Research Database
Curated neuroscience and AI research papers
Showing 20 of 110 papers
Human Brain Inspired Artificial Intelligence Neural Networks.
Theotokis, Paschalis
It is becoming increasingly evident that Artificial intelligence (AI) development draws inspiration from the architecture and functions of the human brain. This manuscript examines the alignment...
The application of cognitive neuroscience to judicial models: recent progress and trends.
Zhang, Ni; Zhang, Zixuan
Legal prediction presents one of the most significant challenges when applying artificial intelligence (AI) to the legal field. The legal system is a complex adaptive system characterized by the...
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 Methods for Multi-Channel EEG-Based Emotion Recognition.
Olamat, Ali; Ozel, Pinar; Atasever, Sema
Currently, Fourier-based, wavelet-based, and Hilbert-based time-frequency techniques have generated considerable interest in classification studies for emotion recognition in human-computer interface...
Chaotic recurrent neural networks for brain modelling: A review.
Mattera, Andrea; Alfieri, Valerio; Granato, Giovanni; Baldassarre, Gianluca
Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest...
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...