Our Research

IndiBrain advances a new era of personalised computational neuroscience, focused on understanding how and why brains differ from one another.

Although all human brains share a similar structure, every individual shows unique neural patterns, developmental trajectories, and responses to disease or treatment. Understanding these individual differences is essential for transforming neuroscience — from group-averaged knowledge to brain-specific prediction, diagnosis, and rehabilitation.

  • IndiBrain brings together expertise in:
  • Advanced neuroimaging (including ultra-high-field and ultrafast MRI)
  • Computational and network neuroscience
  • Machine learning and biologically inspired AI
  • Vision science and predictive coding
  • Clinical neuroscience and neurotechnology

Vision serves as our core model system, allowing us to link detailed neural mechanisms to perception, behaviour, and disease.

Scientific Goals

Our network focuses on three interconnected goals:

1. Build next-generation computational models of the human brain
We develop tools and models that capture individual brain structure and function — including methods for modelling brain dynamics, neural circuit interactions, and excitation–inhibition balance.
2. Understand individual variability in brain networks
We investigate how individual differences shape perception, cognition, and recovery in both healthy individuals and people with visual or neurological conditions.
3. Translate neuroscience into personalised brain health
By developing biomarkers and mechanistic models, we aim to improve early diagnosis, treatment monitoring, and rehabilitation strategies for visual and neurological disorders.

Research Themes & PhD Projects

Our research is structured across two major pillars:

Work Package: Computational Methods & Modeling

  • Bayesian models of visual cortex organization
  • Feedforward and feedback signal modelling
  • Directional connectivity analysis with ultrafast MRI
  • Dynamics of excitation–inhibition balance
  • Biologically realistic neural networks & generative modelling
  • Individualised high-resolution brain models
  • Eye-movement–related neural signal modelling

Work Package: Individual Differences in Brain Health & Disease

  • Neural & psychosocial predictors in central vision loss
  • Stereo vision and interhemispheric connectivity
  • Predictive processing variability
  • Visual dysfunction after extrastriate lesions
  • Visual network integrity in Multiple Sclerosis
  • Biomarkers for ocular gene therapy outcomes
  • Personalised detection of visual cortex abnormalities

Together, these projects guide PhD candidates from fundamental theory and method development to real-world clinical applications.