16 papers · ranked by Valyu relevance
Stefan Bode, Anna Hanxi He, Chun Siong Soon, Robert Trampel + 3 more
'Robert Turner' 'John-Dylan Haynes' 'Sam Gilbert'] Recently, we demonstrated using functional magnetic resonance imaging (fMRI) that the outcome of free decisions can be decoded from brain activity several seconds before reaching conscious awareness. Activity patterns in anterior frontopolar cortex (BA 10) were…
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…
João R. Sato, Rodrigo Basilio, Fernando F. Paiva, Griselda J. Garrido + 6 more
The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI…
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…
Arjen Alink, Alexandra Krugliak, Alexander Walther, Nikolaus Kriegeskorte
'Nikolaus Kriegeskorte'] The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability…
Bing Du, Xiaomu Cheng, Yiping Duan, Huansheng Ning + 5 more
'Andrea Luigi Guerra' 'Gabriele Baronio' 'Domenico Speranza' 'Luca Ulrich'] Brain neural activity decoding is an important branch of neuroscience research and a key technology for the brain-computer interface (BCI). Researchers initially developed simple linear models and machine learning algorithms to classify and…
Philip A. Kragel, R. McKell Carter, Scott A. Huettel
Research in neuroscience faces the challenge of integrating information across different spatial scales of brain function. A promising technique for harnessing information at a range of spatial scales is multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data. While the prevalence of…
Martin Wegrzyn, Joana Aust, Larissa Barnstorf, Magdalena Gippert + 15 more
'Mareike Harms' 'Antonia Hautum' 'Shanna Heidel' 'Friederike Herold' 'Sarah M. Hommel' 'Anna-Katharina Knigge' 'Dominik Neu' 'Diana Peters' 'Marius Schaefer' 'Julia Schneider' 'Ria Vormbrock' 'Sabrina M. Zimmer' 'Friedrich G. Woermann' 'Kirsten Labudda' 'Satoru Hayasaka'] Cognitive processes, such as the generation of…
Trung Quang Pham, Shota Nishiyama, Norihiro Sadato, Junichi Chikazoe
Multivoxel pattern analysis (MVPA) has become a standard tool for decoding mental states from brain activity patterns. Recent studies have demonstrated that MVPA can be applied to decode activity patterns of a certain region from those of the other regions. By applying a similar region-to-region decoding technique, we…
Luca Vizioli, Federico De Martino, Lucy S. Petro, Daniel Kersten + 3 more
'Kamil Ugurbil' 'Essa Yacoub' 'Lars Muckli'] At ultra-high field, fMRI voxels can span the sub-millimeter range, allowing the recording of blood oxygenation level dependent (BOLD) responses at the level of fundamental units of neural computation, such as cortical columns and layers. This sub-millimeter resolution…
Marc M. Himmelberg, Justin L. Gardner, Jonathan Winawer
In the domain of human neuroimaging, much attention has been paid to the question of whether and how the development of functional magnetic resonance imaging (fMRI) has advanced our scientific knowledge of the human brain. However, the opposite question is also important; how has our knowledge of the brain advanced our…
Tomoyasu Horikawa, Yukiyasu Kamitani
Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a…
Olivia Guest, Bradley C Love, Russell Poldrack
The success of fMRI places constraints on the nature of the neural code. The fact that researchers can infer similarities between neural representations, despite fMRI’s limitations, implies that certain neural coding schemes are more likely than others. For fMRI to succeed given its low temporal and spatial resolution…
Gael Varoquaux, Bertrand Thirion
Functional brain images are rich and noisy data that can capture indirect signatures of neural activity underlying cognition in a given experimental setting. Can data mining leverage them to build models of cognition? Only if it is applied to well-posed questions, crafted to reveal cognitive mechanisms. Here we review…
Yaoda Xu, Benjamin Swinchoski, JohnMark Taylor, Marvin Chun
Two defining visual features of a real-world object are its shape and color. While previous fMRI pattern decoding studies showed that these features are represented in a largely orthogonal and independent manner in the human occipitotemporal cortex (OTC) during visual perception, how they are coded together in visual…
David Eriksson, Sonata Valentiniene, Stylianos Papaioannou, Eric Warrant
'Eric Warrant'] Neurons in the primary visual cortex typically reach their highest firing rate after an abrupt image transition. Since the mutual information between the firing rate and the currently presented image is largest during this early firing period it is tempting to conclude this early firing encodes the…