Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by Crossref.
Kesner, Ladislav
2014.
The predictive mind and the experience of visual art work.
Frontiers in Psychology,
Vol. 5,
Issue. ,
Schaefer, Rebecca S.
2014.
Auditory rhythmic cueing in movement rehabilitation: findings and possible mechanisms.
Philosophical Transactions of the Royal Society B: Biological Sciences,
Vol. 369,
Issue. 1658,
p.
20130402.
Trapp, Sabrina
Shenhav, Amitai
Bitzer, Sebastian
and
Bar, Moshe
2015.
Human preferences are biased towards associative information.
Cognition and Emotion,
Vol. 29,
Issue. 6,
p.
1054.
Vassena, Eliana
Kochman, Katty
Latomme, Julie
and
Verguts, Tom
2016.
Unimodal and cross-modal prediction is enhanced in musicians.
Scientific Reports,
Vol. 6,
Issue. 1,
Vuust, Peter
Dietz, Martin J.
Witek, Maria
and
Kringelbach, Morten L.
2018.
Now you hear it: a predictive coding model for understanding rhythmic incongruity.
Annals of the New York Academy of Sciences,
Vol. 1423,
Issue. 1,
p.
19.
Overy, Katie
2018.
Dynamic emotional narratives and vocal expression: Comment on “An integrative review of the enjoyment of sadness associated with music” by Tuomas Eerola et al..
Physics of Life Reviews,
Vol. 25,
Issue. ,
p.
142.
Vuust, Peter
2018.
Music Technology with Swing.
Vol. 11265,
Issue. ,
p.
101.
Braem, Senne
and
Trapp, Sabrina
2019.
Humans show a higher preference for stimuli that are predictive relative to those that are predictable.
Psychological Research,
Vol. 83,
Issue. 3,
p.
567.
De Souza, Jonathan
2020.
Instrumental Transformations in Heinrich Biber’s Mystery Sonatas.
Music Theory Online,
Vol. 26,
Issue. 4,
Li, Chia-Wei
Guo, Fong-Yi
and
Tsai, Chen-Gia
2021.
Predictive processing, cognitive control, and tonality stability of music: An fMRI study of chromatic harmony.
Brain and Cognition,
Vol. 151,
Issue. ,
p.
105751.
Campbell, Iain
and
Nelson, Peter
2022.
Rhythm and Signification.
Angelaki,
Vol. 27,
Issue. 5,
p.
56.
Matthews, Tomas E.
Stupacher, Jan
and
Vuust, Peter
2023.
The Pleasurable Urge to Move to Music Through the Lens of Learning Progress.
Journal of Cognition,
Vol. 6,
Issue. 1,
Omigie, Diana
and
Mencke, Iris
2024.
A model of time-varying music engagement.
Philosophical Transactions of the Royal Society B: Biological Sciences,
Vol. 379,
Issue. 1895,
Target article
Whatever next? Predictive brains, situated agents, and the future of cognitive science
Related commentaries (30)
Action-oriented predictive processing and the neuroeconomics of sub-cognitive reward
Active inference and free energy
Affect and non-uniform characteristics of predictive processing in musical behaviour
Applications of predictive control in neuroscience
Attention and perceptual adaptation
Attention is more than prediction precision
Backwards is the way forward: Feedback in the cortical hierarchy predicts the expected future
Bayesian animals sense ecological constraints to predict fitness and organize individually flexible reproductive decisions
Distinguishing theory from implementation in predictive coding accounts of brain function
Expecting ourselves to expect: The Bayesian brain as a projector
Extending predictive processing to the body: Emotion as interoceptive inference
God, the devil, and the details: Fleshing out the predictive processing framework
Grounding predictive coding models in empirical neuroscience research
Interactively human: Sharing time, constructing materiality
Maximal mutual information, not minimal entropy, for escaping the “Dark Room”
Neuronal inference must be local, selective, and coordinated
Perception versus action: The computations may be the same but the direction of fit differs
Personal narratives as the highest level of cognitive integration
Prediction, explanation, and the role of generative models in language processing
Predictions in the light of your own action repertoire as a general computational principle
Schizophrenia-related phenomena that challenge prediction error as the basis of cognitive functioning
Skull-bound perception and precision optimization through culture
Sparse coding and challenges for Bayesian models of the brain
The brain is not an isolated “black box,” nor is its goal to become one
The problem with brain GUTs: Conflation of different senses of “prediction” threatens metaphysical disaster
Two kinds of theory-laden cognitive processes: Distinguishing intransigence from dogmatism
Unraveling the mind
What else can brains do?
When the predictive brain gets it really wrong
Whenever next: Hierarchical timing of perception and action
Author response
Are we predictive engines? Perils, prospects, and the puzzle of the porous perceiver