21 papers · ranked by Valyu relevance
Hannah H. McDermott, Federico De Martino, Caspar M. Schwiedrzik, Ryszard Auksztulewicz
The brain is thought to generate internal predictions, based on previous statistical regularities in the environment, to optimise behaviour. Predictive processing has been repeatedly demonstrated and seemingly explains expectation suppression (ES), or the attenuation of neural activity in response to expected stimuli.…
Brian J. Fischer, Keanu Shadron, Roland Ferger, José L. Peña + 1 more
'Melissa J. Coleman'] Bayesian models have proven effective in characterizing perception, behavior, and neural encoding across diverse species and systems. The neural implementation of Bayesian inference in the barn owl’s sound localization system and behavior has been previously explained by a non-uniform population…
Jack A. Kilgallen, Barak A. Pearlmutter, Jeffrey Mark Siskind
—Within neuroimgaing studies it is a common practice to perform repetitions of trials in an experiment when working with a noisy class of data acquisition system, such as electroencephalography (EEG) or magnetoencephalography (MEG). While this approach can be useful in some experimental designs, it presents significant…
Silvia Maggi, Mark D. Humphries
Medial prefrontal cortex (mPfC) activity represents information about the state of the world, including present behavior, such as decisions, and the immediate past, such as short-term memory. Unknown is whether information about different states of the world are represented in the same mPfC neural population and, if…
Anqi Zhang, Anthony M. Zador, Thomas Klausberger
Neurons in primary visual cortex (area V1) are strongly driven by both sensory stimuli and non-sensory events. However, although the representation of sensory stimuli has been well characterized, much less is known about the representation of non-sensory events. Here, we characterize the specificity and organization of…
Yang Yiling, Katharine Shapcott, Alina Peter, Johanna Klon-Lipok + 3 more
'Huang Xuhui' 'Andreea Lazar' 'Wolf Singer'] Parallel multisite recordings in the visual cortex of trained monkeys revealed that the responses of spatially distributed neurons to natural scenes are ordered in sequences. The rank order of these sequences is stimulus-specific and maintained even if the absolute timing of…
Akihiro Funamizu, Fred Marbach, Anthony M Zador
The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks.…
H. Fareed Ahmed, Toktam Samiei, Erfan Nozari
A unique feature, and challenge, in comparing decoding accuracies across scales is the potentially confounding effects of dimensionality. Unlike most machine learning problems where feature dimensions are either fixed or variable independently of the choice of model (due to missing data, e.g.), here the dimension of…
Yizi Zhang, Tianxiao He, Julien Boussard, Charlie Windolf + 9 more
Neural decoding and its applications to brain computer interfaces (BCI) are essential for understanding the association between neural activity and behavior. A prerequisite for many decoding approaches is spike sorting, the assignment of action potentials (spikes) to individual neurons. Current spike sorting…
Yunus Can Gültekin, Péter Scheepers, Yuncheng Yuan, Federico Corradi + 1 more
'Alex Alvarado'] Abstract—We investigate the design of two neural network (NN) architectures recently proposed as decoders for forward error correction: the so-called single-label NN (SLNN) and multilabel NN (MLNN) decoders. These decoders have been reported to achieve near-optimal codeword- and bit-wise performance…
Yan Yuan, Péter Scheepers, Lydia Tasiou, Yunus Can Gültekin + 2 more
Decoders Authors: ['Yan Yuan' 'Péter Scheepers' 'Lydia Tasiou' 'Yunus Can Gültekin' 'Federico Corradi' 'Alex Alvarado'] Abstract—This paper analyzes the design and competitiveness of four neural network (NN) architectures recently proposed as decoders for forward error correction (FEC) codes. We first consider 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…
Dechuan Sun, Forough Habibollahi Saatlou, Yang Yu, Ranjith Rajasekharan Unnithan + 1 more
The hippocampus has been proposed to integrate information from multiple sensory modalities, supporting a comprehensive “cognitive map” for both spatial and non-spatial information. Previous studies have demonstrated decoding of hippocampal spatial information in real time by recording neuronal action potentials with…
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…
Daniel Anthes, Sushrut Thorat, Anna Mitola, Paolo Papale + 2 more
In studying primate vision, a large body of work focuses on the first feedforward sweep. During this initial time window, information is thought to pass through ventral stream regions in a stage-like fashion in an effort to extract high-level information from the retinal input. Consequently, electrophysiological…
Zeyuan Ye, Haoran Li, Liang Tian, Changsong Zhou
Understanding how the brain preserves information despite intrinsic noise is a fundamental question in working memory. Typical working memory tasks consist of delay phase for maintaining information, and decoding phase for retrieving information. While previous works have focused on the delay neural dynamics, it is…
Ilshat Sagitov, Charles Pillet, Pascal Giard
Channel-Production Rate Authors: ['Ilshat Sagitov' 'Charles Pillet' 'Pascal Giard'] Abstract—Polar codes are a class of error-correcting codes that provably achieve the capacity of practical channels under the low-complexity successive-cancellation flip (SCF) decoding algorithm. However, the SCF decoding algorithm has…
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…
Zita Abreu, Julia Lieb, Michael Schaller
The classical way of dealing with errors during data transmission over some communication channel have been linear block codes, which are vector spaces over some finite field Fq. Convolutional codes as modules over Fq[z] are a generalization of linear block codes to the polynomial setting. These codes are often used in…
Anisha Banerjee, Andreas Lenz, Antonia Wachter-Zeh
—Sequential decoding, commonly applied to substitution channels, is a sub-optimal alternative to Viterbi decoding with significantly reduced memory costs. In this work, a sequential decoder for convolutional codes over channels that are prone to insertion, deletion, and substitution errors, is described and analyzed.…
Nima Maleki, Hamid Karimi-Rouzbahani
Sensory neural coding, the brain’s process of transforming inputs into informative patterns of neural activity, generates complex and multiplexed neural codes which are hard to interpret. Although decoding methods have facilitated the interpretation of these codes, the specific features of neural activity that…