1
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Rhee JY, Echavarría C, Soucy E, Greenwood J, Masís JA, Cox DD. Neural correlates of visual object recognition in rats. Cell Rep 2025; 44:115461. [PMID: 40153435 DOI: 10.1016/j.celrep.2025.115461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/20/2024] [Accepted: 03/05/2025] [Indexed: 03/30/2025] Open
Abstract
Invariant object recognition-the ability to recognize objects across size, rotation, or context-is fundamental for making sense of a dynamic visual world. Though traditionally studied in primates, emerging evidence suggests rodents recognize objects across a range of identity-preserving transformations. We demonstrate that rats robustly perform visual object recognition and explore a neural pathway that may underlie this capacity by developing a pipeline from high-throughput behavior training to cellular resolution imaging in awake, head-fixed animals. Leveraging our optical approach, we systematically profile neurons in primary and higher-order visual areas and their spatial organization. We find that rat visual cortex exhibits several features similar to those observed in the primate ventral stream but also marked deviations, suggesting species-specific differences in how brains solve visual object recognition. This work reinforces the sophisticated visual abilities of rats and offers the technical foundation to use them as a powerful model for mechanistic perception.
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Affiliation(s)
- Juliana Y Rhee
- The Rockefeller University, New York, NY 10065, USA; Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
| | - César Echavarría
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Edward Soucy
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Joel Greenwood
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA; Kavli Center for Neurotechnology, Yale University, New Haven, CT 06510, USA
| | - Javier A Masís
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA; Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - David D Cox
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA; IBM Research, Cambridge, MA 02142, USA
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2
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Koh M, Anselmi F, Kaushalya SK, Hernandez DE, Bast WG, Villar PS, Chae H, Davis MB, Teja SS, Qu Z, Gradinaru V, Gupta P, Banerjee A, Albeanu DF. Axially decoupled photo-stimulation and two photon readout ( ADePT) for mapping functional connectivity of neural circuits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.24.639992. [PMID: 40161637 PMCID: PMC11952351 DOI: 10.1101/2025.02.24.639992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
All optical physiology in vivo provides a conduit for investigating the function of neural circuits in 3-D. Here, we report a new strategy for flexible, axially-decoupled photo-stimulation and two photon readout (ADePT) of neuronal activity. To achieve axially-contained widefield optogenetic patterned stimulation, we couple a digital micro-mirror device illuminated by a solid-state laser with a motorized holographic diffuser. In parallel, we use multiphoton imaging of neural activity across different z-planes. We use ADePT to analyze the excitatory and inhibitory functional connectivity of the mouse early olfactory system. Specifically, we control the activity of individual input glomeruli on the olfactory bulb surface, and map the ensuing responses of output mitral and tufted cell bodies in deeper layers. This approach identifies cohorts of sister mitral and tufted cells, whose firing is driven by the same parent glomerulus, and also reveals their differential inhibition by other glomeruli. In addition, selective optogenetic activation of glomerular GABAergic/dopaminergic (DAT+) interneurons triggers dense, but spatially heterogeneous suppression of mitral and tufted cell baseline activity and odor responses, further demonstrating specificity in the inhibitory olfactory bulb connectivity. In summary, ADePT enables high-throughput functional connectivity mapping in optically accessible brain regions.
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Affiliation(s)
- Matthew Koh
- CSHL School for Biological Sciences
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | | | | | | | | | - Pablo S. Villar
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Honggoo Chae
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Martin B. Davis
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Sadhu Sai Teja
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Zhe Qu
- California Institute of Technology, Pasadena, CA, 91125
| | | | - Priyanka Gupta
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Arkarup Banerjee
- CSHL School for Biological Sciences
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Dinu F. Albeanu
- CSHL School for Biological Sciences
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
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3
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Koren V, Blanco Malerba S, Schwalger T, Panzeri S. Efficient coding in biophysically realistic excitatory-inhibitory spiking networks. eLife 2025; 13:RP99545. [PMID: 40053385 PMCID: PMC11888603 DOI: 10.7554/elife.99545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2025] Open
Abstract
The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuroscience, it has remained unclear whether fundamental empirical properties of neural network activity can be explained solely based on this normative principle. Here, we derive the structural, coding, and biophysical properties of excitatory-inhibitory recurrent networks of spiking neurons that emerge directly from imposing that the network minimizes an instantaneous loss function and a time-averaged performance measure enacting efficient coding. We assumed that the network encodes a number of independent stimulus features varying with a time scale equal to the membrane time constant of excitatory and inhibitory neurons. The optimal network has biologically plausible biophysical features, including realistic integrate-and-fire spiking dynamics, spike-triggered adaptation, and a non-specific excitatory external input. The excitatory-inhibitory recurrent connectivity between neurons with similar stimulus tuning implements feature-specific competition, similar to that recently found in visual cortex. Networks with unstructured connectivity cannot reach comparable levels of coding efficiency. The optimal ratio of excitatory vs inhibitory neurons and the ratio of mean inhibitory-to-inhibitory vs excitatory-to-inhibitory connectivity are comparable to those of cortical sensory networks. The efficient network solution exhibits an instantaneous balance between excitation and inhibition. The network can perform efficient coding even when external stimuli vary over multiple time scales. Together, these results suggest that key properties of biological neural networks may be accounted for by efficient coding.
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Affiliation(s)
- Veronika Koren
- Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-EppendorfHamburgGermany
- Institute of Mathematics, Technische Universität BerlinBerlinGermany
- Bernstein Center for Computational Neuroscience BerlinBerlinGermany
| | - Simone Blanco Malerba
- Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-EppendorfHamburgGermany
| | - Tilo Schwalger
- Institute of Mathematics, Technische Universität BerlinBerlinGermany
- Bernstein Center for Computational Neuroscience BerlinBerlinGermany
| | - Stefano Panzeri
- Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-EppendorfHamburgGermany
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4
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Park W, Kim J, Jeong I, Lee KJ. Temporal pavlovian conditioning of a model spiking neural network for discrimination sequences of short time intervals. J Comput Neurosci 2025; 53:163-179. [PMID: 39891868 PMCID: PMC11868207 DOI: 10.1007/s10827-025-00896-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2024] [Revised: 12/18/2024] [Accepted: 01/24/2025] [Indexed: 02/03/2025]
Abstract
The brain's ability to learn and distinguish rapid sequences of events is essential for timing-dependent tasks, such as those in sports and music. However, the mechanisms underlying this ability remain an active area of research. Here, we present a Pavlovian-conditioned spiking neural network model that may help elucidate these mechanisms. Using "three-factor learning rule," we conditioned an initially random spiking neural network to discriminate a specific spatiotemporal stimulus - a sequence of two or three pulses delivered within ∼ 10 ms to two or three distinct neuronal subpopulations - from other pulse sequences differing by only a few milliseconds. Through conditioning, a feedforward structure emerges that encodes the target pattern's temporal information into specific topographic arrangements of stimulated subpopulations. In the readout phase, discrimination of different inputs is achieved by evaluating the shape and peak-shift characteristics of the spike density functions (SDFs) of input-triggered population bursts. The network's dynamic range - defined by the duration over which pulse sequences are processed accurately - is limited to around 10 ms, as determined by the duration of the input-triggered population burst. However, by introducing axonal conduction delays, we show that the network can generate "superbursts," producing a more complex and extended SDF lasting up to ∼ 30 ms, and potentially much longer. This extension effectively broadens the network's dynamic range for processing temporal sequences. We propose that such conditioning mechanisms may provide insight into the brain's ability to perceive and interpret complex spatiotemporal sensory information encountered in real-world contexts.
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Affiliation(s)
- Woojun Park
- Physics, Korea University, Seoul, 02841, Korea
| | - Jongmu Kim
- Mechanical Engineering, Korea University, Seoul, 02841, Korea
| | - Inhoi Jeong
- Physics, Korea University, Seoul, 02841, Korea
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5
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Patel H, Garrido Portilla V, Shneidman AV, Movilli J, Alvarenga J, Dupré C, Aizenberg M, Murthy VN, Tropsha A, Aizenberg J. Design Principles From Natural Olfaction for Electronic Noses. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2412669. [PMID: 39835449 PMCID: PMC11948017 DOI: 10.1002/advs.202412669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Revised: 11/29/2024] [Indexed: 01/22/2025]
Abstract
Natural olfactory systems possess remarkable sensitivity and precision beyond what is currently achievable by engineered gas sensors. Unlike their artificial counterparts, noses are capable of distinguishing scents associated with mixtures of volatile molecules in complex, typically fluctuating environments and can adapt to changes. This perspective examines the multifaceted biological principles that provide olfactory systems their discriminatory prowess, and how these ideas can be ported to the design of electronic noses for substantial improvements in performance across metrics such as sensitivity and ability to speciate chemical mixtures. The topics examined herein include the fluid dynamics of odorants in natural channels; specificity and kinetics of odorant interactions with olfactory receptors and mucus linings; complex signal processing that spatiotemporally encodes physicochemical properties of odorants; active sampling techniques, like biological sniffing and nose repositioning; biological priming; and molecular chaperoning. Each of these components of natural olfactory systems are systmatically investigated, as to how they have been or can be applied to electronic noses. While not all artificial sensors can employ these strategies simultaneously, integrating a subset of bioinspired principles can address issues like sensitivity, drift, and poor selectivity, offering advancements in many sectors such as environmental monitoring, industrial safety, and disease diagnostics.
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Affiliation(s)
- Haritosh Patel
- Harvard John A. Paulson School of Engineering and Applied SciencesHarvard UniversityBostonMA02134USA
| | - Vicente Garrido Portilla
- Harvard John A. Paulson School of Engineering and Applied SciencesHarvard UniversityBostonMA02134USA
| | - Anna V. Shneidman
- Harvard John A. Paulson School of Engineering and Applied SciencesHarvard UniversityBostonMA02134USA
| | - Jacopo Movilli
- Harvard John A. Paulson School of Engineering and Applied SciencesHarvard UniversityBostonMA02134USA
- Department of Chemical SciencesUniversity of PadovaPadova35131Italy
| | - Jack Alvarenga
- Harvard John A. Paulson School of Engineering and Applied SciencesHarvard UniversityBostonMA02134USA
| | - Christophe Dupré
- Department of Molecular & Cellular BiologyHarvard UniversityCambridgeMA02138USA
| | - Michael Aizenberg
- Harvard John A. Paulson School of Engineering and Applied SciencesHarvard UniversityBostonMA02134USA
| | - Venkatesh N. Murthy
- Department of Molecular & Cellular BiologyHarvard UniversityCambridgeMA02138USA
- Center for Brain ScienceHarvard UniversityCambridgeMA02138USA
- Kempner InstituteHarvard UniversityBostonMA02134USA
| | - Alexander Tropsha
- Department of ChemistryThe University of North Carolina at Chapel HillChapel HillNC27516USA
| | - Joanna Aizenberg
- Harvard John A. Paulson School of Engineering and Applied SciencesHarvard UniversityBostonMA02134USA
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeMA02138USA
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6
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Conway M, Oncul M, Allen K, Zhang Z, Johnston J. Perceptual constancy for an odor is acquired through changes in primary sensory neurons. SCIENCE ADVANCES 2024; 10:eado9205. [PMID: 39661686 PMCID: PMC11633753 DOI: 10.1126/sciadv.ado9205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 11/04/2024] [Indexed: 12/13/2024]
Abstract
The ability to consistently recognize an object despite variable sensory input is termed perceptual constancy. This ability is not innate; rather, it develops with experience early in life. We show that, when mice are naïve to an odor object, perceptual constancy is absent across increasing concentrations. The perceptual change coincides with a rapid reduction in activity from a single olfactory receptor channel that is most sensitive to the odor. This drop in activity is not a property of circuit interactions within the olfactory bulb; instead, it is due to a sensitivity mismatch of olfactory receptor neurons within the nose. We show that, after forming an association of this odor with food, the sensitivity of the receptor channel is matched to the odor object, preventing transmission failure and promoting perceptual stability. These data show that plasticity of the primary sensory organ enables learning of perceptual constancy.
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Affiliation(s)
- Mark Conway
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Merve Oncul
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Kate Allen
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Zongqian Zhang
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Jamie Johnston
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
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Sunil A, Pedroncini O, Schaefer AT, Ackels T. How do mammals convert dynamic odor information into neural maps for landscape navigation? PLoS Biol 2024; 22:e3002908. [PMID: 39571004 PMCID: PMC11581409 DOI: 10.1371/journal.pbio.3002908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2024] Open
Abstract
Odors are transported by seemingly chaotic plumes, whose spatiotemporal structure contains rich information about space, with olfaction serving as a gateway for obtaining and processing this spatial information. Beyond tracking odors, olfaction provides localization and chemical communication cues for detecting conspecifics and predators, and linking external environments to internal cognitive maps. In this Essay, we discuss recent physiological, behavioral, and methodological advancements in mammalian olfactory research to present our current understanding of how olfaction can be used to navigate the environment. We also examine potential neural mechanisms that might convert dynamic olfactory inputs into environmental maps along this axis. Finally, we consider technological applications of odor dynamics for developing bio-inspired sensor technologies, robotics, and computational models. By shedding light on the principles underlying the processing of odor dynamics, olfactory research will pave the way for innovative solutions that bridge the gap between biology and technology, enriching our understanding of the natural world.
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Affiliation(s)
- Anantu Sunil
- Sensory Dynamics and Behaviour Lab, Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
| | - Olivia Pedroncini
- Sensory Circuits and Neurotechnology Laboratory, Francis Crick Institute, London, United Kingdom
| | - Andreas T. Schaefer
- Sensory Circuits and Neurotechnology Laboratory, Francis Crick Institute, London, United Kingdom
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom
| | - Tobias Ackels
- Sensory Dynamics and Behaviour Lab, Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
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8
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Wu Y, Chen K, Xing C, Huang M, Zhao K, Zhou W. Human olfactory perception embeds fine temporal resolution within a single sniff. Nat Hum Behav 2024; 8:2168-2178. [PMID: 39402256 DOI: 10.1038/s41562-024-01984-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 08/13/2024] [Indexed: 10/20/2024]
Abstract
A sniff in humans typically lasts one to three seconds and is commonly considered to produce a long-exposure shot of the chemical environment that sets the temporal limit of olfactory perception. To break this limit, we devised a sniff-triggered apparatus that controls odorant deliveries within a sniff with a precision of 18 milliseconds. Using this apparatus, we show through rigorous psychophysical testing of 229 participants (649 sessions) that two odorants presented in one order and its reverse become perceptually discriminable when the stimulus onset asynchrony is merely 60 milliseconds (Cohen's d = 0.48; 95% confidence interval, (55, 59); 120-millisecond difference). Discrimination performance improves with the length of stimulus onset asynchrony and is independent of explicit knowledge of the temporal order of odorants or the relative amount of odorant molecules accumulated in a sniff. Our findings demonstrate that human olfactory perception is sensitive to chemical dynamics within a single sniff and provide behavioural evidence for a temporal code of odour identity.
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Affiliation(s)
- Yuli Wu
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Kepu Chen
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Chen Xing
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Meihe Huang
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Kai Zhao
- Department of Otolaryngology, Ohio State University, Columbus, OH, USA
| | - Wen Zhou
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
- Chinese Institute for Brain Research, Beijing, China.
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9
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Lazar AA, Liu T, Yeh CH, Zhou Y. Modeling and characterization of pure and odorant mixture processing in the Drosophila mushroom body calyx. Front Physiol 2024; 15:1410946. [PMID: 39479309 PMCID: PMC11521939 DOI: 10.3389/fphys.2024.1410946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 09/05/2024] [Indexed: 11/02/2024] Open
Abstract
Associative memory in the Mushroom Body of the fruit fly brain depends on the encoding and processing of odorants in the first three stages of the Early Olfactory System: the Antenna, the Antennal Lobe and the Mushroom Body Calyx. The Kenyon Cells (KCs) of the Calyx provide the Mushroom Body compartments the identity of pure and odorant mixtures encoded as a train of spikes. Characterizing the code underlying the KC spike trains is a major challenge in neuroscience. To address this challenge we start by explicitly modeling the space of odorants using constructs of both semantic and syntactic information. Odorant semantics concerns the identity of odorants while odorant syntactics pertains to their concentration amplitude. These odorant attributes are multiplicatively coupled in the process of olfactory transduction. A key question that early olfactory systems must address is how to disentangle the odorant semantic information from the odorant syntactic information. To address the untanglement we devised an Odorant Encoding Machine (OEM) modeling the first three stages of early olfactory processing in the fruit fly brain. Each processing stage is modeled by Divisive Normalization Processors (DNPs). DNPs are spatio-temporal models of canonical computation of brain circuits. The end-to-end OEM is constructed as cascaded DNPs. By extensively modeling and characterizing the processing of pure and odorant mixtures in the Calyx, we seek to answer the question of its functional significance. We demonstrate that the DNP circuits in the OEM combinedly reduce the variability of the Calyx response to odorant concentration, thereby separating odorant semantic information from syntactic information. We then advance a code, called first spike sequence code, that the KCs make available at the output of the Calyx. We show that the semantics of odorants can be represented by this code in the spike domain and is ready for easy memory access in the Mushroom Body compartments.
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Affiliation(s)
- Aurel A. Lazar
- Bionet Group, Department of Electrical Engineering, Columbia University, New York, NY, United States
| | - Tingkai Liu
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States
| | - Chung-Heng Yeh
- Bionet Group, Department of Electrical Engineering, Columbia University, New York, NY, United States
| | - Yiyin Zhou
- Department of Computer and Information Science, Fordham University, New York, NY, United States
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10
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Wang P, Li S, Li A. Odor representation and coding by the mitral/tufted cells in the olfactory bulb. J Zhejiang Univ Sci B 2024; 25:824-840. [PMID: 39420520 PMCID: PMC11494158 DOI: 10.1631/jzus.b2400051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 07/14/2024] [Indexed: 10/19/2024]
Abstract
The olfactory bulb (OB) is the first relay station in the olfactory system and functions as a crucial hub. It can represent odor information precisely and accurately in an ever-changing environment. As the only output neurons in the OB, mitral/tufted cells encode information such as odor identity and concentration. Recently, the neural strategies and mechanisms underlying odor representation and encoding in the OB have been investigated extensively. Here we review the main progress on this topic. We first review the neurons and circuits involved in odor representation, including the different cell types in the OB and the neural circuits within and beyond the OB. We will then discuss how two different coding strategies-spatial coding and temporal coding-work in the rodent OB. Finally, we discuss potential future directions for this research topic. Overall, this review provides a comprehensive description of our current understanding of how odor information is represented and encoded by mitral/tufted cells in the OB.
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Affiliation(s)
- Panke Wang
- School of Biomedical Engineering, Guangdong Medical University, Dongguan 523808, China
| | - Shan Li
- Jiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou 221002, China
| | - An'an Li
- Jiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou 221002, China.
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11
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Sourisse JM, Semmelhack JL, Schunter C. Parental thermal conditions affect the brain activity response to alarm cue in larval zebrafish. PeerJ 2024; 12:e18241. [PMID: 39399440 PMCID: PMC11471146 DOI: 10.7717/peerj.18241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Accepted: 09/15/2024] [Indexed: 10/15/2024] Open
Abstract
Temperature is a crucial factor affecting the physiology of ectothermic animals, but exposure to elevated temperature during specific life stages and across generations may confer fish resilience through phenotypic plasticity. In this study, we investigate the effects of developmental and parental temperature on brain activity response to an olfactory cue in the larval zebrafish, Danio rerio. We exposed parents during reproduction and their offspring during development to control (28 °C) or elevated temperature (30 °C) and observed the response of the larval telencephalon to an alarm cue using live calcium imaging. Parental exposure to elevated temperature decreased the time till maximum brain activity response regardless of the offspring's developmental temperature, revealing that parental thermal conditions can affect the excitability of the offspring's neural circuitry. Furthermore, brain activity duration was affected by the interaction between parental and offspring thermal conditions, where longer brain activity duration was seen when either parents or offspring were exposed to elevated temperature. Conversely, we found shorter brain activity duration when the offspring were exposed to the same temperature as their parents, in both control and elevated temperature. This could represent an anticipatory parental effect influencing the offspring's brain response to match the parental environment, or an early developmental effect occurring within a susceptible short time window post-fertilization. Overall, our results suggest that warming can alter processes involved in brain transmission and show that parental conditions could aid in the preparation of their offspring to respond to olfactory stimuli in a warming environment.
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Affiliation(s)
- Jade M. Sourisse
- The Swire Institute of Marine Science, School of Biological Sciences, The University of Hong Kong, Hong Kong SAR, China
- Marine and Environmental Sciences Centre, Laboratório Marítimo da Guia, Faculdade de Ciências, Universidade de Lisboa, Cascais, Portugal
| | - Julie L. Semmelhack
- The Division of Life Science, The Hong Kong University of Science and Technology, Clearwater Bay, Kowloon, Hong Kong
| | - Celia Schunter
- The Swire Institute of Marine Science, School of Biological Sciences, The University of Hong Kong, Hong Kong SAR, China
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12
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Rokni D, Ben-Shaul Y. Object-oriented olfaction: challenges for chemosensation and for chemosensory research. Trends Neurosci 2024; 47:834-848. [PMID: 39245626 DOI: 10.1016/j.tins.2024.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 08/02/2024] [Accepted: 08/16/2024] [Indexed: 09/10/2024]
Abstract
Many animal species use olfaction to extract information about objects in their environment. Yet, the specific molecular signature that any given object emits varies due to various factors. Here, we detail why such variability makes chemosensory-mediated object recognition such a hard problem, and we propose that a major function of the elaborate chemosensory network is to overcome it. We describe previous work addressing different elements of the problem and outline future research directions that we consider essential for a full understanding of object-oriented olfaction. In particular, we call for extensive representation of olfactory object variability in chemical, behavioral, and electrophysiological analyses. While written with an emphasis on macrosmatic mammalian species, our arguments apply to all organisms that employ chemosensation to navigate complex environments.
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Affiliation(s)
- Dan Rokni
- Department of Medical Neurobiology, The Hebrew University Faculty of Medicine, Institute for Medical Research, Israel-Canada (IMRIC), Jerusalem, Israel.
| | - Yoram Ben-Shaul
- Department of Medical Neurobiology, The Hebrew University Faculty of Medicine, Institute for Medical Research, Israel-Canada (IMRIC), Jerusalem, Israel.
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13
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Pirhayati D, Smith CL, Kroeger R, Navlakha S, Pfaffinger P, Reimer J, Arenkiel BR, Patel A, Moss EH. Dense and Persistent Odor Representations in the Olfactory Bulb of Awake Mice. J Neurosci 2024; 44:e0116242024. [PMID: 39187379 PMCID: PMC11426377 DOI: 10.1523/jneurosci.0116-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 08/12/2024] [Accepted: 08/14/2024] [Indexed: 08/28/2024] Open
Abstract
Recording and analysis of neural activity are often biased toward detecting sparse subsets of highly active neurons, masking important signals carried in low-magnitude and variable responses. To investigate the contribution of seemingly noisy activity to odor encoding, we used mesoscale calcium imaging from mice of both sexes to record odor responses from the dorsal surface of bilateral olfactory bulbs (OBs). The outer layer of the mouse OB is comprised of dendrites organized into discrete "glomeruli," which are defined by odor receptor-specific sensory neuron input. We extracted activity from a large population of glomeruli and used logistic regression to classify odors from individual trials with high accuracy. We then used add-in and dropout analyses to determine subsets of glomeruli necessary and sufficient for odor classification. Classifiers successfully predicted odor identity even after excluding sparse, highly active glomeruli, indicating that odor information is redundantly represented across a large population of glomeruli. Additionally, we found that random forest (RF) feature selection informed by Gini inequality (RF Gini impurity, RFGI) reliably ranked glomeruli by their contribution to overall odor classification. RFGI provided a measure of "feature importance" for each glomerulus that correlated with intuitive features like response magnitude. Finally, in agreement with previous work, we found that odor information persists in glomerular activity after the odor offset. Together, our findings support a model of OB odor coding where sparse activity is sufficient for odor identification, but information is widely, redundantly available across a large population of glomeruli, with each glomerulus representing information about more than one odor.
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Affiliation(s)
- Delaram Pirhayati
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas 97030
| | - Cameron L Smith
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 97030
| | - Ryan Kroeger
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 97030
| | - Saket Navlakha
- Cold Spring Harbor Laboratory, Cold Spring Harbor, Laurel Hollow, New York 11724
| | - Paul Pfaffinger
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 97030
| | - Jacob Reimer
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 97030
| | - Benjamin R Arenkiel
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 97030
| | - Ankit Patel
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas 97030
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 97030
| | - Elizabeth H Moss
- Department of Anesthesiology and Perioperative Medicine, Oregon Health & Science University, Portland, Oregon 97239
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14
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Giaffar H, Shuvaev S, Rinberg D, Koulakov AA. The primacy model and the structure of olfactory space. PLoS Comput Biol 2024; 20:e1012379. [PMID: 39255274 PMCID: PMC11423968 DOI: 10.1371/journal.pcbi.1012379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 09/25/2024] [Accepted: 07/30/2024] [Indexed: 09/12/2024] Open
Abstract
Understanding sensory processing involves relating the stimulus space, its neural representation, and perceptual quality. In olfaction, the difficulty in establishing these links lies partly in the complexity of the underlying odor input space and perceptual responses. Based on the recently proposed primacy model for concentration invariant odor identity representation and a few assumptions, we have developed a theoretical framework for mapping the odor input space to the response properties of olfactory receptors. We analyze a geometrical structure containing odor representations in a multidimensional space of receptor affinities and describe its low-dimensional implementation, the primacy hull. We propose the implications of the primacy hull for the structure of feedforward connectivity in early olfactory networks. We test the predictions of our theory by comparing the existing receptor-ligand affinity and connectivity data obtained in the fruit fly olfactory system. We find that the Kenyon cells of the insect mushroom body integrate inputs from the high-affinity (primacy) sets of olfactory receptors in agreement with the primacy theory.
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Affiliation(s)
- Hamza Giaffar
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Sergey Shuvaev
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Dmitry Rinberg
- Neuroscience Institute, New York University Langone Health, New York, New York, United States of America
- Center for Neural Science, New York University, New York, New York, United States of America
| | - Alexei A. Koulakov
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
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15
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Bokman E, Pritz CO, Ruach R, Itskovits E, Sharvit H, Zaslaver A. Intricate response dynamics enhances stimulus discrimination in the resource-limited C. elegans chemosensory system. BMC Biol 2024; 22:173. [PMID: 39148065 PMCID: PMC11328493 DOI: 10.1186/s12915-024-01977-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 08/08/2024] [Indexed: 08/17/2024] Open
Abstract
BACKGROUND Sensory systems evolved intricate designs to accurately encode perplexing environments. However, this encoding task may become particularly challenging for animals harboring a small number of sensory neurons. Here, we studied how the compact resource-limited chemosensory system of Caenorhabditis elegans uniquely encodes a range of chemical stimuli. RESULTS We find that each stimulus is encoded using a small and unique subset of neurons, where only a portion of the encoding neurons sense the stimulus directly, and the rest are recruited via inter-neuronal communication. Furthermore, while most neurons show stereotypical response dynamics, some neurons exhibit versatile dynamics that are either stimulus specific or network-activity dependent. Notably, it is the collective dynamics of all responding neurons which provides valuable information that ultimately enhances stimulus identification, particularly when required to discriminate between closely related stimuli. CONCLUSIONS Together, these findings demonstrate how a compact and resource-limited chemosensory system can efficiently encode and discriminate a diverse range of chemical stimuli.
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Affiliation(s)
- Eduard Bokman
- Department of Genetics, Silberman Institute of Life Science, Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Christian O Pritz
- Department of Genetics, Silberman Institute of Life Science, Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Rotem Ruach
- Department of Genetics, Silberman Institute of Life Science, Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Eyal Itskovits
- Department of Genetics, Silberman Institute of Life Science, Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Hadar Sharvit
- Department of Statistics and Data Science, Center for Interdisciplinary Data Research, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Alon Zaslaver
- Department of Genetics, Silberman Institute of Life Science, Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem, Israel.
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16
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Karunanayaka PR, Lu J, Elyan R, Yang QX, Sathian K. Olfactory-trigeminal integration in the primary olfactory cortex. Hum Brain Mapp 2024; 45:e26772. [PMID: 38962966 PMCID: PMC11222875 DOI: 10.1002/hbm.26772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 06/07/2024] [Accepted: 06/16/2024] [Indexed: 07/05/2024] Open
Abstract
Humans naturally integrate signals from the olfactory and intranasal trigeminal systems. A tight interplay has been demonstrated between these two systems, and yet the neural circuitry mediating olfactory-trigeminal (OT) integration remains poorly understood. Using functional magnetic resonance imaging (fMRI), combined with psychophysics, this study investigated the neural mechanisms underlying OT integration. Fifteen participants with normal olfactory function performed a localization task with air-puff stimuli, phenylethyl alcohol (PEA; rose odor), or a combination thereof while being scanned. The ability to localize PEA to either nostril was at chance. Yet, its presence significantly improved the localization accuracy of weak, but not strong, air-puffs, when both stimuli were delivered concurrently to the same nostril, but not when different nostrils received the two stimuli. This enhancement in localization accuracy, exemplifying the principles of spatial coincidence and inverse effectiveness in multisensory integration, was associated with multisensory integrative activity in the primary olfactory (POC), orbitofrontal (OFC), superior temporal (STC), inferior parietal (IPC) and cingulate cortices, and in the cerebellum. Multisensory enhancement in most of these regions correlated with behavioral multisensory enhancement, as did increases in connectivity between some of these regions. We interpret these findings as indicating that the POC is part of a distributed brain network mediating integration between the olfactory and trigeminal systems. PRACTITIONER POINTS: Psychophysical and neuroimaging study of olfactory-trigeminal (OT) integration. Behavior, cortical activity, and network connectivity show OT integration. OT integration obeys principles of inverse effectiveness and spatial coincidence. Behavioral and neural measures of OT integration are correlated.
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Affiliation(s)
- Prasanna R. Karunanayaka
- Department of RadiologyPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
- Department of Neural and Behavioral SciencesPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
- Department of Public Health SciencesPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
| | - Jiaming Lu
- Department of RadiologyPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
- Drum Tower HospitalMedical School of Nanjing UniversityNanjingChina
| | - Rommy Elyan
- Department of RadiologyPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
| | - Qing X. Yang
- Department of RadiologyPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
- Department of NeurosurgeryPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
| | - K. Sathian
- Department of Neural and Behavioral SciencesPennsylvania State University College of MedicineHersheyPennsylvaniaUSA
- Department of NeurologyPenn State Health Milton S. Hershey Medical CenterHersheyPennsylvaniaUSA
- Department of PsychologyPennsylvania State University College of Liberal ArtsState CollegePennsylvaniaUSA
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17
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Chen Z, Padmanabhan K. Adult-neurogenesis allows for representational stability and flexibility in early olfactory system. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601573. [PMID: 39005290 PMCID: PMC11244980 DOI: 10.1101/2024.07.02.601573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
In the early olfactory system, adult-neurogenesis, a process of neuronal replacement results in the continuous reorganization of synaptic connections and network architecture throughout the animal's life. This poses a critical challenge: How does the olfactory system maintain stable representations of odors and therefore allow for stable sensory perceptions amidst this ongoing circuit instability? Utilizing a detailed spiking network model of early olfactory circuits, we uncovered dual roles for adult-neurogenesis: one that both supports representational stability to faithfully encode odor information and also one that facilitates plasticity to allow for learning and adaptation. In the main olfactory bulb, adult-neurogenesis affects neural codes in individual mitral and tufted cells but preserves odor representations at the neuronal population level. By contrast, in the olfactory piriform cortex, both individual cell responses and overall population dynamics undergo progressive changes due to adult-neurogenesis. This leads to representational drift, a gradual alteration in sensory perception. Both processes are dynamic and depend on experience such that repeated exposure to specific odors reduces the drift due to adult-neurogenesis; thus, when the odor environment is stable over the course of adult-neurogenesis, it is neurogenesis that actually allows the representations to remain stable in piriform cortex; when those olfactory environments change, adult-neurogenesis allows the cortical representations to track environmental change. Whereas perceptual stability and plasticity due to learning are often thought of as two distinct, often contradictory processing in neuronal coding, we find that adult-neurogenesis serves as a shared mechanism for both. In this regard, the quixotic presence of adult-neurogenesis in the mammalian olfactory bulb that has been the focus of considerable debate in chemosensory neuroscience may be the mechanistic underpinning behind an array of complex computations.
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Affiliation(s)
- Zhen Chen
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY14627
| | - Krishnan Padmanabhan
- Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642
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18
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Fulton KA, Zimmerman D, Samuel A, Vogt K, Datta SR. Common principles for odour coding across vertebrates and invertebrates. Nat Rev Neurosci 2024; 25:453-472. [PMID: 38806946 DOI: 10.1038/s41583-024-00822-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/30/2024] [Indexed: 05/30/2024]
Abstract
The olfactory system is an ideal and tractable system for exploring how the brain transforms sensory inputs into behaviour. The basic tasks of any olfactory system include odour detection, discrimination and categorization. The challenge for the olfactory system is to transform the high-dimensional space of olfactory stimuli into the much smaller space of perceived objects and valence that endows odours with meaning. Our current understanding of how neural circuits address this challenge has come primarily from observations of the mechanisms of the brain for processing other sensory modalities, such as vision and hearing, in which optimized deep hierarchical circuits are used to extract sensory features that vary along continuous physical dimensions. The olfactory system, by contrast, contends with an ill-defined, high-dimensional stimulus space and discrete stimuli using a circuit architecture that is shallow and parallelized. Here, we present recent observations in vertebrate and invertebrate systems that relate the statistical structure and state-dependent modulation of olfactory codes to mechanisms of perception and odour-guided behaviour.
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Affiliation(s)
- Kara A Fulton
- Department of Neuroscience, Harvard Medical School, Boston, MA, USA
| | - David Zimmerman
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Aravi Samuel
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Katrin Vogt
- Department of Physics, Harvard University, Cambridge, MA, USA.
- Department of Biology, University of Konstanz, Konstanz, Germany.
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany.
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19
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Lewis SM, Suarez LM, Rigolli N, Franks KM, Steinmetz NA, Gire DH. The spiking output of the mouse olfactory bulb encodes large-scale temporal features of natural odor environments. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.01.582978. [PMID: 38496526 PMCID: PMC10942328 DOI: 10.1101/2024.03.01.582978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
In natural odor environments, odor travels in plumes. Odor concentration dynamics change in characteristic ways across the width and length of a plume. Thus, spatiotemporal dynamics of plumes have informative features for animals navigating to an odor source. Population activity in the olfactory bulb (OB) has been shown to follow odor concentration across plumes to a moderate degree (Lewis et al., 2021). However, it is unknown whether the ability to follow plume dynamics is driven by individual cells or whether it emerges at the population level. Previous research has explored the responses of individual OB cells to isolated features of plumes, but it is difficult to adequately sample the full feature space of plumes as it is still undetermined which features navigating mice employ during olfactory guided search. Here we released odor from an upwind odor source and simultaneously recorded both odor concentration dynamics and cellular response dynamics in awake, head-fixed mice. We found that longer timescale features of odor concentration dynamics were encoded at both the cellular and population level. At the cellular level, responses were elicited at the beginning of the plume for each trial, signaling plume onset. Plumes with high odor concentration elicited responses at the end of the plume, signaling plume offset. Although cellular level tracking of plume dynamics was observed to be weak, we found that at the population level, OB activity distinguished whiffs and blanks (accurately detected odor presence versus absence) throughout the duration of a plume. Even ~20 OB cells were enough to accurately discern odor presence throughout a plume. Our findings indicate that the full range of odor concentration dynamics and high frequency fluctuations are not encoded by OB spiking activity. Instead, relatively lower-frequency temporal features of plumes, such as plume onset, plume offset, whiffs, and blanks, are represented in the OB.
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Affiliation(s)
- Suzanne M. Lewis
- Department of Psychology, University of Washington, Seattle, WA, United States
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Lucas M. Suarez
- Department of Psychology, University of Washington, Seattle, WA, United States
| | - Nicola Rigolli
- Laboratoire de Physique, École Normale Supérieure (LPENS), Paris, France
| | - Kevin M. Franks
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Nicholas A. Steinmetz
- Department of Biological Structure, University of Washington, Seattle, WA, United States
| | - David H. Gire
- Department of Psychology, University of Washington, Seattle, WA, United States
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20
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Emonet T, Vergassola M. Olfactory cues and memories in animal navigation. NATURE REVIEWS. PHYSICS 2024; 6:215-216. [PMID: 39166103 PMCID: PMC11331761 DOI: 10.1038/s42254-024-00710-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/22/2024]
Abstract
Thierry Emonet and Massimo Vergassola discuss what research shows about how animals perform the feat of navigating by smell.
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Affiliation(s)
- Thierry Emonet
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520
- Department of Physics, Yale University, New Haven, CT 06520
- Quantitative Biology Institute, Yale University, New Haven, CT 06520
| | - Massimo Vergassola
- Laboratoire de physique de l'École Normale Supérieure, CNRS, PSL Research University, Sorbonne Université, Paris, France
- Department of Physics, University of California San Diego, La Jolla, CA 92093
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21
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Lindeman S, Fu X, Reinert JK, Fukunaga I. Value-related learning in the olfactory bulb occurs through pathway-dependent perisomatic inhibition of mitral cells. PLoS Biol 2024; 22:e3002536. [PMID: 38427708 PMCID: PMC10936853 DOI: 10.1371/journal.pbio.3002536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 03/13/2024] [Accepted: 02/05/2024] [Indexed: 03/03/2024] Open
Abstract
Associating values to environmental cues is a critical aspect of learning from experiences, allowing animals to predict and maximise future rewards. Value-related signals in the brain were once considered a property of higher sensory regions, but their wide distribution across many brain regions is increasingly recognised. Here, we investigate how reward-related signals begin to be incorporated, mechanistically, at the earliest stage of olfactory processing, namely, in the olfactory bulb. In head-fixed mice performing Go/No-Go discrimination of closely related olfactory mixtures, rewarded odours evoke widespread inhibition in one class of output neurons, that is, in mitral cells but not tufted cells. The temporal characteristics of this reward-related inhibition suggest it is odour-driven, but it is also context-dependent since it is absent during pseudo-conditioning and pharmacological silencing of the piriform cortex. Further, the reward-related modulation is present in the somata but not in the apical dendritic tuft of mitral cells, suggesting an involvement of circuit components located deep in the olfactory bulb. Depth-resolved imaging from granule cell dendritic gemmules suggests that granule cells that target mitral cells receive a reward-related extrinsic drive. Thus, our study supports the notion that value-related modulation of olfactory signals is a characteristic of olfactory processing in the primary olfactory area and narrows down the possible underlying mechanisms to deeper circuit components that contact mitral cells perisomatically.
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Affiliation(s)
- Sander Lindeman
- Sensory and Behavioural Neuroscience Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Xiaochen Fu
- Sensory and Behavioural Neuroscience Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Janine Kristin Reinert
- Sensory and Behavioural Neuroscience Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Izumi Fukunaga
- Sensory and Behavioural Neuroscience Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
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22
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Zavatone-Veth JA, Masset P, Tong WL, Zak JD, Murthy VN, Pehlevan C. Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.21.545947. [PMID: 37961548 PMCID: PMC10634677 DOI: 10.1101/2023.06.21.545947] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Within a single sniff, the mammalian olfactory system can decode the identity and concentration of odorants wafted on turbulent plumes of air. Yet, it must do so given access only to the noisy, dimensionally-reduced representation of the odor world provided by olfactory receptor neurons. As a result, the olfactory system must solve a compressed sensing problem, relying on the fact that only a handful of the millions of possible odorants are present in a given scene. Inspired by this principle, past works have proposed normative compressed sensing models for olfactory decoding. However, these models have not captured the unique anatomy and physiology of the olfactory bulb, nor have they shown that sensing can be achieved within the 100-millisecond timescale of a single sniff. Here, we propose a rate-based Poisson compressed sensing circuit model for the olfactory bulb. This model maps onto the neuron classes of the olfactory bulb, and recapitulates salient features of their connectivity and physiology. For circuit sizes comparable to the human olfactory bulb, we show that this model can accurately detect tens of odors within the timescale of a single sniff. We also show that this model can perform Bayesian posterior sampling for accurate uncertainty estimation. Fast inference is possible only if the geometry of the neural code is chosen to match receptor properties, yielding a distributed neural code that is not axis-aligned to individual odor identities. Our results illustrate how normative modeling can help us map function onto specific neural circuits to generate new hypotheses.
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Affiliation(s)
- Jacob A Zavatone-Veth
- Center for Brain Science, Harvard University Cambridge, MA 02138
- Department of Physics, Harvard University Cambridge, MA 02138
| | - Paul Masset
- Center for Brain Science, Harvard University Cambridge, MA 02138
- Department of Molecular and Cellular Biology, Harvard University Cambridge, MA 02138
| | - William L Tong
- Center for Brain Science, Harvard University Cambridge, MA 02138
- John A. Paulson School of Engineering and Applied Sciences, Harvard University Cambridge, MA 02138
- Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University Cambridge, MA 02138
| | - Joseph D Zak
- Department of Biological Sciences, University of Illinois at Chicago Chicago, IL 60607
| | - Venkatesh N Murthy
- Center for Brain Science, Harvard University Cambridge, MA 02138
- Department of Molecular and Cellular Biology, Harvard University Cambridge, MA 02138
| | - Cengiz Pehlevan
- Center for Brain Science, Harvard University Cambridge, MA 02138
- John A. Paulson School of Engineering and Applied Sciences, Harvard University Cambridge, MA 02138
- Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University Cambridge, MA 02138
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23
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Chandak R, Raman B. Neural manifolds for odor-driven innate and acquired appetitive preferences. Nat Commun 2023; 14:4719. [PMID: 37543628 PMCID: PMC10404252 DOI: 10.1038/s41467-023-40443-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 07/27/2023] [Indexed: 08/07/2023] Open
Abstract
Sensory stimuli evoke spiking neural responses that innately or after learning drive suitable behavioral outputs. How are these spiking activities intrinsically patterned to encode for innate preferences, and could the neural response organization impose constraints on learning? We examined this issue in the locust olfactory system. Using a diverse odor panel, we found that ensemble activities both during ('ON response') and after stimulus presentations ('OFF response') could be linearly mapped onto overall appetitive preference indices. Although diverse, ON and OFF response patterns generated by innately appetitive odorants (higher palp-opening responses) were still limited to a low-dimensional subspace (a 'neural manifold'). Similarly, innately non-appetitive odorants evoked responses that were separable yet confined to another neural manifold. Notably, only odorants that evoked neural response excursions in the appetitive manifold could be associated with gustatory reward. In sum, these results provide insights into how encoding for innate preferences can also impact associative learning.
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Affiliation(s)
- Rishabh Chandak
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Baranidharan Raman
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA.
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24
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Venegas JP, Navarrete M, Orellana-Garcia L, Rojas M, Avello-Duarte F, Nunez-Parra A. Basal Forebrain Modulation of Olfactory Coding In Vivo. Int J Psychol Res (Medellin) 2023; 16:62-86. [PMID: 38106956 PMCID: PMC10723750 DOI: 10.21500/20112084.6486] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/23/2022] [Accepted: 12/07/2022] [Indexed: 12/19/2023] Open
Abstract
Sensory perception is one of the most fundamental brain functions, allowing individuals to properly interact and adapt to a constantly changing environment. This process requires the integration of bottom-up and topdown neuronal activity, which is centrally mediated by the basal forebrain, a brain region that has been linked to a series of cognitive processes such as attention and alertness. Here, we review the latest research using optogenetic approaches in rodents and in vivo electrophysiological recordings that are shedding light on the role of this region, in regulating olfactory processing and decisionmaking. Moreover, we summarize evidence highlighting the anatomical and physiological differences in the basal forebrain of individuals with autism spectrum disorder, which could underpin the sensory perception abnormalities they exhibit, and propose this research line as a potential opportunity to understand the neurobiological basis of this disorder.
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Affiliation(s)
- Juan Pablo Venegas
- Physiology Laboratory, Biology Department, Faculty of Science, University of Chile, Chile.Universidad de ChileUniversity of ChileChile
| | - Marcela Navarrete
- Physiology Laboratory, Biology Department, Faculty of Science, University of Chile, Chile.Universidad de ChileUniversity of ChileChile
| | - Laura Orellana-Garcia
- Physiology Laboratory, Biology Department, Faculty of Science, University of Chile, Chile.Universidad de ChileUniversity of ChileChile
| | - Marcelo Rojas
- Physiology Laboratory, Biology Department, Faculty of Science, University of Chile, Chile.Universidad de ChileUniversity of ChileChile
| | - Felipe Avello-Duarte
- Physiology Laboratory, Biology Department, Faculty of Science, University of Chile, Chile.Universidad de ChileUniversity of ChileChile
| | - Alexia Nunez-Parra
- Physiology Laboratory, Biology Department, Faculty of Science, University of Chile, Chile.Universidad de ChileUniversity of ChileChile
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25
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Yiling Y, Shapcott K, Peter A, Klon-Lipok J, Xuhui H, Lazar A, Singer W. Robust encoding of natural stimuli by neuronal response sequences in monkey visual cortex. Nat Commun 2023; 14:3021. [PMID: 37231014 DOI: 10.1038/s41467-023-38587-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 05/08/2023] [Indexed: 05/27/2023] Open
Abstract
Parallel multisite recordings in the visual cortex of trained monkeys revealed that the responses of spatially distributed neurons to natural scenes are ordered in sequences. The rank order of these sequences is stimulus-specific and maintained even if the absolute timing of the responses is modified by manipulating stimulus parameters. The stimulus specificity of these sequences was highest when they were evoked by natural stimuli and deteriorated for stimulus versions in which certain statistical regularities were removed. This suggests that the response sequences result from a matching operation between sensory evidence and priors stored in the cortical network. Decoders trained on sequence order performed as well as decoders trained on rate vectors but the former could decode stimulus identity from considerably shorter response intervals than the latter. A simulated recurrent network reproduced similarly structured stimulus-specific response sequences, particularly once it was familiarized with the stimuli through non-supervised Hebbian learning. We propose that recurrent processing transforms signals from stationary visual scenes into sequential responses whose rank order is the result of a Bayesian matching operation. If this temporal code were used by the visual system it would allow for ultrafast processing of visual scenes.
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Affiliation(s)
- Yang Yiling
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- International Max Planck Research School (IMPRS) for Neural Circuits, 60438, Frankfurt am Main, Germany
- Faculty of Biological Sciences, Goethe-University Frankfurt am Main, 60438, Frankfurt am Main, Germany
| | - Katharine Shapcott
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
| | - Alina Peter
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- International Max Planck Research School (IMPRS) for Neural Circuits, 60438, Frankfurt am Main, Germany
- Faculty of Biological Sciences, Goethe-University Frankfurt am Main, 60438, Frankfurt am Main, Germany
| | - Johanna Klon-Lipok
- Max Planck Institute for Brain Research, 60438, Frankfurt am Main, Germany
| | - Huang Xuhui
- Intelligent Science and Technology Academy, China Aerospace Science and Industry Corporation (CASIC), 100144, Beijing, China
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
| | - Andreea Lazar
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
| | - Wolf Singer
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany.
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany.
- Max Planck Institute for Brain Research, 60438, Frankfurt am Main, Germany.
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26
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Faini G, Tanese D, Molinier C, Telliez C, Hamdani M, Blot F, Tourain C, de Sars V, Del Bene F, Forget BC, Ronzitti E, Emiliani V. Ultrafast light targeting for high-throughput precise control of neuronal networks. Nat Commun 2023; 14:1888. [PMID: 37019891 PMCID: PMC10074378 DOI: 10.1038/s41467-023-37416-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/16/2023] [Indexed: 04/07/2023] Open
Abstract
Two-photon, single-cell resolution optogenetics based on holographic light-targeting approaches enables the generation of precise spatiotemporal neuronal activity patterns and thus a broad range of experimental applications, such as high throughput connectivity mapping and probing neural codes for perception. Yet, current holographic approaches limit the resolution for tuning the relative spiking time of distinct cells to a few milliseconds, and the achievable number of targets to 100-200, depending on the working depth. To overcome these limitations and expand the capabilities of single-cell optogenetics, we introduce an ultra-fast sequential light targeting (FLiT) optical configuration based on the rapid switching of a temporally focused beam between holograms at kHz rates. We used FLiT to demonstrate two illumination protocols, termed hybrid- and cyclic-illumination, and achieve sub-millisecond control of sequential neuronal activation and high throughput multicell illumination in vitro (mouse organotypic and acute brain slices) and in vivo (zebrafish larvae and mice), while minimizing light-induced thermal rise. These approaches will be important for experiments that require rapid and precise cell stimulation with defined spatio-temporal activity patterns and optical control of large neuronal ensembles.
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Affiliation(s)
- Giulia Faini
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Dimitrii Tanese
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Clément Molinier
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Cécile Telliez
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Massilia Hamdani
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Francois Blot
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Christophe Tourain
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Vincent de Sars
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Filippo Del Bene
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Benoît C Forget
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France
| | - Emiliano Ronzitti
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France.
| | - Valentina Emiliani
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012, Paris, France.
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27
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Verhagen JV, Baker KL, Vasan G, Pieribone VA, Rolls ET. Odor encoding by signals in the olfactory bulb. J Neurophysiol 2023; 129:431-444. [PMID: 36598147 PMCID: PMC9925169 DOI: 10.1152/jn.00449.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 01/05/2023] Open
Abstract
To understand the operation of the olfactory system, it is essential to know how information is encoded in the olfactory bulb. We applied Shannon information theoretic methods to address this, with signals from up to 57 glomeruli simultaneously optically imaged from presynaptic inputs in glomeruli in the mouse dorsal (dOB) and lateral (lOB) olfactory bulb, in response to six exemplar pure chemical odors. We discovered that, first, the tuning of these signals from glomeruli to a set of odors is remarkably broad, with a mean sparseness of 0.83 and a mean signal correlation of 0.64. Second, both of these factors contribute to the low information that is available from the responses of even populations of many tens of glomeruli, which was only 1.35 bits across 33 glomeruli on average, compared with the 2.58 bits required to perfectly encode these six odors. Third, although there is considerable interest in the possibility of temporal encoding of stimulus including odor identity, the amount of information in the temporal aspects of the presynaptic glomerular responses was low (mean 0.11 bits) and, importantly, was redundant with respect to the information available from the rates. Fourth, the information from simultaneously recorded glomeruli asymptotes very gradually and nonlinearly, showing that glomeruli do not have independent responses. Fifth, the information from a population became available quite rapidly, within 100 ms of sniff onset, and the peak of the glomerular response was at 200 ms. Sixth, the information from the lOB was not additive with that of the dOB.NEW & NOTEWORTHY We report broad tuning and low odor information available across the lateral and dorsal bulb populations of glomeruli. Even though response latencies can be significantly predictive of stimulus identity, such contained very little information and none that was not redundant with information based on rate coding alone. Last, in line with the emerging notion of the important role of earliest stages of responses ("primacy"), we report a very rapid rise in information after each inhalation.
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Affiliation(s)
- Justus V Verhagen
- The John B. Pierce Laboratory, New Haven, Connecticut
- Department of Neuroscience, Yale University, New Haven, Connecticut
| | - Keeley L Baker
- The John B. Pierce Laboratory, New Haven, Connecticut
- Department of Neuroscience, Yale University, New Haven, Connecticut
| | - Ganesh Vasan
- The John B. Pierce Laboratory, New Haven, Connecticut
- Department of Neuroscience, Yale University, New Haven, Connecticut
| | - Vincent A Pieribone
- The John B. Pierce Laboratory, New Haven, Connecticut
- Department of Neuroscience, Yale University, New Haven, Connecticut
- Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, Connecticut
| | - Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, United Kingdom
- University of Warwick, Coventry, United Kingdom
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28
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Accanto N, Blot FGC, Lorca-Cámara A, Zampini V, Bui F, Tourain C, Badt N, Katz O, Emiliani V. A flexible two-photon fiberscope for fast activity imaging and precise optogenetic photostimulation of neurons in freely moving mice. Neuron 2023; 111:176-189.e6. [PMID: 36395773 DOI: 10.1016/j.neuron.2022.10.030] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 07/28/2022] [Accepted: 10/19/2022] [Indexed: 11/17/2022]
Abstract
We developed a flexible two-photon microendoscope (2P-FENDO) capable of all-optical brain investigation at near cellular resolution in freely moving mice. The system performs fast two-photon (2P) functional imaging and 2P holographic photostimulation of single and multiple cells using axially confined extended spots. Proof-of-principle experiments were performed in freely moving mice co-expressing jGCaMP7s and the opsin ChRmine in the visual or barrel cortex. On a field of view of 250 μm in diameter, we demonstrated functional imaging at a frame rate of up to 50 Hz and precise photostimulation of selected groups of cells. With the capability to simultaneously image and control defined neuronal networks in freely moving animals, 2P-FENDO will enable a precise investigation of neuronal functions in the brain during naturalistic behaviors.
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Affiliation(s)
- Nicolò Accanto
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France.
| | - François G C Blot
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | | | - Valeria Zampini
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | - Florence Bui
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | - Christophe Tourain
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | - Noam Badt
- Department of Applied Physics, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Ori Katz
- Department of Applied Physics, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Valentina Emiliani
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France.
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29
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Zavatone-Veth JA, Masset P, Tong WL, Zak JD, Murthy VN, Pehlevan C. Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 2023; 36:64793-64828. [PMID: 40376274 PMCID: PMC12079577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 05/18/2025]
Abstract
Within a single sniff, the mammalian olfactory system can decode the identity and concentration of odorants wafted on turbulent plumes of air. Yet, it must do so given access only to the noisy, dimensionally-reduced representation of the odor world provided by olfactory receptor neurons. As a result, the olfactory system must solve a compressed sensing problem, relying on the fact that only a handful of the millions of possible odorants are present in a given scene. Inspired by this principle, past works have proposed normative compressed sensing models for olfactory decoding. However, these models have not captured the unique anatomy and physiology of the olfactory bulb, nor have they shown that sensing can be achieved within the 100-millisecond timescale of a single sniff. Here, we propose a rate-based Poisson compressed sensing circuit model for the olfactory bulb. This model maps onto the neuron classes of the olfactory bulb, and recapitulates salient features of their connectivity and physiology. For circuit sizes comparable to the human olfactory bulb, we show that this model can accurately detect tens of odors within the timescale of a single sniff. We also show that this model can perform Bayesian posterior sampling for accurate uncertainty estimation. Fast inference is possible only if the geometry of the neural code is chosen to match receptor properties, yielding a distributed neural code that is not axis-aligned to individual odor identities. Our results illustrate how normative modeling can help us map function onto specific neural circuits to generate new hypotheses.
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Affiliation(s)
- Jacob A Zavatone-Veth
- Center for Brain Science, Harvard University, Cambridge, MA 02138
- Department of Physics, Harvard University, Cambridge, MA 02138
| | - Paul Masset
- Center for Brain Science, Harvard University, Cambridge, MA 02138
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138
| | - William L Tong
- Center for Brain Science, Harvard University, Cambridge, MA 02138
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
- Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University Cambridge, MA 02138
| | - Joseph D Zak
- Department of Biological Sciences, University of Illinois at Chicago Chicago, IL 60607
| | - Venkatesh N Murthy
- Center for Brain Science, Harvard University, Cambridge, MA 02138
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138
| | - Cengiz Pehlevan
- Center for Brain Science, Harvard University, Cambridge, MA 02138
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
- Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University Cambridge, MA 02138
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30
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Chae H, Banerjee A, Dussauze M, Albeanu DF. Long-range functional loops in the mouse olfactory system and their roles in computing odor identity. Neuron 2022; 110:3970-3985.e7. [PMID: 36174573 PMCID: PMC9742324 DOI: 10.1016/j.neuron.2022.09.005] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 07/12/2022] [Accepted: 09/02/2022] [Indexed: 12/15/2022]
Abstract
Elucidating the neural circuits supporting odor identification remains an open challenge. Here, we analyze the contribution of the two output cell types of the mouse olfactory bulb (mitral and tufted cells) to decode odor identity and concentration and its dependence on top-down feedback from their respective major cortical targets: piriform cortex versus anterior olfactory nucleus. We find that tufted cells substantially outperform mitral cells in decoding both odor identity and intensity. Cortical feedback selectively regulates the activity of its dominant bulb projection cell type and implements different computations. Piriform feedback specifically restructures mitral responses, whereas feedback from the anterior olfactory nucleus preferentially controls the gain of tufted representations without altering their odor tuning. Our results identify distinct functional loops involving the mitral and tufted cells and their cortical targets. We suggest that in addition to the canonical mitral-to-piriform pathway, tufted cells and their target regions are ideally positioned to compute odor identity.
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Affiliation(s)
- Honggoo Chae
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Arkarup Banerjee
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA; Cold Spring Harbor Laboratory School for Biological Sciences, Cold Spring Harbor, NY, USA
| | - Marie Dussauze
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA; Cold Spring Harbor Laboratory School for Biological Sciences, Cold Spring Harbor, NY, USA
| | - Dinu F Albeanu
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA; Cold Spring Harbor Laboratory School for Biological Sciences, Cold Spring Harbor, NY, USA.
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31
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Weible AP, Yavorska I, Narayanan A, Wehr M. A genetically identified population of layer 4 neurons in auditory cortex that contributes to pre-pulse inhibition of the acoustic startle response. Front Neural Circuits 2022; 16:972157. [PMID: 36160948 PMCID: PMC9492996 DOI: 10.3389/fncir.2022.972157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 08/12/2022] [Indexed: 11/24/2022] Open
Abstract
A fundamental task faced by the auditory system is the detection of events that are signaled by fluctuations in sound. Spiking in auditory cortical neurons is critical for sound detection, but the causal roles of specific cell types and circuits are still mostly unknown. Here we tested the role of a genetically identified population of layer 4 auditory cortical neurons in sound detection. We measured sound detection using a common variant of pre-pulse inhibition of the acoustic startle response, in which a silent gap in background noise acts as a cue that attenuates startle. We used a Gpr26-Cre driver line, which we found expressed predominantly in layer 4 of auditory cortex. Photostimulation of these cells, which were responsive to gaps in noise, was sufficient to attenuate the startle reflex. Photosuppression of these cells reduced neural responses to gaps throughout cortex, and impaired behavioral gap detection. These data demonstrate that cortical Gpr26 neurons are both necessary and sufficient for top–down modulation of the acoustic startle reflex, and are thus likely to be involved in sound detection.
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32
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The facets of olfactory learning. Curr Opin Neurobiol 2022; 76:102623. [PMID: 35998474 DOI: 10.1016/j.conb.2022.102623] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/17/2022] [Accepted: 07/21/2022] [Indexed: 11/23/2022]
Abstract
Volatile chemicals in the environment provide ethologically important information to many animals. However, how animals learn to use this information is only beginning to be understood. This review highlights recent experimental advances elucidating olfactory learning in rodents, ranging from adaptations to the environment to task-dependent refinement and multisensory associations. The broad range of phenomena, mechanisms, and brain areas involved demonstrate the complex and multifaceted nature of olfactory learning.
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33
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Moroni M, Brondi M, Fellin T, Panzeri S. SmaRT2P: a software for generating and processing smart line recording trajectories for population two-photon calcium imaging. Brain Inform 2022; 9:18. [PMID: 35927517 PMCID: PMC9352634 DOI: 10.1186/s40708-022-00166-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 07/01/2022] [Indexed: 11/17/2022] Open
Abstract
Two-photon fluorescence calcium imaging allows recording the activity of large neural populations with subcellular spatial resolution, but it is typically characterized by low signal-to-noise ratio (SNR) and poor accuracy in detecting single or few action potentials when large number of neurons are imaged. We recently showed that implementing a smart line scanning approach using trajectories that optimally sample the regions of interest increases both the SNR fluorescence signals and the accuracy of single spike detection in population imaging in vivo. However, smart line scanning requires highly specialised software to design recording trajectories, interface with acquisition hardware, and efficiently process acquired data. Furthermore, smart line scanning needs optimized strategies to cope with movement artefacts and neuropil contamination. Here, we develop and validate SmaRT2P, an open-source, user-friendly and easy-to-interface Matlab-based software environment to perform optimized smart line scanning in two-photon calcium imaging experiments. SmaRT2P is designed to interface with popular acquisition software (e.g., ScanImage) and implements novel strategies to detect motion artefacts, estimate neuropil contamination, and minimize their impact on functional signals extracted from neuronal population imaging. SmaRT2P is structured in a modular way to allow flexibility in the processing pipeline, requiring minimal user intervention in parameter setting. The use of SmaRT2P for smart line scanning has the potential to facilitate the functional investigation of large neuronal populations with increased SNR and accuracy in detecting the discharge of single and few action potentials.
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Affiliation(s)
- Monica Moroni
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems, UniTn, Istituto Italiano Di Tecnologia, 38068, Rovereto, Italy.
| | - Marco Brondi
- Optical Approaches to Brain Function Laboratory, Istituto Italiano Di Tecnologia, 16163, Genoa, Italy.,Department of Biomedical Sciences-UNIPD, Università Degli Studi Di Padova, 35121, Padua, Italy.,Padova Neuroscience Center (PNC), Università Degli Studi Di Padova, 35129, Padua, Italy
| | - Tommaso Fellin
- Optical Approaches to Brain Function Laboratory, Istituto Italiano Di Tecnologia, 16163, Genoa, Italy
| | - Stefano Panzeri
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems, UniTn, Istituto Italiano Di Tecnologia, 38068, Rovereto, Italy. .,Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), 20251, Hamburg, Germany.
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34
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Panzeri S, Moroni M, Safaai H, Harvey CD. The structures and functions of correlations in neural population codes. Nat Rev Neurosci 2022; 23:551-567. [PMID: 35732917 DOI: 10.1038/s41583-022-00606-4] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2022] [Indexed: 12/17/2022]
Abstract
The collective activity of a population of neurons, beyond the properties of individual cells, is crucial for many brain functions. A fundamental question is how activity correlations between neurons affect how neural populations process information. Over the past 30 years, major progress has been made on how the levels and structures of correlations shape the encoding of information in population codes. Correlations influence population coding through the organization of pairwise-activity correlations with respect to the similarity of tuning of individual neurons, by their stimulus modulation and by the presence of higher-order correlations. Recent work has shown that correlations also profoundly shape other important functions performed by neural populations, including generating codes across multiple timescales and facilitating information transmission to, and readout by, downstream brain areas to guide behaviour. Here, we review this recent work and discuss how the structures of correlations can have opposite effects on the different functions of neural populations, thus creating trade-offs and constraints for the structure-function relationships of population codes. Further, we present ideas on how to combine large-scale simultaneous recordings of neural populations, computational models, analyses of behaviour, optogenetics and anatomy to unravel how the structures of correlations might be optimized to serve multiple functions.
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Affiliation(s)
- Stefano Panzeri
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany. .,Istituto Italiano di Tecnologia, Rovereto, Italy.
| | | | - Houman Safaai
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
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35
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Ackels T, Schaefer AT. Getting out the caliper: Behavioral quantification of perceptual odor similarity. CELL REPORTS METHODS 2022; 2:100240. [PMID: 35784647 PMCID: PMC9243597 DOI: 10.1016/j.crmeth.2022.100240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Rigorously quantifying perceptual similarity is essential to link sensory stimuli to neural activity and to define the dimensionality of perceptual space, which is challenging for the chemical senses in particular. Nakayama, Gerkin, and Rinberg present an efficient delayed match-to-sample behavioral paradigm that promises to provide a metric for odor similarity.
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Affiliation(s)
- Tobias Ackels
- Sensory Circuits and Neurotechnology Lab, The Francis Crick Institute, London, UK
- Department of Neuroscience, Physiology and Pharmacology, University College, London, UK
| | - Andreas T. Schaefer
- Sensory Circuits and Neurotechnology Lab, The Francis Crick Institute, London, UK
- Department of Neuroscience, Physiology and Pharmacology, University College, London, UK
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36
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Nakayama H, Gerkin RC, Rinberg D. A behavioral paradigm for measuring perceptual distances in mice. CELL REPORTS METHODS 2022; 2:100233. [PMID: 35784646 PMCID: PMC9243525 DOI: 10.1016/j.crmeth.2022.100233] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 02/20/2022] [Accepted: 05/17/2022] [Indexed: 01/22/2023]
Abstract
Perceptual similarities between a specific stimulus and other stimuli of the same modality provide valuable information about the structure and geometry of sensory spaces. While typically assessed in human behavioral experiments, perceptual similarities-or distances-are rarely measured in other species. However, understanding the neural computations responsible for sensory representations requires the monitoring and often manipulation of neural activity, which is more readily achieved in non-human experimental models. Here, we develop a behavioral paradigm that enables the quantification of perceptual similarity between sensory stimuli using mouse olfaction as a model system.
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Affiliation(s)
| | - Richard C. Gerkin
- School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - Dmitry Rinberg
- Neuroscience Institute, NYU Langone Health, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
- Department of Physics, New York University, New York, NY 10003, USA
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37
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Dorrego-Rivas A, Grubb MS. Developing and maintaining a nose-to-brain map of odorant identity. Open Biol 2022; 12:220053. [PMID: 35765817 PMCID: PMC9240688 DOI: 10.1098/rsob.220053] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/24/2022] [Indexed: 01/04/2023] Open
Abstract
Olfactory sensory neurons (OSNs) in the olfactory epithelium of the nose transduce chemical odorant stimuli into electrical signals. These signals are then sent to the OSNs' target structure in the brain, the main olfactory bulb (OB), which performs the initial stages of sensory processing in olfaction. The projection of OSNs to the OB is highly organized in a chemospatial map, whereby axon terminals from OSNs expressing the same odorant receptor (OR) coalesce into individual spherical structures known as glomeruli. This nose-to-brain map of odorant identity is built from late embryonic development to early postnatal life, through a complex combination of genetically encoded, OR-dependent and activity-dependent mechanisms. It must then be actively maintained throughout adulthood as OSNs experience turnover due to external insult and ongoing neurogenesis. Our review describes and discusses these two distinct and crucial processes in olfaction, focusing on the known mechanisms that first establish and then maintain chemospatial order in the mammalian OSN-to-OB projection.
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Affiliation(s)
- Ana Dorrego-Rivas
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Matthew S. Grubb
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
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38
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Augusto PPC, Bolini HMA. The role of conching in chocolate flavor development: A review. Compr Rev Food Sci Food Saf 2022; 21:3274-3296. [DOI: 10.1111/1541-4337.12975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 04/13/2022] [Accepted: 04/21/2022] [Indexed: 12/01/2022]
Affiliation(s)
- Pedro Pio C. Augusto
- Food Engineering and Technology Department, School of Food Engineering University of Campinas (UNICAMP) Campinas Brazil
| | - Helena M. A. Bolini
- Food Engineering and Technology Department, School of Food Engineering University of Campinas (UNICAMP) Campinas Brazil
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39
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Zhao Z, Zung JL, Hinze A, Kriete AL, Iqbal A, Younger MA, Matthews BJ, Merhof D, Thiberge S, Ignell R, Strauch M, McBride CS. Mosquito brains encode unique features of human odour to drive host seeking. Nature 2022; 605:706-712. [PMID: 35508661 PMCID: PMC9725754 DOI: 10.1038/s41586-022-04675-4] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Accepted: 03/22/2022] [Indexed: 11/09/2022]
Abstract
A globally invasive form of the mosquito Aedes aegypti specializes in biting humans, making it an efficient disease vector1. Host-seeking female mosquitoes strongly prefer human odour over the odour of animals2,3, but exactly how they distinguish between the two is not known. Vertebrate odours are complex blends of volatile chemicals with many shared components4-7, making discrimination an interesting sensory coding challenge. Here we show that human and animal odours evoke activity in distinct combinations of olfactory glomeruli within the Ae. aegypti antennal lobe. One glomerulus in particular is strongly activated by human odour but responds weakly, or not at all, to animal odour. This human-sensitive glomerulus is selectively tuned to the long-chain aldehydes decanal and undecanal, which we show are consistently enriched in human odour and which probably originate from unique human skin lipids. Using synthetic blends, we further demonstrate that signalling in the human-sensitive glomerulus significantly enhances long-range host-seeking behaviour in a wind tunnel, recapitulating preference for human over animal odours. Our research suggests that animal brains may distil complex odour stimuli of innate biological relevance into simple neural codes and reveals targets for the design of next-generation mosquito-control strategies.
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Affiliation(s)
- Zhilei Zhao
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA.
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA.
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA.
| | - Jessica L Zung
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Annika Hinze
- Unit of Chemical Ecology, Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Alexis L Kriete
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Graduate Program in Entomology, North Carolina State University, Raleigh, NC, USA
| | - Azwad Iqbal
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Department of Natural Resources and the Environment, Cornell University, Ithaca, NY, USA
| | - Meg A Younger
- Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY, USA
- Department of Biology, Boston University, Boston, MA, USA
| | - Benjamin J Matthews
- Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY, USA
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Dorit Merhof
- Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany
| | - Stephan Thiberge
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA
| | - Rickard Ignell
- Unit of Chemical Ecology, Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Martin Strauch
- Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany
| | - Carolyn S McBride
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA.
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA.
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40
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Perks KE, Sawtell NB. Neural readout of a latency code in the active electrosensory system. Cell Rep 2022; 38:110605. [PMID: 35354029 PMCID: PMC9045710 DOI: 10.1016/j.celrep.2022.110605] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/03/2022] [Accepted: 03/10/2022] [Indexed: 11/29/2022] Open
Abstract
The latency of spikes relative to a stimulus conveys sensory information across modalities. However, in most cases, it remains unclear whether and how such latency codes are utilized by postsynaptic neurons. In the active electrosensory system of mormyrid fish, a latency code for stimulus amplitude in electroreceptor afferent nerve fibers (EAs) is hypothesized to be read out by a central reference provided by motor corollary discharge (CD). Here, we demonstrate that CD enhances sensory responses in postsynaptic granular cells of the electrosensory lobe but is not required for reading out EA input. Instead, diverse latency and spike count tuning across the EA population give rise to graded information about stimulus amplitude that can be read out by standard integration of converging excitatory synaptic inputs. Inhibitory control over the temporal window of integration renders two granular cell subclasses differentially sensitive to information derived from relative spike latency versus spike count.
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Affiliation(s)
- Krista E Perks
- Department of Biology, Wesleyan University, Middletown, CT 06459, USA; Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA
| | - Nathaniel B Sawtell
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA.
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41
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Chen X, Shi J, Wang T, Zheng S, Lv W, Chen X, Yang J, Zeng M, Hu N, Su Y, Wei H, Zhou Z, Yang Z. High-Performance Wearable Sensor Inspired by the Neuron Conduction Mechanism through Gold-Induced Sulfur Vacancies. ACS Sens 2022; 7:816-826. [PMID: 35188381 DOI: 10.1021/acssensors.1c02452] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Practical application of wearable gas-sensing devices has been greatly inhibited by the poorly sensitive and specific recognition of target gases. Rapid charge transfer caused by rich sensory neurons in the biological olfactory system has inspired the construction of a highly sensitive sensor network with abundant defect sites for adsorption. Herein, for the first time, we demonstrate an in situ formed neuron-mimic gas sensor in a single gas-sensing channel, which is derived from lattice deviation of S atoms in Bi2S3 nanosheets induced by gold quantum dots. Due to the favorable gas adsorption and charge transfer properties arising from S vacancies, the fabricated sensor exhibits a significantly enhanced response value of 5.6-5 ppm NO2, ultrafast response/recovery performance (18 and 338 s), and excellent selectivity. Furthermore, real-time visual detection of target gases has been accomplished by integrating the flexible sensor into a wearable device.
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Affiliation(s)
- Xinwei Chen
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Jia Shi
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Tao Wang
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Shuyue Zheng
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, P. R. China
| | - Wen Lv
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Xiyu Chen
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Jianhua Yang
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Min Zeng
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Nantao Hu
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Yanjie Su
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Hao Wei
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Zhihua Zhou
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Zhi Yang
- Key Laboratory of Thin Film and Microfabrication (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
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42
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Chen Z, Padmanabhan K. Top-down feedback enables flexible coding strategies in the olfactory cortex. Cell Rep 2022; 38:110545. [PMID: 35320723 DOI: 10.1016/j.celrep.2022.110545] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/30/2021] [Accepted: 03/01/2022] [Indexed: 11/03/2022] Open
Abstract
In chemical sensation, multiple models have been proposed to explain how odors are represented in the olfactory cortex. One hypothesis is that the combinatorial identity of active neurons within sniff-related time windows is critical, whereas another model proposes that it is the temporal structure of neural activity that is essential for encoding odor information. We find that top-down feedback to the main olfactory bulb dictates the information transmitted to the piriform cortex and switches between these coding strategies. Using a detailed network model, we demonstrate that feedback control of inhibition influences the excitation-inhibition balance in mitral cells, restructuring the dynamics of piriform cortical cells. This results in performance improvement in odor discrimination tasks. These findings present a framework for early olfactory computation, where top-down feedback to the bulb flexibly shapes the temporal structure of neural activity in the piriform cortex, allowing the early olfactory system to dynamically switch between two distinct coding models.
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Affiliation(s)
- Zhen Chen
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA
| | - Krishnan Padmanabhan
- Department of Neuroscience, Neuroscience Graduate Program, Del Monte Institute for Neuroscience, Center for Visual Sciences, Intellectual and Developmental Disability Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
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43
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Amores J, Dotan M, Maes P. Development and Study of Ezzence: A Modular Scent Wearable to Improve Wellbeing in Home Sleep Environments. Front Psychol 2022; 13:791768. [PMID: 35369196 PMCID: PMC8970317 DOI: 10.3389/fpsyg.2022.791768] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 01/31/2022] [Indexed: 11/26/2022] Open
Abstract
Ezzence is the first smartphone-controlled olfactometer designed for both day and night conditions. We discuss the design and technical implementation of Ezzence and report on a study to evaluate the feasibility of using the device in home-based sleep environments. The study results (N = 40) show that participants were satisfied with the device and found it easy to use. Furthermore, participants reported a significant improvement in sleep quality when using the device with scent in comparison to the control condition (p = 0.003), as well as better mood the following morning (p = 0.038) and shorter time to sleep onset (p = 0.008). The device is integrated with a wearable EEG and real-time sleep staging algorithm to release scent during specific sleep stages (N1, N2, N3, and REM), which is important for certain use cases (e.g., to study the effect of scent on REM dreams, or to improve memory consolidation with a re-exposure of scent during N2 and N3). Ezzence can be used for several applications, including those that require scent triggered day and night. They include targeted memory reactivation, longitudinal health treatments, therapy, and mental or physical exercises. Finally, this article proposes an interaction framework to understand relationships between scents and environments based on proxemic dimensions and passive or active interactions during sleep.
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Affiliation(s)
- Judith Amores
- MIT Media Lab, Cambridge, MA, United States
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Mae Dotan
- MIT Media Lab, Cambridge, MA, United States
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44
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Coureaud G, Thomas-Danguin T, Sandoz JC, Wilson DA. Biological constraints on configural odour mixture perception. J Exp Biol 2022; 225:274695. [PMID: 35285471 PMCID: PMC8996812 DOI: 10.1242/jeb.242274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Animals, including humans, detect odours and use this information to behave efficiently in the environment. Frequently, odours consist of complex mixtures of odorants rather than single odorants, and mixtures are often perceived as configural wholes, i.e. as odour objects (e.g. food, partners). The biological rules governing this 'configural perception' (as opposed to the elemental perception of mixtures through their components) remain weakly understood. Here, we first review examples of configural mixture processing in diverse species involving species-specific biological signals. Then, we present the original hypothesis that at least certain mixtures can be processed configurally across species. Indeed, experiments conducted in human adults, newborn rabbits and, more recently, in rodents and honeybees show that these species process some mixtures in a remarkably similar fashion. Strikingly, a mixture AB (A, ethyl isobutyrate; B, ethyl maltol) induces configural processing in humans, who perceive a mixture odour quality (pineapple) distinct from the component qualities (A, strawberry; B, caramel). The same mixture is weakly configurally processed in rabbit neonates, which perceive a particular odour for the mixture in addition to the component odours. Mice and honeybees also perceive the AB mixture configurally, as they respond differently to the mixture compared with its components. Based on these results and others, including neurophysiological approaches, we propose that certain mixtures are convergently perceived across various species of vertebrates/invertebrates, possibly as a result of a similar anatomical organization of their olfactory systems and the common necessity to simplify the environment's chemical complexity in order to display adaptive behaviours.
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Affiliation(s)
- Gérard Coureaud
- Centre de Recherche en Neurosciences de Lyon, Team Sensory Neuroethology (ENES), CNRS/INSERM/UCBL1/UJM, 69500 Lyon, France
| | - Thierry Thomas-Danguin
- Centre des Sciences du Goût et de l'Alimentation, Team Flavor, Food Oral Processing and Perception, INRAE, CNRS, Institut Agro Dijon, Université Bourgogne Franche-Comté, 21000 Dijon, France
| | - Jean-Christophe Sandoz
- Evolution, Genomes, Behavior and Ecology, CNRS, Université Paris-Saclay, IRD, 91190 Gif-sur-Yvette, France
| | - Donald A Wilson
- Department of Child & Adolescent Psychiatry, New York University Langone School of Medicine and Nathan S. Kline Institute for Psychiatric Research, New York, NY 10016, USA
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45
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Schreck MR, Zhuang L, Janke E, Moberly AH, Bhattarai JP, Gottfried JA, Wesson DW, Ma M. State-dependent olfactory processing in freely behaving mice. Cell Rep 2022; 38:110450. [PMID: 35235805 PMCID: PMC8958632 DOI: 10.1016/j.celrep.2022.110450] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 11/07/2021] [Accepted: 02/07/2022] [Indexed: 11/06/2022] Open
Abstract
Decreased responsiveness to sensory stimuli during sleep is presumably mediated via thalamic gating. Without an obligatory thalamic relay in the olfactory system, the anterior piriform cortex (APC) is suggested to be a gate in anesthetized states. However, olfactory processing in natural sleep states remains undetermined. Here, we simultaneously record local field potentials (LFPs) in hierarchical olfactory regions (olfactory bulb [OB], APC, and orbitofrontal cortex) while optogenetically activating olfactory sensory neurons, ensuring consistent peripheral inputs across states in behaving mice. Surprisingly, evoked LFPs in sleep states (both non-rapid eye movement [NREM] and rapid eye movement [REM]) are larger and contain greater gamma-band power and cross-region coherence (compared to wakefulness) throughout the olfactory pathway, suggesting the lack of a central gate. Single-unit recordings from the OB and APC reveal a higher percentage of responsive neurons during sleep with a higher incidence of suppressed firing. Additionally, nasal breathing is slower and shallower during sleep, suggesting a partial peripheral gating mechanism. Schreck et al. examine how the olfactory system responds to the same peripheral stimulus during natural sleep and wake in mice. Larger responses along the pathway during sleep suggest the lack of a central gate, but slower and shallower breathing may act as a partial peripheral gate to reduce olfactory input.
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Affiliation(s)
- Mary R Schreck
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
| | - Liujing Zhuang
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Emma Janke
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Andrew H Moberly
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Janardhan P Bhattarai
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Jay A Gottfried
- Department of Psychology, University of Pennsylvania, School of Arts and Sciences; Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Daniel W Wesson
- Department of Pharmacology and Therapeutics, University of Florida, Gainesville, FL 32610, USA
| | - Minghong Ma
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
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46
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Bitzenhofer SH, Westeinde EA, Zhang HXB, Isaacson JS. Rapid odor processing by layer 2 subcircuits in lateral entorhinal cortex. eLife 2022; 11:75065. [PMID: 35129439 PMCID: PMC8860446 DOI: 10.7554/elife.75065] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 02/04/2022] [Indexed: 11/27/2022] Open
Abstract
Olfactory information is encoded in lateral entorhinal cortex (LEC) by two classes of layer 2 (L2) principal neurons: fan and pyramidal cells. However, the functional properties of L2 cells and how they contribute to odor coding are unclear. Here, we show in awake mice that L2 cells respond to odors early during single sniffs and that LEC is essential for rapid discrimination of both odor identity and intensity. Population analyses of L2 ensembles reveal that rate coding distinguishes odor identity, but firing rates are only weakly concentration dependent and changes in spike timing can represent odor intensity. L2 principal cells differ in afferent olfactory input and connectivity with inhibitory circuits and the relative timing of pyramidal and fan cell spikes provides a temporal code for odor intensity. Downstream, intensity is encoded purely by spike timing in hippocampal CA1. Together, these results reveal the unique processing of odor information by LEC subcircuits and highlight the importance of temporal coding in higher olfactory areas.
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Affiliation(s)
| | - Elena A Westeinde
- Department of Neurosciences, University of California, San Diego, La Jolla, United States
| | - Han-Xiong Bear Zhang
- Department of Neurosciences, University of California, San Diego, La Jolla, United States
| | - Jeffry S Isaacson
- Department of Neurosciences, University of California, San Diego, La Jolla, United States
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47
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Tufo C, Poopalasundaram S, Dorrego-Rivas A, Ford MC, Graham A, Grubb MS. Development of the mammalian main olfactory bulb. Development 2022; 149:274348. [PMID: 35147186 PMCID: PMC8918810 DOI: 10.1242/dev.200210] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The mammalian main olfactory bulb is a crucial processing centre for the sense of smell. The olfactory bulb forms early during development and is functional from birth. However, the olfactory system continues to mature and change throughout life as a target of constitutive adult neurogenesis. Our Review synthesises current knowledge of prenatal, postnatal and adult olfactory bulb development, focusing on the maturation, morphology, functions and interactions of its diverse constituent glutamatergic and GABAergic cell types. We highlight not only the great advances in the understanding of olfactory bulb development made in recent years, but also the gaps in our present knowledge that most urgently require addressing. Summary: This Review describes the morphological and functional maturation of cells in the mammalian main olfactory bulb, from embryonic development to adult neurogenesis.
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Affiliation(s)
- Candida Tufo
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Subathra Poopalasundaram
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Ana Dorrego-Rivas
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Marc C Ford
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Anthony Graham
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Matthew S Grubb
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
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48
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Abdelfattah AS, Ahuja S, Akkin T, Allu SR, Brake J, Boas DA, Buckley EM, Campbell RE, Chen AI, Cheng X, Čižmár T, Costantini I, De Vittorio M, Devor A, Doran PR, El Khatib M, Emiliani V, Fomin-Thunemann N, Fainman Y, Fernandez-Alfonso T, Ferri CGL, Gilad A, Han X, Harris A, Hillman EMC, Hochgeschwender U, Holt MG, Ji N, Kılıç K, Lake EMR, Li L, Li T, Mächler P, Miller EW, Mesquita RC, Nadella KMNS, Nägerl UV, Nasu Y, Nimmerjahn A, Ondráčková P, Pavone FS, Perez Campos C, Peterka DS, Pisano F, Pisanello F, Puppo F, Sabatini BL, Sadegh S, Sakadzic S, Shoham S, Shroff SN, Silver RA, Sims RR, Smith SL, Srinivasan VJ, Thunemann M, Tian L, Tian L, Troxler T, Valera A, Vaziri A, Vinogradov SA, Vitale F, Wang LV, Uhlířová H, Xu C, Yang C, Yang MH, Yellen G, Yizhar O, Zhao Y. Neurophotonic tools for microscopic measurements and manipulation: status report. NEUROPHOTONICS 2022; 9:013001. [PMID: 35493335 PMCID: PMC9047450 DOI: 10.1117/1.nph.9.s1.013001] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Ahmed S. Abdelfattah
- Brown University, Department of Neuroscience, Providence, Rhode Island, United States
| | - Sapna Ahuja
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Taner Akkin
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Srinivasa Rao Allu
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - David A. Boas
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Erin M. Buckley
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University, Department of Pediatrics, Atlanta, Georgia, United States
| | - Robert E. Campbell
- University of Tokyo, Department of Chemistry, Tokyo, Japan
- University of Alberta, Department of Chemistry, Edmonton, Alberta, Canada
| | - Anderson I. Chen
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Xiaojun Cheng
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Tomáš Čižmár
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Irene Costantini
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Biology, Florence, Italy
- National Institute of Optics, National Research Council, Rome, Italy
| | - Massimo De Vittorio
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Anna Devor
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Patrick R. Doran
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Mirna El Khatib
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | | | - Natalie Fomin-Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Yeshaiahu Fainman
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Tomas Fernandez-Alfonso
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Christopher G. L. Ferri
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Ariel Gilad
- The Hebrew University of Jerusalem, Institute for Medical Research Israel–Canada, Department of Medical Neurobiology, Faculty of Medicine, Jerusalem, Israel
| | - Xue Han
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Andrew Harris
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | | | - Ute Hochgeschwender
- Central Michigan University, Department of Neuroscience, Mount Pleasant, Michigan, United States
| | - Matthew G. Holt
- University of Porto, Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal
| | - Na Ji
- University of California Berkeley, Department of Physics, Berkeley, California, United States
| | - Kıvılcım Kılıç
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evelyn M. R. Lake
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, Connecticut, United States
| | - Lei Li
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Tianqi Li
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Philipp Mächler
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evan W. Miller
- University of California Berkeley, Departments of Chemistry and Molecular & Cell Biology and Helen Wills Neuroscience Institute, Berkeley, California, United States
| | | | | | - U. Valentin Nägerl
- Interdisciplinary Institute for Neuroscience University of Bordeaux & CNRS, Bordeaux, France
| | - Yusuke Nasu
- University of Tokyo, Department of Chemistry, Tokyo, Japan
| | - Axel Nimmerjahn
- Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, California, United States
| | - Petra Ondráčková
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Francesco S. Pavone
- National Institute of Optics, National Research Council, Rome, Italy
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Physics, Florence, Italy
| | - Citlali Perez Campos
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Filippo Pisano
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Ferruccio Pisanello
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Francesca Puppo
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Bernardo L. Sabatini
- Harvard Medical School, Howard Hughes Medical Institute, Department of Neurobiology, Boston, Massachusetts, United States
| | - Sanaz Sadegh
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Sava Sakadzic
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Shy Shoham
- New York University Grossman School of Medicine, Tech4Health and Neuroscience Institutes, New York, New York, United States
| | - Sanaya N. Shroff
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - R. Angus Silver
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Ruth R. Sims
- Sorbonne University, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Spencer L. Smith
- University of California Santa Barbara, Department of Electrical and Computer Engineering, Santa Barbara, California, United States
| | - Vivek J. Srinivasan
- New York University Langone Health, Departments of Ophthalmology and Radiology, New York, New York, United States
| | - Martin Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Lei Tian
- Boston University, Departments of Electrical Engineering and Biomedical Engineering, Boston, Massachusetts, United States
| | - Lin Tian
- University of California Davis, Department of Biochemistry and Molecular Medicine, Davis, California, United States
| | - Thomas Troxler
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Antoine Valera
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Alipasha Vaziri
- Rockefeller University, Laboratory of Neurotechnology and Biophysics, New York, New York, United States
- The Rockefeller University, The Kavli Neural Systems Institute, New York, New York, United States
| | - Sergei A. Vinogradov
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Flavia Vitale
- Center for Neuroengineering and Therapeutics, Departments of Neurology, Bioengineering, Physical Medicine and Rehabilitation, Philadelphia, Pennsylvania, United States
| | - Lihong V. Wang
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Hana Uhlířová
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Chris Xu
- Cornell University, School of Applied and Engineering Physics, Ithaca, New York, United States
| | - Changhuei Yang
- California Institute of Technology, Departments of Electrical Engineering, Bioengineering and Medical Engineering, Pasadena, California, United States
| | - Mu-Han Yang
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Gary Yellen
- Harvard Medical School, Department of Neurobiology, Boston, Massachusetts, United States
| | - Ofer Yizhar
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | - Yongxin Zhao
- Carnegie Mellon University, Department of Biological Sciences, Pittsburgh, Pennsylvania, United States
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Abstract
Measures of behavioral sensitivity provide an important guide for choosing the stimulus concentrations used in functional experiments. This information is particularly valuable in the olfactory system as the neural representation of an odorant changes with concentration. This study focuses on acetate esters because they are commonly used to survey neural activity in a variety of olfactory regions, probe the behavioral limits of odor discrimination, and assess odor structure–activity relationships in mice. Despite their frequent use, the relative sensitivity of these odorants in mice is not available. Thus, we assayed the ability of C57BL/6J mice to detect seven different acetates (propyl acetate, butyl acetate, pentyl acetate, hexyl acetate, octyl acetate, isobutyl acetate, and isoamyl acetate) using a head-fixed Go/No-Go operant conditioning assay combined with highly reproducible stimulus delivery. To aid in the accessibility and applicability of our data, we have estimated the vapor-phase concentrations of these odorants in five different solvents using a photoionization detector-based approach. The resulting liquid-/vapor-phase equilibrium equations successfully corrected for behavioral sensitivity differences observed in animals tested with the same odorant in different solvents. We found that mice are most sensitive to isobutyl acetate and least sensitive to propyl acetate. These updated measures of sensitivity will hopefully guide experimenters in choosing appropriate stimulus concentrations for experiments using these odorants.
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Affiliation(s)
- Liam Jennings
- Department of Psychology, Florida State University, Tallahassee, FL, United States
| | - Ellie Williams
- Department of Psychology, Florida State University, Tallahassee, FL, United States
| | - Marta Avlas
- Department of Psychology, Florida State University, Tallahassee, FL, United States
| | - Adam Dewan
- Department of Psychology, Florida State University, Tallahassee, FL, United States
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50
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Derby CD, McClintock TS, Caprio J. Understanding responses to chemical mixtures: looking forward from the past. Chem Senses 2022; 47:bjac002. [PMID: 35226060 PMCID: PMC8883806 DOI: 10.1093/chemse/bjac002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Our goal in this article is to provide a perspective on how to understand the nature of responses to chemical mixtures. In studying responses to mixtures, researchers often identify "mixture interactions"-responses to mixtures that are not accurately predicted from the responses to the mixture's individual components. Critical in these studies is how to predict responses to mixtures and thus to identify a mixture interaction. We explore this issue with a focus on olfaction and on the first level of neural processing-olfactory sensory neurons-although we use examples from taste systems as well and we consider responses beyond sensory neurons, including behavior and psychophysics. We provide a broadly comparative perspective that includes examples from vertebrates and invertebrates, from genetic and nongenetic animal models, and from literature old and new. In the end, we attempt to recommend how to approach these problems, including possible future research directions.
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Affiliation(s)
- Charles D Derby
- Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | | | - John Caprio
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA
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