21 papers · ranked by Valyu relevance
Han G. Yi, Zilong Xie, Rachel Reetzke, Alexandros G. Dimakis + 1 more
4## Discussion We demonstrate an innovative application of machine learning principles to reliably extract vowel information from the single-trial speech-evoked FFRs. In our approach, the raw FFR was first projected onto a spectral feature space defined by a multitude of sounds not used in the experiment, contributing…
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…
Ioannis Delis, Bastien Berret, Thierry Pozzo, Stefano Panzeri
Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements. Several efficient dimensionality reduction algorithms that extract putative…
Stefano Panzeri, Robin A. A. Ince, Mathew E. Diamond, Christoph Kayser
'Christoph Kayser'] The precise timing of action potentials of sensory neurons relative to the time of stimulus presentation carries substantial sensory information that is lost or degraded when these responses are summed over longer time windows. However, it is unclear whether and how downstream networks can access…
Joaquín Rapela, Marissa Westerfield, Jeanne Townsend, Scott Makeig
Expecting events in time leads to more efficient behavior. A remarkable early finding in the study of temporal expectancy is the foreperiod effect on reaction times; i.e., the influence or reaction time of the time period between a warning signal and an imperative stimulus to which subjects are instructed to respond as…
Joram Soch, Carsten Allefeld, John-Dylan Haynes
Techniques of multivariate pattern analysis (MVPA) can be used to decode the discrete experimental condition or a continuous modulator variable from measured brain activity during a particular trial. In functional magnetic resonance imaging (fMRI), trial-wise response amplitudes are sometimes estimated from the…
Caroline Haimerl, Douglas A. Ruff, Marlene R. Cohen, Cristina Savin + 1 more
Sensory-guided behavior requires reliable encoding of stimulus information in neural responses, and task-specific decoding through selective combination of these responses. The former has been the topic of intensive study, but the latter remains largely a mystery. We propose a framework in which shared stochastic…
Srinivas Ravishankar, Nora Zajzon, Virginia de Sa
Patients with extreme forms of paralysis face challenges in communication, adversely impacting their quality of life. Recent studies have reported higher-than-chance performance in decoding handwritten letters from EEG signals, potentially allowing these subjects to communicate. However, all prior works have attempted…
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…
Jorrit S. Montijn, Martin Vinck, Cyriel M. A. Pennartz
The primary visual cortex is an excellent model system for investigating how neuronal populations encode information, because of well-documented relationships between stimulus characteristics and neuronal activation patterns. We used two-photon calcium imaging data to relate the performance of different methods for…
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…
Caroline Haimerl, Cristina Savin, Eero P. Simoncelli
Sensory-guided behavior requires reliable encoding of information (from stimuli to neural responses) and flexible decoding (from neural responses to behavior). In typical decision tasks, a small subset of cells within a large population encode task-relevant stimulus information and need to be identified by later…
Vicente Botella‐Soler, Stéphane Deny, Olivier Marre, Gašper Tkačik
Retinal circuitry transforms spatiotemporal patterns of light into spiking activity of ganglion cells, which provide the sole visual input to the brain. Recent advances have led to a detailed characterization of retinal activity and stimulus encoding by large neural populations. The inverse problem of decoding, where…
S. Thomas Christie, Hayden R. Johnson, Paul R. Schrater
Human response times conform to several regularities including the Hick-Hyman law, the power law of practice, speed-accuracy trade-offs, and the Stroop effect. Each of these has been thoroughly modeled in isolation, but no account describes these phenomena as predictions of a unified framework. We provide such a…
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…
Hyeji Kim, Yihan Jiang, Ranvir Rana, Sreeram Kannan + 2 more
'Pramod Viswanath'] Coding theory is a central discipline underpinning wireline and wireless modems that are the workhorses of the information age. Progress in coding theory is largely driven by individual human ingenuity with sporadic breakthroughs over the past century. In this paper we study whether it is possible…
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…
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…
ARIF ULLAH, Pavlo O. Dral
Nonadiabatic quantum dynamics are important for understanding light-harvesting processes, but their propagation with traditional methods can be rather expensive. Here we present a one-shot trajectory learning approach that allows to directly make ultra-fast prediction of the entire trajectory of the reduced density…