Beyond the matrix: Experimental approaches to studying cognitive agents in social-ecological systems.

Studying social-ecological systems, in which agents interact with each other and their environment are important both for sustainability applications and for understanding how human cognition functions in context. In such systems, the environment shapes the agents' experience and actions, and in turn collective action of agents changes social and physical aspects of the environment. Here we review current investigation approaches, which rely on a lean design, with discrete actions and outcomes and little scope for varying environmental parameters and cognitive demands.

AI can help humans find common ground in democratic deliberation.

Finding agreement through a free exchange of views is often difficult. Collective deliberation can be slow, difficult to scale, and unequally attentive to different voices. In this study, we trained an artificial intelligence (AI) to mediate human deliberation.

The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults - a multicentric cross-sectional study.

Background: The decline in everyday life physical activity reflects and contributes to the frailty syndrome. While especially self-reported frailty assessments have the advantage of reaching large groups at low costs, little is known about the relationship between the self-report and objective measured daily physical activity behavior. The main objective was to evaluate whether and to what extent a self-reported assessment of frailty is associated with daily physical activity patterns.

What is the simplest model that can account for high-fidelity imitation?

What inductive biases must be incorporated into multi-agent artificial intelligence models to get them to capture high-fidelity imitation? We think very little is needed. In the right environments, both instrumental- and ritual-stance imitation can emerge from generic learning mechanisms operating on non-deliberative decision architectures. In this view, imitation emerges from trial-and-error learning and does not require explicit deliberation.

Human-centred mechanism design with Democratic AI.

Building artificial intelligence (AI) that aligns with human values is an unsolved problem. Here we developed a human-in-the-loop research pipeline called Democratic AI, in which reinforcement learning is used to design a social mechanism that humans prefer by majority. A large group of humans played an online investment game that involved deciding whether to keep a monetary endowment or to share it with others for collective benefit.

Spurious normativity enhances learning of compliance and enforcement behavior in artificial agents.

How do societies learn and maintain social norms? Here we use multiagent reinforcement learning to investigate the learning dynamics of enforcement and compliance behaviors. Artificial agents populate a foraging environment and need to learn to avoid a poisonous berry. Agents learn to avoid eating poisonous berries better when doing so is taboo, meaning the behavior is punished by other agents.

What can classic Atari video games tell us about the human brain?

In this issue of Neuron, Cross et. al (2021) use a deep reinforcement learning algorithm to understand human neural activation evoked by playing different video games. The results shed light on the neural principles underlying reward-guided decisions in naturalistic domains.

Human hippocampal theta oscillations reflect sequential dependencies during spatial planning.

Movement-related theta oscillations in rodent hippocampus coordinate 'forward sweeps' of location-specific neural activity that could be used to evaluate spatial trajectories online. This raises the possibility that increases in human hippocampal theta power accompany the evaluation of upcoming spatial choices. To test this hypothesis, we measured neural oscillations during a spatial planning task that closely resembles a perceptual decision-making paradigm.

Big-Loop Recurrence within the Hippocampal System Supports Integration of Information across Episodes.

Recent evidence challenges the widely held view that the hippocampus is specialized for episodic memory, by demonstrating that it also underpins the integration of information across experiences. Contemporary computational theories propose that these two contrasting functions can be accomplished by big-loop recurrence, whereby the output of the system is recirculated back into the hippocampus. We use ultra-high-resolution fMRI to provide support for this hypothesis, by showing that retrieved information is presented as a new input on the superficial entorhinal cortex-driven by functional connectivity between the deep and superficial entorhinal layers.

The Neural Representation of Prospective Choice during Spatial Planning and Decisions.

We are remarkably adept at inferring the consequences of our actions, yet the neuronal mechanisms that allow us to plan a sequence of novel choices remain unclear. We used functional magnetic resonance imaging (fMRI) to investigate how the human brain plans the shortest path to a goal in novel mazes with one (shallow maze) or two (deep maze) choice points. We observed two distinct anterior prefrontal responses to demanding choices at the second choice point: one in rostrodorsal medial prefrontal cortex (rd-mPFC)/superior frontal gyrus (SFG) that was also sensitive to (deactivated by) demanding initial choices and another in lateral frontopolar cortex (lFPC), which was only engaged by demanding choices at the second choice point.

Selective perturbation of cognitive conflict in the human brain-A combined fMRI and rTMS study.

We investigated if single and double conflicts are processed separately in different brain regions and if they are differentially vulnerable to TMS perturbation. Fifteen human volunteers performed a single (Flanker or Simon) conflict task or a double (Flanker and Simon) conflict task in a combined functional Magnetic Resonance Imaging (fMRI) and Transcranial Magnetic Stimulation (TMS) study. The fMRI approach aimed at localizing brain regions involved in interference resolution induced by single Flanker (stimulus-stimulus, S-S) and Simon (stimulus-response, S-R) conflicts as well as regions involved in the double conflict condition.

Retrieval-Based Model Accounts for Striking Profile of Episodic Memory and Generalization.

A fundamental theoretical tension exists between the role of the hippocampus in generalizing across a set of related episodes, and in supporting memory for individual episodes. Whilst the former requires an appreciation of the commonalities across episodes, the latter emphasizes the representation of the specifics of individual experiences. We developed a novel version of the hippocampal-dependent paired associate inference (PAI) paradigm, which afforded us the unique opportunity to investigate the relationship between episodic memory and generalization in parallel.

Stimulus Novelty Energizes Actions in the Absence of Explicit Reward.

Novelty seeking has been tied to impulsive choice and biased value based choice. It has been postulated that novel stimuli should trigger more vigorous approach and exploration. However, it is unclear whether stimulus novelty can enhance simple motor actions in the absence of explicit reward, a necessary condition for energizing approach and exploration in an entirely unfamiliar situation.

Context-specific activation of hippocampus and SN/VTA by reward is related to enhanced long-term memory for embedded objects.

Animal studies indicate that hippocampal representations of environmental context modulate reward-related processing in the substantia nigra and ventral tegmental area (SN/VTA), a major origin of dopamine in the brain. Using functional magnetic resonance imaging (fMRI) in humans, we investigated the neural specificity of context-reward associations under conditions where the presence of perceptually similar neutral contexts imposed high demands on a putative hippocampal function, pattern separation. The design also allowed us to investigate how contextual reward enhances long-term memory for embedded neutral objects.

Basal Ganglia Activity Mirrors a Benefit of Action and Reward on Long-Lasting Event Memory.

The expectation of reward is known to enhance a consolidation of long-term memory for events. We tested whether this effect is driven by positive valence or action requirements tied to expected reward. Using a functional magnetic resonance imaging (fMRI) paradigm in young adults, novel images predicted gain or loss outcomes, which in turn were either obtained or avoided by action or inaction.

How beliefs about self-creation inflate value in the human brain.

Humans have a tendency to overvalue their own ideas and creations. Understanding how these errors in judgement emerge is important for explaining suboptimal decisions, as when individuals and groups choose self-created alternatives over superior or equal ones. We show that such overvaluation is a reconstructive process that emerges when participants believe they have created an item, regardless of whether this belief is true or false.

Action and valence modulate choice and choice-induced preference change.

Choices are not only communicated via explicit actions but also passively through inaction. In this study we investigated how active or passive choice impacts upon the choice process itself as well as a preference change induced by choice. Subjects were tasked to select a preference for unfamiliar photographs by action or inaction, before and after they gave valuation ratings for all photographs.

Is choice-induced preference change long lasting?

The idea that decisions alter preferences has had a considerable influence on the field of psychology and underpins cognitive dissonance theory. Yet it is unknown whether choice-induced changes in preferences are long lasting or are transient manifestations seen in the immediate aftermath of decisions. In the research reported here, we investigated whether these changes in preferences are fleeting or stable.