IntelliCage: the development and perspectives of a mouse-and user-friendly automated behavioral test system
HP Lipp, S Krackow, E Turkes, S Benner… - Frontiers in Behavioral …, 2024 - frontiersin.org
IntelliCage for mice is a rodent home-cage equipped with four corner structures harboring
symmetrical double panels for operant conditioning at each of the two sides, either by …
symmetrical double panels for operant conditioning at each of the two sides, either by …
Active reinforcement learning versus action bias and hysteresis: control with a mixture of experts and nonexperts
Active reinforcement learning enables dynamic prediction and control, where one should not
only maximize rewards but also minimize costs such as of inference, decisions, actions, and …
only maximize rewards but also minimize costs such as of inference, decisions, actions, and …
Enhancement of Mediodorsal Thalamus Rescues Aberrant Belief Dynamics in a Novel Mouse Model for Schizophrenia
Optimizing behavioral strategy requires belief updating based on new evidence, a process
that engages higher cognition. In schizophrenia, aberrant belief dynamics may lead to …
that engages higher cognition. In schizophrenia, aberrant belief dynamics may lead to …
Diverse and flexible behavioral strategies arise in recurrent neural networks trained on multisensory decision making
Behavioral variability across individuals leads to substantial performance differences during
cognitive tasks, although its neuronal origin and mechanisms remain elusive. Here we use …
cognitive tasks, although its neuronal origin and mechanisms remain elusive. Here we use …
An agent-based model of behaviour change calibrated to reversal learning data
Behaviour change lies at the heart of many observable collective phenomena such as the
transmission and control of infectious diseases, adoption of public health policies, and …
transmission and control of infectious diseases, adoption of public health policies, and …
L (M) V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization
In advancing the understanding of decision-making processes, mathematical models,
particularly Inverse Reinforcement Learning (IRL), have proven instrumental in …
particularly Inverse Reinforcement Learning (IRL), have proven instrumental in …
[HTML][HTML] Enhancement of mediodorsal thalamus rescues aberrant belief dynamics in a mouse model with schizophrenia-associated mutation
Optimizing behavioral strategy requires belief updating based on new evidence, a process
that engages higher cognition. In schizophrenia, aberrant belief dynamics may lead to …
that engages higher cognition. In schizophrenia, aberrant belief dynamics may lead to …
Dorsal prefrontal cortex drives perseverative behavior in mice
Perseveration--repeating one choice when others would generate larger rewards--is a
common behavior, but neither its purpose nor neuronal mechanisms are understood. Here …
common behavior, but neither its purpose nor neuronal mechanisms are understood. Here …
Dynamic reinforcement learning reveals time-dependent shifts in strategy during reward learning
Different brain systems have been hypothesized to subserve multiple “experts” that compete
to generate behavior. In reinforcement learning, two general processes, one model-free …
to generate behavior. In reinforcement learning, two general processes, one model-free …
Neural networks representing temporal expectation in mice
AT Wendlandt, P Wenk, JU Henschke, A Michalek… - bioRxiv, 2024 - biorxiv.org
The ability to attend to specific moments in time is crucial for survival across species
facilitating perception and motor performance by leveraging prior temporal knowledge for …
facilitating perception and motor performance by leveraging prior temporal knowledge for …