1
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Bowen Z, Shilling-Scrivo K, Losert W, Kanold PO. Fractured columnar small-world functional network organization in volumes of L2/3 of mouse auditory cortex. PNAS NEXUS 2024; 3:pgae074. [PMID: 38415223 PMCID: PMC10898513 DOI: 10.1093/pnasnexus/pgae074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 02/06/2024] [Indexed: 02/29/2024]
Abstract
The sensory cortices of the brain exhibit large-scale functional topographic organization, such as the tonotopic organization of the primary auditory cortex (A1) according to sound frequency. However, at the level of individual neurons, layer 2/3 (L2/3) A1 appears functionally heterogeneous. To identify if there exists a higher-order functional organization of meso-scale neuronal networks within L2/3 that bridges order and disorder, we used in vivo two-photon calcium imaging of pyramidal neurons to identify networks in three-dimensional volumes of L2/3 A1 in awake mice. Using tonal stimuli, we found diverse receptive fields with measurable colocalization of similarly tuned neurons across depth but less so across L2/3 sublayers. These results indicate a fractured microcolumnar organization with a column radius of ∼50 µm, with a more random organization of the receptive field over larger radii. We further characterized the functional networks formed within L2/3 by analyzing the spatial distribution of signal correlations (SCs). Networks show evidence of Rentian scaling in physical space, suggesting effective spatial embedding of subnetworks. Indeed, functional networks have characteristics of small-world topology, implying that there are clusters of functionally similar neurons with sparse connections between differently tuned neurons. These results indicate that underlying the regularity of the tonotopic map on large scales in L2/3 is significant tuning diversity arranged in a hybrid organization with microcolumnar structures and efficient network topologies.
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Affiliation(s)
- Zac Bowen
- Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, USA
- Fraunhofer USA Center Mid-Atlantic, Riverdale, MD 20737, USA
| | - Kelson Shilling-Scrivo
- Department of Biology, University of Maryland, College Park, MD 20742, USA
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21230, USA
| | - Wolfgang Losert
- Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, USA
| | - Patrick O Kanold
- Department of Biology, University of Maryland, College Park, MD 20742, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 20215, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 20215, USA
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2
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Weiss O, Bounds HA, Adesnik H, Coen-Cagli R. Modeling the diverse effects of divisive normalization on noise correlations. PLoS Comput Biol 2023; 19:e1011667. [PMID: 38033166 PMCID: PMC10715670 DOI: 10.1371/journal.pcbi.1011667] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 12/12/2023] [Accepted: 11/07/2023] [Indexed: 12/02/2023] Open
Abstract
Divisive normalization, a prominent descriptive model of neural activity, is employed by theories of neural coding across many different brain areas. Yet, the relationship between normalization and the statistics of neural responses beyond single neurons remains largely unexplored. Here we focus on noise correlations, a widely studied pairwise statistic, because its stimulus and state dependence plays a central role in neural coding. Existing models of covariability typically ignore normalization despite empirical evidence suggesting it affects correlation structure in neural populations. We therefore propose a pairwise stochastic divisive normalization model that accounts for the effects of normalization and other factors on covariability. We first show that normalization modulates noise correlations in qualitatively different ways depending on whether normalization is shared between neurons, and we discuss how to infer when normalization signals are shared. We then apply our model to calcium imaging data from mouse primary visual cortex (V1), and find that it accurately fits the data, often outperforming a popular alternative model of correlations. Our analysis indicates that normalization signals are often shared between V1 neurons in this dataset. Our model will enable quantifying the relation between normalization and covariability in a broad range of neural systems, which could provide new constraints on circuit mechanisms of normalization and their role in information transmission and representation.
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Affiliation(s)
- Oren Weiss
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Hayley A. Bounds
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, United States of America
| | - Hillel Adesnik
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, United States of America
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California, United States of America
| | - Ruben Coen-Cagli
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, United States of America
- Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, New York, United States of America
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3
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Calhoun G, Chen CT, Kanold PO. Bilateral widefield calcium imaging reveals circuit asymmetries and lateralized functional activation of the mouse auditory cortex. Proc Natl Acad Sci U S A 2023; 120:e2219340120. [PMID: 37459544 PMCID: PMC10372568 DOI: 10.1073/pnas.2219340120] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 05/29/2023] [Indexed: 07/20/2023] Open
Abstract
Coordinated functioning of the two cortical hemispheres is crucial for perception. The human auditory cortex (ACx) shows functional lateralization with the left hemisphere specialized for processing speech, whereas the right analyzes spectral content. In mice, virgin females demonstrate a left-hemisphere response bias to pup vocalizations that strengthens with motherhood. However, how this lateralized function is established is unclear. We developed a widefield imaging microscope to simultaneously image both hemispheres of mice to bilaterally monitor functional responses. We found that global ACx topography is symmetrical and stereotyped. In both male and virgin female mice, the secondary auditory cortex (A2) in the left hemisphere shows larger responses than right to high-frequency tones and adult vocalizations; however, only virgin female mice show a left-hemisphere bias in A2 in response to adult pain calls. These results indicate hemispheric bias with both sex-independent and -dependent aspects. Analyzing cross-hemispheric functional correlations showed that asymmetries exist in the strength of correlations between DM-AAF and A2-AAF, while other ACx areas showed smaller differences. We found that A2 showed lower cross-hemisphere correlation than other cortical areas, consistent with the lateralized functional activation of A2. Cross-hemispheric activity correlations are lower in deaf, otoferlin knockout (OTOF-/-) mice, indicating that the development of functional cross-hemispheric connections is experience dependent. Together, our results reveal that ACx is topographically symmetric at the macroscopic scale but that higher-order A2 shows sex-dependent and independent lateralized responses due to asymmetric intercortical functional connections. Moreover, our results suggest that sensory experience is required to establish functional cross-hemispheric connectivity.
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Affiliation(s)
- Georgia Calhoun
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD21205
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD21205
| | - Chih-Ting Chen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD21205
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD21205
| | - Patrick O. Kanold
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD21205
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD21205
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4
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Shilling-Scrivo K, Mittelstadt J, Kanold PO. Decreased Modulation of Population Correlations in Auditory Cortex Is Associated with Decreased Auditory Detection Performance in Old Mice. J Neurosci 2022; 42:9278-9292. [PMID: 36302637 PMCID: PMC9761686 DOI: 10.1523/jneurosci.0955-22.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 09/17/2022] [Accepted: 10/24/2022] [Indexed: 02/02/2023] Open
Abstract
Age-related hearing loss (presbycusis) affects one-third of the world's population. One hallmark of presbycusis is difficulty hearing in noisy environments. Presbycusis can be separated into two components: the aging ear and the aging brain. To date, the role of the aging brain in presbycusis is not well understood. Activity in the primary auditory cortex (A1) during a behavioral task is because of a combination of responses representing the acoustic stimuli, attentional gain, and behavioral choice. Disruptions in any of these aspects can lead to decreased auditory processing. To investigate how these distinct components are disrupted in aging, we performed in vivo 2-photon Ca2+ imaging in both male and female mice (Thy1-GCaMP6s × CBA/CaJ mice) that retain peripheral hearing into old age. We imaged A1 neurons of young adult (2-6 months) and old mice (16-24 months) during a tone detection task in broadband noise. While young mice performed well, old mice performed worse at low signal-to-noise ratios. Calcium imaging showed that old animals have increased prestimulus activity, reduced attentional gain, and increased noise correlations. Increased correlations in old animals exist regardless of cell tuning and behavioral outcome, and these correlated networks exist over a much larger portion of cortical space. Neural decoding techniques suggest that this prestimulus activity is predictive of old animals making early responses. Together, our results suggest a model in which old animals have higher and more correlated prestimulus activity and cannot fully suppress this activity, leading to the decreased representation of targets among distracting stimuli.SIGNIFICANCE STATEMENT Aging inhibits the ability to hear clearly in noisy environments. We show that the aging auditory cortex is unable to fully suppress its responses to background noise. During an auditory behavior, fewer neurons were suppressed in the old relative to young animals, which leads to higher prestimulus activity and more false alarms. We show that this excess activity additionally leads to increased correlations between neurons, reducing the amount of relevant stimulus information in the auditory cortex. Future work identifying the lost circuits that are responsible for proper background suppression could provide new targets for therapeutic strategies to preserve auditory processing ability into old age.
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Affiliation(s)
- Kelson Shilling-Scrivo
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, Maryland 21230
| | - Jonah Mittelstadt
- Department of Biology, University of Maryland, College Park, Maryland 20742
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
| | - Patrick O Kanold
- Department of Biology, University of Maryland, College Park, Maryland 20742
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
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5
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Jeon BB, Fuchs T, Chase SM, Kuhlman SJ. Visual experience has opposing influences on the quality of stimulus representation in adult primary visual cortex. eLife 2022; 11:80361. [PMID: 36321876 PMCID: PMC9629826 DOI: 10.7554/elife.80361] [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: 05/18/2022] [Accepted: 10/21/2022] [Indexed: 11/07/2022] Open
Abstract
Transient dark exposure, typically 7–10 days in duration, followed by light reintroduction is an emerging treatment for improving the restoration of vision in amblyopic subjects whose occlusion is removed in adulthood. Dark exposure initiates homeostatic mechanisms that together with light-induced changes in cellular signaling pathways result in the re-engagement of juvenile-like plasticity in the adult such that previously deprived inputs can gain cortical territory. It is possible that dark exposure itself degrades visual responses, and this could place constraints on the optimal duration of dark exposure treatment. To determine whether eight days of dark exposure has a lasting negative impact on responses to classic grating stimuli, neural activity was recorded before and after dark exposure in awake head-fixed mice using two-photon calcium imaging. Neural discriminability, assessed using classifiers, was transiently reduced following dark exposure; a decrease in response reliability across a broad range of spatial frequencies likely contributed to the disruption. Both discriminability and reliability recovered. Fixed classifiers were used to demonstrate that stimulus representation rebounded to the original, pre-deprivation state, thus dark exposure did not appear to have a lasting negative impact on visual processing. Unexpectedly, we found that dark exposure significantly stabilized orientation preference and signal correlation. Our results reveal that natural vision exerts a disrupting influence on the stability of stimulus preference for classic grating stimuli and, at the same time, improves neural discriminability for both low and high-spatial frequency stimuli.
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Affiliation(s)
- Brian B Jeon
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States
| | - Thomas Fuchs
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States.,Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, United States
| | - Steven M Chase
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States
| | - Sandra J Kuhlman
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States.,Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, United States
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6
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Trejo EJA, Martin DA, De Zoysa D, Bowen Z, Grigera TS, Cannas SA, Losert W, Chialvo DR. Finite-size correlation behavior near a critical point: A simple metric for monitoring the state of a neural network. Phys Rev E 2022; 106:054313. [PMID: 36559402 DOI: 10.1103/physreve.106.054313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 10/28/2022] [Indexed: 12/03/2022]
Abstract
In this article, a correlation metric κ_{c} is proposed for the inference of the dynamical state of neuronal networks. κ_{C} is computed from the scaling of the correlation length with the size of the observation region, which shows qualitatively different behavior near and away from the critical point of a continuous phase transition. The implementation is first studied on a neuronal network model, where the results of this new metric coincide with those obtained from neuronal avalanche analysis, thus well characterizing the critical state of the network. The approach is further tested with brain optogenetic recordings in behaving mice from a publicly available database. Potential applications and limitations for its use with currently available optical imaging techniques are discussed.
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Affiliation(s)
- Eyisto J Aguilar Trejo
- Instituto de Ciencias Físicas (ICIFI-CONICET), Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de Gral. San Martín, Campus Miguelete, 25 de Mayo y Francia, 1650, San Martín, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, 1425, Buenos Aires, Argentina
| | - Daniel A Martin
- Instituto de Ciencias Físicas (ICIFI-CONICET), Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de Gral. San Martín, Campus Miguelete, 25 de Mayo y Francia, 1650, San Martín, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, 1425, Buenos Aires, Argentina
| | - Dulara De Zoysa
- Department of Physics & Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742, USA
| | - Zac Bowen
- Fraunhofer USA Center Mid-Atlantic, Riverdale, Maryland 20737, USA
| | - Tomas S Grigera
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, 1425, Buenos Aires, Argentina.,Departamento de Física, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 1900, La Plata, Buenos Aires, Argentina.,Instituto de Física de Líquidos y Sistemas Biológicos (IFLySiB-CONICET) Universidad Nacional de La Plata, 1900, La Plata, Buenos Aires, Argentina.,Istituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, via dei Taurini 19, 00185 Rome, Italy
| | - Sergio A Cannas
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, 1425, Buenos Aires, Argentina.,Instituto de Física Enrique Gaviola (IFEG-CONICET), Facultad de Matemática Astronomía Física y Computación, Universidad Nacional de Córdoba, 5000, Córdoba, Argentina
| | - Wolfgang Losert
- Department of Physics & Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742, USA
| | - Dante R Chialvo
- Instituto de Ciencias Físicas (ICIFI-CONICET), Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de Gral. San Martín, Campus Miguelete, 25 de Mayo y Francia, 1650, San Martín, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, 1425, Buenos Aires, Argentina
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7
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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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8
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Xue B, Alipio JB, Kao JPY, Kanold PO. Perinatal Opioid Exposure Results in Persistent Hypoconnectivity of Excitatory Circuits and Reduced Activity Correlations in Mouse Primary Auditory Cortex. J Neurosci 2022; 42:3676-3687. [PMID: 35332087 PMCID: PMC9053845 DOI: 10.1523/jneurosci.2542-21.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/21/2022] [Accepted: 03/14/2022] [Indexed: 11/21/2022] Open
Abstract
Opioid use by pregnant women results in neonatal opioid withdrawal syndrome (NOWS) and lifelong neurobehavioral deficits including language impairments. Animal models of NOWS show impaired performance in a two-tone auditory discrimination task, suggesting abnormalities in sensory processing in the auditory cortex. To investigate the consequences of perinatal opioid exposure on auditory cortex circuits, we administered fentanyl to mouse dams in their drinking water throughout gestation and until litters were weaned at postnatal day (P)21. We then used in vivo two-photon Ca2+ imaging in adult animals of both sexes to investigate how primary auditory cortex (A1) function was altered. Perinatally exposed animals showed fewer sound-responsive neurons in A1, and the remaining sound-responsive cells exhibited lower response amplitudes but normal frequency selectivity and stimulus-specific adaptation (SSA). Populations of nearby layer 2/3 (L2/3) cells in exposed animals showed reduced correlated activity, suggesting a reduction of shared inputs. We then investigated A1 microcircuits to L2/3 cells by performing laser-scanning photostimulation (LSPS) combined with whole-cell patch-clamp recordings from A1 L2/3 cells. L2/3 cells in exposed animals showed functional hypoconnectivity of excitatory circuits of ascending inputs from L4 and L5/6 to L2/3, while inhibitory connections were unchanged, leading to an altered excitatory/inhibitory balance. These results suggest a specific reduction in excitatory ascending interlaminar cortical circuits resulting in decreased activity correlations after fentanyl exposure. We speculate that these changes in cortical circuits contribute to the impaired auditory discrimination ability after perinatal opioid exposure.SIGNIFICANCE STATEMENT This is the first study to investigate the functional effects of perinatal fentanyl exposure on the auditory cortex. Experiments show that perinatal fentanyl exposure results in decreased excitatory functional circuits and altered population activity in primary sensory areas in adult mice. These circuit changes might underlie the observed language and cognitive deficits in infants exposed to opioids.
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Affiliation(s)
- Binghan Xue
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
- Department of Biology, University of Maryland, College Park, Maryland 20742
| | - Jason B Alipio
- Department of Anatomy and Neurobiology, Program in Neuroscience, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Joseph P Y Kao
- Center for Biomedical Engineering and Technology, and Department of Physiology, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Patrick O Kanold
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
- Department of Biology, University of Maryland, College Park, Maryland 20742
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9
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Shilling-Scrivo K, Mittelstadt J, Kanold PO. Altered Response Dynamics and Increased Population Correlation to Tonal Stimuli Embedded in Noise in Aging Auditory Cortex. J Neurosci 2021; 41:9650-9668. [PMID: 34611028 PMCID: PMC8612470 DOI: 10.1523/jneurosci.0839-21.2021] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 09/25/2021] [Accepted: 09/29/2021] [Indexed: 11/21/2022] Open
Abstract
Age-related hearing loss (presbycusis) is a chronic health condition that affects one-third of the world population. One hallmark of presbycusis is a difficulty hearing in noisy environments. Presbycusis can be separated into two components: alterations of peripheral mechanotransduction of sound in the cochlea and central alterations of auditory processing areas of the brain. Although the effects of the aging cochlea in hearing loss have been well studied, the role of the aging brain in hearing loss is less well understood. Therefore, to examine how age-related central processing changes affect hearing in noisy environments, we used a mouse model (Thy1-GCaMP6s X CBA) that has excellent peripheral hearing in old age. We used in vivo two-photon Ca2+ imaging to measure the responses of neuronal populations in auditory cortex (ACtx) of adult (2-6 months, nine male, six female, 4180 neurons) and aging mice (15-17 months, six male, three female, 1055 neurons) while listening to tones in noisy backgrounds. We found that ACtx neurons in aging mice showed larger responses to tones and have less suppressed responses consistent with reduced inhibition. Aging neurons also showed less sensitivity to temporal changes. Population analysis showed that neurons in aging mice showed higher pairwise activity correlations and showed a reduced diversity in responses to sound stimuli. Using neural decoding techniques, we show a loss of information in neuronal populations in the aging brain. Thus, aging not only affects the responses of single neurons but also affects how these neurons jointly represent stimuli.SIGNIFICANCE STATEMENT Aging results in hearing deficits particularly under challenging listening conditions. We show that auditory cortex contains distinct subpopulations of excitatory neurons that preferentially encode different stimulus features and that aging selectively reduces certain subpopulations. We also show that aging increases correlated activity between neurons and thereby reduces the response diversity in auditory cortex. The loss of population response diversity leads to a decrease of stimulus information and deficits in sound encoding, especially in noisy backgrounds. Future work determining the identities of circuits affected by aging could provide new targets for therapeutic strategies.
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Affiliation(s)
- Kelson Shilling-Scrivo
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, Maryland 21230
| | - Jonah Mittelstadt
- Department of Biology, University of Maryland, College Park, Maryland 20742
| | - Patrick O Kanold
- Department of Biology, University of Maryland, College Park, Maryland 20742
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21205
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10
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Rupasinghe A, Francis N, Liu J, Bowen Z, Kanold PO, Babadi B. Direct extraction of signal and noise correlations from two-photon calcium imaging of ensemble neuronal activity. eLife 2021; 10:68046. [PMID: 34180397 PMCID: PMC8354639 DOI: 10.7554/elife.68046] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 06/27/2021] [Indexed: 12/21/2022] Open
Abstract
Neuronal activity correlations are key to understanding how populations of neurons collectively encode information. While two-photon calcium imaging has created a unique opportunity to record the activity of large populations of neurons, existing methods for inferring correlations from these data face several challenges. First, the observations of spiking activity produced by two-photon imaging are temporally blurred and noisy. Secondly, even if the spiking data were perfectly recovered via deconvolution, inferring network-level features from binary spiking data is a challenging task due to the non-linear relation of neuronal spiking to endogenous and exogenous inputs. In this work, we propose a methodology to explicitly model and directly estimate signal and noise correlations from two-photon fluorescence observations, without requiring intermediate spike deconvolution. We provide theoretical guarantees on the performance of the proposed estimator and demonstrate its utility through applications to simulated and experimentally recorded data from the mouse auditory cortex.
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Affiliation(s)
- Anuththara Rupasinghe
- Department of Electrical and Computer Engineering, University of Maryland, College Park, United States
| | - Nikolas Francis
- The Institute for Systems Research, University of Maryland, College Park, United States.,Department of Biology, University of Maryland, College Park, United States
| | - Ji Liu
- The Institute for Systems Research, University of Maryland, College Park, United States.,Department of Biology, University of Maryland, College Park, United States
| | - Zac Bowen
- The Institute for Systems Research, University of Maryland, College Park, United States.,Department of Biology, University of Maryland, College Park, United States
| | - Patrick O Kanold
- The Institute for Systems Research, University of Maryland, College Park, United States.,Department of Biology, University of Maryland, College Park, United States.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, United States
| | - Behtash Babadi
- Department of Electrical and Computer Engineering, University of Maryland, College Park, United States
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