Keep it real: rethinking the primacy of experimental control in cognitive neuroscience

Nastase, Samuel A.; Goldstein, Ariel; Hasson, Uri

doi:10.1016/j.neuroimage.2020.117254

Cited by 239 publications

(168 citation statements)

References 116 publications

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“…In recent years, the quest for increasing the ecology of how cognition and its neurobiological foundations are investigated has surged (Spiers & Maguire, 2007). Within this trend, the use of naturalistic audiovisual stimuli like movies has rapidly increased, due to their inherent visual complexity, dynamicity, and affective potential which make movies an ideal probe to investigate multiple cognitive domains while avoiding the artificiality that usually characterizes experimental paradigms in cognitive neuroscience (Hasson & Honey, 2012; Nastase, Goldstein, & Hasson, 2020). Indeed, it is very common to investigate cognitive and emotional processes using very simple stimuli, which are easier to control (in terms of their physical and perceptual properties).…”

Section: Introductionmentioning

confidence: 99%

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Spectrally resolved EEG intersubject correlation reveals distinct cortical oscillatory patterns during free‐viewing of affective scenes

Maffei

2020

Psychophysiology

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In recent years, the quest for increasing the ecology of how cognition and its neurobiological foundations are investigated has surged (Spiers & Maguire, 2007). Within this trend, the use of naturalistic audiovisual stimuli like movies has rapidly increased, due to their inherent visual complexity, dynamicity, and affective potential which make movies an ideal probe to investigate multiple cognitive domains while avoiding the artificiality that usually characterizes experimental paradigms in cognitive neuroscience (Hasson & Honey, 2012; Nastase, Goldstein, & Hasson, 2020). Indeed, it is very common to

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Section: Introductionmentioning

confidence: 99%

“…Indeed, it is very common to investigate cognitive and emotional processes using very simple stimuli, which are easier to control (in terms of their physical and perceptual properties). However, they often represent an over‐simplification of what the brain has to process in real‐life (Hasson & Honey, 2012; Nastase et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Spectrally resolved EEG intersubject correlation reveals distinct cortical oscillatory patterns during free‐viewing of affective scenes

Maffei

2020

Psychophysiology

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“…Recently, there has been increasing interest in using naturalistic stimuli such as movies or audio narratives in psychological experiments, to complement results from traditional experiments using simple and well-controlled stimuli (Nastase et al, 2020; Sonkusare et al, 2019). These experiments have the potential to shed light on when encoding and retrieval take place during event perception in a naturalistic context, where no one is explicitly instructing participants about how to use episodic memory.…”

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confidence: 99%

When to retrieve and encode episodic memories: a neural network model of hippocampal-cortical interaction

Hasson

Norman

2020

Preprint

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When should episodic memories be stored and retrieved to support event understanding? Traditional list-learning memory experiments make it obvious when to store and retrieve memories, but it is less obvious when to do this in naturalistic settings. To address this question, we trained a memory-augmented neural network to predict upcoming events, in an environment where situations (sets of parameters governing transitions between events) sometimes reoccurred. The model was allowed to learn a policy for when to consult episodic memory, and we explored how this learned policy varied as a function of the task environment. We found that the learned retrieval policy is shaped by internal uncertainty about upcoming events, the level of penalty associated with incorrect predictions, the confusability of stored memories, the presence of a “familiarity signal” indicating the availability of relevant memories, and the presence of statistical regularities (prototypical events). With regard to encoding policy, we found that selectively storing episodic memories at the end of an event (but not mid-event) leads to better subsequent event prediction performance and less incorrect recall. Additionally, we found that the model can integrate information over long timescales even without the hippocampus; it can link information over many event segments via episodic memory; and it shows classic schema-consistent memory effects when the upcoming time point has a prototypical event. Overall, these modeling results provide a normative explanation of several existing behavioral and neuroimaging findings regarding the use of episodic memory in naturalistic settings, and lead to a wide range of testable predictions.

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“…We showed the feasibility of conducting a human-robot interaction study while measuring EEG from the human participant. With full experimental control, we explored neural correlations of human-robot interactions in an ecologically valid setup (29,51). There is vast literature on the topic of joint actions between humans and robot partners (52,53).…”

Section: Discussionmentioning

confidence: 99%

Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing

Czeszumski

Keshava

König

2021

Preprint

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Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adopted a collaborative dynamical paradigm from Hwang et al. (2018). All 16 participants held two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. To explore the temporal and spatial differences in the two conditions, we used time-regression with overlap-control and corrected for multiple-comparisons using Threshold-Free-Cluster Enhancement. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions withother humans.

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Keep it real: rethinking the primacy of experimental control in cognitive neuroscience

Cited by 239 publications

References 116 publications

Spectrally resolved EEG intersubject correlation reveals distinct cortical oscillatory patterns during free‐viewing of affective scenes

Spectrally resolved EEG intersubject correlation reveals distinct cortical oscillatory patterns during free‐viewing of affective scenes

When to retrieve and encode episodic memories: a neural network model of hippocampal-cortical interaction

Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing

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