Lindsey M. Kitchell

Pre-Training for Large-Scale Functional Connectome Fingerprinting Supports Generalization and Transfer Learning in Functional Neuroimaging

The paper pre-trains a neural network on functional connectome data to enable generalization and transfer learning in fMRI, achieving high recognition accuracy across datasets and scan durations.

NEURD offers automated proofreading and feature extraction for connectomics

NEURD automates proofreading and feature extraction from connectomics data to improve accuracy and accessibility of neural morphology analyses.

Functional connectomics spanning multiple areas of mouse visual cortex

The paper presents a functional connectomics dataset of mouse visual cortex, combining calcium imaging with EM reconstruction to study neural circuits and their connectivity.

Optimizing Artificial Neural Network Models to Predict Brain-Age from Functional MRI

This study optimizes deep learning models to predict brain-age from resting state fMRI data, achieving accurate predictions but showing mixed results for clinical populations.

Local graph-motif features improve gene interaction network prediction

This paper introduces LAMP features to enhance VGAEs for gene interaction network prediction, showing improved performance on missing-link prediction tasks.

A Novel Semi-automated Proofreading and Mesh Error Detection Pipeline for Neuron Extension

This paper introduces a semi-automated pipeline for detecting mesh errors in neuronal EM data, improving the accuracy of connectomic reconstructions by highlighting potential inaccuracies near neuronal tips.

NeuVue: A scalable and customizable framework for electron microscopy proofreading

NeuVue is a framework for managing and prioritizing proofreading tasks in connectomic datasets, enabling scalable and coordinated error correction by over forty proofreaders.

Collegiate athlete brain data for white matter mapping and network neuroscience

The paper shares a dataset of diffusion MRI data and derivatives from collegiate athletes and non-athletes to study the effects of long-term athletic exposure on brain structure.