File size: 1,866 Bytes
815055c 6aa5daa 932d9ba dac4f78 815055c 335b093 815055c a074dd6 a189f0d 335b093 a074dd6 0f544c9 a189f0d 0f544c9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | ---
license: gpl-3.0
library_name: manas-1
# model-index:
# - name: MANAS-1
# results:
# - task:
# type: motor-imagery
# dataset:
# name: BCI-IV-2a
# type: BCI-IV-2a
# metrics:
# - name: Balanced Accuracy
# type: balanced_accuracy
# value: 0.489
---
# MANAS-1
NeuroDX announces India's first Brain Language Model, MANAS-1. Designed as a Foundation Model for EEGs, MANAS-1 demonstrates SOTA performance across various tasks in BCI and clinical applications.
More details coming soon!
## Benchmarking Results:
More benchmark results will be added soon.
#### EEG-Bench Results
These metrics were computed using the EEG-Bench codebase. MANAS-1 and REVE (reve-base) were finetuned with a flatten-MLP setup. Finetuning setups for LaBraM and NeuroGPT were used as present in the EEG-Bench codebase.
| Dataset | REVE | MANAS-1 | LaBraM | NeuroGPT |
|-------------------|--------------------|--------------------|--------------------|-------------------|
| BCI-IV-2b | <u>0.712 ± 0.01</u> | **0.723 ± 0.01** | 0.707 ± 0.02 | 0.709 |
| Cho2017 | 0.526 ± 0.09 | <u>0.533 ± 0.02</u> | 0.504 ± 0.01 | **0.651 ± 0** |
| BCI-IV-2a | 0.434 ± 0.10 | **0.489 ± 0.03** | 0.303 ± 0.04 | <u>0.461 ± 0.00</u> |
| Faller2012 | **0.566 ± 0.03** | <u>0.560 ± 0.01</u> | 0.542 ± 0.01 | 0.513 |
| PhysioNet | 0.348 ± 0.08 | <u>0.368 ± 0.01</u> | 0.284 ± 0.01 | **0.375 ± 0.00** |
| Weibo2014 | **0.335 ± 0.04** | <u>0.321 ± 0.01</u> | 0.254 ± 0.02 | 0.303 |
| Zhou2016 | 0.818 ± 0.16 | **0.865 ± 0.01** | 0.687 ± 0.19 | <u>0.834</u> |
|