Thomas Macrina

Thomas Macrina

Princeton University

H-index: 15

North America-United States

About Thomas Macrina

Thomas Macrina, With an exceptional h-index of 15 and a recent h-index of 15 (since 2020), a distinguished researcher at Princeton University, specializes in the field of connectomics, neuroscience, deep learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Petascale pipeline for precise alignment of images from serial section electron microscopy

CAVE: Connectome annotation versioning engine

Neuronal wiring diagram of an adult brain

Synaptic architecture of leg and wing motor control networks in Drosophila

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Functional connectomics reveals general wiring rule in mouse visual cortex

Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex

The Synaptic Architecture of Layer 5 Thick Tufted Excitatory Neurons in the Visual Cortex of Mice

Thomas Macrina Information

University

Position

PhD student

Citations(all)

899

Citations(since 2020)

897

Cited By

73

hIndex(all)

15

hIndex(since 2020)

15

i10Index(all)

17

i10Index(since 2020)

17

Email

University Profile Page

Google Scholar

Thomas Macrina Skills & Research Interests

connectomics

neuroscience

deep learning

Top articles of Thomas Macrina

Petascale pipeline for precise alignment of images from serial section electron microscopy

Nature Communications

2024/1/4

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

bioRxiv

2023/3/24

Oligodendrocyte precursor cells ingest axons in the mouse neocortex

Proceedings of the National Academy of Sciences

2022/11/29

Precise Alignment of Serial Section Electron Microscopy Images and Analysis of Neural Circuits

2022

See List of Professors in Thomas Macrina University(Princeton University)

Co-Authors

academic-engine