VidCognition vs Brainsight
Brainsight predicts where attention lands on a frame. VidCognition predicts the full brain engagement response — emotion, attention, memory — for every second of your TikTok or Reels video.
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Bottom line
Brainsight provides AI-predicted attention heatmaps for static and video frames. VidCognition goes further: it uses Meta's TRIBE v2 fMRI model to predict not just visual attention, but brain-region-level engagement across your entire short-form video, with a hook score and retention timeline built specifically for creators.
| Feature | VidCognition | Brainsight |
|---|---|---|
| Technology | fMRI neural prediction (Meta TRIBE v2) | AI saliency / attention prediction |
| Short-form video (TikTok / Reels / Shorts) | Specialized | General video |
| Brain engagement timeline (per second) | Yes — powered by TRIBE v2 | No |
| 3D brain heatmap | Shows which brain regions activate | No |
| Hook score | Yes | No |
| Attention heatmap | Brain-region based | Saliency-based |
| Free tier | Yes | Not clearly available |
| Pricing | Free–~$49/mo | Not published |
| Active development | Yes | Unclear |
VidCognition runs your video through Meta's TRIBE v2 AI model, trained on 7T fMRI scan data. It predicts how the amygdala (emotion), hippocampus (memory), and attention networks in a viewer's brain respond to your video — second by second. This is a fundamentally deeper signal than visual attention: a viewer can look at your hook without being emotionally compelled by it.
The result is a brain engagement timeline, a 3D brain heatmap, and a hook score built specifically for short-form video creators.
Brainsight uses AI saliency models to predict visual attention — where a viewer's eyes are likely to fixate on a given frame. It claims 94% accuracy against eye-tracking benchmarks and is primarily designed for design and UX work rather than short-form video optimization. It does not provide a brain engagement timeline, hook score, or neural response breakdown by brain region.
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