Biology subjects

Bakkour, A.

Publications and source records attributed to Bakkour, A..

8 recordsLinked to original sources

bioRxiv2026

Older Adults Forage Broadly for Information Despite Cost

Healthy aging has long been associated with impairments in learning from rewards. However, typical paradigms do not adequately distinguish between being motivated by information to learn about the world and being motivated by rewarding outcomes from our decisions. The present study describes how these distinct motivations guide learning about the environment across the lifespan. Participants (N=169; ages 18-71 [M=39, SD=15.4]) completed a task based on the board game Battleship, making sequential choices about which tile to uncover on a grid with the goal of finding and learning hidden shapes. While older adults performed worse on the task in terms of overall score, their search behavior stabilized earlier. Older adults also preferred to seek information over reward, spreading their choices more widely, making more choices per trial, and acquiring more information per trial. Additionally, older adults showed a persistent reliance on information gained from the outcomes of their choices. These findings suggest that, as individuals age, they prefer to seek information, which earns them fewer points and slows learning but incurs no cost to long-run projected performance. Despite the conventional view linking age with diminished learning, in a complex environment that disentangled information and reward, older adults remained engaged with no projected learning deficits. Our findings challenge assumptions about cognitive decline in aging and reframe information seeking in older adults as a persistent motivational preference that need not serve learning, raising the question of why the drive to seek information intensifies with age even when it confers no advantage.

animal behavior and cognition↗

bioRxiv2025

Overcoming distortion in multidimensional predictive representation

Predicting how our actions will affect future events is essential for effective behavior. However, learning predictive relationships is not trivial in a multidimensional world where numerous causes bring any one event about. Here we examine (1) how these multidimensional dynamics may distort predictive learning, and (2) how inductive biases may mitigate these harmful effects. We developed a theoretical framework for studying this problem using a computational successor features model. Model simulations demonstrate how spurious observations arise in such contexts to compound noise in memory and limit the generalizability of learning. We then provide behavioral evidence in human participants for a semantic inductive bias that constrains these predictive learning dynamics based on the semantic relatedness of causes and outcomes. Together, these results show that prior knowledge can shape multidimensional predictive learning, potentially minimizing severe memory distortions that may arise from complex everyday observations.

animal behavior and cognition↗

bioRxiv2024

Value construction through sequential sampling explains serial dependencies in decision making

Many decisions are expressed as a preference for one item over another. When these items are familiar, it is often assumed that the decision maker assigns a value to each of the items and chooses the item with the highest value. These values may be imperfectly recalled, but are assumed to be stable over the course of an interview or psychological experiment. Choices that are inconsistent with a stated valuation are thought to occur because of unspecified noise that corrupts the neural representation of value. Assuming that the noise is uncorrelated over time, the pattern of choices and response times in value-based decisions are modeled within the framework of Bounded Evidence Accumulation (BEA), similar to that used in perceptual decision-making. In BEA, noisy evidence samples accumulate over time until the accumulated evidence for one of the options reaches a threshold. Here, we argue that the assumption of temporally uncorrelated noise, while reasonable for perceptual decisions, is not reasonable for value-based decisions. Subjective values depend on the internal state of the decision maker, including their desires, needs, priorities, attentional state, and goals. These internal states may change over time, or undergo revaluation, as will the subjective values. We reasoned that these hypothetical value changes should be detectable in the pattern of choices made over a sequence of decisions. We reanalyzed data from a well-studied task in which participants were presented with pairs of snacks and asked to choose the one they preferred. Using a novel algorithm (Reval), we show that the subjective value of the items changes significantly during a short experimental session (about 1 hour). Values derived with Reval explain choice and response time better than explicitly stated values. They also better explain the BOLD signal in the ventromedial prefrontal cortex, known to represent the value of decision alternatives. Revaluation is also observed in a BEA model in which successive evidence samples are not assumed to be independent. We argue that revaluation is a consequence of the process by which values are constructed during deliberation to resolve preference choices.

neuroscience↗

bioRxiv2021

Signatures of visuospatial information foraging during learning of complex environments

In the real world, making sequences of decisions to achieve goals often depends upon the ability to learn aspects of the environment that are not directly perceptible. Learning these so-called latent features requires seeking information about them, a process distinct from learning about near-term reward contingencies. Prior efforts to study latent feature learning often use single decisions, use few features, and fail to distinguish between reward-seeking and informationseeking. To overcome this, we designed a task in which humans and monkeys made a series of choices to search for shapes hidden on a grid. Reward and information outcomes from uncovering parts of shapes were not perfectly correlated and their effects could be disentangled. Members of both species adeptly learned the shapes and preferred to select informative tiles earlier in trials than rewarding ones, searching a part of the grid until their outcomes dropped below the average information outcome-a pattern consistent with foraging behavior. In addition, how quickly humans learned the shapes was predicted by how well their choice sequences matched the foraging pattern. This adaptive search for information may underlie the ability in humans and monkeys to learn latent features to support goal-directed behavior in the long run.

animal behavior and cognition↗

bioRxiv2021

Neural Representations of Food-Related Attributes in the Human Orbitofrontal Cortex in Health and Disease

Decisions about what to eat recruit the orbitofrontal cortex (OFC) and involve the evaluation of food-related attributes, such as taste and health. These attributes are utilized differently by healthy individuals and patients with disordered eating behavior, but it is unclear whether these attributes are decodable from activity in the OFC in both groups and whether neural representations of these attributes are differentially related to decisions about food. We used fMRI combined with behavioral tasks to investigate the representation of taste and health attributes in the human OFC and the role of these representations in food choices in healthy individuals and patients with anorexia nervosa (AN). We found that subjective ratings of tastiness and healthiness could be decoded from patterns of activity in the OFC in both groups. However, health-related patterns of activity in the OFC were more related to the magnitude of choice preferences among patients with AN than healthy individuals. These findings suggest that maladaptive decision-making in AN is associated with more consideration of health information represented by the OFC during deliberation about what to eat. Significance StatementAn open question about the orbitofrontal cortex (OFC) is whether it supports the evaluation of food-related attributes during deliberation about what to eat. We found that healthiness and tastiness information were decodable from patterns of neural activity in the OFC in both patients with anorexia nervosa (AN) and healthy controls. Critically, neural representations of health were more strongly related to choices in patients with AN, suggesting that maladaptive overconsideration of healthiness during deliberation about what to eat is related to activity in the OFC. More broadly, these results show that activity in the human OFC is associated with the evaluation of relevant attributes during value-based decision-making. These findings may also guide future research into the development of treatments for AN.

neuroscience↗

bioRxiv2019

Memory for Individual Items is Related to Non-Reinforced Preference Change

It is commonly assumed that memories contribute to value-based decisions. Nevertheless, most theories of value-based decision-making do not account for memory influences on choice. Recently, new interest has emerged in the interactions between these two fundamental processes, mainly using reinforcement-based paradigms. Here, we aimed to study the role memory processes play in preference change following the non-reinforced cue-approach training (CAT) paradigm. In CAT, the mere association of cued items with a speeded motor response influences choices. Previous studies with this paradigm showed that a single training session induces a long-lasting effect of enhanced preferences for high-value trained stimuli, that is maintained for several months. We hypothesized that CAT influences memory accessibility for trained items, leading to enhanced accessibility of their positive associative memories and in turn to preference changes. In two pre-registered experiments, we tested whether memory for trained items was enhanced following CAT, in the short and in the long-term, and whether memory modifications were related to choices. We found that memory was enhanced for trained items and that better memory was correlated with enhanced preferences at the individual item level, both immediately and one month following CAT. Our findings show that memory plays a central role in value-based decision-making following CAT, even in the absence of external reinforcements. These findings contribute to new theories relating memory and value-based decision-making and set the groundwork for the implementation of novel behavioral interventions that lead to long-lasting behavioral change.

neuroscience↗

bioRxiv2018

Value-based decisions involve sequential sampling from memory

Deciding between two equally appealing options can take considerable time. This observation has puzzled economists and philosophers, because more deliberation only delays the reward. Here we show that this seemingly irrational behavior is explained by the constructive use of memory. Using functional brain imaging in humans, we show that how long it takes to decide between two familiar food items is related to activity in the hippocampus, within specific regions shown to be associated with the retrieval of long-term memories. Moreover, we show that value is partially constructed during deliberation to resolve preference, and this constructive process changes behavior and brain responses. These results render memory as a supplier of evidence in value-based decisions, resolving a central paradox of choice.

animal behavior and cognition↗

bioRxiv2018

Spacing of Cue-approach Training Leads to Better Maintenance of Behavioral Change

The maintenance of behavioral change over the long term is essential to achieve public health goals such as combatting obesity and drug use. Previous work by our group has demonstrated a reliable shift in preferences for appetitive foods following a novel non-reinforced training paradigm. In the current studies, we tested whether distributing training trials over two consecutive days would affect preferences immediately after training as well as over time at a one-month follow-up. In four studies, three different designs and an additional pre-registered replication of one sample, we found that spacing of cue-approach training induced a shift in food choice preferences over one month. The spacing and massing schedule employed governed the long-term changes in choice behavior. Applying spacing strategies to training paradigms that target automatic processes could prove a useful tool for the long-term maintenance of health improvement goals with the development of real-world behavioral change paradigms that incorporate distributed practice principles.

animal behavior and cognition↗