scholarly journals Gain modulation and odor concentration invariance in early olfactory networks

2019 ◽  
Author(s):  
Emiliano Marachlian ◽  
Ramon Huerta ◽  
Fernando F. Locatelli
Keyword(s):  
Signal Processing ◽  
Antennal Lobe ◽  
Activity Patterns ◽  
Olfactory Receptors ◽  
Gaba A ◽  
Early Signal ◽  
Dependent Inhibition ◽  
Odorant Molecule ◽  
Processing Properties ◽  
Temporal Profiles

A conserved principle of the olfactory system, in most, if not all animals, is that each olfactory receptor interacts with different odorant molecules and each odorant molecule interacts with different olfactory receptors. This broad receptive field of the receptors constitutes the basis of a combinatorial code that allows animals to discriminate many more odorants than the actual number of receptor types that they express. A drawback is that high odorant concentrations recruit lower affinity receptors, which can give rise to the perception of qualitatively different odors. Here we addressed the contribution that early signal-processing in the honey bee antennal lobe does to keep odor representation stable across concentrations. We describe the contribution that GABA-A and GABA-B receptors-dependent-inhibition plays in terms of the amplitude and temporal profiles of the signals that convey odor information from the antennal lobes to the mushroom bodies. GABA reduces the amplitude of odor elicited signals and the number of glomeruli that are recruited in a concentration-dependent way. Blocking GABA-A and GABA-B receptors decreases the correlation among glomerular activity patterns elicited by different concentrations of the same odor. Based on the results we built a realistic computational model of the antennal lobe that could be further used to evaluate the signal processing properties of the AL network under conditions that cannot be achieved in physiology experiments. Interestingly, even though based on rather simplistic topology and interactions among cells solely mediated by GABA-A and GABA-B interactions, the AL model reproduced the key features of the AL stable response in relation to different concentrations.

Structure-dependent inhibition of the human α 1 β 2 γ 2 GABA A receptor by piperazine derivatives: A novel mode of action

2015 ◽  
Vol 51 ◽  
pp. 1-9 ◽  
Author(s):  
Laura Hondebrink ◽  
Elise J.P. Hermans ◽  
Stijn Schmeink ◽  
Regina G.D.M. van Kleef ◽  
Jan Meulenbelt ◽  
...  
Keyword(s):  
Mode Of Action ◽  
Gaba A ◽  
Piperazine Derivatives ◽  
Dependent Inhibition

scholarly journals Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures

2019 ◽  
Vol 116 (19) ◽  
pp. 9598-9603 ◽  
Author(s):  
Vijay Singh ◽  
Nicolle R. Murphy ◽  
Vijay Balasubramanian ◽  
Joel D. Mainland
Keyword(s):  
Olfactory Receptors ◽  
Competitive Binding ◽  
Complex Mixtures ◽  
Biophysical Model ◽  
Target Color ◽  
Receptor Binding Site ◽  
Binding Model ◽  
Vast Number ◽  
Nonlinear Responses ◽  
Odorant Molecule

In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding (CB): Only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to 12 monomolecular odorants to within 15% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive-binding model.

Experimental Study of Mine AE Signal Based on Wavelet Analysis

2011 ◽  
Vol 148-149 ◽  
pp. 1127-1130 ◽  
Author(s):  
Xiu Zhi Cheng ◽  
Zhen Yu ◽  
Guang Zhu
Keyword(s):  
Experimental Study ◽  
Signal Processing ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Frequency Domain ◽  
Activity Patterns ◽  
Audio Signal ◽  
P Wave ◽  
Audio Signal Processing ◽  
Ae Signal

Because the wavelet transform can characterize the local signals in time and frequency domain, in the coal mine’s sound signals’ process, an audio signal processing based on wavelet analysis is proposed, the audio signal P wave is isolated and determined by wavelet transform, at the same time, the earthquake source can be located. Through the research of the mine AE signal’s activity patterns, the sound monitoring technology to forecast the mine power disaster is achieved.

scholarly journals Inhibitory connections in the honeybee antennal lobe are spatially patchy

2013 ◽  
Vol 109 (2) ◽  
pp. 332-343 ◽  
Author(s):  
Cyrille C. Girardin ◽  
Sabine Kreissl ◽  
C. Giovanni Galizia
Keyword(s):  
Sensory Processing ◽  
Antennal Lobe ◽  
Functional Organization ◽  
Classical Model ◽  
Activity Patterns ◽  
Spatial Logic ◽  
Brain Center ◽  
In Vivo Calcium Imaging ◽  
Inhibitory Interactions

The olfactory system is a classical model for studying sensory processing. The first olfactory brain center [the olfactory bulb of vertebrates and the antennal lobe (AL) of insects] contains spherical neuropiles called glomeruli. Each glomerulus receives the information from one olfactory receptor type. Interglomerular computation is accomplished by lateral connectivity via interneurons. However, the spatial and functional organization of these lateral connections is not completely understood. Here we studied the spatial logic in the AL of the honeybee. We combined topical application of neurotransmitters, olfactory stimulations, and in vivo calcium imaging to visualize the arrangement of lateral connections. Suppression of activity in a single glomerulus with γ-aminobutyric acid (GABA) while presenting an odor reveals the existence of inhibitory interactions. Stimulating a glomerulus with acetylcholine (ACh) activates inhibitory interglomerular connections that can reduce odor-evoked responses. We show that this lateral network is patchy, in that individual glomeruli inhibit other glomeruli with graded strength, but in a spatially discontinuous manner. These results suggest that processing of olfactory information requires combinatorial activity patterns with complex topologies across the AL.

Signal processing properties of fast spiking interneurons

Biosystems ◽  
2006 ◽  
Vol 86 (1-3) ◽  
pp. 27-37 ◽  
Author(s):  
Angelo Di Garbo ◽  
Michele Barbi ◽  
Santi Chillemi
Keyword(s):  
Signal Processing ◽  
Fast Spiking ◽  
Processing Properties

scholarly journals Genetic variation across the human olfactory receptor repertoire alters odor perception

2019 ◽  
Vol 116 (19) ◽  
pp. 9475-9480 ◽  
Author(s):  
C. Trimmer ◽  
A. Keller ◽  
N. R. Murphy ◽  
L. L. Snyder ◽  
J. R. Willer ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Activity Patterns ◽  
Olfactory Receptors ◽  
Functional Assay ◽  
Olfactory Perception ◽  
Receptor Function ◽  
Receptor Repertoire ◽  
And Gender

Humans use a family of more than 400 olfactory receptors (ORs) to detect odors, but there is currently no model that can predict olfactory perception from receptor activity patterns. Genetic variation in human ORs is abundant and alters receptor function, allowing us to examine the relationship between receptor function and perception. We sequenced the OR repertoire in 332 individuals and examined how genetic variation affected 276 olfactory phenotypes, including the perceived intensity and pleasantness of 68 odorants at two concentrations, detection thresholds of three odorants, and general olfactory acuity. Genetic variation in a single OR was frequently associated with changes in odorant perception, and we validated 10 cases in which in vitro OR function correlated with in vivo odorant perception using a functional assay. In 8 of these 10 cases, reduced receptor function was associated with reduced intensity perception. In addition, we used participant genotypes to quantify genetic ancestry and found that, in combination with single OR genotype, age, and gender, we can explain between 10% and 20% of the perceptual variation in 15 olfactory phenotypes, highlighting the importance of single OR genotype, ancestry, and demographic factors in the variation of olfactory perception.

scholarly journals Pattern recognition through source signal separation

2016 ◽  
Author(s):  
◽  
Luis Alberto Rivera
Keyword(s):  
Pattern Recognition ◽  
Signal Processing ◽  
Hyperspectral Image ◽  
Feature Vector ◽  
Activity Patterns ◽  
Hybrid Technique ◽  
Apparent Paradox ◽  
Hyperspectral Image Analysis ◽  
Independent Observations ◽  
Good Set

In typical problems involving pattern recognition, the challenge lies in selecting a good set of features and in devising a reliable algorithm to identify the class of learned patterns that most resembles the observed feature vector. Some times, however, the observed vector is not a single, but a mixture of multiple learned patterns and the challenge becomes to recognize all the present patterns and not just one of them. In order to do so, the patterns in the observed feature vector must first be separated -- an apparent paradox since the actual patterns forming the observed vector are hitherto unknown and should probably be identified first. At the same time, many techniques to separate mixture of signals have emerged from the literature in signal processing, but they require multiple and independent observations of the mixture of patterns, which is not usually possible or desirable in a pattern recognition setting. However, we believe that these two problems -- pattern separation and recognition -- are one and the same, and it can benefit from a hybrid technique derived from both contexts. So, in this research, we propose a technique based on Source Separation for recognizing patterns in mixtures of signals. From the signal processing perspective, our method can handle extremely under-determined cases, i.e., cases where one measurement is required despite the existence of multiple patterns mixed in the measurement -- a typical scenario from the pattern recognition perspective. We have run extensive tests to demonstrate the robustness and effectiveness of the method. We have also proposed frameworks for applications in various areas such as classification of chemical compounds using terahertz signatures; root phenotyping using terahertz imaging; recognition of muscle activity patterns using surface electromyographic signals (sEMG) for Robotic Assistive Technology; detection of vocal dysfunctions; and Hyperspectral Image analysis.

scholarly journals A competitive binding model predicts nonlinear responses of olfactory receptors to complex mixtures

2018 ◽  
Author(s):  
Vijay Singh ◽  
Nicolle R. Murphy ◽  
Vijay Balasubramanian ◽  
Joel D. Mainland
Keyword(s):  
Olfactory Receptors ◽  
Competitive Binding ◽  
Complex Mixtures ◽  
Biophysical Model ◽  
Target Color ◽  
Receptor Binding Site ◽  
Binding Model ◽  
Vast Number ◽  
Nonlinear Responses ◽  
Odorant Molecule

In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding (CB): only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to twelve monomolecular odorants to within 15% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive binding model.

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