Biology subjects

Eluchans, M.

Publications and source records attributed to Eluchans, M..

4 recordsLinked to original sources

bioRxiv2024

Separable cognitive and motor decline tracked across adult life-span for goal-directed navigation

Spatial navigation is a fundamental cognitive skill, yet our understanding of the strategies people employ in real-world navigation remains incomplete. This study investigates navigation strategies using data from the large-scale Sea Hero Quest (SHQ) game, in which participants face navigational problems consisting in controlling a boat to reach a series of goal locations, within maps having different shapes. By using a combination of behavioral and computational modeling approaches, we report three key findings: First, participants predominantly use goal-directed strategies compared to visibility-based strategies. Second, participants show signatures of sequential planning, both during memorization - as they spend more time looking at difficult levels - and during navigation - as they show primacy effects, suggesting that they remember better the first navigational goal. Third, our results show a significant age-related decline in navigation performance, which depends both on reduced motor skill - as indexed by poorer control of the boat - and decreased cognitive strategy - as indexed by a loss of goal-directedness during spatial navigation. Unexpectedly, the loss of goal-directedness with age is not associated with a shift to visibility-based strategy or to an incorrect sequencing of goals. Taken together, our findings offer a nuanced understanding of spatial navigation strategies in naturalistic conditions and their decline with age. Our computational approach permits distinguishing motoric and cognitive variables, showing that both decline with age. These results align with and extent previous research on spatial memory decline with age, including potential links to neurodegenerative diseases like Alzheimers. The computational models developed in this study provide a robust framework for analyzing navigation strategies, applicable to other virtual environments and video games.

animal behavior and cognition↗

bioRxiv2024

Eye and hand coarticulation during problem solving reveals hierarchically organized planning

During everyday activities--such as preparing a cup of coffee or traveling across cities--we often plan ahead and execute sequences of actions. However, much remains to be understood about how we plan and coordinate such sequences (e.g., eye and hand movements) to solve novel and challenging tasks, for which plans must be formed from scratch. This study investigates how participants coordinate gaze and cursor movements during problem solving tasks that involve selecting a trajectory on a grid connecting multiple targets. By focusing on the action execution phase, we aimed to probe the structure of the gaze-cursor plans that participants used to solve the tasks. Our analysis reveals three main findings. First, consistent with previous studies, participants segment the problem into sequences of gestures; within each gesture, gaze focuses on a target and remains fixed until the cursor reaches it, then shifts to the next target. Second, both gaze position--while fixating on the current target--and the kinematics of cursor movement leading up to the current target allow prediction of the next cursor movements direction, revealing coarticulation in both cursor-cursor and gaze-cursor movements. Third, and most interestingly, the position of the gaze around the current target aligns with the direction of the next saccade, revealing coarticulation between successive gaze fixations. Together, these findings show that participants break the problem into gesture sequences and plan multiple eye and cursor movements in advance to efficiently reach both the current and upcoming gesture targets. This suggests a hierarchical planning strategy, with participants planning ahead at two levels: gesture targets and cursor movements.

animal behavior and cognition↗

bioRxiv2023

Adaptive planning depth in human problem solving

We humans are capable of solving challenging planning problems, but the range of adaptive strategies that we use to address them are not yet fully characterized. Here, we designed a series of problem-solving tasks that require planning at different depths. After systematically comparing the performance of participants and planning models, we found that when facing problems that require planning to a certain number of subgoals (from 1 to 8), participants make an adaptive use of their cognitive resources - namely, they tend to select an initial plan having the minimum required depth, rather than selecting the same depth for all problems. These results support the view of problem solving as a bounded rational process, which adapts costly cognitive resources to task demands.

neuroscience↗

bioRxiv2022

Humans account for cognitive costs when finding shortcuts: An information-theoretic analysis of navigation

When faced with navigating back somewhere we have been before we might either retrace our steps or seek a shorter path. Both choices have costs. Here, we ask whether it is possible to characterize formally the choice of navigational plans as a bounded rational process that trades off the quality of the plan (e.g., its length) and the cognitive cost required to find and implement it. We analyze the navigation strategies of two groups of people that are firstly trained to follow a "default policy" taking a route in a virtual maze and then asked to navigate to various known goal destinations, either in the way they want ("Go To Goal") or by taking novel shortcuts ("Take Shortcut"). We address these wayfinding problems using InfoRL: an information-theoretic approach that formalizes the cognitive cost of devising a navigational plan, as the informational cost to deviate from a well-learned route (the "default policy"). In InfoRL, optimality refers to finding the best trade-off between route length and the amount of control information required to find it. We report five main findings. First, the navigational strategies automatically identified by InfoRL correspond closely to different routes (optimal or suboptimal) in the virtual reality map, which were annotated by hand in previous research. Second, people deliberate more in places where the value of investing cognitive resources (i.e., relevant goal information) is greater. Third, compared to the group of people who receive the "Go To Goal" instruction, those who receive the "Take Shortcut" instruction find shorter but less optimal solutions, reflecting the intrinsic difficulty of finding optimal shortcuts. Fourth, those who receive the "Go To Goal" instruction modulate flexibly their cognitive resources, depending on the benefits of finding the shortcut. Finally, we found a surprising amount of variability in the choice of navigational strategies and resource investment across participants. Taken together, these results illustrate the benefits of using InfoRL to address navigational planning problems from a bounded rational perspective.

animal behavior and cognition↗