Evidence map›Paper›PMID 42361933›Full record

SynthesisNeuroscience and biobehavioral reviews2026

From microstates to macroscales: A critical review of maximum entropy modeling and energy landscape analysis in functional MRI.

Konasale Prasad, Ouyang Bowei, Nicholas Theis

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Neuroscience and biobehavioral reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Temporal stability of functional network configurations and its relationship to cognition and psychopathology in early psychoses.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Konasale PrasadDepartment of Psychiatry, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States; Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States; VA Pittsburgh Healthcare System, Pittsburgh, PA, United States. Electronic address: Kmp8@pitt.edu.
Ouyang BoweiDepartment of Psychiatry, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
Nicholas TheisDepartment of Psychiatry, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional magnetic resonance imaging has revolutionized neuroscience. Traditional analyses focusing on differences in regional activations and pairwise regional interactions (functional connectivity) cannot capture the collective nature of inherently time-variant network dynamics, which would be crucial to better understand the brain function at the systems level. This systematic review on maximum entropy models (MEMs), derived from statistical physics, critically appraises a principled framework that integrates regional activations and pairwise interactions to characterize patterns of dynamic functional network reorganizations at much shorter timescales. This method provides a global statistical structure of network configurations as energy landscapes enabling the tracking of evolution of network configurations over the duration of fMRI acquisition. Unlike correlation-based functional connectivity that assumes independence of regional correlations, MEMs capture the interdependent nature of network dynamics providing a statistically more persuasive picture of the network. The MEM utilizes binarized activation patterns to estimate the probability of network configurations, assigning "energy" values that represent the statistical likelihood of occurrence of specific brain states. MEMs reveal fundamentally altered dynamic functional network reconfigurations and energy landscapes in schizophrenia and other disorders where patients spend more time in high-energy (low-probability network configuration) brain states associated with cognitive dysfunction and more severe psychopathology. MEM also revealed distinct findings related to autism spectrum disorder, sleep, perception, and memory and show superior correspondence to structural connectivity compared to traditional methods, providing biologically grounded functional biomarkers. This approach bridges statistical physics with systems neuroscience, offering new perspectives on brain criticality and psychiatric pathophysiology.

Indexed as

BrainBrain MappingEntropyMagnetic Resonance ImagingModels, NeurologicalNerve NetAnimalsHumansDynamical systemDynamic functional networkEnergy landscapeFunctional MRIMaximum Entropy ModelNetwork Neuroscience

Identifiers

What OpenQuestion holds

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Registered trials

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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.