Cortical feedback and gating in odor discrimination and generalization

Tavoni, Gaia; Kersen, David E. Chen; Balasubramanian, Vijay

doi:10.1371/journal.pcbi.1009479

Cited by 3 publications

(3 citation statements)

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“…This implies that theories of feedback and neurogenesis in the bulb that rely on specific targeting of GCs and MCs [ 12 , 28 , 98 ] may require additional components beyond the basic MC-GC network to be feasible. Interestingly, however, when we used this model in a recent study to examine the effect of GC feedback on cortical odor representation, we found that even highly correlated feedback patterns to GCs in a given network configuration produced robust odor discrimination following cortical transformation of the OB output [ 53 ]. This suggests that differential inhibition of MC firing may not be necessary to produce meaningful separation of odor patterns in cortex.…”

Section: Resultsmentioning

confidence: 99%

“…Our model reproduced important empirical features of the OB, including differential connectivity patterns among sister and non-sister MCs, decorrelation over short timescales, as well as theta, beta and gamma oscillations in the local field potential (LFP). The model makes the surprising, and testable, prediction that cortical feedback inhibition of MCs via GCs is a network property largely independent of which GCs are targeted, an observation with consequences for our understanding of how context modulates odor representations [ 28 , 44 – 53 ], and for theories of the functional purpose of granule cell neurogenesis [ 12 , 21 , 26 , 36 ]. The model also predicts that beta and gamma oscillations, which are implicated in numerous theories of odor coding and decoding [ 54 – 57 ], are network properties intrinsic to the bulb that can be modified, suppressed, or enhanced by the extent of granule cell activity [ 14 , 23 , 39 ].…”

Section: Introductionmentioning

confidence: 99%

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Connectivity and dynamics in the olfactory bulb

2022

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Dendrodendritic interactions between excitatory mitral cells and inhibitory granule cells in the olfactory bulb create a dense interaction network, reorganizing sensory representations of odors and, consequently, perception. Large-scale computational models are needed for revealing how the collective behavior of this network emerges from its global architecture. We propose an approach where we summarize anatomical information through dendritic geometry and density distributions which we use to calculate the connection probability between mitral and granule cells, while capturing activity patterns of each cell type in the neural dynamical systems theory of Izhikevich. In this way, we generate an efficient, anatomically and physiologically realistic large-scale model of the olfactory bulb network. Our model reproduces known connectivity between sister vs. non-sister mitral cells; measured patterns of lateral inhibition; and theta, beta, and gamma oscillations. The model in turn predicts testable relationships between network structure and several functional properties, including lateral inhibition, odor pattern decorrelation, and LFP oscillation frequency. We use the model to explore the influence of cortex on the olfactory bulb, demonstrating possible mechanisms by which cortical feedback to mitral cells or granule cells can influence bulbar activity, as well as how neurogenesis can improve bulbar decorrelation without requiring cell death. Our methodology provides a tractable tool for other researchers.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Connectivity and dynamics in the olfactory bulb

2022

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“…These changes may be entrained by the extensive feedback that is present from the central brain to the olfactory bulb. Interestingly, recent work (Tavoni et al, 2021 ; Kersen et al, 2022 ) suggests that these feedback effects of context and valence need not be structured, and instead can also be disordered. That is, each behavioral context can effectively be represented as a random vector of feedback to the circuit elements of the bulb.…”

Section: Discussionmentioning

confidence: 99%

Disorder and the Neural Representation of Complex Odors

Krishnamurthy

Hermundstad

Mora

et al. 2022

Front. Comput. Neurosci.

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Animals smelling in the real world use a small number of receptors to sense a vast number of natural molecular mixtures, and proceed to learn arbitrary associations between odors and valences. Here, we propose how the architecture of olfactory circuits leverages disorder, diffuse sensing and redundancy in representation to meet these immense complementary challenges. First, the diffuse and disordered binding of receptors to many molecules compresses a vast but sparsely-structured odor space into a small receptor space, yielding an odor code that preserves similarity in a precise sense. Introducing any order/structure in the sensing degrades similarity preservation. Next, lateral interactions further reduce the correlation present in the low-dimensional receptor code. Finally, expansive disordered projections from the periphery to the central brain reconfigure the densely packed information into a high-dimensional representation, which contains multiple redundant subsets from which downstream neurons can learn flexible associations and valences. Moreover, introducing any order in the expansive projections degrades the ability to recall the learned associations in the presence of noise. We test our theory empirically using data from Drosophila. Our theory suggests that the neural processing of sparse but high-dimensional olfactory information differs from the other senses in its fundamental use of disorder.

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Neurogenesis dynamics in the olfactory bulb: deciphering circuitry organization, function, and adaptive plasticity

Naffaa

2024

Neural Regeneration Research

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Adult neurogenesis persists after birth in the subventricular zone, with new neurons migrating to the granule cell layer and glomerular layers of the olfactory bulb, where they integrate into existing circuitry as inhibitory interneurons. The generation of these new neurons in the olfactory bulb supports both structural and functional plasticity, aiding in circuit remodeling triggered by memory and learning processes. However, the presence of these neurons, coupled with the cellular diversity within the olfactory bulb, presents an ongoing challenge in understanding its network organization and function. Moreover, the continuous integration of new neurons in the olfactory bulb plays a pivotal role in regulating olfactory information processing. This adaptive process responds to changes in epithelial composition and contributes to the formation of olfactory memories by modulating cellular connectivity within the olfactory bulb and interacting intricately with higher-order brain regions. The role of adult neurogenesis in olfactory bulb functions remains a topic of debate. Nevertheless, the functionality of the olfactory bulb is intricately linked to the organization of granule cells around mitral and tufted cells. This organizational pattern significantly impacts output, network behavior, and synaptic plasticity, which are crucial for olfactory perception and memory. Additionally, this organization is further shaped by axon terminals originating from cortical and subcortical regions. Despite the crucial role of olfactory bulb in brain functions and behaviors related to olfaction, these complex and highly interconnected processes have not been comprehensively studied as a whole. Therefore, this manuscript aims to discuss our current understanding and explore how neural plasticity and olfactory neurogenesis contribute to enhancing the adaptability of the olfactory system. These mechanisms are thought to support olfactory learning and memory, potentially through increased complexity and restructuring of neural network structures, as well as the addition of new granule granule cells that aid in olfactory adaptation. Additionally, the manuscript underscores the importance of employing precise methodologies to elucidate the specific roles of adult neurogenesis amidst conflicting data and varying experimental paradigms. Understanding these processes is essential for gaining insights into the complexities of olfactory function and behavior.

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Cortical feedback and gating in odor discrimination and generalization

Cited by 3 publications

References 118 publications

Connectivity and dynamics in the olfactory bulb

Connectivity and dynamics in the olfactory bulb

Disorder and the Neural Representation of Complex Odors

Neurogenesis dynamics in the olfactory bulb: deciphering circuitry organization, function, and adaptive plasticity

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