Reward Learning over Weeks Versus Minutes Increases the Neural Representation of Value in the Human Brain.

Over the past few decades, neuroscience research has illuminated the neural mechanisms supporting learning from reward feedback. Learning paradigms are increasingly being extended to study mood and psychiatric disorders as well as addiction. However, one potentially critical characteristic that this research ignores is the effect of time on learning: human feedback learning paradigms are usually conducted in a single rapidly paced session, whereas learning experiences in ecologically relevant circumstances and in animal research are almost always separated by longer periods of time. In our experiments, we examined reward learning in short condensed sessions distributed across weeks versus learning completed in a single "massed" session in male and female participants. As expected, we found that after equal amounts of training, accuracy was matched between the spaced and massed conditions. However, in a 3-week follow-up, we found that participants exhibited significantly greater memory for the value of spaced-trained stimuli. Supporting a role for short-term memory in massed learning, we found a significant positive correlation between initial learning and working memory capacity. Neurally, we found that patterns of activity in the medial temporal lobe and prefrontal cortex showed stronger discrimination of spaced- versus massed-trained reward values. Further, patterns in the striatum discriminated between spaced- and massed-trained stimuli overall. Our results indicate that single-session learning tasks engage partially distinct learning mechanisms from distributed training. Our studies begin to address a large gap in our knowledge of human learning from reinforcement, with potential implications for our understanding of mood disorders and addiction.SIGNIFICANCE STATEMENT Humans and animals learn to associate predictive value with stimuli and actions, and these values then guide future behavior. Such reinforcement-based learning often happens over long time periods, in contrast to most studies of reward-based learning in humans. In experiments that tested the effect of spacing on learning, we found that associations learned in a single massed session were correlated with short-term memory and significantly decayed over time, whereas associations learned in short massed sessions over weeks were well maintained. Additionally, patterns of activity in the medial temporal lobe and prefrontal cortex discriminated the values of stimuli learned over weeks but not minutes. These results highlight the importance of studying learning over time, with potential applications to drug addiction and psychiatry.

A dual-task approach to inform the taxonomy of inhibition-related processes.

Response inhibition is key to controlled behavior and is commonly investigated with the stop-signal paradigm. The authors investigated how response inhibition is situated within a taxonomy of control processes by combining multiple forms of control within dual tasks. Response inhibition, as measured by stop-signal reaction time (SSRT), was impaired when combined with shape matching, but not the flanker task, and when combined with cued task switching, but not predictable task switching, suggesting that response inhibition may be weakly or variably impaired when combined with selective attention and set shifting demands, respectively. Response inhibition was also consistently impaired when combined with the N-back or directed forgetting tasks, putative measures of working memory. Impairments of response inhibition by other control demands appeared to be primarily driven by task context, as SSRT slowing was similar for trials where control demands were either high (e.g., task switch) or low (e.g., task stay). These results demonstrate that response inhibition processes are often impaired in the context of other control demands, even on trials where direct engagement of those other control processes is not required. This suggests a taxonomy of control in which response inhibition overlaps with related control processes, especially working memory. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cognitive tasks, anatomical MRI, and functional MRI data evaluating the construct of self-regulation.

We describe the following shared data from N=103 healthy adults who completed a broad set cognitive tasks, surveys, and neuroimaging measurements to examine the construct of self-regulation. The neuroimaging acquisition involved task-based fMRI, resting fMRI, and structural MRI. Each subject completed the following ten tasks in the scanner across two 90-minute scanning sessions: attention network test (ANT), cued task switching, Columbia card task, dot pattern expectancy (DPX), delay discounting, simple and motor selective stop signal, Stroop, a towers task, and a set of survey questions. Subjects also completed resting state scans. The dataset is shared openly through the OpenNeuro project, and the dataset is formatted according to the Brain Imaging Data Structure (BIDS) standard.

Secondary Motor Cortex Transforms Spatial Information into Planned Action during Navigation.

Fluid navigation requires constant updating of planned movements to adapt to evolving obstacles and goals. For that reason, a neural substrate for navigation demands spatial and environmental information and the ability to effect actions through efferents. The secondary motor cortex (M2) is a prime candidate for this role given its interconnectivity with association cortices that encode spatial relationships and its projection to the primary motor cortex. Here, we report that M2 neurons robustly encode both planned and current left/right turning actions across multiple turn locations in a multi-route navigational task. Comparisons within a common statistical framework reveal that M2 neurons differentiate contextual factors, including environmental position, route, action sequence, orientation, and choice availability. Despite significant modulation by environmental factors, action planning, and execution are the dominant output signals of M2 neurons. These results identify the M2 as a structure integrating spatial information toward the updating of planned movements.