Disentangling negative reinforcement, working memory, and deductive reasoning deficits in elevated BMI.

Neuropsychological data suggest that being overweight or obese is associated with a tendency to perseverate behavior despite negative feedback. This deficit might be observed due to other cognitive factors, such as working memory (WM) deficits or decreased ability to deduce model-based strategies when learning by trial-and-error. In the present study, a group of subjects with overweight or obesity (Ow/Ob, n = 30) was compared to normal-weight individuals (n = 42) in a modified Reinforcement Learning (RL) task.

Switching to online: Testing the validity of supervised remote testing for online reinforcement learning experiments.

Online experiments are an alternative for researchers interested in conducting behavioral research outside the laboratory. However, an online assessment might become a challenge when long and complex experiments need to be conducted in a specific order or with supervision from a researcher. The aim of this study was to test the computational validity and the feasibility of a remote and synchronous reinforcement learning (RL) experiment conducted during the social-distancing measures imposed by the pandemic.

The transfer function of neuron spike.

The mathematical modeling of neuronal signals is a relevant problem in neuroscience. The complexity of the neuron behavior, however, makes this problem a particularly difficult task. Here, we propose a discrete-time linear time-invariant (LTI) model with a rational function in order to represent the neuronal spike detected by an electrode located in the surroundings of the nerve cell.