AI Article Synopsis

  • The Modular-Integrative Modeling approach is a new framework in neuroscience designed to create brain models that accurately reflect biological processes.
  • It aims to combine realistic biological elements with functional performance, offering a comprehensive understanding of how the brain interacts with the body and environment.
  • This perspective emphasizes the importance of integrating different aspects of brain function for a better overall view of neuroscience.

Article Abstract

This Perspective presents the Modular-Integrative Modeling approach, a novel framework in neuroscience for developing brain models that blend biological realism with functional performance to provide a holistic view on brain function in interaction with the body and environment.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10989280PMC
http://dx.doi.org/10.1093/nsr/nwad318DOI Listing

Publication Analysis

Top Keywords

modular-integrative modeling
8
brain models
8
models blend
8
blend biological
8
biological realism
8
realism functional
8
functional performance
8
modeling framework
4
framework building
4
building brain
4

Similar Publications

Article Synopsis
  • The Modular-Integrative Modeling approach is a new framework in neuroscience designed to create brain models that accurately reflect biological processes.
  • It aims to combine realistic biological elements with functional performance, offering a comprehensive understanding of how the brain interacts with the body and environment.
  • This perspective emphasizes the importance of integrating different aspects of brain function for a better overall view of neuroscience.
View Article and Find Full Text PDF

Building digital patient pathways for the management and treatment of multiple sclerosis.

Front Immunol

March 2024

Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.

Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!