19 papers · ranked by Valyu relevance
Timothy N. Rubin, Oluwasanmi Koyejo, Krzysztof J. Gorgolewski, Michael N. Jones + 3 more
'Michael N. Jones' 'Russell A. Poldrack' 'Tal Yarkoni' 'Samuel J. Gershman'] A central goal of cognitive neuroscience is to decode human brain activity-that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small…
Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux
We show in this paper how to extract shared brain representations that predict mental processes across many cognitive neuroimaging studies. Focused cognitive-neuroimaging experiments study precise mental processes with carefully-designed cognitive paradigms; however the cost of imaging limits their statistical power.…
Joshua Krause, Jacolien van Rij, Jelmer P. Borst
Hidden (semi-) Markov Models (HsMMs) are increasingly being used to segment neuro-physiological signals into sequences of latent cognitive processes. The idea: different processes will leave distinct traces in trial-level recordings of (multivariate) neuro-physiological signals. Markov models, equipped with an emission…
Reese Kneeland, Paul S. Scotti, Ghislain St-Yves, Jesse Breedlove + 2 more
The ability to decode mental states from brain activity is a longstanding goal of neuroscience. Mental images–visual representations not driven by retinal input–are an especially appealing target for decoding since an externalized mental image could, in principle, depict information stored in brain activity patterns…
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…
Armin W. Thomas, Christopher Ré, Russell A. Poldrack
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., perceiving fear or joy) and brain activity by identifying those brain regions (and networks) whose activity allows to accurately identify (i.e., decode) these…
Thomas A. Carlson, Tijl Grootswagers, Amanda K. Robinson
The human brain is constantly processing and integrating information in order to make decisions and interact with the world, for tasks from recognizing a familiar face to playing a game of tennis. These complex cognitive processes require communication between large populations of neurons. The noninvasive neuroimaging…
Moritz F. Wurm, Seoyoung Lee
Higher-level action interpretation, such as inferring underlying intentions and predicting future actions, requires the integration of conceptual action information (e.g. "opening") with semantic knowledge about persons and objects (e.g. "my friend Anna", "pizza box"). However, how the neural systems for action and…
Timothy N. Rubin, Oluwasanmi Koyejo, Krzysztof J. Gorgolewski, Michael N. Jones + 2 more
A central goal of cognitive neuroscience is to decode human brain activity--i.e., to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding…
Nikolaus Kriegeskorte, Pamela K. Douglas
Encoding and decoding models are widely used in systems, cognitive, and computational neuroscience to make sense of brain-activity data. However, the interpretation of their results requires care. Decoding models can help reveal whether particular information is present in a brain region in a format the decoder can…
Keisuke Nagata, Naoto Kunii, Seijiro Shimada, Shigeta Fujitani + 2 more
'Megumi Takasago' 'Nobuhito Saito'] Title: Abstract Decoding the inner representation of a word meaning from human cortical activity is a substantial challenge in the development of speech brain-machine interfaces (BMIs). The semantic aspect of speech is a novel target of speech decoding that may enable versatile…
David Soto, Usman Ayub Sheikh, Ning Mei, Roberto Santana
How the brain representation of conceptual knowledge vary as a function of processing goals, strategies and task-factors remains a key unresolved question in cognitive neuroscience. Here we asked how the brain representation of semantic categories is shaped by the depth of processing during mental simulation.…
Xuanyi Lin, Danni Chen, Jing Liu, Ziqing Yao + 3 more
'Michael C Anderson' 'Xiaoqing Hu'] Title: Abstract When reminded of an unpleasant experience, people often try to exclude the unwanted memory from awareness, a process known as retrieval suppression. Here we used multivariate decoding (MVPA) and representational similarity analyses on EEG data to track how suppression…
Hans P. Op de Beeck, Ben Vermaercke, Daniel G. Woolley, Nicole Wenderoth
'Nicole Wenderoth'] Complex behavior typically relies upon many different processes which are related to activity in multiple brain regions. In contrast, neuroimaging analyses typically focus upon isolated processes. Here we present a new approach, combinatorial brain decoding, in which we decode complex behavior by…
J. Brendan Ritchie, David Michael Kaplan, Colin Klein
Since its introduction, multivariate pattern analysis (MVPA), or “neural decoding”, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the Decoder’s Dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence…
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…
Rosemary A. Cowell, Morgan D. Barense, Patrick S. Sadil
Thanks to patients Phineas Gage and Henry Molaison, we have long known that behavioral control depends on the frontal lobes, whereas declarative memory depends on the medial temporal lobes (MTL). For decades, cognitive functions-behavioral control, declarative memory-have served as labels for characterizing the…
Alexander A Sulfaro, Amanda K Robinson, Thomas A Carlson
Mental imagery is a process by which thoughts become experienced with sensory characteristics. Yet, it is not clear why mental images appear diminished compared to veridical images, nor how mental images are phenomenologically distinct from hallucinations, another type of non-veridical sensory experience. Current…
Reiji Ohkuma, Yuto Kurihara, Toru Takahashi, Rieko Osu
People solve insight problems that they encounter daily with a sudden sense of ‘aha!’ to reach a solution. Chunk decomposition, which decomposes the factors of the problem, and constraint relaxation, which manipulates filters to organize the information necessary to solve the problem, are important in insight…