Hello, I'm

Dr. Miro Grundei

I combine neuroscience, neuroimaging, and data science to study how the brain predicts sensory input and forms, maintains, and updates representations of the world.

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About Me

I'm a computational neuroscientist working at the intersection of cognitive neuroscience, predictive processing, brain stimulation, and data science. My research combines EEG, fMRI, multivariate decoding, computational modeling, and experimental design to investigate how the brain represents information, detects surprise, and adapts behavior.

I focus on translating complex neural signals into interpretable models and reproducible pipelines that connect brain dynamics with cognition.

5+ Years Experience
10+ Research Studies
176+ Citations h=6
3 Core Focus Areas

Selected Research

📊

Bayesian Modeling & Prediction Error

I investigate how the brain encodes surprise and updates beliefs across sensory systems, combining Bayesian modeling, EEG/fMRI, and predictive-processing frameworks.

  • Bayesian surprise
  • Multimodal EEG
  • fMRI expectation violation
  • Active inference
  • Somatosensory MMN

Brain Stimulation & Cognitive Dynamics

I study how non-invasive brain stimulation interacts with neural activity and cognitive performance, especially in working-memory and concurrent tDCS-fMRI contexts.

  • tDCS
  • Working memory
  • Concurrent tDCS-fMRI
  • Cognitive performance
🔍

Neural Decoding of Working Memory

I use multivariate decoding to link parietal fMRI activity patterns with tactile working-memory content and behavioral performance.

  • MVPA
  • Tactile working memory
  • Parietal cortex
  • fMRI patterns

Methods & Tools

🧠

Experimental Design & Neuroimaging

  • Behavioral task design for sensory, working-memory, and decision-making experiments
  • EEG and fMRI studies, non-invasive brain stimulation, and concurrent tDCS-fMRI
📊

Computational Modeling & Data Analysis

  • Bayesian modeling, probabilistic inference, and predictive-processing frameworks
  • Multivariate analyses including decoding, representational similarity analysis, and connectivity modeling
🔧

Scientific Computing & Reproducibility

  • Analysis pipelines in Python and MATLAB for neuroimaging, statistics, and model-based workflows
  • High-performance computing with SLURM, plus Git, Docker, Linux, and reproducible scientific workflows

Get in Touch

I'm open to collaborations in neuroscience, neuroimaging, and data science. The easiest way to reach me is through my academic and code profiles.