On extracting spiking network models from experiments - with Richard Gao - #38
Failed to add items
Sorry, we are unable to add the item because your shopping basket is already at capacity.
Add to cart failed.
Please try again later
Add to wishlist failed.
Please try again later
Remove from wishlist failed.
Please try again later
Follow podcast failed
Unfollow podcast failed
On extracting spiking network models from experiments - with Richard Gao - #38
-
Narrated by:
-
Written by:
While some models aim to explain qualitative features of brain activity, other aim to reproduce experimental data quantitatively. If so, model parameters must be adjusted to make the model predictions fit the experimental data.
A complication is that in most neurobiological applications, there is not a unique best fit: many parameter combinations give equally good model fits.
Recently, the guest, together with colleagues, made the tool AutoMIND to fit spiking network models to data.
adbl_web_anon_alc_button_suppression_c
No reviews yet