skip to main content


Title: Changes in pairwise correlations during running reshape global network state in the main olfactory bulb
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 constraints 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.  more » « less
Award ID(s):
1749772
NSF-PAR ID:
10285446
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Journal of Neurophysiology
Volume:
125
Issue:
5
ISSN:
0022-3077
Page Range / eLocation ID:
1612 to 1623
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Migliore, Michele (Ed.)
    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 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. 
    more » « less
  2. Jonathan R. Whitlock (Ed.)
    Introduction

    Understanding the neural code has been one of the central aims of neuroscience research for decades. Spikes are commonly referred to as the units of information transfer, but multi-unit activity (MUA) recordings are routinely analyzed in aggregate forms such as binned spike counts, peri-stimulus time histograms, firing rates, or population codes. Various forms of averaging also occur in the brain, from the spatial averaging of spikes within dendritic trees to their temporal averaging through synaptic dynamics. However, how these forms of averaging are related to each other or to the spatial and temporal units of information representation within the neural code has remained poorly understood.

    Materials and methods

    In this work we developed NeuroPixelHD, a symbolic hyperdimensional model of MUA, and used it to decode the spatial location and identity of static images shown ton= 9 mice in the Allen Institute Visual Coding—NeuroPixels dataset from large-scale MUA recordings. We parametrically varied the spatial and temporal resolutions of the MUA data provided to the model, and compared its resulting decoding accuracy.

    Results

    For almost all subjects, we found 125ms temporal resolution to maximize decoding accuracy for both the spatial location of Gabor patches (81 classes for patches presented over a 9×9 grid) as well as the identity of natural images (118 classes corresponding to 118 images) across the whole brain. This optimal temporal resolution nevertheless varied greatly between different regions, followed a sensory-associate hierarchy, and was significantly modulated by the central frequency of theta-band oscillations across different regions. Spatially, the optimal resolution was at either of two mesoscale levels for almost all mice: the area level, where the spiking activity of all neurons within each brain area are combined, and the population level, where neuronal spikes within each area are combined across fast spiking (putatively inhibitory) and regular spiking (putatively excitatory) neurons, respectively. We also observed an expected interplay between optimal spatial and temporal resolutions, whereby increasing the amount of averaging across one dimension (space or time) decreases the amount of averaging that is optimal across the other dimension, and vice versa.

    Discussion

    Our findings corroborate existing empirical practices of spatiotemporal binning and averaging in MUA data analysis, and provide a rigorous computational framework for optimizing the level of such aggregations. Our findings can also synthesize these empirical practices with existing knowledge of the various sources of biological averaging in the brain into a new theory of neural information processing in which theunit of informationvaries dynamically based on neuronal signal and noise correlations across space and time.

     
    more » « less
  3. 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.

     
    more » « less
  4. A small library of novel fluorinated N-benzamide enaminones were synthesized and evaluated in a battery of acute preclinical seizure models. Three compounds (GSA 62, TTA 35, and WWB 67) were found to have good anticonvulsant activity in the 6-Hz ‘psychomotor’ 44-mA rodent model. The focus of this study was to elucidate the active analogs’ mode of action on seizure-related molecular targets. Electrophysiology studies were employed to evaluate the compounds’ ability to inhibit neuronal activity in central olfactory neurons, mitral cells, and sensory-like ND7/23 cells, which express an assortment of voltage and ligand-gated ion channels. We did not find any significant effects of the three compounds on action potential generation in mitral cells. The treatment of ND7/23 cells with 50 µM of GSA 62, TTA 35, and WWB 67 generated a significant reduction in the amplitude of whole-cell sodium currents. Similar treatment of ND7/23 cells with these compounds had no effect on T-type calcium currents, indicating that fluorinated N-benzamide enaminone analogs may have a selective effect on voltage-gated sodium channels, but not calcium channels. 
    more » « less
  5. Synopsis Locomotion is a hallmark of organisms which has enabled adaptive radiation to an extraordinarily diverse class of ecological niches, and allows animals to move across vast distances. Sampling from multiple sensory modalities enables animals to acquire rich information to guide locomotion. Locomotion without sensory feedback is haphazard; therefore, sensory and motor systems have evolved complex interactions to generate adaptive behavior. Notably, sensory-guided locomotion acts over broad spatial and temporal scales to permit goal-seeking behavior, whether to localize food by tracking an attractive odor plume or to search for a potential mate. How does the brain integrate multimodal stimuli over different temporal and spatial scales to effectively control behavior? In this review, we classify locomotion into three ordinally ranked hierarchical layers that act over distinct spatiotemporal scales: stabilization, motor primitives, and higher-order tasks, respectively. We discuss how these layers present unique challenges and opportunities for sensorimotor integration. We focus on recent advances in invertebrate locomotion due to their accessible neural and mechanical signals from the whole brain, limbs, and sensors. Throughout, we emphasize neural-level description of computations for multimodal integration in genetic model systems, including the fruit fly, Drosophila melanogaster, and the yellow fever mosquito, Aedes aegypti. We identify that summation (e.g., gating) and weighting—which are inherent computations of spiking neurons—underlie multimodal integration across spatial and temporal scales, therefore suggesting collective strategies to guide locomotion. 
    more » « less