Challenging Paradigms Through Ecological Neuroscience: Lessons From Visual Models

Bucci-Mansilla, Giuliana; Vicencio-Jimenez, Sergio; Concha-Miranda, Miguel; Loyola-Navarro, Rocio

doi:10.3389/fnins.2021.758388

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…One should rather be guided by the research objective when designing the VR. A sensible design can at times mean reduction and simplification, without losing ecological validity (Bucci-Mansilla et al, 2021 ). Related to this is the uncanny valley phenomenon, in which high realism of an artificial stimulus makes observers feel uneasy (Chouinard-Thuly et al, 2017 ; LaValle, 2020 ).…”

Section: Limitations and Potentials For Naturalistic Vrmentioning

confidence: 99%

Naturalistic neuroscience and virtual reality

Thurley

2022

Front. Syst. Neurosci.

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Virtual reality (VR) is one of the techniques that became particularly popular in neuroscience over the past few decades. VR experiments feature a closed-loop between sensory stimulation and behavior. Participants interact with the stimuli and not just passively perceive them. Several senses can be stimulated at once, large-scale environments can be simulated as well as social interactions. All of this makes VR experiences more natural than those in traditional lab paradigms. Compared to the situation in field research, a VR simulation is highly controllable and reproducible, as required of a laboratory technique used in the search for neural correlates of perception and behavior. VR is therefore considered a middle ground between ecological validity and experimental control. In this review, I explore the potential of VR in eliciting naturalistic perception and behavior in humans and non-human animals. In this context, I give an overview of recent virtual reality approaches used in neuroscientific research.

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Section: Limitations and Potentials For Naturalistic Vrmentioning

confidence: 99%

Naturalistic neuroscience and virtual reality

Thurley

2022

Front. Syst. Neurosci.

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“…In psychology and neuroscience studies, various types of visual stimuli are used to evaluate behavioral and neural responses. These materials can include images, videos, drawings created by professionals or designed through artificial intelligence (AI), virtual reality, and other purpose-built visual materials that can be compiled from online sources (Parsons, 2015; Bucci Mansilla et al, 2021; Gobet et al, 2019). While creating these stimuli, not only the generation techniques but also the content and context of the materials are of great importance.…”

Section: Introductionmentioning

confidence: 99%

A database of digital line drawings that depict expected and unexpected action-place relationships

Aydemir,

Umul,

Urgen

2024

Preprint

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In the present study, we introduce an image database created with a simple digital line-drawing tool to represent the expected and unexpected action-place relationships. This database consists of 70 drawings. We validated the dataset with 207 participants. They evaluated the actions, places, and the probability of an action taking place in the respective location. The comprehensibility of each drawing was evaluated using three measures: H-statistics (entropy), which is a measure of the uncertainty of the definition; the definition similarity percentages which is a measure of the naming agreement that is consistent among participants; and the mean probability of the depicted action taking place in the depicted location. Each drawing includes different agents and environments, providing researchers with the opportunity to use this dataset in various fields of cognitive neuroscience, including visual recognition, memory, predictive coding, and novelty detection.

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Challenging Paradigms Through Ecological Neuroscience: Lessons From Visual Models

Cited by 2 publications

References 33 publications

Naturalistic neuroscience and virtual reality

Naturalistic neuroscience and virtual reality

A database of digital line drawings that depict expected and unexpected action-place relationships

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