscience research.
Becker, Casey; Laycock, Robin
The rise of deepfakes and AI-generated images has raised concerns regarding their potential misuse. However, this commentary highlights the valuable opportunities these technologies offer for...
Large-scale foundation models and generative AI for BigData neuroscience.
Wang, Ran; Chen, Zhe Sage
Recent advances in machine learning have led to revolutionary breakthroughs in computer games, image and natural language understanding, and scientific discovery. Foundation models and large-scale...
A new era in cognitive neuroscience: the tidal wave of artificial intelligence (AI).
Chen, Zhiyi; Yadollahpour, Ali
Translating artificial intelligence techniques into the realm of cognitive neuroscience holds promise for significant breakthroughs in our ability to probe the intrinsic mechanisms of the brain. The...
Neural bases of atypical emotional face processing in autism: A meta-analysis of fMRI studies.
Aoki, Yuta; Cortese, Samuele; Tansella, Michele
We aim to outline the neural correlates of atypical emotional face processing in individuals with ASD.
AI-driven discovery of brain-penetrant Galectin-3 inhibitors for Alzheimer's disease therapy.
Liu, Xueyan; Xu, Jiexin; Zheng, Shuping; Yang, Yaoyao; Xie, Yuchong et al.
Galectin-3 (Gal-3) has emerged as a critical regulator of neuroinflammation and a promising therapeutic target for Alzheimer's disease (AD). Nevertheless, the development of brain-penetrant...