Results 81 to 90 of about 33,138 (231)

Learning and Choice in Mood Disorders: Searching for the Computational Parameters of Anhedonia

Computational Psychiatry, 2017
Computational approaches are increasingly being used to model behavioral and neural processes in mood and anxiety disorders. Here we explore the extent to which the parameters of popular learning and decision-making models are implicated in anhedonic ...
Oliver J. Robinson, Henry W. Chase
doaj   +1 more source

WONOEP XVII appraisal: The role of the extracellular matrix in epilepsy

Epilepsia, EarlyView.
Abstract The extracellular matrix (ECM) is composed of proteoglycans and glycoproteins that regulate the external environment surrounding neurons, glia, and the vascular system. The ECM is vital for maintaining the structure and function of the brain and also acts as a reservoir for various signaling molecules and neurotransmitters, modulating synaptic
Eleonora Lugara, Erwin A. van Vliet, Alessia Romagnolo, Kevin Staley, Kyle P. Lillis, Chris Dulla, David C. Henshall, Katja Kobow   +7 more
wiley   +1 more source

Hacking the Predictive Mind

Entropy
According to active inference, constantly running prediction engines in our brain play a large role in delivering all human experience. These predictions help deliver everything we see, hear, touch, and feel.
Andy Clark
doaj   +1 more source

Computation in Psychotherapy, or How Computational Psychiatry Can Aid Learning-Based Psychological Therapies

Computational Psychiatry, 2018
Learning-based therapies, such as cognitive-behavioral therapy, are used worldwide, and their efficacy is endorsed by health and research funding agencies.
Michael Moutoussis, Nitzan Shahar, Tobias U. Hauser, Raymond J. Dolan   +3 more
doaj   +1 more source

Fully automated three‐dimensional deep learning‐based magnetic resonance imaging segmentation of brain cavities in epilepsy surgery

Epilepsia, EarlyView.
Abstract Objective There are several clinical and research applications for determining the amount of brain tissue resected after epilepsy surgery; however, manual segmentation of postoperative magnetic resonance imaging (MRI) is imprecise and time‐consuming.
Raphael Fernandes Casseb, Brunno Machado de Campos, Wallace Souza Loos, Marcelo Eduardo Ramos Barbosa, Marina Koutsodontis Machado Alvim, Gabriel Chagas Lutfala Paulino, Enrico Ghizoni, Francesco Pucci, Samuel Worrell, Clarissa Lin Yassuda, Roberto Medeiros de Souza, Lara Jehi, Fernando Cendes   +12 more
wiley   +1 more source

Signatures of Perseveration and Heuristic-Based Directed Exploration in Two-Step Sequential Decision Task Behaviour

Computational Psychiatry
Processes formalized in classic Reinforcement Learning (RL) theory, such as model-based (MB) control, habit formation, and exploration have proven fertile in cognitive and computational neuroscience, as well as computational psychiatry. Dysregulations in
Angela Mariele Brands, David Mathar, Jan Peters   +2 more
doaj   +1 more source

A translational multimodal machine‐learning prototype predicting valproate response in epilepsy treatment

Epilepsia, EarlyView.
Abstract Objective Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a commonly prescribed first‐line ASM, yet only approximately half of patients achieve sustained seizure freedom. Treatment selection remains largely empirical.
Simeon Platte, Afsheen Kumar, Giorgia Guerini, Massimo Pandolfo, Denise Haslinger, Colin B. Josephson, Guillermo Delgado‐García, Navprabhjot Kaur, Michaela‐Pauline Lux, Heiko Stempfle, Chantal Depondt, Reetta Kälviäinen, Felix Rosenow, Sophie von Brauchitsch, Karl Martin Klein, Andreas G. Chiocchetti   +15 more
wiley   +1 more source

Development and preclinical evaluation of a hybrid stereoelectroencephalographic–laser depth electrode for magnetic resonance imaging‐guided interstitial thermal therapy in drug‐resistant epilepsy

Epilepsia, EarlyView.
Abstract Objective This study was undertaken to design and validate a hybrid depth electrode combining stereoelectroencephalographic (sEEG) recording and magnetic resonance‐guided laser interstitial thermal therapy (MRgLITT) under real‐time magnetic resonance thermometry, to streamline the transition from invasive localization to focal ablation in ...
Bertrand Mathon, Karima Mokhtari, Damien Galanaud, Alexandre Carpentier   +3 more
wiley   +1 more source

Presurgical magnetoencephalography‐derived network control metrics distinguish successful hippocampal resection vs sparing in temporal lobe epilepsy

Epilepsia, EarlyView.
Abstract Objective Surgical decision‐making in temporal lobe epilepsy (TLE) faces a critical challenge in determining whether the hippocampus can be safely spared during anterior temporal resection, particularly when surgery involves the language‐dominant hemisphere.
Guhan Seshadri NP, Himanshu Kumar, Neha Sara John, Andreas V. Alexopoulos, Richard C. Burgess, Hiroatsu Murakami, Balu Krishnan   +6 more
wiley   +1 more source

Individual‐specific resting‐state networks predict language dominance in drug‐resistant epilepsy

Epilepsia, EarlyView.
Abstract Objective This study was undertaken to reliably estimate individual‐specific resting‐state cortical networks and determine whether language network topography can predict task‐based language dominance in drug‐resistant epilepsy. Methods We utilized a multisession hierarchical Bayesian model (MS‐HBM) trained on drug‐resistant epilepsy patients ...
Mervyn Jun Rui Lim, Shaoshi Zhang, Shreya Pande, Aihuiping Xue, Ru Kong, Kareem Zaghloul, Sara Inati, B. T. Thomas Yeo   +7 more
wiley   +1 more source