Training tracers

Like with most things, to get good at tracing neurons, some training is needed. The introduction for tracing neurons helps with first steps, but managing a whole team and being confident in the quality of the results, will require some supervision. There are of course many ways on how to go about this, and an ad-hoc approach is surely fine for smaller groups. Below we show one example of a systematic approach that was developed by Ruchi Parekh and trainers in the Connectome Annotation Team (CAT) at Janelia Research Campus, where it worked for groups of tracers with 20 and more people.

Systematic training and evaluation

This approach trains new users in using CATMAID and was developed with the FAFB dataset in mind along with manually reconstructed neurons that have been published for it. New trainees follow first the introductory training to get familiar with both the dataset and software, which is described in the next section. A small collection of training videos highlights some basic workflows in CATMAID.

Once the introductory training is completed, trainees will do the training pipeline, explained in the second part. There, tracers were asked to reconstruct particular neurons in increasing difficulty, highlighting different aspects of CATMAID and the dataset.

For any questions on the training protocol, please email Ruchi Parekh (

Introductory Training Protocol

This training protocol is meant to introduce manual neuron reconstruction with CATMAID, using the FAFB dataset. This dataset consists of the EM data of the brain of a female adult Drosophila melanogaster. at a resolution of 4 x 4 x 40 nm/vx. An example on how such a brain is dissected and prepared, Janelia’s FlyLight team has some helpful videos. It might also be worthwile to check out the standard fly brain nomenclature. A publicly accessible CATMAID server can be found at, which allows creating personal and shared training projects for the FAFBv14 dataset. Virtual Fly Brain also hosts a read-only version of the FAFB dataset. For those interested in a broader context on the training neurons and in further understanding of the mushroom body, have a look here and here.

When introducing new trainees to CATMAID, the following rough outline seemed like a useful path to take:

  • Open FAFB project from front page

  • Browse EM data

  • Open Tracing Tool, select a few neurons by both clicking and G key

  • Open 3D Viewer and add a neuron, demo space manipulation

  • Activate node in 3D to see in EM

  • Link from 3D Viewer to EM gray space (F10 function)

  • Volume display of neuropils/whole brains (Volumes & Geometry tab in 3D)

  • Provide a general intro to hot keys, help page (F1 or ? icon) and context help (upper right corner)

Trainers create seed nodes for new trainees, named after their initials (see video linked above). Assuming this has been done, the following steps are taken in order to provide an introduction that provides trainees with the skills required to actually step through the training pipeline.


Each trainee will look at three intro neurons, before they can move to the training pipeline above: 1. PN -> 2. KC -> 3. PN -> 4. Pipeline.

  1. Select Neuron Search widget (toolbar icon: tag and question mark)

  2. Enter neuron number (users initials) from trainer

  3. Click on neuron seed number in window, append in 3D widget using ‘Active skeleton’ Start with Projection Neuron (PN)

  4. Start at seed node (will be the active node) and place a ‘TODO’ tag - go to step 1 ‘Projection Neuron (PN)’ section of protocol

  5. Once finished with step 1 PN, trainee will be assigned a Kenyon Cell (KC) - Repeat above steps - Go to step 2 ‘Kenyon Cell (KC)’ section of protocol

  6. Once finished with step 2 KC, trainee will return to finish PN - Repeat above steps - Go to step 3 ‘Projection neuron (PN)’ section of protocol

  7. Once finished with step 3 PN, trainee will move into the pipeline

1. PN - Projection Neuron

PN - Projection Neuron

Besides 1. and 2. in the image above, the goals are also

  1. Review own work

  2. Review with trainer

At end of PN - you should know


  • Recognize a branching point

  • Understand the 3D of branching structures

  • Recognize a synapse - Understand 4 major indicators

  • Recognize differences in morphology of a bouton and fingers of a claw

  • Preliminary understanding of ‘stringiness’ (it’s not a characteristic of the neuron itself- it’s a term we’ve given to describe the morphological ‘look’ of the neuron)


  • Place nodes in center

  • Create connecting skeletons

  • Create “clean” skeleton (i.e. a biologically realistic neuronal skeleton)

  • Check your neuron going “forward” and “backward”

  • Know how to go from an active node without forming parallel lines

  • To tackle small jumps and crappy section


  • +/- to zoom in and out of EM stack

  • Searching for neuron

  • 3D viewer - zoom, rotate, activate a node, pre, post and meta tags, taking off bounding box and floor, coloring neuron etc

  • F10 function

  • Tags - L, K, N

  • Untag - shift + whatever tag you need to untag (ex: shift+L gets rid of TODO)

  • “keyboard shortcut help”

2. KC - Kenyon Cell

KC - Kenyon Cell

Besides 1. to 4. in the image above, the goal is also

  1. Review own work

  2. Review with Trainer

At end of KC - you should know

All “you should know”s from PN + the following:


  • See further examples of synapses

    • See and recognize structural differences in synapses in KC and PN (especially in the calyx vs lobes)

    • Discuss how some indicators are more prevalent in different brain regions (vesicle clumping in PN boutons vs KC lobes)

    • Discuss different types of syn (e.g. en passant and en face)

  • Differences in pedunculus, lobe, and calyx EM anatomy and 3D morphology (refer to Illustration/explanation provided by trainer)


  • Continue to understand how each node helps shape the 3D morphology of the neuron

  • Know how to correctly tag soma

  • Know how to properly use uncertain tags

3. PN - Projection Neuron

PN - Projection Neuron

Besides 1. in the image above, the goal is also

  1. Review own work

  2. Review 1-1 with Trainer

At end of PN - you should know

All “you should know”s from PN + KC + the following:


  • Synapses in detail (bouton to claw)

  • Invagination

  • Cistern/ER

  • Vacuole

  • Vesicles

  • Synaptic cleft

  • Mitochondria

  • Microtubules - follow for continuations

  • Understand the above neurobiology in general context with the understanding that each may look different in different brain regions


  • Solid understanding of difference between PN trunk/KC pedunculus (tract) synapse and bouton/calyx (dendritic) synapse


  • Good sense of the hot keys and how to navigate them without a trainer

Synapse information

Identify a synapse:

  • T-bars - presynaptic protein where vesicles bind and neurotransmitter is released

  • Vesicles - small neurotransmitter filled spheres

    • Important to identify clumping around T-bars

    • Scroll between sections to determine how long T-bars and vesicles exist

  • Synaptic cleft - extracellular space where neurotransmitter diffuses to postsynaptic partners.

    • The cleft is located between the T-bar and the postsynaptic cells

  • Postsynaptic density (PSD) - postsynaptic receptor proteins that signify uptake of neurotransmitter


Note the movement across the first two images of the second row.

Neurons used in training

  • 4PN and 4KC neurons used in training. (Neurons used in training in 2019)

  • Uniglomerular mALT VC3l adPN 23135 BH

  • Uniglomerular mALT VM5d adPN 49866 JMR

  • Uniglomerular mALT VC1 lPN 22133 BH

  • Uniglomerular mALT VC3l adPN 46801 JMR

  • KCaBs 515202 NM

  • KCaBc 514395 NM

  • KCaBs 31268 IJA

  • KCaBs 7675 EW AJ

Training materials

CAT Trainer, Henrique Ludwig, has created short tutorials explaining some common tasks within the FAFB training environment, available as a playlist or here individually:

Starting in CATMAID

Keyboard shortcuts in CATMAID

Create a seed node

Trace and review neurons

Annotate synapses

Correcting Mistakes in a Traced Skeleton

Training pipeline

We found that going through four levels of difficulty over the course of multiple weeks gave tracers the skills they needed. We started with asking trainees to look at 22 neurons, eventually settled on 18 though, where the easiest level now includes only a single neuron. A shared spreadsheet was used to keep track of the progress of all trainees. This was also used as a means of communication between trainees and trainers. An example of such a spreadsheet is shown as table below can be downloaded as Open Document Spreadsheet or Excel format.

CAT Training Pipeline

Neuron name

CAT L1-5 “initials”

CAT L2-1

CAT L2-2

CAT L2-3

CAT L2-4

CAT L2-5

CAT L3-1

CAT L3-2

CAT L3-3

CAT L3-4

CAT L3-5





CAT L4-3A ***

CAT L4-3B ***

CAT L4-3C ***

*** If soma and soma tract found, then stop tracing

Brain region


















Cell type

Giant fiber input interneuron

LC4 neuron

Projection neuron









Giant fiber branch







What to trace

Main trunk skeleton only

Trace arborization only (no synapses)

Trace arborization only (no synapses)

Trunk + soma tract + soma (no synapses)

Skeleton + synapses + soma tract + soma

Skeleton + synapses

Skeleton (no synapses)

Skeleton + synapses

Skeleton + soma tract + soma + synapses

Skeleton + synapses (tracing reviewed at 1 week mark)

Skeleton (no synapses) **

Skeleton + synapses

Skeleton + synapses

Skeleton (no synapses)

Skeleton (no synapses)

Skeleton (no synapses) + soma + soma tract

Skeleton (no synapses) + soma + soma tract

Skeleton (no synapses) + soma + soma tract

Where to trace (Z)

Start on 3470 towards 3469. Stop on 3256.

Start on 4771 towards 4772

Start on 4622 towards 4621

Start on 5368 towards 5369 and stop at end node tagged with “DO NOT PROCEED”. There will be a small soma tract between the tagged end node and seed node - do not trace beyond the two nodes!

Start on 4991 towards 4992

Start on 1635 towards 1636

Start on 5397 towards 5398

Start on 2869 towards 2868

Start on 4423 towards 4424

Start on 2889 towards 2888

Start on 5588 seed node towards 5055 end node (only stop at 5055 if there is an end node with tag “DO NOT PROCEED”. Continue if there is no end node)

Start on 3795 towards 3796

Start on 4874 towards 4875

Start on 3569 seed node towards 3570. Stop on “DO NOT PROCEED” end node 3698

Start on 2364 seed node towards 2365. Stop on “DO NOT PROCEED” end node 2559

Start on 4291 towards 4292. Stop on “DO NOT PROCEED” end node 4925. Find and trace soma tract between start and end nodes

Start on 5638 towards 5637. Stop on 4682. Find and trace soma tract between start and end sections

Start on 6271 towards 6272. Stop on tagged as “DO NOT PROCEED” end node 5830 (only stop on section 5830 if this tag exists). Find and trace soma tract between start and end nodes


Trainee A

Trainee B

Trainee C

Generally, the training pipeline follows following steps:

  1. Trainee - Select “your” neuron name from above CAT LX-X list and search in CATMAID

  2. Trainee - Trace neuron

  3. Trainee - On completion - update progress sheet

  4. Trainee - Pick next neuron from list

  5. Trainer - Review completed neuron

  6. Trainer - Update progress sheet

Example neuron names in the training dataset are:

  • CAT L1-1 SC

  • CAT L2-4 LR

  • CAT L1-3 AW

  • CAT L5-1 TP

  • CAT L4-4 CP

  • CAT L3-1 SA

The status of each training neuron for each trainee follows the following color code:

Status colors

Trainee working on tracing

Trainee completed tracing

Trainer completed review

Tracing on hold

While tracing, trainees where advised to follow the following general guidelines regarding the use of node tags and edge confidence values:

  • use uncertain continuation/uncertain ends as necessary, however you will be evaluated based on how you use it

  • L2-2 onwards - place confidence intervals as described below for uncertain continuations/ends

  • L3-5 - If needed, clarify instructions with trainer

With confidence values assigned through the numeric keys 1-5 should be used like the following:

Confidence intervals






I am






sure it continues/ends

don’t add # 5 to node

add # 4 to node

add # 3 to node

add # 2 to node

add # 1 to node

continue tracing

continue tracing if uncertain continuation or stop if uncertain end

stop tracing

stop tracing

stop tracing

While also using the following rules on deciding when to mark an uncertain continuation with a tag versus a low confidence value:

And in addition:

  • Trainees should ask questions if confused about where to stop

  • USE uncertain tags when confused about anything

This document allows trainees to move through a defined and comparable process to learn about CATMAID and tracing, as well as the dataset itself.

A Trainer would guide new trainees according to the above plan and track their progress using the different color codes above in the trainee’s “swim lane”.