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Zohar Tal

dblp:180/7740 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0001-7430-3563ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 87% Health and well-being technologies · 13%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › social robot
perceived animacy
1.012026
Perceiving Animacy in Robots: A Neuroimaging Study · HRI 2026
Human-robot interaction
social robot
1.012026
Perceiving Animacy in Robots: A Neuroimaging Study · HRI 2026
Health and well-being technologies › medical technology
neuroimaging
0.312026
Perceiving Animacy in Robots: A Neuroimaging Study · HRI 2026

Methods — techniques the papers use, named apart from their topics

subjective ratings · 1.0functional magnetic resonance imaging · 1.0
YearPublicationVenuePosition
2026 Perceiving Animacy in Robots: A Neuroimaging Study
abstract
Animacy is central to HRI, as it is critical for perceptions of intentionality and influences acceptance, interaction quality, and trust. In order to better understand the underlying mechanisms of the sense of animacy and its role in HRI, we conducted an experiment (n=13) using a social robotic object that is ambiguous with respect to its perceived animacy. We examined how brain activity related to a subjective animacy rating of the robot by participants after watching it perform simple gestures. Using functional imaging, we found that the ventral occipitotemporal (VOT) cortex, a region known to distinguish animate from inanimate entities, also responds to robots along this same organizational gradient. In an exploratory analysis, activity in the left VOT was associated with the individual differences in participants’ subjective animacy rating of the robot. This extends established principles of animacy perception to non-humanoid robots and suggests that individual differences in brain responses may shape how robots are experienced. We discuss implications for HRI, including guiding social cue design, informing gesture alignment with robot roles, and raising ethical considerations around attachment and trust.
Or Yizhar, Amber Maimon, Zohar Tal, Iddo Wald, Hadas Erel, Doron Friedman, Oren Zuckerman, Amir Amedi
HRI3