Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 41 min ago
PreprintCC BYbioRxiv

From Wandering Thoughts to Mental Stillness: A Minimal Computational Statistical-Mechanical Model of Driven Relaxation

  1. 1IIT Kharagpur

Abstract

Reduced spontaneous thought during meditation is often described phenomenologically, but a mechanistic account should specify how a dynamical system can enter and persist in such a regime. Here we formulate a minimal statistical-mechanical model in which a dimensionless coordinate, q, represents a coarse-grained propensity for spontaneous-thought activity, and a slowly relaxing variable, r of t, represents the history-dependent effect of an attentional manipulation. The model combines a tilted double-well landscape with Langevin noise, allowing a high-q and a low-q dynamical regime to coexist. We numerically integrate the model under a controlled focusing protocol followed by removal of the drive and quantify low-state occupancy, first-passage times, dwell times, occupancy entropy, and transition entropy. For the chosen dimensionless parameterization, increasing the drive amplitude produces a sharp crossover in low-state occupancy near the deterministic spinodal threshold, A-sub-sp, approximately equal to 0.0148. At a noise intensity of D equal to 0.01, the probability of occupying the low-q regime at drive removal increases from 0.094 at A equal to zero to 0.994 at A equal to 0.02, while the mean first-passage time decreases from 48.0 to 13.5 model time units. Noise produces a non-monotonic effect: for A equal to 0.01, low-state occupancy at drive removal is only 0.033 at D equal to 0.0025, rises to 0.842 at D equal to 0.02, and falls to 0.718 at D equal to 0.04. Strong driving also reduces the effective number of occupied states while changing transition entropy much less, illustrating why a single entropy measure cannot identify thoughtlessness. These results do not establish that human neural dynamics obey this model. Instead, they show that a driven stochastic bistable system can generate the qualitative sequence of focusing, switching, relaxation, and metastable low-activity residence, and they provide quantitative predictions that can be tested against time-resolved neural recordings and independent reports of subjective experience.

Related

  1. Common attentional mechanisms, but distinct computational dynamics, across Statistical and Reward Learning
    C. Dolci, T. Verguts, W. J. Louter +2
    bioRxivPreprintCC BYFull textNeurosciencebioRxiv
  2. LLM-assisted analytical review catches statistical errors that human researchers miss: documented evidence from two computational biology case studies
    O. Chhaya, V. Ananth
    bioRxivPreprintCC BYFull textNeurosciencebioRxiv
  3. Validation of a Computational Respiratory System Model for Mechanical Ventilation
    Carlotta Hennigs, Charlott Danielson, Franziska Bilda +7
    arXivPreprintCC BY 4.0Full textGeneral biologyDynamical systemsarXiv
  4. Simple calls to increase effort influence attention, mind wandering, and learning during online lectures
    Derek A. Albert, Jackie Heitzner, Daniel Smilek
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textNeuroscienceCrossref
  5. Stability and Wandering of Bumps in Neural Fields with Interneuron Subtypes
    Bilal Ahmed, Heather Cihak, Gregory Handy
    arXivPreprintCC BY 4.0Full textNeuroscienceDynamical systemsarXiv
BibTeX
@misc{karmakar2026from,
  title = {{From Wandering Thoughts to Mental Stillness: A Minimal Computational Statistical-Mechanical Model of Driven Relaxation}},
  author = {S. Karmakar},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.11.758288},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.11.758288v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - From Wandering Thoughts to Mental Stillness: A Minimal Computational Statistical-Mechanical Model of Driven Relaxation
AU  - S. Karmakar
PY  - 2026
DA  - 2026/10/11
PB  - bioRxiv
DO  - 10.64898/2026.10.11.758288
UR  - https://www.biorxiv.org/content/10.64898/2026.10.11.758288v1
AB  - Reduced spontaneous thought during meditation is often described phenomenologically, but a mechanistic account should specify how a dynamical system can enter and persist in such a regime. Here we formulate a minimal statistical-mechanical model in which a dimensionless coordinate, q, represents a coarse-grained propensity for spontaneous-thought activity, and a slowly relaxing variable, r of t, represents the history-dependent effect of an attentional manipulation. The model combines a tilted double-well landscape with Langevin noise, allowing a high-q and a low-q dynamical regime to coexist. We numerically integrate the model under a controlled focusing protocol followed by removal of the drive and quantify low-state occupancy, first-passage times, dwell times, occupancy entropy, and transition entropy. For the chosen dimensionless parameterization, increasing the drive amplitude produces a sharp crossover in low-state occupancy near the deterministic spinodal threshold, A-sub-sp, approximately equal to 0.0148. At a noise intensity of D equal to 0.01, the probability of occupying the low-q regime at drive removal increases from 0.094 at A equal to zero to 0.994 at A equal to 0.02, while the mean first-passage time decreases from 48.0 to 13.5 model time units. Noise produces a non-monotonic effect: for A equal to 0.01, low-state occupancy at drive removal is only 0.033 at D equal to 0.0025, rises to 0.842 at D equal to 0.02, and falls to 0.718 at D equal to 0.04. Strong driving also reduces the effective number of occupied states while changing transition entropy much less, illustrating why a single entropy measure cannot identify thoughtlessness. These results do not establish that human neural dynamics obey this model. Instead, they show that a driven stochastic bistable system can generate the qualitative sequence of focusing, switching, relaxation, and metastable low-activity residence, and they provide quantitative predictions that can be tested against time-resolved neural recordings and independent reports of subjective experience.
ER  -