12 papers · ranked by Valyu relevance
Lulu Ding, Kun Wang, Hongmei Zhang, Shaohui Xie + 5 more
DNA storage offers exceptional information density and archival longevity, but is constrained by the complex, heterogeneous errors inherent to synthesis, storage, and sequencing. Conventional error-correction schemes often rely on excessive logical redundancy to mitigate these biochemical imperfections, thereby…
Camille Gontier, William Hockeimer, Nicolas G. Kunigk, Edgar Canario + 5 more
Intracortical brain-computer interfaces (BCIs) are used to decode motor intent from neural population activity; their main clinical application is to restore function for individuals with motor or communication deficits. However, when trying to reconstruct movement trajectories, such as in computer cursor control, even…
Ramy Khabbaz, Jérémy Mateos, Marc Antonini, Serge Kas Hanna
The biochemical processes underlying DNA data storage, including synthesis, amplification, and sequencing, are inherently noisy. Consequently, base-level insertion, deletion, and substitution (IDS) errors, as well as sequence-level dropouts, occur and pose major challenges for reliable data retrieval. Here we introduce…
Nikita Paplavsky, Mikhail Lebedev
P300 spellers convert electroencephalographic (EEG) activity into text by presenting users with a matrix of flickering characters. While these systems can achieve high classification accuracy, communication is severely slowed by the need for many stimulus repetitions to obtain a reliable signal. Reducing repetitions…
Nikolay Syrov, Skyla Schmidt, Robin Rademacher, Xenia Kobeleva
Theta oscillations are hypothesized to provide a temporal scaffold for short-term memory (STM). In this model, memory representations are organized into successive theta phases, reducing conflict between competing representations during encoding and maintenance. Previous studies have shown that sensory representations…
Sena N. Bilgin, Dunia Giomo, Urfan Mustafali, Tadeusz W. Kononowicz
Metacognition refers to the capacity to monitor one’s own actions, internal states, and cognitive processes. A central question in cognitive neuroscience is whether metacognitive evaluation operates as a direct readout of performance signals or requires computationally independent neural mechanisms. Single-process…
Ibrahim Nawaz, Parv Agarwal, Thomas Heinis
DNA storage is a developing field that uses DNA to archive digital data owing to its superior information density and stability. Although DNA storage has been performed on a significant scale, challenges arise from the synthesis and sequencing of data-encoded oligonucleotides. Synthesis of DNA introduces significant…
Seonghyun Yoon, Donald T. Avansino, Sasidhar Madugula, Alisa D. Levin + 20 more
Speech brain-computer interfaces (BCIs) can restore rapid communication to people with paralysis, but decoding errors still limit performance. In recent brain-to-text decoding competitions, deep ensemble methods, which combine predictions from multiple independently trained decoders, have delivered striking accuracy…
Guanghui Zhang, Xinran Wang, Steven J. Luck
Regularization has been extensively used in multivariate pattern classification (MVPA; decoding) of EEG data to mitigate the risk of overfitting. N-fold cross-validation is also used to mitigate this risk, and it is often combined with averaging across trials to improve the signal-to-noise ratio. However, the impact of…
Dennis London, Marisol Soula, Ling Pan, Michael Pourfar + 2 more
Flexible behavior requires binding actions to their underlying cognitive variables, yet classical basal ganglia models emphasize a serial architecture where striatal action selection precedes a pallidothalamic motor gate. We tested this framework by recording single-neuron activity across the human pallidothalamic…
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…