19 papers · ranked by Valyu relevance
Joram Soch, John-Dylan Haynes
The data acquired during a functional magnetic resonance imaging (fMRI) experiment usually comprise experimental conditions, brain signals and behavioral responses. This reflects the underlying causal flow where the experimental conditions evoke brain responses that in turn result in behavior. In multivariate analyses…
Romuald Menuet, Raphael Meudec, Jérôme Dockès, Gael Varoquaux + 1 more
Associating brain systems with mental processes requires statistical analysis of brain activity across many cognitive processes. These analyses typically face a difficult compromise between scope-from domain-specific to system-level analysis-and accuracy. Using all the functional Magnetic Resonance Imaging (fMRI)…
Peng, Yueh-Po, Cheung, Vincent K. M. + 2 more
— A fundamental challenge in neuroscience is to decode mental states from brain activity. While functional magnetic resonance imaging (fMRI) offers a non-invasive approach to capture brain-wide neural dynamics with high spatial precision, decoding from fMRI data—particularly from task-evoked activity—remains…
Sahal Alotaibi, Maher Mohammed Alotaibi, Faisal Saleh Alghamdi, Mishaal Abdullah Alshehri + 8 more
'Mishaal Abdullah Alshehri' 'Khaled Majed Bamusa' 'Ziyad Faiz Almalki' 'Sultan Alamri' 'Ahmad Joman Alghamdi' 'Mohammed Alhazmi' 'Hamid Osman' 'Mayeen U. Khandaker' 'Nuno Silva'] Background Functional magnetic resonance imaging (fMRI) has revolutionized our understanding of brain activity by non-invasively detecting…
Yoichi Miyawaki, Kenshu Koiso, Daniel A Handwerker, Javier Gonzalez-Castillo + 5 more
High spatio-temporal resolution is crucial for neuroimaging techniques to improve our understanding of human brain function. While the fMRI signal is slow and shows a spread in latencies over space, the precision of hemodynamic response latency for each voxel is preserved and has been shown to be able to detect…
Jerry Tang, Amanda LeBel, Shailee Jain, Alexander G. Huth
A brain-computer interface that decodes continuous language from non-invasive recordings would have many scientific and practical applications. Currently, however, decoders that reconstruct continuous language use invasive recordings from surgically implanted electrodes^1–3^, while decoders that use non-invasive…
Yun Wang, Tjeerd Olde Scheper
Background/Objectives: Neural decoding methods are often limited by the performance of brain encoders, which map complex brain signals into a latent representation space of perception information. These brain encoders are constrained by the limited amount of paired brain and stimuli data available for training, making…
João F. Guassi Moreira, Jennifer A. Silvers
The current prevailing approaches to analyzing task fMRI data in developmental cognitive neuroscience are brain connectivity and mass univariate task-based analyses, used either in isolation or as part of a broader analytic framework (e.g., BWAS). While these are powerful tools, it is somewhat surprising that…
Pengyu Liu, Guohua Dong, Dan Guo, Kun Li + 4 more
'Meng Wang' 'Xiaomin Ying'] Abstract—In our daily lives, we are exposed to a vast array of external stimuli, including images, sounds, and videos. As research into multimodal stimuli and neuroscience continues to advance, fMRI-based brain decoding has emerged as a powerful tool for understanding how the brain processes…
Hamid Karimi-Rouzbahani, Anina N. Rich, Alexandra Woolgar
The multiple-demand network (MDN), a set of highly interconnected, domain-general regions active across a wide variety of cognitively demanding tasks, is thought to support cognitive functions by integrating distinct types of information depending on the task. However, the spatiotemporal characteristics with which each…
Richard Antonello, Nihita Sarma, Jerry Tang, Jiaru Song + 1 more
'Alexander G. Huth'] Brain-computer interfaces have promising medical and scientific applications for aiding speech and studying the brain. In this work, we propose an informationbased evaluation metric for brain-to-text decoders. Using this metric, we examine two methods to augment existing state-of-the-art continuous…
Km Bhavna, Azman Akhter, Romi Banerjee, Dipanjan Roy
Decoding of brain tasks aims to identify individuals’ brain states and brain fingerprints to predict behavior. Deep learning provides an important platform for analyzing brain signals at different developmental stages to understand brain dynamics. Due to their internal architecture and feature extraction techniques…
Yifan Wang, Shaonan Wang, Yunhao Zhang, Changde Du + 10 more
The ability to decode human thoughts, intentions, and perceptions directly from non-invasive brain recordings holds transformative potential for healthcare, communication, and human-computer interaction. However, translating the safety and scalability of methods like fMRI, EEG, and MEG into real-world utility has…
Matteo Ferrante, Tommaso Boccato, Nicola Toschi
To-date, brain decoding literature has focused on singlesubject studies, i.e. reconstructing stimuli presented to a subject under fMRI acquisition from the fMRI activity of the same subject. The objective of this study is to introduce a generalization technique that enables the decoding of a subject's brain based on…
Kalyan Tripathy, Zachary E. Markow, Morgan Fogarty, Mariel L. Schroeder + 5 more
'Mariel L. Schroeder' 'Alexa M. Svoboda' 'Adam T. Eggebrecht' 'Bradley L. Schlaggar' 'Jason W. Trobaugh' 'Joseph P. Culver'] Title: Abstract. Significance Decoding naturalistic content from brain activity has important neuroscience and clinical implications. Information about visual scenes and intelligible speech has…
Andrew D. Vigotsky, Rami Jabakhanji, Paulo Branco, Gian Domenico Iannetti + 2 more
How does the human brain generate coherent, subjective perceptions—transforming yellow and oblong visual sensory information into the perception of an edible banana ^1^? This is a hard problem. The standard viewpoint posits that anatomical and functional networks somehow integrate local, specialized processing across…
Authors not listed
Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline and widespread neurovascular disturbances. Traditional fMRI provides valuable spatial maps of blood-oxygen-level-dependent (BOLD) changes but often lacks the capacity to quantify the interplay of cerebral blood flow…
Célia Loriette, Julian L. Amengual, Suliann Ben Hamed
One of the major challenges in system neurosciences consists in developing techniques for estimating the cognitive information content in brain activity. This has an enormous potential in different domains spanning from clinical applications, cognitive enhancement to a better understanding of the neural bases of…
Shirin Vafaei, Ryohei Fukuma, Huixiang Yang, Haruhiko Kishima + 1 more
stimuli Authors: ['Shirin Vafaei' 'Ryohei Fukuma' 'Huixiang Yang' 'Haruhiko Kishima' 'Takufumi Yanagisawa'] Developing algorithms for accurate and comprehensive neural decoding of mental contents is one of the longcherished goals in the field of neuroscience and brain-machine interfaces. Previous studies have…