The computational foundations of dynamic coding in working memory

JP Stroud, J Duncan, M Lengyel - Trends in Cognitive Sciences, 2024 - cell.com
Working memory (WM) is a fundamental aspect of cognition. WM maintenance is classically
thought to rely on stable patterns of neural activities. However, recent evidence shows that …

[HTML][HTML] Biologically plausible models of cognitive flexibility: merging recurrent neural networks with full-brain dynamics

M van Holk, JF Mejias - Current Opinion in Behavioral Sciences, 2024 - Elsevier
Highlights•Computational models aid to explore biological mechanisms of cognitive
flexibility.•Recurrent network models can be used to model flexible decisions.•Large-scale …

Automatic discovery of cognitive strategies with tiny recurrent neural networks

L Ji-An, MK Benna, MG Mattar - bioRxiv, 2023 - biorxiv.org
Normative frameworks such as Bayesian inference and reward-based learning are useful
tools for explaining the fundamental principles of adaptive behavior. However, their ability to …

When and why does motor preparation arise in recurrent neural network models of motor control?

M Schimel, TC Kao, G Hennequin - bioRxiv, 2023 - biorxiv.org
During delayed ballistic reaches, motor areas consistently display movement-specific activity
patterns prior to movement onset. It is unclear why these patterns arise: while they have …

Limitation of switching sensory information flow in flexible perceptual decision making

T Luo, M Xu, Z Zheng, G Okazawa - bioRxiv, 2023 - biorxiv.org
Humans can flexibly change rules to categorize sensory stimuli, but their performance
degrades immediately after a task switch. This switch cost is believed to reflect a limitation in …

Models of neural circuits as optimally driven dynamical systems

M Schimel - 2024 - repository.cam.ac.uk
Animal brains are composed of large numbers of neurons, whose time-varying activity is
shaped by their recurrent connections.% neurons are connected. Recent advances in …