22 papers · ranked by Valyu relevance
Hongming Li, Yong Fan
Decoding brain functional states underlying different cognitive processes using multivariate pattern recognition techniques has attracted increasing interests in brain imaging studies. Promising performance has been achieved using brain functional connectivity or brain activation signatures for a variety of brain…
Yu Zhang, Loïc Tetrel, Bertrand Thirion, Pierre Bellec
A key goal in neuroscience is to understand brain mechanisms of cognitive functions. An emerging approach is “brain decoding”, which consists of inferring a set of experimental conditions performed by a participant, using pattern classification of brain activity. Few works so far have attempted to train a brain…
Raheel Zafar, Sarat C. Dass, Aamir Saeed Malik, Bin He
Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types…
Km Bhavna, Azman Akhter, Romi Banerjee, Dipanjan Roy
Decoding of cognitive states 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…
R. Jabakhanji, A.D. Vigotsky, J. Bielefeld, L. Huang + 3 more
High-profile studies claim to assess mental states across individuals using multi-voxel decoders of brain activity. The fixed, fine-grained, multi-voxel patterns in these “optimized” decoders are purportedly necessary for discriminating between, and accurately identifying, mental states. Here, we present compelling…
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…
David A Weiss, Adriano MF Borsa, Aurélie Pala, Audrey J Sederberg + 1 more
Cortical function is under constant modulation by internally-driven, latent variables that regulate excitability, collectively known as “cortical state”. Despite a vast literature in this area, the estimation of cortical state remains relatively ad hoc, and not amenable to real-time implementation. Here, we implement…
Ziyuan Ye, Youzhi Qu, Zhichao Liang, Mo Wang + 1 more
—Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and neural engineering. However, existing machine learning methods for fMRI-based brain decoding either suffer from low classification performance or poor explainability. Here, we address this issue by…
Armin W. Thomas, Hauke R. Heekeren, Klaus-Robert Müller, Wojciech Samek
'Wojciech Samek'] The application of deep learning (DL) models to neuroimaging data poses several challenges, due to the high dimensionality, low sample size, and complex temporo-spatial dependency structure of these data. Even further, DL models often act as black boxes, impeding insight into the association of…
Stefano Panzeri, Houman Safaai, Vito De Feo, Alessandro Vato
Brain-machine interfaces (BMIs) can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet…
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…
Jianfei Zhu, Baichun Wei, Jiaru Tian, Feng Jiang + 1 more
Extraction of fMRI-based Brain Decoding Authors: ['Jianfei Zhu' 'Baichun Wei' 'Jiaru Tian' 'Feng Jiang' 'Chunzhi Yi'] Brain decoding that classifies cognitive states using the functional fluctuations of the brain can provide insightful information for understanding the brain mechanisms of cognitive functions. Among the…
Armin W. Thomas, Hauke R. Heekeren, Klaus‐Robert Müller, Wojciech Samek
'Wojciech Samek'] The application of deep learning (DL) models to neuroimaging data poses several challenges, due to the high dimensionality, low sample size and complex temporo-spatial dependency structure of these datasets. Even further, DL models act as as black-box models, impeding insight into the association of…
Yifan Yang, David A. Leopold, Jeff H. Duyn, Grayson O. Sipe + 1 more
'Xiao Liu'] Title: Abstract The brain's response to external events depends on its internal arousal states, which are dynamically governed by neuromodulatory systems and have recently been linked to coordinated spike timing cascades in widespread brain networks. At rest, both arousal fluctuations and spiking cascades…
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…
Anira Escrichs, Yonatan Sanz Perl, Carme Uribe, Estela Camara + 14 more
Recently, significant advances have been made by identifying the levels of synchronicity of the underlying dynamics of a given brain state. This research has demonstrated that unconscious dynamics tend to be more synchronous than those found in conscious states, which are more asynchronous. Here we go beyond this…
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…
Brent J. Lance, Scott E. Kerick, Anthony J. Ries, Kelvin S. Oie + 1 more
'Kaleb McDowell'] Lance, B.J.; Kerick, S.E.; Ries, A.J.; Oie, K.S.; McDowell, K.; , "Brain–Computer Interface Technologies in the Coming Decades," Proceedings of the IEEE , vol.100, no. Special Centennial Issue, pp.1585-1599, May 13 2012. doi: 10.1109/JPROC.2012.2184830 URL…
Shahrzad Latifi, Jonathan Chang, Mehdi Pedram, Roshanak Latifikhereshki + 1 more
Neuronal networks in the motor cortex are crucial for driving complex movements. Yet it remains unclear whether distinct neuronal populations in motor cortical subregions encode complex movements. Using in vivo two-photon calcium imaging (2P) on head- fixed grid-walking animals, we tracked the activity of excitatory…
James Barnard Wilsenach, Charlotte M. Deane, Gesine Reinert, Katie Warnaby
Anesthetisia is an important surgical and explorative tool in the study of consciousness. Much work has been done to connect the deeply anesthetized condition with decreased complexity. However, anesthesia-induced unconsciousness is also a dynamic condition in which functional activity and complexity may fluctuate…
Diego Vidaurre, Nicholas E. Myers, Mark Stokes, Anna C. Nobre + 1 more
In this paper, we propose a method to track trial-specific neural dynamics of stimulus processing and decision making with high temporal precision. By applying this novel method to a perceptual template-matching task, we tracked representational brain states associated with the cascade of neural processing, from early…
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…