Convergence of artificial intelligence and neuroscience towards the diagnosis of neurological disorders—a sco** review

C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) is a field of computer science that deals with the simulation of
human intelligence using machines so that such machines gain problem-solving and …

The basal ganglia and the cerebellum: nodes in an integrated network

AC Bostan, PL Strick - Nature Reviews Neuroscience, 2018 - nature.com
The basal ganglia and the cerebellum are considered to be distinct subcortical systems that
perform unique functional operations. The outputs of the basal ganglia and the cerebellum …

Frontostriatal salience network expansion in individuals in depression

CJ Lynch, IG Elbau, T Ng, A Ayaz, S Zhu, D Wolk… - Nature, 2024 - nature.com
Decades of neuroimaging studies have shown modest differences in brain structure and
connectivity in depression, hindering mechanistic insights or the identification of risk factors …

An introduction to deep reinforcement learning

V François-Lavet, P Henderson, R Islam… - … and Trends® in …, 2018 - nowpublishers.com
Deep reinforcement learning is the combination of reinforcement learning (RL) and deep
learning. This field of research has been able to solve a wide range of complex …

Deep reinforcement learning and its neuroscientific implications

M Botvinick, JX Wang, W Dabney, KJ Miller… - Neuron, 2020 - cell.com
The emergence of powerful artificial intelligence (AI) is defining new research directions in
neuroscience. To date, this research has focused largely on deep neural networks trained …

Towards a neuroscience of active sampling and curiosity

J Gottlieb, PY Oudeyer - Nature Reviews Neuroscience, 2018 - nature.com
In natural behaviour, animals actively interrogate their environments using endogenously
generated 'question-and-answer'strategies. However, in laboratory settings participants …

Reinforcement learning in patients with mood and anxiety disorders vs control individuals: A systematic review and meta-analysis

AC Pike, OJ Robinson - JAMA psychiatry, 2022 - jamanetwork.com
Importance Computational psychiatry studies have investigated how reinforcement learning
may be different in individuals with mood and anxiety disorders compared with control …

Hearing impairment and cognitive energy: The framework for understanding effortful listening (FUEL)

MK Pichora-Fuller, SE Kramer, MA Eckert… - Ear and …, 2016 - journals.lww.com
Abstract The Fifth Eriksholm Workshop on “Hearing Impairment and Cognitive Energy” was
convened to develop a consensus among interdisciplinary experts about what is known on …

The role of variability in motor learning

AK Dhawale, MA Smith… - Annual review of …, 2017 - annualreviews.org
Trial-to-trial variability in the execution of movements and motor skills is ubiquitous and
widely considered to be the unwanted consequence of a noisy nervous system. However …

Updates in motor learning: implications for physical therapist practice and education

KA Leech, RT Roemmich, J Gordon… - Physical …, 2022 - academic.oup.com
Over the past 3 decades, the volume of human motor learning research has grown
enormously. As such, the understanding of motor learning (ie, sustained change in motor …