15 papers · ranked by Valyu relevance
Matteo Ferrante, Tommaso Boccato, Furkan Ozcelik, Rufin VanRullen + 1 more
'Nicola Toschi'] Title: Abstract To-date, brain decoding literature has focused on single-subject studies, that is, reconstructing stimuli presented to a subject under fMRI acquisition from the fMRI activity of the same subject. The objective of this study is to introduce a generalization technique that enables the…
Fabian A. Soto, Sanjay Narasiwodeyar, Emma Claire Robinson
Many research questions in sensory neuroscience involve determining whether the neural representation of a stimulus property is invariant or specific to a particular stimulus context (e.g., Is object representation invariant to translation? Is the representation of a face feature specific to the context of other face…
Seong‐Joon Park, Hee-Youl Kwak, Sang‐Hyo Kim, Yongjune Kim + 1 more
—Channel coding for 6G networks is expected to support a wide range of requirements arising from heterogeneous communication scenarios. These demands challenge traditional code-specific decoders, which lack the flexibility and scalability required for next-generation systems. To tackle this problem, we propose an…
Ethan M. Meyers
Neural decoding is a powerful method to analyze neural activity. However, the code needed to run a decoding analysis can be complex, which can present a barrier to using the method. In this paper we introduce a package that makes it easy to perform decoding analyses in the R programing language. We describe how the…
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…
Ethan M. Meyers
Neural decoding is a powerful method to analyze neural activity. However, the code needed to run a decoding analysis can be complex, which can present a barrier to using the method. In this paper we introduce a package that makes it easy to perform decoding analyses in the R programing language. We describe how the…
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…
Seong‐Joon Park, Hee-Youl Kwak, Sang‐Hyo Kim, Yongjune Kim + 1 more
Correcting Codes Authors: ['Seong‐Joon Park' 'Hee-Youl Kwak' 'Sang‐Hyo Kim' 'Yongjune Kim' 'Jong‐Seon No'] Error correcting codes (ECCs) are indispensable for reliable transmission in communication systems. The recent advancements in deep learning have catalyzed the exploration of ECC decoders based on neural networks.…
Martin N. Hebart, Chris I. Baker
Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the…
Diego Vidaurre, Nicholas E Myers, Mark Stokes, Anna C Nobre + 1 more
'Mark W Woolrich'] Title: Abstract In this article, 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…
Rostislav Gusev, Nikita Aleksandrov, Artem Solomkin, Dmitry Artemasov
Forward error correction is essential for reliable communication over noisy channels. Attention-based model-free neural decoders have shown strong performance for short codes, but their scalability to longer codes is limited by the quadratic memory and computational cost of attention. In this paper, we introduce the…
Denis Kleyko, Connor Bybee, Ping-Chen Huang, Christopher J. Kymn + 3 more
'Bruno A. Olshausen' 'E. Paxon Frady' 'Friedrich T. Sommer'] We investigate the task of retrieving information from compositional distributed representations formed by Hyperdimensional Computing/Vector Symbolic Architectures and present novel techniques which achieve new information rate bounds. First, we provide an…
Diego Vidaurre, Radoslaw M. Cichy, Mark W. Woolrich
Brain decoding can predict visual perception from non-invasive electrophysiological data by combining information across multiple channels. However, decoding methods typically confound together the multi-faceted and distributed neural processes underlying perception, so it is unclear what specific aspects of the neural…
David Kracht, Steffen Schober
Background Barcode multiplexing is a key strategy for sharing the rising capacity of next-generation sequencing devices: Synthetic DNA tags, called barcodes, are attached to natural DNA fragments within the library preparation procedure. Different libraries, can individually be labeled with barcodes for a joint…
Qimin You, Yonghui Li, Soung Chang Liew, Branka Vucetic
This is the second part of a series of papers on a revisit to the bidirectional Bahl-Cocke-Jelinek-Raviv (BCJR) soft-in-soft-out (SISO) maximum a posteriori probability (MAP) decoding algorithm. Part I revisited the BCJR MAP decoding algorithm for rate-1 binary convolutional codes and proposed a linear complexity…