Olfactory object recognition, segmentation, adaptation, target seeking, and discrimination by the network of the olfactory bulb and cortex: computational model and experimental data

2016 ◽  
Vol 11 ◽  
pp. 30-39 ◽  
Author(s):  
Li Zhaoping
2020 ◽  
Author(s):  
Daniel Zavitz ◽  
Isaac A. Youngstrom ◽  
Alla Borisyuk ◽  
Matt Wachowiak

AbstractLateral inhibition is a fundamental feature of circuits that process sensory information. In the mammalian olfactory system, inhibitory interneurons called short axon cells comprise the first network mediating lateral inhibition between glomeruli, the functional units of early olfactory coding and processing. The connectivity of this network and its impact on odor representations is not well understood. To explore this question, we constructed a computational model of the interglomerular inhibitory network using detailed characterizations of short axon cell morphologies taken from mouse olfactory bulb. We then examined how this network transformed glomerular patterns of odorant-evoked sensory input (taken from previously-published datasets) as a function of the selectivity of interglomerular inhibition. We examined three connectivity schemes: selective (each glomerulus connects to few others with heterogeneous strength), nonselective (glomeruli connect to most others with heterogenous strength) or global (glomeruli connect to all others with equal strength). We found that both selective and nonselective interglomerular networks could mediate heterogeneous patterns of inhibition across glomeruli when driven by realistic sensory input patterns, but that global inhibitory networks were unable to produce input-output transformations that matched experimental data and were poor mediators of intensity-dependent gain control. We further found that networks whose interglomerular connectivity was tuned by sensory input profile decorrelated odor representations more effectively. These results suggest that, despite their multiglomerular innervation patterns, short axon cells are capable of mediating odorant-specific patterns of inhibition between glomeruli that could, theoretically, be tuned by experience or evolution to optimize discrimination of particular odorants.Significance StatementLateral inhibition is a key feature of circuitry in many sensory systems including vision, audition, and olfaction. We investigate how lateral inhibitory networks mediated by short axon cells in the mouse olfactory bulb might shape odor representations as a function of their interglomerular connectivity. Using a computational model of interglomerular connectivity derived from experimental data, we find that short axon cell networks, despite their broad innervation patterns, can mediate heterogeneous patterns of inhibition across glomeruli, and that the canonical model of global inhibition does not generate experimentally observed responses to stimuli. In addition, inhibitory connections tuned by input statistics yield enhanced decorrelation of similar input patterns. These results elucidate how the organization of inhibition between neural elements may affect computations.


2013 ◽  
Vol 109 (5) ◽  
pp. 1360-1377 ◽  
Author(s):  
Licurgo de Almeida ◽  
Marco Idiart ◽  
Christiane Linster

In this work we investigate in a computational model how cholinergic inputs to the olfactory bulb (OB) and piriform cortex (PC) modulate odor representations. We use experimental data derived from different physiological studies of ACh modulation of the bulbar and cortical circuitry and the interaction between these two areas. The results presented here indicate that cholinergic modulation in the OB significantly increases contrast and synchronization in mitral cell output. Each of these effects is derived from distinct neuronal interactions, with different groups of interneurons playing different roles. Both bulbar modulation effects contribute to more stable learned representations in PC, with pyramidal networks trained with cholinergic-modulated inputs from the bulb exhibiting more robust learning than those trained with unmodulated bulbar inputs. This increased robustness is evidenced as better recovery of memories from corrupted patterns and lower-concentration inputs as well as increased memory capacity.


2013 ◽  
Vol 17 (5) ◽  
pp. 1504-1507 ◽  
Author(s):  
Zhi-Fei Li ◽  
Zheng Du ◽  
Kai Zhang ◽  
Dong-Sheng Li ◽  
Zhong-Di Su ◽  
...  

Three-dimensional computational model for a gas turbine flowmeter is proposed, and the finite volume based SIMPLEC method and k-? turbulence model are used to obtain the detailed information of flow field in turbine flowmeter, such as velocity and pressure distribution. Comparison between numerical results and experimental data reveals a good agreement. A rectifier with little pressure loss is optimally designed and validated numerically and experimentally.


2007 ◽  
Vol 347 ◽  
pp. 19-34 ◽  
Author(s):  
Michael Link ◽  
Stefan Stöhr ◽  
Matthias Weiland

Computational model updating techniques are used to adjust selected parameters of finite element models in order to make the models compatible with experimental data. This is done by minimizing the differences of analytical and experimental data, for example, natural frequencies and mode shapes by numerical optimization procedures. For a long time updating techniques have also been investigated with regard to their ability to localize and quantify structural damage. The success of such an approach is mainly governed by the quality of the damage model and its ability to describe the structural property changes due to damage in a physical meaningful way. Our experience has shown that due to unavoidable modelling simplifications and measurement errors the changes of the corresponding damage parameters do not always indicate structural modifications introduced by damage alone but indicate also the existence of other modelling uncertainties which may be distributed all over the structure. This means that there are two types of parameters which have to be distinguished: the damage parameters and the other parameters accounting for general modelling and test data uncertainties. Although these general parameters may be physically meaningless they are necessary to achieve a good fit of the test data and it might happen that they cannot be distinguished from the damage parameters. For complex industrial structures it is seldom possible to generate unique structural models covering all possible damage scenarios so that one has to expect, that the parameters introduced for describing the damage will not be fully consistent with the physical reality. This is the reason why in the scientific community there is still some doubt if model based techniques can be used at all for practical purposes of damage detection and quantification under in-situ environment conditions. In the present paper we summarize the methodology of computational model updating and report about our experience with damage identification exemplified by practical examples. A new technique and an application of localising and quantifying the damage from updating the parameters of the damaged and the undamaged models simultaneously using the differences of the test data from the damaged and the undamaged structure is also presented. In this application we used the deflections (influence lines) of a beam structure measured under a slowly moving load.


1993 ◽  
Vol 69 (6) ◽  
pp. 1948-1965 ◽  
Author(s):  
U. S. Bhalla ◽  
J. M. Bower

1. Detailed compartmental computer simulations of single mitral and granule cells of the vertebrate olfactory bulb were constructed using previously published geometric data. Electrophysiological properties were determined by comparing model output to previously published experimental data, mainly current-clamp recordings. 2. The passive electrical properties of each model were explored by comparing model output with intracellular potential data from hyperpolarizing current injection experiments. The results suggest that membrane resistivity in both cells is nonuniform, with somatas having a substantially lower resistivity than the dendrites. 3. The active properties of these cells were explored by incorporating active ion channels into modeled compartments. On the basis of evidence from the literature, the mitral cell model included six channel types: fast sodium, fast delayed rectifier (Kfast), slow delayed rectifier (K), transient outward potassium current (KA), voltage- and calcium-dependent potassium current (KCa), and L-type calcium current. The granule cell model included four channel types: rat brain sodium, K, KA, and the non-inactivating muscarinic potassium current (KM). Modeled channels were based on the Hodgkin-Huxley formalism. 4. Representative kinetics for each of the channel classes above were obtained from the literature. The experimentally unknown spatial distributions of each included channel were obtained by systematic parameter searches. These were conducted in two ways: large-scale simulation series, in which each parameter was varied in turn, and an adaptation of a multidimensional conjugate gradient method. In each case, the simulated results were compared wtih experimental data using a curve-matching function evaluating mean squared differences of several aspects of the simulated and experimental voltage waveforms. 5. Systematic parameter variations revealed a single distinct region of parameter space in which the mitral cell model best fit the data. This region of parameter space was also very robust to parameter variations. Specifically, optimum performance was obtained when calcium and slow K channels were concentrated in the glomeruli, with a lower density in the soma and proximal secondary dendrites. The distribution of sodium and fast potassium channels, on the other hand, was highest at the soma and axon, with a much lighter distribution throughout the secondary dendrites. The KA and KCa channels were also concentrated near the soma. 6. The parameter search of the granule cell model was much less restrained by experimental data. Several parameter regimes were found that gave a good match to the data.(ABSTRACT TRUNCATED AT 400 WORDS)


2013 ◽  
Vol 597 ◽  
pp. 125-130 ◽  
Author(s):  
Krzysztof J. Kalinski ◽  
Marek A. Galewski ◽  
Michał R. Mazur

The paper presents the method of the surveillance of the self-excited chatter vibration. At first, the workpiece modal parameters are estimated based on experimental data which leads to verification of computational model. Then, for selected surface points optimal spindle speeds are calculated. By considering sufficient amount of points it is possible to build a map of optimal spindle speeds. Experimental results show that this map may be used effectively for eliminating chatter in case of the process of ball end milling of a curved flexible detail.


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