Tesi etd-05122019-162959 |
Link copiato negli appunti
Tipo di tesi
Tesi di laurea magistrale
Autore
FRUZZETTI, LORENZO
URN
etd-05122019-162959
Titolo
Analysis of intracortical recording in visual and premotor cortices using supervised learning algorithms
Dipartimento
BIOLOGIA
Corso di studi
NEUROSCIENCE
Relatori
relatore Caleo, Matteo
relatore Mazzoni, Alberto
relatore Mazzoni, Alberto
Parole chiave
- Decoding
- intracortical-recording
- premotor-cortex
- supervised-learning
- visual-cortex
Data inizio appello
27/05/2019
Consultabilità
Non consultabile
Data di rilascio
27/05/2089
Riassunto
In this thesis we will apply supervised learning algorithms in the classification of visual stimuli, using recording in the primary visual cortex, and of motor intention, using recording in the Anterior Lateral Motor cortex (ALM), in a mouse model. The two types of classifiers are: a k-nearest neighbors (KNN) and a feed forward neural network (FFNN).
In the first part we are going to compare the two types considering their behaviur changing different parameters, in the second part we are going to evaluate the change in performance over time.
In the first part we are going to compare the two types considering their behaviur changing different parameters, in the second part we are going to evaluate the change in performance over time.
File
| Nome file | Dimensione |
|---|---|
La tesi non è consultabile. |
|