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A central challenge in continual learning is forgetting, the loss of performance on previously learned tasks induced by sequential adaptation to new ones. While forgetting has been extensively studied empirically, rigorous theoretical…

Machine Learning · Computer Science 2026-04-16 Zonghuan Xu , Xingjun Ma

Correlated fluctuations in the activity of neural populations reflect the network's dynamics and connectivity. The temporal and spatial dimensions of neural correlations are interdependent. However, prior theoretical work mainly analyzed…

Neurons and Cognition · Quantitative Biology 2022-07-19 Yan-Liang Shi , Roxana Zeraati , Anna Levina , Tatiana A. Engel

We consider a few quantities that characterize trading on a stock market in a fixed time interval: logarithmic returns, volatility, trading activity (i.e., the number of transactions), and volume traded. We search for the power-law…

Statistical Finance · Quantitative Finance 2016-01-20 Rafal Rak , Stanislaw Drozdz , Jaroslaw Kwapien , Pawel Oswiecimka

Over the past decade, studies of naturalistic language processing where participants are scanned while listening to continuous text have flourished. Using word embeddings at first, then large language models, researchers have created…

Computation and Language · Computer Science 2024-11-05 Laurent Bonnasse-Gahot , Christophe Pallier

Critical branching is a theoretical interaction in-between simple units, such as neuronal elements of the human brain. Zhigalov, Kaplan, and Palva (2016, Clin. Neurophysiol., 127(8), 2882-2889) revealed that neurofeedback flash stimulation…

Neurons and Cognition · Quantitative Biology 2017-02-22 Tom Campbell

Large efforts are currently under way to systematically map functional connectivity between all pairs of millimeter-scale brain regions using big volumes of neuroimaging data. Functional magnetic resonance imaging (fMRI) can produce these…

Neurons and Cognition · Quantitative Biology 2014-09-24 Enzo Tagliazucchi , Helmut Laufs , Dante R. Chialvo

Vision-Language models (VLMs) show impressive abilities to answer questions on visual inputs (e.g., counting objects in an image), yet demonstrate higher accuracies when performing an analogous task on text (e.g., counting words in a text).…

Computation and Language · Computer Science 2025-10-06 Yaniv Nikankin , Dana Arad , Yossi Gandelsman , Yonatan Belinkov

The distributed nature of the neural substrate, and the difficulty of establishing necessity from correlative data, combine to render the mapping of brain function a far harder task than it seems. Methods capable of combining connective…

Task-free connectivity analyses have emerged as a powerful tool in functional neuroimaging. Because the cross-correlations that underlie connectivity measures are sensitive to distortion of time-series, here we used a novel dynamic phantom…

Neurons and Cognition · Quantitative Biology 2020-02-05 D. J. DeDora , S. Nedic , P. Katti , S. Arnab , L. L. Wald , A. Takahashi , K. R. A. Van Dijk , H. H. Strey , L. R. Mujica-Parodi

The technology of functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygen Level Dependent (BOLD) signal has been widely used in clinical treatments and brain function researches. The BOLD signal has to be preprocessed before…

Neurons and Cognition · Quantitative Biology 2017-12-29 Yunxiang Ge , Yu Pan , Weibei Dou

This thesis delves into the world of non-invasive electrophysiological brain signals like electroencephalography (EEG) and magnetoencephalography (MEG), focusing on modelling and decoding such data. The research aims to investigate what…

Signal Processing · Electrical Eng. & Systems 2025-10-30 Richard Csaky

Residual learning has recently surfaced as an effective means of constructing very deep neural networks for object recognition. However, current incarnations of residual networks do not allow for the modeling and integration of complex…

Computer Vision and Pattern Recognition · Computer Science 2016-07-21 Brendan Jou , Shih-Fu Chang

Brain responses related to working memory originate from distinct brain areas and oscillate at different frequencies. EEG signals with high temporal correlation can effectively capture these responses. Therefore, estimating the functional…

Machine Learning · Computer Science 2024-05-01 Harshini Gangapuram , Vidya Manian

We propose a method for estimating more reproducible functional networks that are more strongly associated with dynamic task activity by using recurrent neural networks with long short term memory (LSTMs). The LSTM model is trained in an…

Quantitative Methods · Quantitative Biology 2021-05-07 Nicha C. Dvornek , Pamela Ventola , James S. Duncan

Working memory is a central component of intelligent behavior, providing a dynamic workspace for maintaining and updating task-relevant information. Recent work has used n-back tasks to probe working-memory-like behavior in large language…

Computation and Language · Computer Science 2026-02-05 Sichu Liang , Hongyu Zhu , Wenwen Wang , Deyu Zhou

Similar to how differences in the proficiency of the cardiovascular and musculoskeletal system predict an individual's athletic ability, differences in how the same brain region encodes information across individuals may explain their…

Neurons and Cognition · Quantitative Biology 2021-12-14 Jennifer Williams , Leila Wehbe

We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject's behavior during a scanning session. Such predictions suffer from the huge number of brain…

Computer Vision and Pattern Recognition · Computer Science 2011-04-29 Vincent Michel , Alexandre Gramfort , Gaël Varoquaux , Evelyn Eger , Christine Keribin , Bertrand Thirion

The scaling property of the brain dynamics is studied based on the zero-crossing of the local electroencephalographic (EEG) recording taken from healthy young adults in eyes closed and eyes open. Evidence of coupling between the EEG fractal…

Biological Physics · Physics 2007-05-23 Der Chyan Lin , Asif Sharif , Hon Kwan

Deficits in working memory, which includes both the ability to learn and to retain information short-term, are a hallmark of many cognitive disorders. Our study analyzes data from a neuroscience experiment on animal subjects, where…

Applications · Statistics 2025-12-23 Maria Laura Battagliola , Laura J. Benoit , Sarah Canetta , Shizhe Zhang , R. Todd Ogden

Structural and functional MRI studies of patients with post-stroke language deficits have contributed substantially to our understanding of how cognitive-behavioral impairments relate to the location of structural damage and to the…

Neurons and Cognition · Quantitative Biology 2016-10-14 Joseph C. Griffis , Rodolphe Nenert , Jane B. Allendorfer , Jerzy P. Szaflarski