Pregled bibliografske jedinice broj: 457668
Brightness estimation in a neural network model with presynaptic inhibition
Brightness estimation in a neural network model with presynaptic inhibition // Fechner Day Proceedings of the 25th Annual Meeting of the International Society for Psychophysics / Elliott, M.A. ; Antonijevic, S. Berthaud ; Mulchay, P ; Martyn, C ; Bargery, B ; Schmidt, H ; (ur.).
Galway: International Society for Psychophysics, 2009. str. 359-362 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 457668 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Brightness estimation in a neural network model with presynaptic inhibition
Autori
Rebić, Veseljka ; Šetić, Mia ; Domijan, Dražen
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Fechner Day Proceedings of the 25th Annual Meeting of the International Society for Psychophysics
/ Elliott, M.A. ; Antonijevic, S. Berthaud ; Mulchay, P ; Martyn, C ; Bargery, B ; Schmidt, H ; - Galway : International Society for Psychophysics, 2009, 359-362
Skup
Fechner Day 2009
Mjesto i datum
Irska, 21.09.2009. - 24.09.2009
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
jarkost; svjetlina; percpecija; neuralna mreža
(brightness; perception; neural network)
Sažetak
Recent psychophysical and neurophysiological investigations showed that visual system encodes luminance and use it to estimate illumination and surface brightness. We proposed a novel neural model for luminance coding based on recurrent inhibition, from the retinal ganglion cells to the axons of the bipolar cells, which modulates the amount of sensory input that ganglion cells receive (Sagdullaev et al., 2006). Extended version of the model, where the amount of presynaptic inhibition is made proportional to the maximum luminance in the visual scene, implements gain control mechanism which adjusts the raw luminance into a measure of brightness of surface. Computer simulations showed that the model scales brightness estimates consistent with the highest-luminance-as-white anchoring rule (Gilchist et al., 2004). Simulations also showed that the model is able to act as a change detector when the presynaptic inhibition temporally lags behind the excitatory input to the ganglion cell.
Izvorni jezik
Engleski
Znanstvena područja
Psihologija
POVEZANOST RADA
Projekti:
130-0000000-3295 - Integracija informacija kao osnova cjelovitog doživljavanja (Ivanec, Dragutin, MZOS ) ( CroRIS)
Ustanove:
Filozofski fakultet, Zagreb