Multisensory integration using dynamical Bayesian networks
نویسندگان
چکیده
منابع مشابه
Multisensory integration using dynamical Bayesian networks
Multisensory Integration (MSI) is the study of how information coming from different sensory modalities, such as vision, audition and etc. are being integrated by the nervous system (Stein et al., 2009) as a complex system. MSI is one of the most important aspects of neuroscience which has a great influence on our decision making system. It plays a key role in our understanding of surrounding e...
متن کاملComparing Bayesian models for multisensory cue combination without mandatory integration
Bayesian models of multisensory perception traditionally address the problem of estimating an underlying variable that is assumed to be the cause of the two sensory signals. The brain, however, has to solve a more general problem: it also has to establish which signals come from the same source and should be integrated, and which ones do not and should be segregated. In the last couple of years...
متن کاملBayesian Filtering in Spiking Neural Networks: Noise, Adaptation, and Multisensory Integration Online Appendix
As mentioned in the paper, the full derivation of the filtering equation (2.4) is presented in [1]. The derivation in [1] is more general than the context of the paper, and uses very sophisticated mathematical tools. In this appendix we present a simplified outline of this derivation. We are aware that in our particular case of interest, the same results can be derived from discrete-time approx...
متن کاملBayesian multisensory integration and cross-modal spatial links.
Our perception of the word is the result of combining information between several senses, such as vision, audition and proprioception. These sensory modalities use widely different frames of reference to represent the properties and locations of object. Moreover, multisensory cues come with different degrees of reliability, and the reliability of a given cue can change in different contexts. Th...
متن کاملBayesian Filtering in Spiking Neural Networks: Noise, Adaptation, and Multisensory Integration
A key requirement facing organisms acting in uncertain dynamic environments is the real-time estimation and prediction of environmental states, based on which effective actions can be selected. While it is becoming evident that organisms employ exact or approximate Bayesian statistical calculations for these purposes, it is far less clear how these putative computations are implemented by neura...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Computational Neuroscience
سال: 2015
ISSN: 1662-5188
DOI: 10.3389/fncom.2015.00058