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| Content Provider | Semantic Scholar |
|---|---|
| Author | Doswell, Jayfus T. |
| Copyright Year | 2018 |
| Abstract | Brain computer interfaces (BCI) (i.e., also known as Brain Machine Interfaces) have the potential to improve human cognition ranging from implantable neuro-prosthesis to repair parts of the injured brain’s hippocampus (i.e., to convert short-term memories into long-term memories); facilitate non-verbal communication among teams of peers; and restore active memories to accelerating human learning and skill acquisition with noninvasive neural-engineering and computational brain-to-human neuron mapping. Although advances have been made in BCI for improving human cognition, this subset of BCI is very new and requires empirical multidisciplinary research to solve challenges including, but not limited to usability, training, information transfer rate, non-linearity, non-stationarity/noise, and high dimensionality. |
| Starting Page | 183 |
| Ending Page | 183 |
| Page Count | 1 |
| File Format | PDF HTM / HTML |
| DOI | 10.1177/1059712318789546 |
| Volume Number | 26 |
| Alternate Webpage(s) | https://www.aapt.org/aboutaapt/ennouncer/upload/GIREP2019_description-Letter.pdf |
| Alternate Webpage(s) | https://www.iaria.org/conferences2017/filesCOGNITIVE17/BRAINCOMAUG.pdf |
| Alternate Webpage(s) | https://doi.org/10.1177/1059712318789546 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
