» Articles » PMID: 38104789

Intrinsic Timescales and Predictive Allostatic Interoception in Brain Health and Disease

Overview
Date 2023 Dec 17
PMID 38104789
Authors
Affiliations
Soon will be listed here.
Abstract

The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.

Citing Articles

Altered spatiotemporal brain dynamics of interoception in behavioural-variant frontotemporal dementia.

Hazelton J, Della Bella G, Barttfeld P, Dottori M, Gonzalez-Gomez R, Migeot J EBioMedicine. 2025; 113:105614.

PMID: 39987747 PMC: 11894334. DOI: 10.1016/j.ebiom.2025.105614.


The Importance of Including Psychophysiological Methods in Psychotherapy.

Lehrer P Appl Psychophysiol Biofeedback. 2024; .

PMID: 39487925 DOI: 10.1007/s10484-024-09667-w.


Interoception in anxiety, depression, and psychosis: a review.

Jenkinson P, Fotopoulou A, Ibanez A, Rossell S EClinicalMedicine. 2024; 73:102673.

PMID: 38873633 PMC: 11169962. DOI: 10.1016/j.eclinm.2024.102673.


Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome.

Takacs A, Toth-Faber E, Schubert L, Tarnok Z, Ghorbani F, Trelenberg M Hum Brain Mapp. 2024; 45(8):e26719.

PMID: 38826009 PMC: 11144952. DOI: 10.1002/hbm.26719.

References
1.
Misiak B, Stanczykiewicz B, Pawlak A, Szewczuk-Boguslawska M, Samochowiec J, Samochowiec A . Adverse childhood experiences and low socioeconomic status with respect to allostatic load in adulthood: A systematic review. Psychoneuroendocrinology. 2021; 136:105602. DOI: 10.1016/j.psyneuen.2021.105602. View

2.
Murray J, Bernacchia A, Freedman D, Romo R, Wallis J, Cai X . A hierarchy of intrinsic timescales across primate cortex. Nat Neurosci. 2014; 17(12):1661-3. PMC: 4241138. DOI: 10.1038/nn.3862. View

3.
Legaz A, Yoris A, Sedeno L, Abrevaya S, Martorell M, Alifano F . Heart-brain interactions during social and cognitive stress in hypertensive disease: A multidimensional approach. Eur J Neurosci. 2020; 55(9-10):2836-2850. PMC: 8231407. DOI: 10.1111/ejn.14979. View

4.
Dik M, Jonker C, Comijs H, Deeg D, Kok A, Yaffe K . Contribution of metabolic syndrome components to cognition in older individuals. Diabetes Care. 2007; 30(10):2655-60. DOI: 10.2337/dc06-1190. View

5.
Braun W, Matsuzaka Y, Mushiake H, Northoff G, Longtin A . Non-additive activity modulation during a decision making task involving tactic selection. Cogn Neurodyn. 2022; 16(1):117-133. PMC: 8807796. DOI: 10.1007/s11571-021-09702-0. View