| Logo placeholder |
| Founded |
2017 |
| Headquarters |
Paris, France |
| Acquired by |
Snap Inc. (2021) |
| Founder |
Devon (last name unknown) |
| Status |
Active as Snap division |
| Website |
[nextmind.tech](https://nextmind.tech) |
NextMind is a neurotechnology company developing non-invasive brain-computer interfaces. Founded in 2017 and acquired by Snap Inc. (parent company of Snapchat) in 2021, NextMind focuses on creating affordable, easy-to-use EEG-based devices for consumer and enterprise applications. The company has positioned itself as a leader in the emerging consumer BCI market, with a particular focus on visual and cognitive state monitoring.
¶ History and Development
¶ Founding and Early Years (2017-2020)
NextMind was founded in 2017 with a mission to make brain-computer interface technology accessible to consumers and researchers. The company developed a novel dry-electrode EEG system that could be used without the lengthy setup times required by traditional EEG systems.
NextMind launched its first commercial product in 2019, a brain-sensing headband designed for:
- Gaming and virtual reality
- Meditation and focus training
- Cognitive performance monitoring
- Research applications
In March 2021, Snap Inc. acquired NextMind for an undisclosed sum, marking one of the first major acquisitions in the consumer BCI space. The acquisition was seen as part of Snap's strategy to expand beyond social media into AR and emerging technologies.
Under Snap's ownership, NextMind has continued to develop its technology with increased resources:
- Integration with Snapchat and Spectacles AR glasses
- Development of new cognitive interface features
- Research into visual cortex neurofeedback
- Enterprise applications for focus and attention training
The NextMind headband represents a significant advancement in consumer-grade EEG:
- Electrode Count: 8 dry electrodes
- Electrode Material: Proprietary conductive polymer
- Sampling Rate: 256 Hz
- Bandwidth: 0.5-40 Hz
- Battery Life: 8+ hours continuous use
- Connectivity: Bluetooth 5.0
- Weight: ~60 grams
- On-board Processing: ARM Cortex-M4 processor
- Artifact Rejection: Real-time motion and muscle artifact removal
- Machine Learning: On-device neural network for classification
- Latency: Less than 100ms from signal to classification
- SDK: Available for Windows, macOS, iOS, and Android
- APIs: REST and WebSocket interfaces
- Unity Integration: Game engine plugin
- Python Support: Research-friendly Python bindings
- Examples: Sample applications for various use cases
- Visual Attention: Classify attended visual targets
- Mental Commands: Binary and multi-class mental states
- Cognitive Load: Measure mental workload
- Meditation State: Track relaxation and focus
NextMind's technology has potential applications in visual prosthetics research:
- Cortical Visual Prosthetics: Research into visual cortex stimulation
- Phosphene Mapping: Understanding artificial vision perception
- Visual Rehabilitation: Training protocols for vision restoration
- Research Platform: Affordable platform for visual neuroscience
Non-invasive monitoring has applications in:
Potential applications for cognitive training:
As a non-invasive tool for stroke recovery:
| Feature |
NextMind (Non-invasive) |
Neuralink (Invasive) |
Blackrock (Invasive) |
| Invasiveness |
None |
Surgical implant |
Surgical implant |
| Spatial Resolution |
Low (cm) |
High (sub-mm) |
High (sub-mm) |
| Temporal Resolution |
High (~250 Hz) |
Very high (~20 kHz) |
Very high (~30 kHz) |
| Setup Time |
2-5 minutes |
Hours (surgery) |
Hours (surgery) |
| Cost |
~$399 USD |
Research only |
Research only |
| Signal Quality |
Moderate |
Excellent |
Excellent |
| Long-term Use |
Unlimited |
Years |
Years |
| Risk |
None |
Surgical risks |
Surgical risks |
- FDA: Cleared as consumer wellness device
- CE Mark: Approved for sale in Europe
- General Availability: Direct consumer sales
- Current Status: Not FDA cleared for medical use
- Research Use: Available for clinical research under IRB
- Future: Exploring FDA clearance for specific applications
¶ Privacy and Data
- On-device Processing: Neural data processed locally
- Cloud Option: Optional cloud analysis (user consent required)
- Data Ownership: Users own their neural data
¶ Partnerships and Integrations
- Snapchat: Mind control features in the app
- Spectacles: AR glasses with BCI integration
- Bitmoji: Mind-controlled avatars
- Lens Studio: AR filters triggered by attention
- Academic Collaborations: Multiple university research programs
- Neuroscience Labs: Used in vision and attention research
- Cognitive Science: Studies on perception and attention
- Gaming: Integration with major gaming platforms
- Meditation Apps: Partnerships with mindfulness companies
- Enterprise: Focus and productivity monitoring tools
- Visual Attention Studies: Mapping attention in visual cortex
- Perceptual Learning: Training effects on visual processing
- Consciousness Research: Studying visual awareness
- Eye Tracking Integration: Combined with eye movement research
- Attention Research: Measuring sustained and selective attention
- Working Memory: Neural correlates of memory load
- Decision Making: Neural signatures of choice
- Meditation Research: Brain states during mindfulness
- Signal Processing: Developing better EEG algorithms
- Machine Learning: Improving BCI classification
- Neurofeedback: Training protocols and outcomes
- Usability Studies: User experience with consumer BCIs
¶ Limitations and Challenges
- Spatial Resolution: Limited to centimeter-scale resolution
- Signal Contamination: Susceptible to eye and muscle artifacts
- Individual Variability: Performance varies across users
- Training Required: Users need practice to achieve accuracy
- Environmental Sensitivity: Performance affected by electrical interference
- Movement Constraints: Head movement degrades signal quality
- Limited Applications: Cannot control complex prosthetics
- Attention Requirements: Requires sustained mental effort
While NextMind offers accessibility, invasive BCIs provide:
- Higher spatial resolution for precise control
- More stable signals over long periods
- Ability to record from deeper brain structures
- Direct neural control of complex devices
- More Electrodes: Higher density arrays in development
- Dry Electrode Advances: Improved comfort and signal quality
- Form Factor: Smaller, more comfortable devices
- Wireless: True wireless (no headband) designs
- Better Algorithms: Improved machine learning models
- More Applications: Expanded use case library
- Personalization: User-specific calibration
- Cloud Analytics: Aggregated insights from user data
- FDA Clearances: Pursuing medical device approvals
- Clinical Trials: Testing efficacy for specific conditions
- Rehabilitation: Stroke and neurological recovery programs
- Monitoring: Long-term cognitive health tracking