Serial dependence in perception

GM Cicchini, K Mikellidou… - Annual Review of …, 2024‏ - annualreviews.org
Much evidence has shown that perception is biased towards previously presented similar
stimuli, an effect recently termed serial dependence. Serial dependence affects nearly every …

Predictive processing: a canonical cortical computation

GB Keller, TD Mrsic-Flogel - Neuron, 2018‏ - cell.com
This perspective describes predictive processing as a computational framework for
understanding cortical function in the context of emerging evidence, with a focus on sensory …

Model-based reinforcement learning: A survey

TM Moerland, J Broekens, A Plaat… - … and Trends® in …, 2023‏ - nowpublishers.com
Sequential decision making, commonly formalized as Markov Decision Process (MDP)
optimization, is an important challenge in artificial intelligence. Two key approaches to this …

Maskvit: Masked visual pre-training for video prediction

A Gupta, S Tian, Y Zhang, J Wu, R Martín-Martín… - arxiv preprint arxiv …, 2022‏ - arxiv.org
The ability to predict future visual observations conditioned on past observations and motor
commands can enable embodied agents to plan solutions to a variety of tasks in complex …

Single-trial neural dynamics are dominated by richly varied movements

S Musall, MT Kaufman, AL Juavinett, S Gluf… - Nature …, 2019‏ - nature.com
When experts are immersed in a task, do their brains prioritize task-related activity? Most
efforts to understand neural activity during well-learned tasks focus on cognitive …

Curiosity-driven exploration by self-supervised prediction

D Pathak, P Agrawal, AA Efros… - … conference on machine …, 2017‏ - proceedings.mlr.press
In many real-world scenarios, rewards extrinsic to the agent are extremely sparse, or absent
altogether. In such cases, curiosity can serve as an intrinsic reward signal to enable the …

[HTML][HTML] The predictive coding account of psychosis

P Sterzer, RA Adams, P Fletcher, C Frith, SM Lawrie… - Biological …, 2018‏ - Elsevier
Fueled by developments in computational neuroscience, there has been increasing interest
in the underlying neurocomputational mechanisms of psychosis. One successful approach …

Contextual inference in learning and memory

JB Heald, M Lengyel, DM Wolpert - Trends in cognitive sciences, 2023‏ - cell.com
Context is widely regarded as a major determinant of learning and memory across
numerous domains, including classical and instrumental conditioning, episodic memory …

[HTML][HTML] Brain-machine interfaces: from basic science to neuroprostheses and neurorehabilitation

MA Lebedev, MAL Nicolelis - Physiological reviews, 2017‏ - journals.physiology.org
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from
neurophysiology, computer science, and engineering in an effort to establish real-time …

Probabilistic machine learning and artificial intelligence

Z Ghahramani - Nature, 2015‏ - nature.com
How can a machine learn from experience? Probabilistic modelling provides a framework
for understanding what learning is, and has therefore emerged as one of the principal …