skip to main content

Title: Differences in olfactory bulb mitral cell spiking with ortho- and retronasal stimulation revealed by data-driven models
The majority of olfaction studies focus on orthonasal stimulation where odors enter via the front nasal cavity, while retronasal olfaction, where odors enter the rear of the nasal cavity during feeding, is understudied. The coding of retronasal odors via coordinated spiking of neurons in the olfactory bulb ( OB ) is largely unknown despite evidence that higher level processing is different than orthonasal. To this end, we use multi-electrode array in vivo recordings of rat OB mitral cells ( MC ) in response to a food odor with both modes of stimulation, and find significant differences in evoked firing rates and spike count covariances (i.e., noise correlations). Differences in spiking activity often have implications for sensory coding, thus we develop a single-compartment biophysical OB model that is able to reproduce key properties of important OB cell types. Prior experiments in olfactory receptor neurons ( ORN ) showed retro stimulation yields slower and spatially smaller ORN inputs than with ortho, yet whether this is consequential for OB activity remains unknown. Indeed with these specifications for ORN inputs, our OB model captures the salient trends in our OB data. We also analyze how first and second order ORN input statistics dynamically transfer more » to MC spiking statistics with a phenomenological linear-nonlinear filter model, and find that retro inputs result in larger linear filters than ortho inputs. Finally, our models show that the temporal profile of ORN is crucial for capturing our data and is thus a distinguishing feature between ortho and retro stimulation, even at the OB. Using data-driven modeling, we detail how ORN inputs result in differences in OB dynamics and MC spiking statistics. These differences may ultimately shape how ortho and retro odors are coded. « less
Authors:
; ; ; ;
Editors:
Migliore, Michele
Award ID(s):
1912338 1912320
Publication Date:
NSF-PAR ID:
10297629
Journal Name:
PLOS Computational Biology
Volume:
17
Issue:
9
Page Range or eLocation-ID:
e1009169
ISSN:
1553-7358
Sponsoring Org:
National Science Foundation
More Like this
  1. Different coding strategies are used to represent odor information at various stages of the mammalian olfactory system. A temporal latency code represents odor identity in olfactory bulb (OB), but this temporal information is discarded in piriform cortex (PCx) where odor identity is instead encoded through ensemble membership. We developed a spiking PCx network model to understand how this transformation is implemented. In the model, the impact of OB inputs activated earliest after inhalation is amplified within PCx by diffuse recurrent collateral excitation, which then recruits strong, sustained feedback inhibition that suppresses the impact of later-responding glomeruli. We model increasing odor concentrations by decreasing glomerulus onset latencies while preserving their activation sequences. This produces a multiplexed cortical odor code in which activated ensembles are robust to concentration changes while concentration information is encoded through population synchrony. Our model demonstrates how PCx circuitry can implement multiplexed ensemble-identity/temporal-concentration odor coding.
  2. Growth-transform (GT) neurons and their population models allow for independent control over the spiking statistics and the transient population dynamics while optimizing a physically plausible distributed energy functional involving continuous-valued neural variables. In this paper we describe a backpropagation-less learning approach to train a network of spiking GT neurons by enforcing sparsity constraints on the overall network spiking activity. The key features of the model and the proposed learning framework are: (a) spike responses are generated as a result of constraint violation and hence can be viewed as Lagrangian parameters; (b) the optimal parameters for a given task can be learned using neurally relevant local learning rules and in an online manner; (c) the network optimizes itself to encode the solution with as few spikes as possible (sparsity); (d) the network optimizes itself to operate at a solution with the maximum dynamic range and away from saturation; and (e) the framework is flexible enough to incorporate additional structural and connectivity constraints on the network. As a result, the proposed formulation is attractive for designing neuromorphic tinyML systems that are constrained in energy, resources, and network structure. In this paper, we show how the approach could be used for unsupervised andmore »supervised learning such that minimizing a training error is equivalent to minimizing the overall spiking activity across the network. We then build on this framework to implement three different multi-layer spiking network architectures with progressively increasing flexibility in training and consequently, sparsity. We demonstrate the applicability of the proposed algorithm for resource-efficient learning using a publicly available machine olfaction dataset with unique challenges like sensor drift and a wide range of stimulus concentrations. In all of these case studies we show that a GT network trained using the proposed learning approach is able to minimize the network-level spiking activity while producing classification accuracy that are comparable to standard approaches on the same dataset.« less
  3. Neural codes for sensory inputs have been hypothesized to reside in a broader space defined by ongoing patterns of spontaneous activity. To understand the structure of this spontaneous activity in the olfactory system, we performed high-density recordings of neural populations in the main olfactory bulb of awake mice. We observed changes in pairwise correlations of spontaneous activity between mitral and tufted (M/T) cells when animals were running, which resulted in an increase in the entropy of the population. Surprisingly, pairwise maximum entropy models that described the population activity using only assumptions about the firing rates and correlations of neurons were better at predicting the global structure of activity when animals were stationary as compared to when they were running, implying that higher order (3rd, 4th order) interactions governed population activity during locomotion. Taken together, we found that locomotion alters the functional interactions that shape spontaneous population activity at the earliest stages of olfactory processing, one synapse away from the sensory receptors in the nasal epithelium. These data suggest that the coding space available for sensory representations responds adaptively to the animal’s behavioral state. NEW & NOTEWORTHY The organization and structure of spontaneous population activity in the olfactory system places constraintsmore »of how odor information is represented. Using high-density electrophysiological recordings of mitral and tufted cells, we found that running increases the dimensionality of spontaneous activity, implicating higher order interactions among neurons during locomotion. Behavior, thus, flexibly alters neuronal activity at the earliest stages of sensory processing.« less
  4. Abstract

    The ability to identify odors in the environment is crucial for survival and reproduction. However, whether olfactory processing in higher-order brain centers is influenced by an animal’s physiological condition is unknown. We usedin vivoneuron and local field potential (LFP) recordings from the ventral telencephalon of dominant and subordinate male cichlids to test the hypothesis that response properties of olfactory neurons differ with social status. Dominant males had a high percentage of neurons that responded to several odor types, suggesting broad tuning or differential sensitivity when males are reproductively active and defending a territory. A greater percentage of neurons in dominant males also responded to sex- and food-related odors, while a greater percentage of neurons in subordinate males responded to complex odors collected from behaving dominant males, possibly as a mechanism to mediate social suppression and allow subordinates to identify opportunities to rise in rank. Odor-evoked LFP spectral densities, indicative of synaptic inputs, were also 2–3-fold greater in dominant males, demonstrating status-dependent differences in processing possibly linking olfactory and other neural inputs to goal-directed behaviors. For the first time we reveal social and reproductive-state plasticity in olfactory processing neurons in the vertebrate forebrain that are associated with status-specific lifestyles.

  5. Abstract Nasal anatomy in rodents is well-studied, but most current knowledge is based on small-bodied muroid species. Nasal anatomy and histology of hystricognaths, the largest living rodents, remains poorly understood. Here, we describe the nasal cavity of agoutis ( Dasyprocta spp.), the first large-bodied South American rodents to be studied histologically throughout the nasal cavity. Two adult agoutis were studied using microcomputed tomography, and in one of these, half the snout was serially sectioned and stained for microscopic study. Certain features are notable in Dasyprocta . The frontal recess has five turbinals within it, the most in this space compared to other rodents that have been studied. The nasoturbinal is particularly large in dorsoventral and rostrocaudal dimensions and is entirely non-olfactory in function, in apparent contrast to known muroids. Whether this relates solely to body size scaling or perhaps also relates to directing airflow or conditioning inspired air requires further study. In addition, olfactory epithelium appears more restricted to the olfactory and frontal recesses compared to muroids. At the same time, the rostral tips of the olfactory turbinals bear at least some non-olfactory epithelium. The findings of this study support the hypothesis that turbinals are multifunctional structures, indicating investigators shouldmore »use caution when categorizing turbinals as specialized for one function (e.g., olfaction or respiratory air-conditioning). Caution may be especially appropriate in the case of large-bodied mammals, in which the different scaling characteristics of respiratory and olfactory mucosa result in relative more of the former type as body size increases.« less