scholarly journals Front-end Weber-Fechner gain control enhances the fidelity of combinatorial odor coding

2018 ◽  
Author(s):  
Nirag Kadakia ◽  
Thierry Emonet
Keyword(s):  
Scaling Law ◽  
Gain Control ◽  
Vital Role ◽  
Biophysical Model ◽  
Natural Environments ◽  
Odor Coding ◽  
Tuning Curves ◽  
Front End ◽  
Receptor Neurons ◽  
Odor Signals

Odor identity is encoded by spatiotemporal patterns of activity in olfactory receptor neurons (ORNs). In natural environments, the intensity and timescales of odor signals can span several orders of magnitude, and odors can mix with one another, potentially scrambling the combinatorial code mapping neural activity to odor identity. Recent studies have shown that inDrosophila melanogasterthe ORNs that express the olfactory co-receptor Orco scale their gain inversely with mean odor concentration according to the Weber-Fechner Law of psychophysics. Here we use a minimal biophysical model of signal transduction, ORN firing, and signal decoding to investigate the implications of this front-end scaling law for the neural representations of odor identity. We find that Weber-Fechner scaling enhances coding capacity and promotes the reconstruction of odor identity from dynamic odor signals, even in the presence of confounding background odors and rapid intensity fluctuations. We show that these enhancements are further aided by downstream transformations in the antennal lobe and mushroom body. Thus, despite the broad overlap between individual ORN tuning curves, a mechanism of front-end adaptation, when endowed with Weber-Fechner scaling, may play a vital role in preserving representations of odor identity in naturalistic odor landscapes.

scholarly journals Front-end Weber-Fechner gain control enhances the fidelity of combinatorial odor coding

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Nirag Kadakia ◽  
Thierry Emonet
Keyword(s):  
Gain Control ◽  
Feedback Mechanism ◽  
Olfactory Receptor Neurons ◽  
Receptor Sensitivity ◽  
Adaptation Mechanism ◽  
Odor Coding ◽  
Front End ◽  
Receptor Neurons ◽  
Odor Classification ◽  
Odor Signals

We showed previously (Gorur-Shandilya et al., 2017) that Drosophila olfactory receptor neurons (ORNs) expressing the co-receptor Orco scale their gain inversely with mean odor intensity according to Weber-Fechner’s law. Here, we show that this front-end adaptation promotes the reconstruction of odor identity from dynamic odor signals, even in the presence of confounding background odors and rapid intensity fluctuations. These enhancements are further aided by known downstream transformations in the antennal lobe and mushroom body. Our results, which are applicable to various odor classification and reconstruction schemes, stem from the fact that this adaptation mechanism is not intrinsic to the identity of the receptor involved. Instead, a feedback mechanism adjusts receptor sensitivity based on the activity of the receptor-Orco complex, according to Weber-Fechner’s law. Thus, a common scaling of the gain across Orco-expressing ORNs may be a key feature of ORN adaptation that helps preserve combinatorial odor codes in naturalistic landscapes.

scholarly journals 14.85 µW Analog Front-End for Photoplethysmography Acquisition with 142-dBΩ Gain and 64.2-pArms Noise

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 512
Author(s):  
Binghui Lin ◽  
Mohamed Atef ◽  
Guoxing Wang
Keyword(s):  
Dynamic Range ◽  
Automatic Gain Control ◽  
Gain Control ◽  
Low Noise ◽  
Total Power ◽  
Cmos Process ◽  
Control Block ◽  
Silicon Area ◽  
Front End ◽  
Analog Front End

A low-power, high-gain, and low-noise analog front-end (AFE) for wearable photoplethysmography (PPG) acquisition systems is designed and fabricated in a 0.35 μm CMOS process. A high transimpedance gain of 142 dBΩ and a low input-referred noise of only 64.2 pArms was achieved. A Sub-Hz filter was integrated using a pseudo resistor, resulting in a small silicon area. To mitigate the saturation problem caused by background light (BGL), a BGL cancellation loop and a new simple automatic gain control block are used to enhance the dynamic range and improve the linearity of the AFE. The measurement results show that a DC photocurrent component up-to-10 μA can be rejected and the PPG output swing can reach 1.42 Vpp at THD < 1%. The chip consumes a total power of 14.85 μW using a single 3.3-V power supply. In this work, the small area and efficiently integrated blocks were used to implement the PPG AFE and the silicon area is minimized to 0.8 mm × 0.8 mm.

Design of Local Oscillator Based on DDS of High Performance Short-Wave Receiver

2013 ◽  
Vol 834-836 ◽  
pp. 1140-1144 ◽  
Author(s):  
Yong Tai Chen ◽  
Chang Jing Sun ◽  
Bin Zang ◽  
Long Cheng ◽  
Jing Tang ◽  
...  
Keyword(s):  
High Performance ◽  
Gain Control ◽  
Local Oscillator ◽  
Short Wave ◽  
Frequency Multiplier ◽  
Test Results ◽  
Frequency Range ◽  
Front End ◽  
Tracking Filter ◽  
Spurious Signals

Phase noise and spurious signals of local oscillator will affect the performance of short-wave receiver. The structure of receiver's front-end part based on DDS is introduced to realize a high-performance local oscillator of short-wave receiver. Then measures were taken to improve the LO's performance, including using external directly frequency multiplier as DDS' clock to improve the purity of frequency spectrum, tracking filter to degrade harmonics and gain control circuit to remain constant amplitude in the desired frequency range. At last, test results show that the above-mentioned measures improve the receiver's performance.

scholarly journals Antagonism in olfactory receptor neurons and its implications for the perception of odor mixtures

2017 ◽  
Author(s):  
Gautam Reddy ◽  
Joseph Zak ◽  
Massimo Vergassola ◽  
Venkatesh N. Murthy
Keyword(s):  
Olfactory Receptor ◽  
Olfactory Receptor Neurons ◽  
Natural Environments ◽  
Response Curves ◽  
Inhibitory Mechanisms ◽  
Calcium Indicator ◽  
Odor Mixtures ◽  
Sensory Pathway ◽  
Receptor Neurons

AbstractNatural environments feature mixtures of odorants of diverse quantities, qualities and complexities. Olfactory receptor neurons (ORNs) are the first layer in the sensory pathway and transmit the olfactory signal to higher regions of the brain. Yet, the response of ORNs to mixtures is strongly non-additive, and exhibits antagonistic interactions among odorants. Here, we model the processing of mixtures by mammalian ORNs, focusing on the role of inhibitory mechanisms. Theoretically predicted response curves capture experimentally determined glomerular responses imaged by a calcium indicator expressed in ORNs of live, breathing mice. Antagonism leads to an effective “normalization” of the ensemble glomerular response, which arises from a novel mechanism involving the distinct statistical properties of receptor binding and activation, without any recurrent neuronal circuitry. Normalization allows our encoding model to outperform noninteracting models in odor discrimination tasks, and to explain several psychophysical experiments in humans.

scholarly journals An update on anatomy and function of the teleost olfactory system

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7808 ◽  
Author(s):  
Jesús Olivares ◽  
Oliver Schmachtenberg
Keyword(s):  
Olfactory System ◽  
Olfactory Receptor Neurons ◽  
Odorant Receptors ◽  
Odor Coding ◽  
Animal Group ◽  
Different Types ◽  
Olfactory Systems ◽  
Receptor Neurons ◽  
Olfactory Organs ◽  
And Function

About half of all extant vertebrates are teleost fishes. Although our knowledge about anatomy and function of their olfactory systems still lags behind that of mammals, recent advances in cellular and molecular biology have provided us with a wealth of novel information about the sense of smell in this important animal group. Its paired olfactory organs contain up to five types of olfactory receptor neurons expressing OR, TAAR, VR1- and VR2-class odorant receptors associated with individual transduction machineries. The different types of receptor neurons are preferentially tuned towards particular classes of odorants, that are associated with specific behaviors, such as feeding, mating or migration. We discuss the connections of the receptor neurons in the olfactory bulb, the differences in bulbar circuitry compared to mammals, and the characteristics of second order projections to telencephalic olfactory areas, considering the everted ontogeny of the teleost telencephalon. The review concludes with a brief overview of current theories about odor coding and the prominent neural oscillations observed in the teleost olfactory system.

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