19 papers · ranked by Valyu relevance
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…
Jan Sobotka, Luca Baroni, Ján Antolík
Decoding visual stimuli from neural population activity is crucial for understanding the brain and for applications in brain-machine interfaces. However, such biological data is often scarce, particularly in primates or humans, where highthroughput recording techniques, such as two-photon imaging, remain challenging or…
Ziyi Zhao, Jinzhao Zhou, Xiaowei Jiang, Beining Cao + 5 more
Decoding linguistic information from electroencephalography (EEG) remains challenging due to the brain's distributed and nonlinear organization. We present BrainStack, a functionally guided neuro–mixture-of-experts (Neuro-MoE) framework that models the brain's modular functional architecture through anatomically…
Stéphane d’Ascoli, Corentin Bel, Jérémy Rapin, Hubert Banville + 3 more
While deep learning has enabled the decoding of language from intracranial brain recordings, achieving this with non-invasive recordings remains an open challenge. We introduce a deep learning pipeline to decode individual words from electro- (EEG) and magneto-encephalography (MEG) signals. We evaluate our approach on…
Théo Desbordes, Itsaso Olasagasti, Nicolas Piron, Sophie Schwartz + 1 more
Multivariate decoding analyses have become a cornerstone method in cognitive neuroscience. When applied to time-resolved brain imaging signals, they provide insights into the temporal dynamics of information processing in the brain. In particular, the temporal generalization (TG) method—where a decoder trained at one…
Lorenzo Posani
Neural decoding is a powerful approach for inferring which variables are represented in the activity of a population of neurons, with broad applications ranging from basic neuroscience to clinical settings such as brain-computer interfaces. More recently, decoding has also been used as a cross-validated tool for…
Xin-Ya Zhang, Hang Lin, Zeyu Deng, Markus Siegel + 2 more
Artificial neural networks (ANNs) offer a data-driven approach to reveal brain regional functions without explicit supervision. Here, we demonstrate that an ANN trained to decode visual stimuli from multi-unit spiking activity in monkeys, can not only reconstruct complex and dynamic scenes, but also spontaneously align…
Chen Frenkel, Leon Y. Deouell
The human visual system represents stimuli in a rich and detailed manner. Traditional methods of studying visual representations in humans, such as event-related potentials (ERP), revealed numerous distinctions between the brain activity elicited by different categories of stimuli. However, these methods miss the…
Maryam Mostafalu, Tommy Clausner, Maxime Ferez, Danila Shelepenkov + 5 more
Attention is a fundamental mechanism enabling the brain to overcome its limited capacity for parallel processing. In non-human primates, invasive electrophysiology has shown that attentional selection operates rhythmically, primarily within the alpha (∼8–12 Hz) and theta (∼4–5 Hz) bands. Whether such finely resolved…
Zhu, Chunzheng, Shao, Jialin + 10 more
—Understanding how the brain responds to external stimuli and decoding this process has been a significant challenge in neuroscience. While previous studies typically concentrated on brain-to-image and brain-to-language reconstruction, our work strives to reconstruct gestures associated with speech stimuli perceived by…
Tao Zou, Na Xiao, Ruihong Weng, Yifan Guo + 3 more
Electrocorticographic brain-computer interfaces (ECoG-BCIs) are powerful emergent technologies for advancing basic neuroscience research and targeted clinical interventions. However, existing devices require trade-offs between coverage area, electrode density, surgical invasiveness and complication risk – limitations…
Robert Worden
This paper uses simple arguments to derive a negative conclusion: that a computer cannot be conscious. If the brain is only a neural computer, brains cannot be conscious. Consciousness implies that there is something else happening in the brain, besides computation. In a running computer, information about outside…
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo + 6 more
Brain-computer interfaces (BCIs) have made consistent advances in supporting motor and communication functions; nevertheless, their adoption in everyday environments remains constrained by enduring challenges, including chronic instability at the electrode-tissue interface, motion-induced artifacts, inter-user…
Haitao Wu, Qirui Zhang, Zhouheng Yao, Shangquan Sun + 7 more
Modeling the bidirectional correspondence between external sensory stimuli and internal neural activity has emerged as a critical frontier in neuroscience. However, existing approaches predominantly treat brain encoding and decoding as isolated tasks, relying heavily on unimodal alignment and external priors while…
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…
Yizhuo Lu, Changde Du, Qingyu Shi, Hang Chen + 4 more
Modeling the interplay between external stimuli and internal neural representations is a pivotal research area for Brain-Computer Interfaces (BCIs). A major limitation of prior work is the prevailing paradigm of specialized, single-task models, which curtails versatility and neglects inter-task synergies. To address…
Toktam Samiei, Hafiz Fareed Ahmed, Edward Zagha, Erfan Nozari
Despite over a century of research into the neural code, the fundamental principles by which the brain encodes sensory information remain debated. In this study we provide converging evidence for the presence of a dynamic, fast-switching integration of rate and temporal coding in the thalamus, primary visual cortex…
Janet M. Baker, Peter Cariani
Waves are fundamental. In our view, waves in the brain may constitute and drive organized neural activity patterns on individual neural and population levels. Their interactions follow basic physical principles. Taking a comprehensive, temporal and spatiotemporal perspective, we endeavor to explain multiple brain…
Authors not listed
Molecular mechanisms governing initiation steps of the assembly of thousands of endogenous multi-protein complexes (EMCs) remain incompletely understood. Here, multiple lines of observations are reported reflecting the biological functions-aligned initiation sequence of hybrid assembly pathways (HAPs) of EMCs. HAPs…