ReviewNature reviews. Neuroscience2017
Algorithms for survival: a comparative perspective on emotions.
Review in Nature reviews. Neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 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
66 citing papers in PubMed.
- Trial
- High-fat diet exposure, internal state, and reward value influence decision making during motivational conflict.Neurobiology of stress · 2026Article
- A computational model of reward learning and habits on social media.Nature communications · 2026Article
- A bio-inspired minimal model for non-stationary K-armed bandits.Biological cybernetics · 2026Article
- Article
- An intracranial dissection of human escape circuits.Nature communications · 2025Article
- How mood-related physiological states bias economic decisions.Communications psychology · 2025Article
- Construction of T-Cell-Related Prognostic Risk Models and Prediction of Tumor Immune Microenvironment Regulation in Pancreatic Adenocarcinoma via Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq.International journal of molecular sciences · 2025Article
- Regulation of interpersonal distance in virtual reality: Implications for socio-emotional functioning in late adulthood.PloS one · 2025Article
- Integration of conditioned threat with pre-existing memories.Learning & memory (Cold Spring Harbor, N.Y.) · 2025Article
- Social threat avoidance depends on action-outcome predictability.Communications psychology · 2024Article
- Wanting to matter and learning to care: A neurodevelopmental window of opportunity for (Pro) social learning?Developmental cognitive neuroscience · 2024Review
- Immersive VR for investigating threat avoidance: The VRthreat toolkit for Unity.Behavior research methods · 2024Article
- The Human Affectome.Neuroscience and biobehavioral reviews · 2024Review
- Neural substrates of parallel devaluation-sensitive and devaluation-insensitive Pavlovian learning in humans.Nature communications · 2023Article
- Functional sophistication in human escape.iScience · 2023Article
- The computational psychopathology of emotion.Psychopharmacology · 2023Review
- Reframing dopamine: A controlled controller at the limbic-motor interface.PLoS computational biology · 2023Article
- The nature and neurobiology of fear and anxiety: State of the science and opportunities for accelerating discovery.Neuroscience and biobehavioral reviews · 2023Review
- A computational model for learning from repeated traumatic experiences under uncertainty.Cognitive, affective & behavioral neuroscience · 2023Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The nature and neural implementation of emotions is the subject of vigorous debate. Here, we use Bayesian decision theory to address key complexities in this field and conceptualize emotions in terms of their relationship to survival-relevant behavioural choices. Decision theory indicates which behaviours are optimal in a given situation; however, the calculations required are radically intractable. We therefore conjecture that the brain uses a range of pre-programmed algorithms that provide approximate solutions. These solutions seem to produce specific behavioural manifestations of emotions and can also be associated with core affective dimensions. We identify principles according to which these algorithms are implemented in the brain and illustrate our approach by considering decision making in the face of proximal threat.
Indexed as
Identifiers
28360419What 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.