AI Helps Scientists See Neurons in Moving Animals

A collaborative team from EPFL and Harvard has introduced an advanced artificial intelligence (AI) technique to track neurons within animals in motion. The new CNN-based AI hopes to address current challenges in decoding the brain activity of flexible organisms like worms.

Two-dimensional projection of 3D volumetric brain activity recordings in C. elegans. (VIDEO) Video Credit: Mahsa Barzegar-Keshteli (EPFL)
Two-dimensional projection of 3D volumetric brain activity recordings in C. elegans. (VIDEO) Video Credit: Mahsa Barzegar-Keshteli (EPFL)

The study, spearheaded by Sahand Jamal Rahi at EPFL’s School of Basic Sciences, has been published in Nature Methods.

Neural Imaging and AI

Historically, whole-brain imaging with single-cell resolution has been pivotal in studying neural circuits in various organisms. However, the dynamic nature of these studies, particularly in animals performing natural behaviors, poses a challenge.

The brain's movement and deformation within flexible organisms make the segmentation and tracking of individual neurons complex. To address this, the team set out to automate this process, overcoming the limitations of manual annotation, which, though reliable, is considerably time-consuming. 

Neuron Segmentation and Tracking

The team's AI-based method centers around a convolutional neural network (CNN), a form of AI known for excelling at pattern recognition in images. The CNN was trained to recognize and comprehend image patterns through convolution, analyzing small picture segments for features like edges, colors, or shapes.

The notable mention of this technology is the introduction of 'targeted augmentation', a method that synthesizes artificial annotations from a limited number of manual annotations. This technique allows the CNN to learn the brain's internal deformations in different postures, thereby significantly reducing the need for manual annotation.

Microscopic photograph of a nematode colored under a phase contrast microscope

Image Credit: Hussmann/

Targettrack: A Comprehensive Pipeline for Neural Analysis

An end-to-end pipeline called 'Targettrack' was developed, which learns the brain-wide deformations in each experiment and adapts to the visual appearance of each animal and the specific imaging conditions. By using Targettrack, a substantial increase in throughput can be achieved compared to full manual annotation, reducing the time needed for manual annotations and proofreading by 50-fold for challenging brain imaging problems.

Tested on the nematode Caenorhabditis elegans, known for its compact neural system and popularity as a model organism in neuroscience, the CNN demonstrated its effectiveness in identifying neurons as key points or 3D volumes.

Furthermore, researchers were able to observe intricate patterns in interneuron dynamics, including changes in neuronal response to varying stimuli like odor bursts. The method's versatility and efficiency make it a valuable tool not only for C. elegans imaging but also for tracking neurons in other moving and deforming entities.

The breakthrough has the potential to accelerate research in brain imaging and deepen our understanding of neural circuits and behaviors."

Sahand Jamal Rahi, School of Basic Sciences, EPFL

Targettrack is also designed with the user in mind, with an accessible graphical interface that integrates targeted augmentation and a streamlined workflow that lays the foundation for gaining in-depth insight into neural circuits and behaviors. 

Journal reference:

Park, C.F., Barzegar-Keshteli, M., Korchagina, K. et al. Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation. Nat Methods (2023).

Megan Craig

Written by

Megan Craig

Megan graduated from The University of Manchester with a B.Sc. in Genetics, and decided to pursue an M.Sc. in Science and Health Communication due to her passion for learning about and sharing scientific innovations. During her time at AZoNetwork, Megan has interviewed key Thought Leaders across several scientific, medical and engineering sectors and attended prominent exhibitions worldwide.


Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Craig, Megan. (2023, December 05). AI Helps Scientists See Neurons in Moving Animals. AZoLifeSciences. Retrieved on March 04, 2024 from

  • MLA

    Craig, Megan. "AI Helps Scientists See Neurons in Moving Animals". AZoLifeSciences. 04 March 2024. <>.

  • Chicago

    Craig, Megan. "AI Helps Scientists See Neurons in Moving Animals". AZoLifeSciences. (accessed March 04, 2024).

  • Harvard

    Craig, Megan. 2023. AI Helps Scientists See Neurons in Moving Animals. AZoLifeSciences, viewed 04 March 2024,


The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
Post a new comment
Azthena logo powered by Azthena AI

Your AI Assistant finding answers from trusted AZoM content

Your AI Powered Scientific Assistant

Hi, I'm Azthena, you can trust me to find commercial scientific answers from

A few things you need to know before we start. Please read and accept to continue.

  • Use of “Azthena” is subject to the terms and conditions of use as set out by OpenAI.
  • Content provided on any AZoNetwork sites are subject to the site Terms & Conditions and Privacy Policy.
  • Large Language Models can make mistakes. Consider checking important information.

Great. Ask your question.

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Prefrontal Neurons’ Cascade of Phonetic Representations