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Serial dependence in perception
Much evidence has shown that perception is biased towards previously presented similar
stimuli, an effect recently termed serial dependence. Serial dependence affects nearly every …
stimuli, an effect recently termed serial dependence. Serial dependence affects nearly every …
Predictive processing: a canonical cortical computation
This perspective describes predictive processing as a computational framework for
understanding cortical function in the context of emerging evidence, with a focus on sensory …
understanding cortical function in the context of emerging evidence, with a focus on sensory …
Model-based reinforcement learning: A survey
Sequential decision making, commonly formalized as Markov Decision Process (MDP)
optimization, is an important challenge in artificial intelligence. Two key approaches to this …
optimization, is an important challenge in artificial intelligence. Two key approaches to this …
Maskvit: Masked visual pre-training for video prediction
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 …
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
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 …
efforts to understand neural activity during well-learned tasks focus on cognitive …
Curiosity-driven exploration by self-supervised prediction
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 …
altogether. In such cases, curiosity can serve as an intrinsic reward signal to enable the …
[HTML][HTML] The predictive coding account of psychosis
Fueled by developments in computational neuroscience, there has been increasing interest
in the underlying neurocomputational mechanisms of psychosis. One successful approach …
in the underlying neurocomputational mechanisms of psychosis. One successful approach …
Contextual inference in learning and memory
Context is widely regarded as a major determinant of learning and memory across
numerous domains, including classical and instrumental conditioning, episodic memory …
numerous domains, including classical and instrumental conditioning, episodic memory …
[HTML][HTML] Brain-machine interfaces: from basic science to neuroprostheses and neurorehabilitation
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from
neurophysiology, computer science, and engineering in an effort to establish real-time …
neurophysiology, computer science, and engineering in an effort to establish real-time …
Probabilistic machine learning and artificial intelligence
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 …
for understanding what learning is, and has therefore emerged as one of the principal …