Independent research · 2025–26

Neuronal cell-type classification

A study of whether morphological and electrophysiological features can help distinguish neuronal cell types across human and mouse datasets.

Timeline
June 2025–March 2026
Data
Allen Brain Atlas
Type
Independent research
Recognition
2026 · First Place Trophy · Grades 9–12

The question

What information is useful?

Neurons can be described by their shape and by how they respond electrically. I wanted to understand how much each type of information contributes to classification.

The work

Preparing comparable data

I prepared human and mouse datasets and aligned morphological, electrophysiological, and structural-layer features for analysis.

Comparing models

I compared decision trees, random forests, and LSTMs rather than assuming that the most complex model would be the most informative.

Looking at errors

Cross-validation and confusion matrices helped show which categories were consistently distinguishable and where the models confused related cell types.

Recognition

Washington State Science & Engineering Fair

2026 · First Place Trophy · Grades 9–12

The neuronal classification project received the fair’s 2026 First Place Trophy for grades 9–12.

Sources & context

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