ReviewNeuron2021
Promises and challenges of human computational ethology.
Review in Neuron, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed.
- Positive affect treatment targets reward sensitivity: A randomized controlled trial.Journal of consulting and clinical psychology · 2023Trial
- Towards Human-Centered Digital Health Interventions.The Psychiatric clinics of North America · 2026Review
- The Spatial Similarity Task: A cross-species approach to spatial memory.Behavior research methods · 2026Article
- Rethinking Ethics for an Era of Trusted Computational Tools.The Psychiatric clinics of North America · 2026Review
- Transdiagnostic mental health symptom dimensions predict use of flexible model-based inference in complex environments.Translational psychiatry · 2026Article
- Threat discrimination of real-world social interactions in schizotypal traits.Psychonomic bulletin & review · 2026Article
- Fear, anxiety, and the extended amygdala-absence of evidence for strict functional segregation.Social cognitive and affective neuroscience · 2026Article
- Stakeholder Perspectives on Humanistic Implementation of Computer Perception in Health Care: Qualitative Study.JMIR mental health · 2026Article
- Fear, anxiety, and the extended amygdala-bioRxiv : the preprint server for biology · 2025Article
- Simultaneous intracranial recordings of interacting brains reveal neurocognitive dynamics of human cooperation.Nature neuroscience · 2025Article
- Emotions and individual differences shape human foraging under threat.Nature. Mental health · 2025Article
- An approach for unsupervised interaction clustering in human-robot co-work using spatiotemporal graph convolutional networks.Frontiers in robotics and AI · 2025Article
- Ecological brain: reframing the study of human behaviour and cognition.Royal Society open science · 2024Review
- Observational threat learning influences costly avoidance behaviour in healthy humans.Scientific reports · 2024Article
- Human navigation strategies and their errors result from dynamic interactions of spatial uncertainties.Nature communications · 2024Article
- Slow and steady: auditory features for discriminating animal vocalizations.bioRxiv : the preprint server for biology · 2024Article
- Article
- A synergetic turn in cognitive neuroscience of brain diseases.Trends in cognitive sciences · 2024Review
- Understanding the heterogeneity of anxiety using a translational neuroscience approach.Cognitive, affective & behavioral neuroscience · 2024Review
- Naturalistic reinforcement learning.Trends in cognitive sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The movements an organism makes provide insights into its internal states and motives. This principle is the foundation of the new field of computational ethology, which links rich automatic measurements of natural behaviors to motivational states and neural activity. Computational ethology has proven transformative for animal behavioral neuroscience. This success raises the question of whether rich automatic measurements of behavior can similarly drive progress in human neuroscience and psychology. New technologies for capturing and analyzing complex behaviors in real and virtual environments enable us to probe the human brain during naturalistic dynamic interactions with the environment that so far were beyond experimental investigation. Inspired by nonhuman computational ethology, we explore how these new tools can be used to test important questions in human neuroscience. We argue that application of this methodology will help human neuroscience and psychology extend limited behavioral measurements such as reaction time and accuracy, permit novel insights into how the human brain produces behavior, and ultimately reduce the growing measurement gap between human and animal neuroscience.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.