Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-23T18:18:03.966Z Has data issue: false hasContentIssue false
  • English
  • Français

Beginning with biology: “Aspects of cognition” exist in the service of the brain's overall function as a resource-regulator

Published online by Cambridge University Press:  11 March 2020

Jordan E. Theriault Open the ORCID record for Jordan E. Theriault [Opens in a new window] ,
Matt Coleman ,
Mallory J. Feldman ,
Joseph D. Fridman ,
Eli Sennesh ,
Lisa Feldman Barrett  and
Karen S. Quigley
Jordan E. Theriault
Affiliation:
Department of Psychology, Northeastern University, Boston, MA, 02115jordan_theriault@northeastern.edum.coleman@northeastern.eduj.fridman@northeastern.edul.barrett@northeastern.eduK.Quigley@northeastern.eduhttp://www.jordan-theriault.com/http://josephfridman.com/https://www.affective-science.org/
Matt Coleman
Affiliation:
Department of Psychology, Northeastern University, Boston, MA, 02115jordan_theriault@northeastern.edum.coleman@northeastern.eduj.fridman@northeastern.edul.barrett@northeastern.eduK.Quigley@northeastern.eduhttp://www.jordan-theriault.com/http://josephfridman.com/https://www.affective-science.org/
Mallory J. Feldman
Affiliation:
Department of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599mjfeld@live.unc.eduhttps://malloryjfeldman.com
Joseph D. Fridman
Affiliation:
Department of Psychology, Northeastern University, Boston, MA, 02115jordan_theriault@northeastern.edum.coleman@northeastern.eduj.fridman@northeastern.edul.barrett@northeastern.eduK.Quigley@northeastern.eduhttp://www.jordan-theriault.com/http://josephfridman.com/https://www.affective-science.org/
Eli Sennesh
Affiliation:
Khoury College of Computer Sciences, Northeastern University, Boston, MA, 02115sennesh.e@husky.neu.eduhttps://esennesh.github.io/
Lisa Feldman Barrett
Affiliation:
Department of Psychology, Northeastern University, Boston, MA, 02115jordan_theriault@northeastern.edum.coleman@northeastern.eduj.fridman@northeastern.edul.barrett@northeastern.eduK.Quigley@northeastern.eduhttp://www.jordan-theriault.com/http://josephfridman.com/https://www.affective-science.org/ Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129 Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129
Karen S. Quigley
Affiliation:
Department of Psychology, Northeastern University, Boston, MA, 02115jordan_theriault@northeastern.edum.coleman@northeastern.eduj.fridman@northeastern.edul.barrett@northeastern.eduK.Quigley@northeastern.eduhttp://www.jordan-theriault.com/http://josephfridman.com/https://www.affective-science.org/ Department of Veterans Affairs, Edith Nourse Rogers Memorial (VA) Medical Center, Bedford, MA, 01730
Get access Rights & Permissions [Opens in a new window]

Abstract

Lieder and Griffiths rightly urge that computational cognitive models be constrained by resource usage, but they should go further. The brain's primary function is to regulate resource usage. As a consequence, resource usage should not simply select among algorithmic models of “aspects of cognition.” Rather, “aspects of cognition” should be understood as existing in the service of resource management.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 43 , 2020 , e26
Check for updates
Copyright
Copyright © Cambridge University Press 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

1.

These authors jointly supervised this work.

References

Attwell, D. & Laughlin, S. B. (2001) An energy budget for signaling in the grey matter of the brain. Journal of Cerebral Blood Flow & Metabolism 21(10):1133–45. Available at: https://doi.org/10.1097/00004647-200110000-00001.CrossRefGoogle ScholarPubMed
Barrett, L. F. (2017a) How emotions are made: The secret life of the brain. Pan Macmillan.Google Scholar
Barrett, L. F. (2017b) The theory of constructed emotion: An active inference account of interoception and categorization. Social Cognitive and Affective Neuroscience 12(1):1–23. Available at: https://doi.org/10.1093/scan/nsw154.CrossRefGoogle Scholar
Barrett, L. F. & Finlay, B. L. (2018) Concepts, goals and the control of survival-related behaviors. Current Opinion in Behavioral Sciences 24:172–79. Available at: https://doi.org/10.1016/j.cobeha.2018.10.001.CrossRefGoogle ScholarPubMed
Barrett, L. F., Quigley, K. S. & Hamilton, P. (2016) An active inference theory of allostasis and interoception in depression. Philosophical Transactions of the Royal Society B: Biological Sciences 371(1708):20160011. Available at: https://doi.org/10.1098/rstb.2016.0011.CrossRefGoogle ScholarPubMed
Barrett, L. F. & Satpute, A. B. (2019) Historical pitfalls and new directions in the neuroscience of emotion. Neuroscience Letters 693:9–18. Available at: https://doi.org/10.1016/j.neulet.2017.07.045.CrossRefGoogle ScholarPubMed
Chanes, L. & Barrett, L. F. (2016) Redefining the role of limbic areas in cortical processing. Trends in Cognitive Sciences 20(2):96–106. Available at: https://doi.org/10.1016/j.tics.2015.11.005.CrossRefGoogle ScholarPubMed
Clark, A. (2013) Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences 36(3):1–24. Available at: https://doi.org/10.1017/S0140525X12000477.CrossRefGoogle ScholarPubMed
Clark, A. (2015) Surfing uncertainty: Prediction, action, and the embodied mind. Oxford University Press.Google Scholar
Clark-Polner, E., Wager, T. D., Satpute, A. B. & Barrett, L. F. (2016) Neural fingerprinting: Meta-analysis, variation and the search for brain-based essences in the science of emotion. In: The handbook of emotion, 4th edition, ed. Barrett, L. F., Lewis, M. & Haviland-Jones, J. M., pp. 146–65. Guilford Press.Google Scholar
Cook, M. & Mineka, S. (1989) Observational conditioning of fear to fear-relevant versus fear-irrelevant stimuli in rhesus monkeys. Journal of Abnormal Psychology 98(4):448–59. Available at: https://doi.org/10.1037/0021-843X.98.4.448.CrossRefGoogle ScholarPubMed
Denève, S. & Jardri, R. (2016) Circular inference: Mistaken belief, misplaced trust. Current Opinion in Behavioral Sciences 11:40–48. Available at: https://doi.org/10.1016/j.cobeha.2016.04.001.CrossRefGoogle Scholar
Fanselow, M. S. (2018) Emotion, motivation and function. Current Opinion in Behavioral Sciences 19:105–09. Available at: https://doi.org/10.1016/j.cobeha.2017.12.013.CrossRefGoogle Scholar
Fanselow, M. S. & Lester, L. S. (1988) A functional behavioristic approach to aversively motivated behavior: Predatory imminence as a determinant of the topography of defensive behavior. In: Evolution and learning, ed. Bolles, R. C. & Beecher, M. D., pp. 185–212. Lawrence Erlbaum Associates, Inc.Google Scholar
Friston, K. (2010) The free-energy principle: A unified brain theory? Nature Reviews Neuroscience 11(2):127–38. Available at: https://doi.org/10.1038/nrn2787.CrossRefGoogle ScholarPubMed
Friston, K., FitzGerald, T., Rigoli, F., Schwartenbeck, P. & Pezzulo, G. (2017) Active inference: A process theory. Neural Computation 29(1):1–49. Available at: https://doi.org/10.1162/NECO_a_00912.CrossRefGoogle ScholarPubMed
Guillory, S. A. & Bujarski, K. A. (2014) Exploring emotions using invasive methods: Review of 60 years of human intracranial electrophysiology. Social Cognitive and Affective Neuroscience 9(12):1880–89. Available at: https://doi.org/10.1093/scan/nsu002.CrossRefGoogle ScholarPubMed
Hutchinson, B. & Barrett, L. F. (2019) The power of predictions: An emerging paradigm for psychological research. Current Directions in Psychological Science 28(3):280–91. Available at: https://doi.org/10.1177/0963721419831992.CrossRefGoogle ScholarPubMed
Kleckner, I. R., Zhang, J., Touroutoglou, A., Chanes, L., Xia, C., Simmons, W. K., Quigley, K. S., Dickerson, B. C. & Barrett, L. F. (2017) Evidence for a large-scale brain system supporting allostasis and interoception in humans. Nature Human Behaviour 1(5):0069. Available at: https://doi.org/10.1038/s41562-017-0069.CrossRefGoogle ScholarPubMed
Mineka, S., Davidson, M., Cook, M. & Keir, R. (1984) Observational conditioning of snake fear in rhesus monkeys. Journal of Abnormal Psychology 93(4):355–72. Available at: https://doi.org/10.1037/0021-843X.93.4.355.CrossRefGoogle ScholarPubMed
Niven, J. E. & Laughlin, S. B. (2008) Energy limitation as a selective pressure on the evolution of sensory systems. Journal of Experimental Biology 211(11):1792–804. Available at: https://doi.org/10.1242/jeb.017574.CrossRefGoogle ScholarPubMed
Pontzer, H. (2015) Energy expenditure in humans and other primates: A new synthesis. Annual Review of Anthropology 44(1):169–87. Available at: https://doi.org/10.1146/annurev-anthro-102214-013925.CrossRefGoogle Scholar
Rao, R. P. N. & Ballard, D. H. (1999) Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience 2(1):79–87. Available at: https://doi.org/10.1038/4580.CrossRefGoogle ScholarPubMed
Sengupta, B., Stemmler, M. B. & Friston, K. J. (2013) Information and efficiency in the nervous system − a synthesis. PLoS Computational Biology 9(7):e1003157. Available at: https://doi.org/10.1371/journal.pcbi.1003157.CrossRefGoogle ScholarPubMed
Seth, A. K. (2015) The cybernetic Bayesian brain: From interoceptive inference to sensorimotor contingencies. In: Open mind, ed. Metzinger, T. & Windt, J. M., pp. 1–24. MIND Group. Available at: http://www.open-mind.net/DOI?isbn=9783958570108.Google Scholar
Shadmehr, R., Smith, M. A. & Krakauer, J. W. (2010) Error correction, sensory prediction, and adaptation in motor control. Annual Review of Neuroscience 33(1):89–108. Available at: https://doi.org/10.1146/annurev-neuro-060909-153135.CrossRefGoogle ScholarPubMed
Shannon, C. & Weaver, W. (1949/1964) The mathematical theory of communication, 10th edition. The University of Illinois Press.Google Scholar
Sterling, P. (2004) Principles of allostasis: Optimal design, predictive regulation, pathophysiology, and rational therapeutics. In: Allostasis, homeostasis, and the costs of physiological adaptation, ed. Schulkin, J., pp. 17–64. Cambridge University Press. Available at: https://doi.org/10.1017/CBO9781316257081.004.CrossRefGoogle Scholar
Sterling, P. (2012) Allostasis: A model of predictive regulation. Physiology & Behavior 106(1):5–15. Available at: https://doi.org/10.1016/j.physbeh.2011.06.004.CrossRefGoogle Scholar
Sterling, P. & Eyer, J. (1988) Allostasis: A new paradigm to explain arousal pathology. In: Handbook of life stress, cognition and health, ed. S., Fisher & J., Reason, pp. 629–49. John Wiley & Sons.Google Scholar
Sterling, P. & Laughlin, S. (2015) Principles of neural design. MIT Press.Google Scholar
Theriault, J. E., Young, L. L. & Barrett, L. F. (2019) The sense of should: A biologically-based model of social pressure. PsyArXiv. Preprint 10.31234/osf.io/x5rbs. Available at: https://doi.org/10.31234/osf.io/x5rbs.CrossRefGoogle Scholar
Weibel, E. R. (2000) Symmorphosis: On form and function in shaping life. Harvard University Press.Google Scholar
Westermann, G., Mareschal, D., Johnson, M. H., Sirois, S., Spratling, M. W. & Thomas, M. S. C. (2007) Neuroconstructivism. Developmental Science 10(1):75–83. Available at: https://doi.org/10.1111/j.1467-7687.2007.00567.x.CrossRefGoogle ScholarPubMed
Zénon, A., Solopchuk, O. & Pezzulo, G. (2019) An information-theoretic perspective on the costs of cognition. Neuropsychologia 123(4):5–18. Available at: https://doi.org/10.1016/j.neuropsychologia.2018.09.013.CrossRefGoogle ScholarPubMed