NextMind is a neurotechnology company that developed a consumer-grade, non-invasive brain-computer interface for visual perception decoding. Founded in 2017, NextMind was acquired by Snap Inc. in 2021, marking one of the first major acquisitions of a BCI company by a large technology firm. The company's mission was to make brain-computer interfaces accessible to consumers, demonstrating that non-invasive BCI technology could work in everyday applications beyond laboratory settings.
NextMind's focus on visual cortex recording represented a unique approach in the BCI field. Rather than attempting to decode complex motor intentions or comprehensive cognitive states, the company specialized in decoding visual attention—what users were literally looking at and focusing their visual attention on. This targeted approach enabled reliable performance in a consumer-friendly form factor.
The NextMind Dev Kit represented a breakthrough in consumer BCI:
| Parameter |
Specification |
| Form Factor |
Wearable EEG headset (single headband) |
| Channels |
9 dry-electrode sensors |
| Focus |
Visual cortex recording |
| Sampling Rate |
256 Hz |
| Bandwidth |
0.1-40 Hz |
| Wireless |
Bluetooth 5.0 |
| Battery |
Rechargeable (8 hours) |
| Weight |
~100g |
The NextMind device records EEG from the visual cortex through a streamlined process:
- Signal Acquisition: User wears the headband with dry electrodes positioned over the occipital cortex
- User Focus: User focuses on visual stimuli presented on a screen or in AR/VR
- Neural Recording: The headset captures electrical activity from the visual cortex
- Machine Learning Decoding: Custom algorithms classify the visual intention in real-time
- Output: Decoded signals control applications, games, or other interfaces
NextMind employed several technical innovations:
- Targeted recording: Focused on visual cortex rather than whole-brain recording
- Dry electrodes: No conductive gel required, enabling quick setup
- Real-time classification: On-device machine learning for low-latency decoding
- Visual stimuli design: Specialized stimuli optimized for neural decoding
NextMind enabled novel consumer experiences:
- Gaming controls: Controlling game elements with visual attention
- AR/VR interaction: Interacting with virtual objects through focus
- Accessibility applications: Alternative input for users with motor impairments
- Focus training: Visual attention improvement tools
The research community adopted NextMind for:
- Visual neuroscience studies: Understanding visual perception mechanisms
- Attention research: Investigating selective attention processes
- BCI algorithm development: Testing new decoding approaches
- Cognitive psychology: Studying perception and awareness
Clinical applications include:
- Vision restoration: Research into visual cortex prosthetics
- Cognitive assessment: Objective attention measurement
- Neurofeedback training: Attention disorder treatment
- Reading research: Eye movement and attention studies
NextMind technology has been validated in peer-reviewed research:
- Visual attention classification studies demonstrating >80% accuracy
- Real-time BCI experiments showing practical utility
- Integration with AR/VR systems for immersive applications
- Comparative studies with clinical-grade EEG systems
Multiple research groups have validated NextMind:
- Visual perception decoding in controlled settings
- Real-time attention classification for BCI control
- Comparison with clinical EEG systems
- Application in cognitive neuroscience experiments
In March 2021, Snap Inc. acquired NextMind to integrate brain-computer interface technology into the Snap AR ecosystem:
- Strategic rationale: Adding neural input to AR glasses
- Technology integration: NextMind technology in Snap's Spectacles
- Research applications: Lens Studio for AR filters
- Future vision: Seamless AR control through visual attention
For neurodegenerative diseases, NextMind offers several relevant capabilities:
- Visual attention research: Understanding attention deficits
- Cognitive assessment: Tracking attention changes over time
- Early detection: Identifying attention-related biomarkers
- Rehabilitation: Neurofeedback for cognitive training
- Visual-motor integration: Understanding visuospatial deficits
- Research applications: Studying PD-related visual processing changes
- Monitoring: Tracking disease progression through attention metrics
- Motor impairment solutions: Alternative input methods
- Communication: Visual selection for AAC devices
- Environmental control: Smart home interaction
¶ Competitive Landscape
NextMind occupies a unique position:
| Feature |
NextMind |
Emotiv |
OpenBCI |
Kernel |
| Focus |
Visual |
General |
General |
General |
| Simplicity |
High |
Medium |
Low |
Medium |
| Consumer |
Yes |
Yes |
No |
Yes |
| Research |
Limited |
Yes |
Yes |
Yes |
Compared to other systems:
- Single purpose: Limited to visual attention
- Lower accuracy: Than research-grade systems
- Limited channels: 9 electrodes vs 32+
- Position sensitivity: Requires precise placement
Since the Snap acquisition:
- Spectacles integration: NextMind technology in AR glasses
- Lens Studio: AR filters responding to attention
- Research partnerships: Academic collaborations
- Consumer apps: Attention-based applications
Potential developments include:
- Improved accuracy: Enhanced machine learning
- Form factor: Smaller, more comfortable design
- Medical applications: Clinical validation
- Broader applications: Beyond visual attention