Question 1

Interaction between climate change and human behavior | Alon Itzkovitch

Accepted Answer

In this project, we aim to study how climate change affects human behavior (e.g., risk-taking, decision-making) across a climatic gradient in a long-term study. We aim to combine brain, VR, and "real-world" approaches to study how long-term climate conditions and extreme climatic events affect human behavior. Furthermore, we aim to sample participants from distinct regions in Israel to obtain a climatic gradient.

Question 2

A longitudinal study comparing functional connectivity changes in non-reinforced learning  | Alon Itzkovitch

Accepted Answer

In this project, participants underwent two distinct non-reinforced learning procedures while scanned with fMRI. Our goal is to study the differences and similarities between the two groups regarding brain network functional connectivity. Participants were scanned five times during one year, enabling us to study underlying neural mechanisms of the sustainability of non-reinforced behavioral change.

Question 3

Studying automatic behavior in humans | Maya Bar Or

Accepted Answer

This research focuses on automatic behavior in different environments. I developed experimental paradigms to test how action tendencies are learned and how they respond to changes in context, rules, or outcomes. My work examines both adaptive forms of automaticity, where efficient responding supports performance, and maladaptive forms, where previously learned responses persist despite new goals or altered contingencies. Using virtual reality and laboratory-based behavioral methods, I aim to refine behavioral measures of automaticity and to identify the task and environmental factors that promote flexibility versus rigidity in learned behavior.

Question 4

Linking  stress scores measured by wearables and decision-making | Hadar Rosenbach

Accepted Answer

In my project I am testing the link between different measures obtained by wearable sensors (sleep, stress etc') and value-based decision-making in the field. At the moment I am testing the accuracy of the stress level score measured by a wrist-worn heart rate monitor – the Garmin vivosmart4 - under stress and relaxed conditions. We are measuring heart rate variability (HRV) using a Polar chest strap in order to detect a stress response in a laboratory setting and compare it with the stress score given by the smartwatch.
Our goal is to validate the Garmin smartwatch for stress detecting and use it for remote data collection in ecological and longitudinal studies to investigate the relationship between decision-making and physiological indices.

Question 5

Patterns of noradrenergic response as a reaction to surprise | Masha Khlopovsky

Accepted Answer

My project is located at the intersection of neurobiology and linguistics. The aim of the project is to measure and detect the noradrenergic response as a reaction to a surprising event which the participants run into while auditioning a sentence. The study incorporates pupillometry in order to establish the visual sign of the response which is pupil dilation. The pattern of pupil dilation in healthy adults will represent a sample, which potentially can be used in diagnosis of the abnormalities where the noradrenergic response is damaged.

Question 6

Predicting subjective preferences in humans by their physiological movements | Eden Ishakov

Accepted Answer

In this project, we aim to study whether physiological movements in humans can predict their subjective preferences. The goal of this study is to see whether active or passive movements can indicate an individual’s subjective preference of pictures shown in a VR environment setup. By using 3 of the tracking devices useable in the VR headset (eye tracking, face tracking and hand tracking), we want to see how by swiping right (if they like the picture) or left (if they don’t), or just observing the pictures passively, one’s movements can predict what will one prefer.

Question 7

VR Museum | Yana Sklyar

Accepted Answer

This study explores the potential of virtual reality (VR) to revolutionize museum experiences by offering personalized, interactive tours that cater to individual visitor preferences. By employing a novel VR application allowing participants to freely navigate a virtual museum space, the research examines the impact of active decision-making on visitor satisfaction. Participants are divided into three groups to compare satisfaction levels based on varying degrees of choice during the tour. Utilizing the Mizne-Blumenthal collection, participants select art features, with the chosen artworks and their sequence remaining consistent across groups to ensure structural validity. Physiological measures, such as facial expressions and eye movements, along with behavioral and satisfaction questionnaires, provide comprehensive data. This approach combines data science with cultural heritage to enhance engagement, optimize museum visits, and address accessibility challenges, ultimately contributing to museums' missions of interpretation and preservation in the digital age.

Question 8

Attention, memory, and preference changes in Cue Approach Training (CAT) | Adi Cantor

Accepted Answer

The research focuses on investigating the underlying mechanisms of Cue Approach Training (CAT), particularly how attention and memory influence preference changes.

Question 9

ArTour – A Naturalistic Study of Museum Decision-Making | Yahli Ranen

Accepted Answer

ArTour is a browser-based museum guidance and research system that provides real-time, on-the-spot personalized navigation in physical exhibition spaces. It enables the study of naturalistic decision-making by linking visitors’ moment-to-moment choices to spatial and curatorial structure.

Question 10

Sudden Insight and the "Aha!" Moment in Spatial Problem-Solving | Yehuda Bergstein

Accepted Answer

This project investigates the relationship between the cognitive phenomenon of "sudden insight" and the subjective "Aha!" experience within the domain of spatial navigation, an area less explored compared to traditional verbal tasks. Building on a successful pilot study utilizing a novel Virtual Reality (VR) maze paradigm, the research aims to elicit and objectively measure how these sudden realizations manifest during spatial problem-solving. Our initial findings indicated a strong link between the self-reported feeling of an "Aha!" moment and immediate, objective improvements in navigation efficiency. We are currently conducting a rigorous, pre-registered (OSF) replication of this work to validate these patterns with expanded analysis. By integrating human introspection with objective behavioral metrics, this work establishes a framework for future cross-species comparisons, aiming to uncover the fundamental mechanisms of how insight drives learning.

Question 11

Multisensory value-based decision making | Yonatan Pappe

Accepted Answer

In this study, we examine how learned values of unisensory stimuli are integrated during multisensory decision making. Participants learn the value of visual, auditory, and somatosensory stimuli and then evaluate multisensory combinations of these cues. We aim to explore the relative contribution of each modality, the effect of value conflict across modalities on decision difficulty and whether participants evaluate multisensory combinations as the sum of their individual components.

Research

What We Do

Current Projects: