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Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

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Related Experiment Video

Updated: Dec 10, 2025

Real-time Video Projection in an MRI for Characterization of Neural Correlates Associated with Mirror Therapy for Phantom Limb Pain

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Neural Processes Underlying Mirror-Induced Visual Illusion: An Activation Likelihood Estimation Meta-Analysis.

Umar Muhammad Bello^1,2, Georg S Kranz^1,3, Stanley John Winser¹

¹Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.

Frontiers in Human Neuroscience

|August 28, 2020

Summary

This meta-analysis reveals brain areas for the mirror-induced visual illusion (MVI). Findings support MVI's potential as a clinical intervention for stroke patients, highlighting visualization and motor processes.

Keywords:

activation likelihood estimation cuneus meta-analysis mirror-induced visual illusion premotor

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Area of Science:

Neuroscience
Cognitive Neuroscience
Neuroimaging

Background:

Growing number of neuroimaging studies on mirror-induced visual illusion (MVI).
Previous systematic reviews utilized qualitative approaches.
Need for quantitative analysis to understand MVI neural processes.

Approach:

Activation Likelihood Estimation (ALE) meta-analysis was employed to synthesize findings from eight neuroimaging studies (14 experiments).
Databases searched included CINAHL, MEDLINE, Scopus, and PubMed to ensure a broad inclusion of relevant research.
Statistical analysis identified consistent brain regions activated during MVI experiences.

Key Points:

Contrast with rest revealed motor planning/execution areas (premotor, inferior parietal lobule) and self-processing/somatosensory areas (precuneus, cerebellum).
Comparison with active movement highlighted visual processing regions (cuneus, fusiform gyrus, middle occipital gyrus V2, lingual gyrus).
Findings indicate MVI involves integrated visual, motor, and self-referential neural networks.

Conclusions:

First meta-analysis to reveal visualization, mental rehearsal, and motor processes in MVI.
Identified key brain areas supporting MVI.
Suggests MVI as a potential clinical intervention for post-stroke patients.