Eneko

Hi, I'm Eneko 👋

I have a PhD in machine learning for neuroimaging.

I want to make healthcare more accessible and affordable to everyone.

Recent publications

Cited by 181

Unraveling Hidden Patterns of Brain Activity: A Journey Through Hemodynamic Deconvolution in Functional MRI

(2024)

0

PyProximal-scalable convex optimization in Python

Journal of Open Source Software (2024)

3

Uncovering the Neural Correlates of the Urge-to-Blink: A Study Utilising Subjective Urge Ratings and Paradigm Free Mapping

bioRxiv (2024)

0

Individual variability in the relationship between physiological and resting-state fMRI metrics

bioRxiv (2024)

0

Bayesian Modelling Approaches for Breath-Hold Induced Cerebrovascular Reactivity

bioRxiv (2024)

0

Whole-brain multivariate hemodynamic deconvolution for functional MRI with stability selection

Medical Image Analysis (2024)

0

Hemodynamic Deconvolution Demystified: Sparsity-Driven Regularization at Work

Aperture Neuro (2023)

6

Conferences

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM Iberian Chapter 3rd Annual Meeting (2023)

Oral Scientific session, Best presentation

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM 32nd Annual Meeting & Exhibition (2023)

Best abstract, Suma Cum Laude Merit Award, Oral Scientific session

Exploring Tensor Decomposition as an Alternative to ICA for Denoising Multi-Echo fMRI Data

ISMRM 32nd Annual Meeting & Exhibition (2023)

A multi-echo low-rank and sparse method to estimate neuronal signal with less global signals bias

ISMRM Iberian Chapter 2nd Annual Meeting (2022)

Power Pitch

A multi-echo low-rank and sparse method to estimate neuronal signal with less global signals bias

OHBM Annual Meeting (2022)

Rica - Reports for visualizing and classifying ICA components of multi-echo fMRI

OHBM Annual Meeting (2022)

Blind estimation of neuronal-related activity in fMRI informed by co-fluctuations of brain regions

OHBM Annual Meeting (2022)

Talks

A Multi-Subject Deconvolution Algorithm to Analyze Naturalistic fMRI Data At The Finest Temporal and Spatial Resolution

ISMRM Workshop on Current Issues in Brain Function.

September 4th, 2023.

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM Iberian Chapter 3rd Annual Meeting.

July 4th, 2023.

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM 32nd Annual Meeting & Exhibition.

June 7th, 2023.

Multi-Subject Paradigm Free Mapping: A Promising Frontier for Analyzing Naturalistic fMRI Data

Cambridge Babylab, University of Cambridge, UK.

May 24th, 2023.

Advancing fMRI Data Analysis with Deconvolution Models: Paradigm Free Mapping Revisited

Developmental Cognition and Neuroimaging (DCAN), University of Minnesota, US.

April 17th, 2023.

Featured projects

tedana

TE-dependent analysis of multi-echo fMRI

161

aroma

ICA-AROMA, as a Python package. A work in progress.

7

mapca

A Python implementation of the moving average principal components analysis methods from GIFT

6

rica

Rica (Reports for ICA) provides an app to visualize ICA components and perform manual classification in an interactive way

7

pySPFM

Python version of 3dPFM and 3dMEPFM

1

pyproximal

PyProximal – Proximal Operators and Algorithms in Python

49

Latest threads

Academic Literature Review with Tana (March 1, 2023)

Scientific writing can be made easier with the right note-taking tools and workflows.

Unlock the power of @tana_inc and other #TfT tools like Notion or Obsidian to easily read, highlight, and synthesize academic literature.

First, you want to import the metadata from Zotero.
Books I'm reading
My interests

  • Working on new machine and deep learning projects.

  • Giving to the Brainhack community.

  • Learning web design and development with React.

  • Exploring new cities and learning from new connections.

  • Making the most of tools for thought .

  • Using AI to be more productive with daily tasks.

Let's chat