NeuroTracker Research Reveals Learning Characteristics Across Neurodevelopmental Conditions

A new study by researchers at McGill and the Universities of Montreal and California investigated if NeuroTracker learning rates could characterize different neurodevelopmental conditions in children. Here we'll run through an overview of the study findings.

What Was Studied

The researchers focused on three different neurodevelopmental conditions.

1. Attention-deficit/hyperactivity disorder (ADHD)

2. Specific learning disorder (SLD)

3. Intellectual developmental disorder (IDD)

They selected these different conditions based on the fact that NeuroTracker is a task which elicits significant attentional demands, and attentional capacities are closely interlinked with higher-order cognition (i.e., intelligence) and learning mechanisms.

The goal of the study was to highlight the role of attentional capacity and learning capability to characterize the difficulties expressed by individuals with ADHD, SLD, and IDD.

To establish learning trajectories with this 3D multiple object tracking task, 101 participants aged 6 to 17 years old completed a total of 30 NeuroTracker sessions over a period of 5 weeks, along with standardized neuropsychological assessments to confirm each neurodevelopmental diagnosis.

Here is a 2D video demonstration of the NeuroTracker task.

Each 6-minute session comprises 20 mini-tests and provides an overall 'speed threshold' score at the end of the session, measuring the upper tracking speed limit a person can achieve.

When completed in 3D at the correct viewing distance, the movement of the balls accurately simulates the speed at which objects would move if viewed as real-world objects (measured in centimeters per second).

Progression in NeuroTracker scores throughout the training program were scientifically analyzed using a latent growth curve modeling technique.

What Was Found

All participants improved at NeuroTracker, showing increased tracking speed with training, but with significant differences in terms of initial baselines and rate of improvement over time.

Performance trajectories as a function of the presence or absence of an ADHD, SLD, and IDD diagnosis revealed distinct learning trajectories in terms of how NeuroTracker scores improved across 30 sessions (2 sessions completed per training day).

Specifically analysis of the training data revealed these findings.

1. A decreased baseline performance for participants with IDD, suggesting pre-existing, diminished attention resource capacities.

2. Individuals with ADHD and SLD did not present pre-existing diminished attention resource capacities.

3. Individuals with IDD required a significant number of sessions to reach baseline performance exhibited by ADHD and SLD individuals.

4. Individuals with ADHD and SLD demonstrated a reduced rate of learning over time compared to those without ADHD and SLD.

5. A significant relationship of high comorbidity between individuals diagnosed with ADHD and SLD.

Takeaways

The study demonstrates that this type of attention-based cognitive task can yield previously undiscovered insights into the specific nature of different neurodevelopmental conditions. The researchers suggest that future studies using manipulations of the NeuroTracker task parameters (e.g. tracking duration and target prioritization), may provide more granular insights.

The open access study can be read here: Distinctive patterns of Multiple Object-Tracking performance trajectories in youth with deficits in attention, learning, and intelligence

Authors: Domenico Tullo, Jocelyn Faubert, Armando Bertone

‍