Integrating neuroplasticity into whole-brain modeling: From synapses to neural populations

The brain’s ability to learn, adapt, and recover hinges on synaptic plasticity, yet most large-scale neural models overlook this core feature. In this review, we argue that embedding plasticity is essential for the simulation of realistic population-level brain activity. To this end, we explore specific computational attempts at scaling microscopic single-neuron plasticity rules to mesoscopic populations, drawing from mechanistic insights into short-term synaptic dynamics, long-term potentiation, and homeostatic regulation. We also discuss how plasticity mechanisms in neural field and neural mass models can potentially help us understand recovery trajectories, and how dysfunctional plasticity can play a role in them. Finally, we review state-of-the-art multiscale co-simulations methods that bridge spiking neuron networks with neural field and mass models and discuss their ability to link microscopic synaptic mechanisms with macroscopic brain dynamics. By embedding plasticity as a core feature, we can develop mean-field models that are more realistic and powerful tools for understanding brain function and recovery.

Authors

Institutions

Publication Details

Journal
Neuroscience & Biobehavioral Reviews
Published
2026-11-02
DOI
https://doi.org/10.1016/j.neubiorev.2026.107020
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating neuroplasticity into whole-brain modeling: From synapses to neural populations

Steven Laureys, Prejaas K. B. Tewarie, Gorka Zamora‐López, Gustavo Deco et al.
Neuroscience & Biobehavioral Reviews
Neural dynamics and brain function
article

Integrating neuroplasticity into whole-brain modeling: From synapses to neural populations

Steven Laureys, Prejaas K. B. Tewarie, Gorka Zamora‐López, Gustavo Deco, Pablo Núñez, Jil Mona Meier, Sahil Mukherjee
article en

Abstract

The brain’s ability to learn, adapt, and recover hinges on synaptic plasticity, yet most large-scale neural models overlook this core feature. In this review, we argue that embedding plasticity is essential for the simulation of realistic population-level brain activity. To this end, we explore specific computational attempts at scaling microscopic single-neuron plasticity rules to mesoscopic populations, drawing from mechanistic insights into short-term synaptic dynamics, long-term potentiation, and homeostatic regulation. We also discuss how plasticity mechanisms in neural field and neural mass models can potentially help us understand recovery trajectories, and how dysfunctional plasticity can play a role in them. Finally, we review state-of-the-art multiscale co-simulations methods that bridge spiking neuron networks with neural field and mass models and discuss their ability to link microscopic synaptic mechanisms with macroscopic brain dynamics. By embedding plasticity as a core feature, we can develop mean-field models that are more realistic and powerful tools for understanding brain function and recovery.

Neuroscience & Biobehavioral ReviewsVol. 192
Universidad de Valladolid (ES), Institució Catalana de Recerca i Estudis Avançats (ES), University of Nottingham (GB), Hangzhou Normal University (CN), Universitat Pompeu Fabra (ES), Czech Academy of Sciences (CZ), St George’s University Hospitals NHS Foundation Trust (GB), Instituto de Salud Carlos III (ES), Humboldt-Universität zu Berlin (DE), Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (ES), Centro de Investigación Biomédica en Red (ES), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Czech Academy of Sciences, Institute of Computer Science (CZ), Université Laval (CA), Hangzhou Institute of Medicine, Chinese Academy of Sciences (CN), Centre de recherche CERVO (CA), Charité - Universitätsmedizin Berlin (DE)
Openalex Percentile: Top 14%
Neural dynamics and brain function
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon