Biology subjects

Huberdeau, D. M.

Publications and source records attributed to Huberdeau, D. M..

4 recordsLinked to original sources

bioRxiv2023

Continuous motor skills as flexible control policies: a video game study

Many motor skills consist of continuous sequential actions, such as a tennis serve. It is currently unclear how these surprisingly understudied behaviors are learned, with the leading hypothesis being that sequences of single actions become "chunked" into larger single executable units. Under this hypothesis, continuous sequential actions should become more task-specific and less generalizable with practice. To test this, we developed a video game that requires participants to hold a tablet with both hands and steer a virtual car (the "ant car") along a curving track. We tested participants ability to generalize their skill to a probe track that required a different sequence of turns. Across days of practice, task success increased, and movement variability decreased. On the probe track, movement quality at the level of kinematics fully generalized but performance at the level of task success showed a consistent decrement. To address this apparent paradox, we empirically derived the control policy participants used at their maximal skill level on the training track. Notably, this policy was fully transferred to the probe track, but there were more instances of momentary deviations from it (lapses), which explains the worse performance despite equivalent skill. We conclude that continuous motor skills are acquired through learning of a flexible control policy that maps states onto actions and not through chunking or automatizing of a specific sequence of actions.

neuroscience↗

bioRxiv2023

Statistical learning in epilepsy: Behavioral, anatomical, and causal mechanisms in the human brain

Statistical learning, the fundamental cognitive ability of humans to extract regularities across experiences over time, engages the medial temporal lobe in the healthy brain. This leads to the hypothesis that statistical learning may be impaired in epilepsy patients, and that this impairment could contribute to their varied memory deficits. In turn, epilepsy patients provide a platform to advance basic understanding of statistical learning by helping to evaluate the necessity of medial temporal lobe circuitry through disease and causal perturbations. We implemented behavioral testing, volumetric analysis of the medial temporal lobe substructures, and direct electrical brain stimulation to examine statistical learning across a cohort of 61 epilepsy patients and 28 healthy controls. Behavioral performance in a statistical learning task was negatively associated with seizure frequency, irrespective of where seizures originated in the brain. The volume of hippocampal subfields CA1 and CA2/3 correlated with statistical learning performance, suggesting a more specific role of the hippocampus. Indeed, transient direct electrical stimulation of the hippocampus disrupted statistical learning. Furthermore, the relationship between statistical learning and seizure frequency was selective: behavioral performance in an episodic memory task was impacted by structural lesions in the medial temporal lobe and by antiseizure medications, but not by seizure frequency. Overall, these results suggest that statistical learning may be hippocampally dependent and that this task could serve as a clinically useful behavioral assay of seizure frequency distinct from existing neuropsychological tests. Simple and short statistical learning tasks may thus provide patient-centered endpoints for evaluating the efficacy of novel treatments in epilepsy.

neuroscience↗

bioRxiv2022

Temporal dynamics of competition between statistical learning and episodic memory in intracranial recordings of human visual cortex

The function of long-term memory is not just to reminisce about the past, but also to make predictions that help us behave appropriately and efficiently in the future. This predictive function of memory provides a new perspective on the classic question from memory research of why we remember some things but not others. If prediction is a key outcome of memory, then the extent to which an item generates a prediction signifies that this information already exists in memory and need not be encoded. We tested this principle using human intracranial EEG as a time-resolved method to quantify prediction in visual cortex during a statistical learning task and link the strength of these predictions to subsequent episodic memory behavior. Epilepsy patients of both sexes viewed rapid streams of scenes, some of which contained regularities that allowed the category of the next scene to be predicted. We verified that statistical learning occurred using neural frequency tagging and measured category prediction with multivariate pattern analysis. Although neural prediction was robust overall, this was driven entirely by items that were subsequently forgotten. Such interference provides a mechanism by which prediction can regulate memory formation to prioritize encoding of information that could help learn new predictive relationships. Significance StatementWhen faced with a new experience, we are rarely at a loss for what to do. Rather, because many aspects of the world are stable over time, we rely upon past experiences to generate expectations that guide behavior. Here we show that these expectations during a new experience come at the expense of memory for that experience. From intracranial recordings of visual cortex, we decoded what humans expected to see next in a series of photographs based on patterns of neural activity. Photographs that generated strong neural expectations were more likely to be forgotten in a later behavioral memory test. Prioritizing the storage of experiences that currently lead to weak expectations could help improve these expectations in future encounters.

neuroscience↗

bioRxiv2017

Practice induces a qualitative change in the memory representation for visuomotor learning

Adaptation of our movements to changes in the environment is known to be supported by multiple learning processes which act in parallel. An implicit process recalibrates motor output to maintain alignment between intended and observed movement outcomes (\"implicit recalibration\"). In parallel, an explicit learning process drives more strategic adjustments of behavior, often by deliberately aiming movements away from an intended target (\"deliberate re-aiming\"). It has long been established that people form a memory for prior experience adapting to a perturbation through the fact that they become able to more rapidly adapt to familiar perturbations (a phenomenon known as \"savings\"). Repeated exposures to the same perturbation can further strengthen savings. It remains unclear, however, which underlying learning process is responsible for this practice-related improvement in savings. We measured the relative contributions of implicit recalibration and deliberate re-aiming to adaptation during multiple exposures to an alternating sequence of perturbations over two days. We found that the implicit recalibration followed an invariant learning curve despite prolonged practice, and thus exhibited no memory of prior experience. Instead, practice led to a qualitative change in re-aiming which, in addition to supporting savings, became able to be expressed rapidly and automatically. This qualitative change appeared to enable participants to form memories for two opposing perturbations, overcoming interference effects that typically prohibit savings when learning multiple, opposing perturbations. Our results are consistent with longstanding theories that frame skill learning as a transition from deliberate to automatic selection of actions.

neuroscience↗