Related Experiment Video
Updated: Oct 10, 2025

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
Published on: July 16, 2015
Anterograde interference emerges along a gradient as a function of task similarity: A behavioural study
Raphaël Hamel1,2, Jean-François Lepage2, Pierre-Michel Bernier1
1Département de kinanthropologie, Faculté des sciences de l'activité physique, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Anterograde interference occurs due to overlapping neural networks, not just competing memories. Minimizing this overlap is key for effective subsequent learning.
Area of Science:
- Cognitive Neuroscience
- Motor Learning
- Neuroplasticity
Background:
- Anterograde interference, observed when learning two tasks sequentially, suggests factors beyond competing memories are involved.
- Previous theories proposed memory competition as the primary driver of this interference.
- Neurobiological evidence points to the role of neural network overlap in learning processes.
Purpose of the Study:
- To test the hypothesis that anterograde interference is dependent on the degree of overlap between neural networks used for learning.
- To investigate whether interference is solely due to memory competition or also influenced by neural network properties.
Main Methods:
- A within-subject, counterbalanced design with 24 participants.
- Behavioral manipulation of neural network overlap by altering reach direction and effector during visuomotor adaptation.
- Four experimental conditions varying task similarity and temporal succession (A→A, B→A).
Main Results:
- Anterograde interference occurred similarly in conditions with competing memories (B→A) and without (A→A).
- Interference increased along a gradient with greater task similarity, indicating a role for overlapping neural networks.
- Learning similar tasks resulted in more interference than learning dissimilar tasks.
Conclusions:
- Competing memories are not the sole cause of anterograde interference.
- Overlapping neural networks between successive learning tasks are necessary to trigger interference.
- Dissociating learning-specific neural networks may minimize interference and enhance subsequent learning capabilities.
More Related Videos
08:35An Operant Intra-/Extra-dimensional Set-shift Task for Mice
Published on: January 22, 2016
09:01A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Published on: May 7, 2014
Related Concept Videos
Causes of Similarity-Dissimilarity Effect
Interference and Decay
Interference occurs when competing memories hinder the retrieval of particular information. It can be classified into two types: proactive and retroactive interference. Proactive...