Yu, Angela J ; Dayan, Peter (2004)
Inference, Attention, and Decision in a Bayesian Neural Architecture.
NIPS 2004. Vancouver (13.12.2004-18.12.2004)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We study the synthesis of neural coding, selective attention and percep- tual decision making. A hierarchical neural architecture is proposed, which implements Bayesian integration of noisy sensory input and top- down attentional priors, leading to sound perceptual discrimination. The model offers an explicit explanation for the experimentally observed modulation that prior information in one stimulus feature (location) can have on an independent feature (orientation). The network's intermediate levels of representation instantiate known physiological properties of vi- sual cortical neurons. The model also illustrates a possible reconciliation of cortical and neuromodulatory representations of uncertainty.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2004 |
Autor(en): | Yu, Angela J ; Dayan, Peter |
Art des Eintrags: | Bibliographie |
Titel: | Inference, Attention, and Decision in a Bayesian Neural Architecture |
Sprache: | Englisch |
Publikationsjahr: | 2004 |
Ort: | Cambridge |
Verlag: | MIT Press |
Buchtitel: | Advances in Neural Information Processing Systems 17 (NIPS 2004) |
Band einer Reihe: | 17 |
Veranstaltungstitel: | NIPS 2004 |
Veranstaltungsort: | Vancouver |
Veranstaltungsdatum: | 13.12.2004-18.12.2004 |
URL / URN: | https://proceedings.neurips.cc/paper_files/paper/2004/hash/0... |
Kurzbeschreibung (Abstract): | We study the synthesis of neural coding, selective attention and percep- tual decision making. A hierarchical neural architecture is proposed, which implements Bayesian integration of noisy sensory input and top- down attentional priors, leading to sound perceptual discrimination. The model offers an explicit explanation for the experimentally observed modulation that prior information in one stimulus feature (location) can have on an independent feature (orientation). The network's intermediate levels of representation instantiate known physiological properties of vi- sual cortical neurons. The model also illustrates a possible reconciliation of cortical and neuromodulatory representations of uncertainty. |
Fachbereich(e)/-gebiet(e): | 03 Fachbereich Humanwissenschaften 03 Fachbereich Humanwissenschaften > Institut für Psychologie |
Hinterlegungsdatum: | 31 Okt 2023 09:42 |
Letzte Änderung: | 01 Nov 2023 07:21 |
PPN: | 512786380 |
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