# name
Biological neural networks: an application to odor information processing

# metadata.dc.description[].value
Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Any: 2014, Tutor: Agustí Gutiérrez

# metadata.dc.description.abstract[].value
Traditionally, there has been a lot of research on how the brain manages visual and
auditory inputs, but not that much attention has been devoted to the olfactory sensory system due,
in part, to the complex nature of volatile organic compounds (VOCs). The aim of this project is to
understand and build a computational neural model of the first stage of the olfactory pathway: the
glomerular layer. Some experts in the field, supported by experimental evidence, point at this first
stage as the neural location where an important aspect of odor information processing takes place:
odor segregation. Our working hypothesis states that this input layer performs normalization and
contrast and concentration enhancement over odorants before the odorant information is conveyed
to deeper olfactory structures for detection. By performing an experiment on the computed neural
network, we will be able to determine whether and how this odor segregation occurs. This is
achieved by statistical analysis of the structure of the high-dimensional output space, understood
as the spiking frequency and synchronization of glomerular neurons firing patterns.

# metadata.dc.title[].value
Biological neural networks: an application to odor information processing