Name
Abstract | ||
|---|---|---|
Construction and application of a neural prosthesis device that enhances existing and replaces lost memory capacity in humans is the focus of research described here in rodents. A unique approach for the analysis and application of neural population firing has been developed to decipher the pattern in which information is successfully encoded by the hippocampus where mnemonic accuracy is critical. A nonlinear dynamic multi-input multi-output (MIMO) model is utilized to extract memory relevant firing patterns in CA3 and CA1 and to predict online what the consequences of the encoded firing patterns reflect for subsequent information retrieval for successful performance of delayed-nonmatch-to-sample (DNMS) memory task in rodents. The MIMO model has been tested successfully in a number of different contexts, each of which produced improved performance by a) utilizing online predicted codes to regulate task difficulty, b) employing electrical stimulation of CA1 output areas in the same pattern as successful cell firing, c) employing electrical stimulation to recover cell firing compromised by pharmacological agents and d) transferring and improving performance in naive animals using the same stimulation patterns that are effective in fully trained animals. The results in rodents formed the basis for extension of the MIMO model to nonhuman primates in the same type of memory task that is now being tested in the last step prior to its application in humans. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IEMBS.2011.6090905 | 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Keywords | Field | DocType |
Hippocampal Prosthesis, Delayed Memory Task, Ensemble Activity, Nonlinear Model, Stimulation patterns, Memory enhancement and recovery | Hippocampal prosthesis,Population,Neuroscience,DECIPHER,Neurophysiology,Computer science,Neural Prosthesis,MIMO,Mnemonic,Encoding (memory) | Conference |
Volume | ISSN | Citations |
2011 | 1557-170X | 0 |
PageRank | References | Authors |
0.34 | 2 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert E Hampson | 1 | 105 | 12.12 |
| V Marmaralis | 2 | 0 | 0.34 |
| Dae C Shin | 3 | 24 | 5.57 |
| Greg A Gerhardt | 4 | 20 | 4.76 |
| dawn song | 5 | 0 | 0.34 |
| Rosa H M Chan | 6 | 182 | 22.79 |
| andrew j sweatt | 7 | 0 | 0.34 |
| John J. Granacki | 8 | 181 | 60.06 |
| theodore w berger | 9 | 380 | 87.26 |
| Sam A Deadwyler | 10 | 98 | 10.89 |