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It has been repeatedly conjectured that the brain retrieves statistical regularities from stimuli. Here we present a new statistical approach allowing to address this conjecture. This approach is based on a new class of stochastic processes…

Neurons and Cognition · Quantitative Biology 2018-01-15 A. Duarte , R. Fraiman , A. Galves , G. Ost , C. Vargas

It has been classically conjectured that the brain compresses data by assigning probabilistic models to sequences of stimuli. An important issue associated to this conjecture is what class of models is used by the brain to perform its…

Neurons and Cognition · Quantitative Biology 2020-08-26 F. A. Najman , A. Galves , C. D. Vargas

It has been classically conjectured that the brain assigns probabilistic models to sequences of stimuli. An important issue associated with this conjecture is the identification of the classes of models used by the brain to perform this…

Neurons and Cognition · Quantitative Biology 2023-12-29 Fernando A. Najman , Antonio Galves , Marcela Svarc , Claudia D. Vargas

This work draws on the conjecture that fingerprints of stochastic event sequences can be retrieved from electroencephalographic data (EEG) recorded during a behavioral task. To test this, we used the Goalkeeper Game (game.numec.prp.usp.br).…

Neurons and Cognition · Quantitative Biology 2025-10-09 P. R. Cabral-Passos , P. S. Azevedo , V. H. Moraes , B. L. Ramalho , A. Duarte , C. D. Vargas

Brain source imaging is an important method for noninvasively characterizing brain activity using Electroencephalogram (EEG) or Magnetoencephalography (MEG) recordings. Traditional EEG/MEG Source Imaging (ESI) methods usually assume that…

Applications · Statistics 2019-06-07 Feng Liu , Li Wang , Yifei Lou , Rencang Li , Patrick Purdon

Many studies have explored brain signals during the performance of a memory task to predict later remembered items. However, prediction methods are still poorly used in real life and are not practical due to the use of…

Signal Processing · Electrical Eng. & Systems 2020-05-11 Jenifer Kalafatovich , Minji Lee , Seong-Whan Lee

Noninvasive brain computer interfaces (BCI), and more specifically Electroencephalography (EEG) based systems for intent detection need to compensate for the low signal to noise ratio of EEG signals. In many applications, the temporal…

Human-Computer Interaction · Computer Science 2017-03-09 Seyed Sadegh Mohseni Salehi , Mohammad Moghadamfalahi , Hooman Nezamfar , Marzieh Haghighi , Deniz Erdogmus

The human brain receives stimuli in multiple ways; among them, audio constitutes an important source of relevant stimuli for the brain regarding communication, amusement, warning, etc. In this context, the aim of this manuscript is to…

Signal Processing · Electrical Eng. & Systems 2024-11-21 Isaac Ariza , Ana M. Barbancho , Lorenzo J. Tardon , Isabel Barbancho

The correlated variability in the responses of a neural population to the repeated presentation of a sensory stimulus is a universally observed phenomenon. Such correlations have been studied in much detail, both with respect to their…

Neurons and Cognition · Quantitative Biology 2018-07-04 Volker Pernice , Rava Azeredo da Silveira

Speech comprehension is an involuntary task for the healthy human brain, yet the understanding of the mechanisms underlying this brain functionality remains obscure. In this paper, we aim to quantify the role of acoustic and semantic…

Audio and Speech Processing · Electrical Eng. & Systems 2025-07-31 Sai Samrat Kankanala , Akshara Soman , Sriram Ganapathy

From ancient philosophers to modern economists, biologists, and other researchers, there has been a continuous effort to unveil causal relations. The most formidable challenge lies in deducing the nature of the causal relationship: whether…

The music signal comprises of different features like rhythm, timbre, melody, harmony. Its impact on the human brain has been an exciting research topic for the past several decades. Electroencephalography (EEG) signal enables non-invasive…

Neurons and Cognition · Quantitative Biology 2020-09-30 Dhananjay Sonawane , Krishna Prasad Miyapuram , Bharatesh RS , Derek J. Lomas

Electroencephalogram (EEG) data is crucial for diagnosing mental health conditions but is costly and time-consuming to collect at scale. Synthetic data generation offers a promising solution to augment datasets for machine learning…

Signal Processing · Electrical Eng. & Systems 2025-07-08 Gideon Vos , Maryam Ebrahimpour , Liza van Eijk , Zoltan Sarnyai , Mostafa Rahimi Azghadi

Information retrieval from brain responses to auditory and visual stimuli has shown success through classification of song names and image classes presented to participants while recording EEG signals. Information retrieval in the form of…

Sound · Computer Science 2022-07-29 Adolfo G. Ramirez-Aristizabal , Chris Kello

In order to obtain a stochastic model that accounts for the stochastic aspects of the dynamics of a business process, usually the following steps are taken. Given an event log, a process tree is obtained through a process discovery…

Computation and Language · Computer Science 2025-04-09 András Horváth , Paolo Ballarini , Pierre Cry

The use of electroencephalogram (EEG) as the main input signal in brain-machine interfaces has been widely proposed due to the non-invasive nature of the EEG. Here we are specifically interested in interfaces that extract information from…

Signal Processing · Electrical Eng. & Systems 2018-04-30 Marc-Antoine Moinnereau , Thomas Brienne , Simon Brodeur , Jean Rouat , Kevin Whittingstall , Eric Plourde

In this article we address two related issues on the learning of probabilistic sequences of events. First, which features make the sequence of events generated by a stochastic chain more difficult to predict. Second, how to model the…

Neural spikes in the brain form stochastic sequences, i.e., belong to the class of pulse noises. This stochasticity is a counterintuitive feature because extracting information - such as the commonly supposed neural information of mean…

Neural and Evolutionary Computing · Computer Science 2015-03-31 Laszlo B. Kish , Claes-Goran Granqvist , Sergey M. Bezrukov , Tamas Horvath

Tonal structure is in part conveyed by statistical regularities between musical events, and research has shown that computational models reflect tonal structure in music by capturing these regularities in schematic constructs like pitch…

Sound · Computer Science 2017-07-21 Carlos Cancino-Chacón , Maarten Grachten , Kat Agres

Cognitively inspired NLP leverages human-derived data to teach machines about language processing mechanisms. Recently, neural networks have been augmented with behavioral data to solve a range of NLP tasks spanning syntax and semantics. We…

Computation and Language · Computer Science 2020-10-06 Lukas Muttenthaler , Nora Hollenstein , Maria Barrett
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