Synaptic adaptation and odor-background segmentation

Linster, Christiane; Henry, Lauren; Kadohisa, Mikiko; Wilson, Donald A.

doi:10.1016/j.nlm.2006.09.011

Cited by 62 publications

(57 citation statements)

References 30 publications

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“…1D). As we have shown before, synaptic adaptation alone, implemented at the mitral-to-pyramidal cell synapse, leads to odor response habituation in pyramidal cells closely matching that observed electrophysiologically and capable of reproducing previous behavioral data showing habituation to background odorants (Linster et al 2007). However, when odor specificity of the formed habituation is tested by using simulated odorants with a high degree of overlap in OSN activation, simulation results do not show the same specificity as electrophysiological results ( Fig.…”

Section: Computational Modelingsupporting

confidence: 86%

“…In stable-odor environments, homosynaptic depression of afferent cortical synapses allows filtering of background odors (Best and Wilson 2004) and maintained responses to other markedly different odors, which activate a different, nondepressed set of afferents (e.g., odors presented against the background [Kadohisa and Wilson 2006;Linster et al 2007]). However, in situations where two familiar odors share similar, potentially overlapping sets of features and afferent input synapses, the modeling results (Figs.…”

Section: Cortical Plasticity and Odor Perceptionmentioning

confidence: 99%

“…1A). The individual elements of this model have been described in detail before Cleland 2002, 2004;Linster et al 2003) and have been interconnected for the present purposes (Linster et al 2007). Olfactory sensory neurons and olfactory bulb mitral cells exhibited odor responses similar to those described experimentally and the olfactory bulb model also exhibited weak odor-evoked oscillations in the gamma-frequency range.…”

Section: Computational Modelingmentioning

confidence: 99%

“…Each OSN, representing the population of OSNs expressing a given receptor, activated mitral and periglomerular cells in a single olfactory bulb glomerulus. Bulbar computations were those described previously with parameters detailed in Table 1 Cleland 2002, 2004;Linster et al 2007). …”

Section: Computational Modelingmentioning

confidence: 99%

“…Using a computational model of the olfactory system (Linster et al 2007), the results suggest that activity-dependent association fiber plasticity is necessary to account for the specificity of odor habituation. Furthermore, in behavioral experiments blockade of cholinergic muscarinic receptors during habituation enhances generalization of odor habituation, consistent with the modeling and with previous electrophysiological results.…”

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confidence: 99%

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Odor-specific habituation arises from interaction of afferent synaptic adaptation and intrinsic synaptic potentiation in olfactory cortex

Linster

Menon²,

Singh³

et al. 2009

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Segmentation of target odorants from background odorants is a fundamental computational requirement for the olfactory system and is thought to be behaviorally mediated by olfactory habituation memory. Data from our laboratory have shown that odor-specific adaptation in piriform neurons, mediated at least partially by synaptic adaptation between the olfactory bulb outputs and piriform cortex pyramidal cells, is highly odor specific, while that observed at the synaptic level is specific only to certain odor features. Behavioral data show that odor habituation memory at short time constants corresponding to synaptic adaptation is also highly odor specific and is blocked by the same pharmacological agents as synaptic adaptation. Using previously developed computational models of the olfactory system we show here how synaptic adaptation and potentiation interact to create the observed specificity of response adaptation. The model analyzes the mechanisms underlying the odor specificity of habituation, the dependence on functioning cholinergic modulation, and makes predictions about connectivity to and within the piriform neural network. Predictions made by the model for the role of cholinergic modulation are supported by behavioral results.

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Section: Computational Modelingsupporting

confidence: 86%

Section: Cortical Plasticity and Odor Perceptionmentioning

confidence: 99%

Section: Computational Modelingmentioning

confidence: 99%

Section: Computational Modelingmentioning

confidence: 99%

mentioning

confidence: 99%

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Odor-specific habituation arises from interaction of afferent synaptic adaptation and intrinsic synaptic potentiation in olfactory cortex

Linster

Menon²,

Singh³

et al. 2009

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Wilson

Chapuis

Sullivan

2015

Handbook of Olfaction and Gustation

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Computation in the Olfactory System

Linster

2017

Computational Models of Brain and Behavior

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Computational models are increasingly essential to systems neuroscience. Models serve as proofs of concept, tests of sufficiency, and as quantitative embodiments of working hypotheses and are important tools for understanding and interpreting complex data sets. In the olfactory system, models have played a particularly prominent role in framing contemporary theories and presenting novel hypotheses, a role that will only grow as the complexity and intricacy of experimental data continue to increase. This review will attempt to provide a comprehensive, functional overview of computational ideas in olfaction and outline a computational framework for olfactory processing based on the insights provided by these diverse models and their supporting data.

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Synaptic adaptation and odor-background segmentation

Cited by 62 publications

References 30 publications

Odor-specific habituation arises from interaction of afferent synaptic adaptation and intrinsic synaptic potentiation in olfactory cortex

Odor-specific habituation arises from interaction of afferent synaptic adaptation and intrinsic synaptic potentiation in olfactory cortex

Untitled

Computation in the Olfactory System

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