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Larsen B, Sydnor VJ, Keller AS, Yeo BTT, Satterthwaite TD. A critical period plasticity framework for the sensorimotor-association axis of cortical neurodevelopment. Trends Neurosci 2023; 46:847-862. [PMID: 37643932 PMCID: PMC10530452 DOI: 10.1016/j.tins.2023.07.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/23/2023] [Accepted: 07/25/2023] [Indexed: 08/31/2023]
Abstract
To understand human brain development it is necessary to describe not only the spatiotemporal patterns of neurodevelopment but also the neurobiological mechanisms that underlie them. Human neuroimaging studies have provided evidence for a hierarchical sensorimotor-to-association (S-A) axis of cortical neurodevelopment. Understanding the biological mechanisms that underlie this program of development using traditional neuroimaging approaches has been challenging. Animal models have been used to identify periods of enhanced experience-dependent plasticity - 'critical periods' - that progress along cortical hierarchies and are governed by a conserved set of neurobiological mechanisms that promote and then restrict plasticity. In this review we hypothesize that the S-A axis of cortical development in humans is partly driven by the cascading maturation of critical period plasticity mechanisms. We then describe how recent advances in in vivo neuroimaging approaches provide a promising path toward testing this hypothesis by linking signals derived from non-invasive imaging to critical period mechanisms.
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Affiliation(s)
- Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - B T Thomas Yeo
- Centre for Sleep and Cognition (CSC), and Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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2
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Sydnor VJ, Larsen B, Seidlitz J, Adebimpe A, Alexander-Bloch AF, Bassett DS, Bertolero MA, Cieslak M, Covitz S, Fan Y, Gur RE, Gur RC, Mackey AP, Moore TM, Roalf DR, Shinohara RT, Satterthwaite TD. Intrinsic activity development unfolds along a sensorimotor-association cortical axis in youth. Nat Neurosci 2023; 26:638-649. [PMID: 36973514 PMCID: PMC10406167 DOI: 10.1038/s41593-023-01282-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 02/15/2023] [Indexed: 03/29/2023]
Abstract
Animal studies of neurodevelopment have shown that recordings of intrinsic cortical activity evolve from synchronized and high amplitude to sparse and low amplitude as plasticity declines and the cortex matures. Leveraging resting-state functional MRI (fMRI) data from 1,033 youths (ages 8-23 years), we find that this stereotyped refinement of intrinsic activity occurs during human development and provides evidence for a cortical gradient of neurodevelopmental change. Declines in the amplitude of intrinsic fMRI activity were initiated heterochronously across regions and were coupled to the maturation of intracortical myelin, a developmental plasticity regulator. Spatiotemporal variability in regional developmental trajectories was organized along a hierarchical, sensorimotor-association cortical axis from ages 8 to 18. The sensorimotor-association axis furthermore captured variation in associations between youths' neighborhood environments and intrinsic fMRI activity; associations suggest that the effects of environmental disadvantage on the maturing brain diverge most across this axis during midadolescence. These results uncover a hierarchical neurodevelopmental axis and offer insight into the progression of cortical plasticity in humans.
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Affiliation(s)
- Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jakob Seidlitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Azeez Adebimpe
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Covitz
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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3
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Kalemaki K, Velli A, Christodoulou O, Denaxa M, Karagogeos D, Sidiropoulou K. The Developmental Changes in Intrinsic and Synaptic Properties of Prefrontal Neurons Enhance Local Network Activity from the Second to the Third Postnatal Weeks in Mice. Cereb Cortex 2021; 32:3633-3650. [PMID: 34905772 DOI: 10.1093/cercor/bhab438] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 11/04/2021] [Accepted: 11/05/2021] [Indexed: 11/13/2022] Open
Abstract
The prefrontal cortex (PFC) is characterized by protracted maturation. The cellular mechanisms controlling the early development of prefrontal circuits are still largely unknown. Our study delineates the developmental cellular processes in the mouse medial PFC (mPFC) during the second and the third postnatal weeks and characterizes their contribution to the changes in network activity. We show that spontaneous inhibitory postsynaptic currents (sIPSC) are increased, whereas spontaneous excitatory postsynaptic currents (sEPSC) are reduced from the second to the third postnatal week. Drug application suggested that the increased sEPSC frequency in mPFC at postnatal day 10 (P10) is due to depolarizing γ-aminobutyric acid (GABA) type A receptor function. To further validate this, perforated patch-clamp recordings were obtained and the expression levels of K-Cl cotransporter 2 (KCC2) protein were examined. The reversal potential of IPSCs in response to current stimulation was significantly more depolarized at P10 than P20 while KCC2 expression is decreased. Moreover, the number of parvalbumin-expressing GABAergic interneurons increases and their intrinsic electrophysiological properties significantly mature in the mPFC from P10 to P20. Using computational modeling, we show that the developmental changes in synaptic and intrinsic properties of mPFC neurons contribute to the enhanced network activity in the juvenile compared with neonatal mPFC.
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Affiliation(s)
- Katerina Kalemaki
- Department of Basic Science, Faculty of Medicine, University of Crete, Heraklion GR70013, Greece.,Institute of Molecular Biology and Biotechnology (IMBB), FORTH, Heraklion GR70013, Greece
| | - Angeliki Velli
- Institute of Molecular Biology and Biotechnology (IMBB), FORTH, Heraklion GR70013, Greece.,Department of Biology, University of Crete, Heraklion GR70013, Greece
| | - Ourania Christodoulou
- Department of Biology, University of Crete, Heraklion GR70013, Greece.,Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center 'Alexander Fleming', Heraklion GR70013, Greece
| | - Myrto Denaxa
- Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center 'Alexander Fleming', Heraklion GR70013, Greece
| | - Domna Karagogeos
- Department of Basic Science, Faculty of Medicine, University of Crete, Heraklion GR70013, Greece.,Institute of Molecular Biology and Biotechnology (IMBB), FORTH, Heraklion GR70013, Greece
| | - Kyriaki Sidiropoulou
- Institute of Molecular Biology and Biotechnology (IMBB), FORTH, Heraklion GR70013, Greece.,Department of Biology, University of Crete, Heraklion GR70013, Greece
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4
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Nakazawa S, Iwasato T. Spatial organization and transitions of spontaneous neuronal activities in the developing sensory cortex. Dev Growth Differ 2021; 63:323-339. [PMID: 34166527 DOI: 10.1111/dgd.12739] [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: 04/06/2021] [Revised: 06/21/2021] [Accepted: 06/22/2021] [Indexed: 12/30/2022]
Abstract
The sensory cortex underlies our ability to perceive and interact with the external world. Sensory perceptions are controlled by specialized neuronal circuits established through fine-tuning, which relies largely on neuronal activity during the development. Spontaneous neuronal activity is an essential driving force of neuronal circuit refinement. At early developmental stages, sensory cortices display spontaneous activities originating from the periphery and characterized by correlated firing arranged spatially according to the modality. The firing patterns are reorganized over time and become sparse, which is typical for the mature brain. This review focuses mainly on rodent sensory cortices. First, the features of the spontaneous activities during early postnatal stages are described. Then, the developmental changes in the spatial organization of the spontaneous activities and the transition mechanisms involved are discussed. The identification of the principles controlling the spatial organization of spontaneous activities in the developing sensory cortex is essential to understand the self-organization process of neuronal circuits.
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Affiliation(s)
- Shingo Nakazawa
- Laboratory of Mammalian Neural Circuits, National Institute of Genetics, Mishima, Japan.,Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
| | - Takuji Iwasato
- Laboratory of Mammalian Neural Circuits, National Institute of Genetics, Mishima, Japan.,Department of Genetics, SOKENDAI (The Graduate University for Advanced Studies), Mishima, Japan
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Wosniack ME, Kirchner JH, Chao LY, Zabouri N, Lohmann C, Gjorgjieva J. Adaptation of spontaneous activity in the developing visual cortex. eLife 2021; 10:61619. [PMID: 33722342 PMCID: PMC7963484 DOI: 10.7554/elife.61619] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 02/03/2021] [Indexed: 12/11/2022] Open
Abstract
Spontaneous activity drives the establishment of appropriate connectivity in different circuits during brain development. In the mouse primary visual cortex, two distinct patterns of spontaneous activity occur before vision onset: local low-synchronicity events originating in the retina and global high-synchronicity events originating in the cortex. We sought to determine the contribution of these activity patterns to jointly organize network connectivity through different activity-dependent plasticity rules. We postulated that local events shape cortical input selectivity and topography, while global events homeostatically regulate connection strength. However, to generate robust selectivity, we found that global events should adapt their amplitude to the history of preceding cortical activation. We confirmed this prediction by analyzing in vivo spontaneous cortical activity. The predicted adaptation leads to the sparsification of spontaneous activity on a slower timescale during development, demonstrating the remarkable capacity of the developing sensory cortex to acquire sensitivity to visual inputs after eye-opening.
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Affiliation(s)
- Marina E Wosniack
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Frankfurt, Germany.,School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | - Jan H Kirchner
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Frankfurt, Germany.,School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | - Ling-Ya Chao
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Nawal Zabouri
- Netherlands Institute for Neuroscience, Amsterdam, Netherlands
| | - Christian Lohmann
- Netherlands Institute for Neuroscience, Amsterdam, Netherlands.,Center for Neurogenomics and Cognitive Research, Vrije Universiteit, Amsterdam, Netherlands
| | - Julijana Gjorgjieva
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Frankfurt, Germany.,School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
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6
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Gutnisky DA, Beaman C, Lew SE, Dragoi V. Cortical response states for enhanced sensory discrimination. eLife 2017; 6:29226. [PMID: 29274146 PMCID: PMC5760207 DOI: 10.7554/elife.29226] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2017] [Accepted: 12/21/2017] [Indexed: 11/20/2022] Open
Abstract
Brain activity during wakefulness is characterized by rapid fluctuations in neuronal responses. Whether these fluctuations play any role in modulating the accuracy of behavioral responses is poorly understood. Here, we investigated whether and how trial changes in the population response impact sensory coding in monkey V1 and perceptual performance. Although the responses of individual neurons varied widely across trials, many cells tended to covary with the local population. When population activity was in a ‘low’ state, neurons had lower evoked responses and correlated variability, yet higher probability to predict perceptual accuracy. The impact of firing rate fluctuations on network and perceptual accuracy was strongest 200 ms before stimulus presentation, and it greatly diminished when the number of cells used to measure the state of the population was decreased. These findings indicate that enhanced perceptual discrimination occurs when population activity is in a ‘silent’ response mode in which neurons increase information extraction.
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Affiliation(s)
- Diego A Gutnisky
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, United States.,Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Charles Beaman
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, United States
| | - Sergio E Lew
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, United States.,Instituto de Ingeniería Biomédica, Universidad de Buenos Aires, Argentina, South America
| | - Valentin Dragoi
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, United States
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O'Donnell C, Gonçalves JT, Portera-Cailliau C, Sejnowski TJ. Beyond excitation/inhibition imbalance in multidimensional models of neural circuit changes in brain disorders. eLife 2017; 6:26724. [PMID: 29019321 PMCID: PMC5663477 DOI: 10.7554/elife.26724] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2017] [Accepted: 10/04/2017] [Indexed: 11/28/2022] Open
Abstract
A leading theory holds that neurodevelopmental brain disorders arise from imbalances in excitatory and inhibitory (E/I) brain circuitry. However, it is unclear whether this one-dimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. Here, we combined computational simulations with analysis of in vivo two-photon Ca2+ imaging data from somatosensory cortex of Fmr1 knock-out (KO) mice, a model of Fragile-X Syndrome, to test the E/I imbalance theory. We found that: (1) The E/I imbalance model cannot account for joint alterations in the observed neural firing rates and correlations; (2) Neural circuit function is vastly more sensitive to changes in some cellular components over others; (3) The direction of circuit alterations in Fmr1 KO mice changes across development. These findings suggest that the basic E/I imbalance model should be updated to higher dimensional models that can better capture the multidimensional computational functions of neural circuits. In many brain disorders, from autism to schizophrenia, the anatomy of the brain appears remarkably unchanged. This implies that the problem may reside in how neurons communicate with one another. Unfortunately, neuroscientists know little about how brain activity might differ from normal in these disorders, or how specific changes in activity give rise to symptoms. One leading theory, first proposed over a decade ago, is that these disorders reflect an imbalance in the activity of excitatory and inhibitory neurons. Excitatory neurons activate their targets, whereas inhibitory neurons suppress or silence them. While studies in mice have lent support to this theory, they have not yet culminated in new treatments for brain disorders. One limitation of the excitation-inhibition imbalance theory is that it is one-dimensional. It assumes that there is an optimal balance of excitation and inhibition, and that brain disorders can be arranged in an imaginary line on either side of this optimum. Disorders to the right of the optimum, such as epilepsy and some forms of autism, feature too much excitation. Disorders to the left, such as the developmental disorder Rett syndrome, feature too much inhibition. But can diverse brain disorders really be classified on the basis of a single property, or do scientists need to consider other factors? To find out, O’Donnell et al. analyzed recordings of brain activity from genetically modified mice with the mutation that causes fragile X syndrome, the most common form of inherited learning disability and autism. The mice showed changes in their overall brain activity compared to control animals. Their neurons also tended to fire in a more synchronized manner. A computer simulation revealed that an imbalance in excitation and inhibition alone could not explain these changes. Yet, a more complex simulation incorporating extra properties of neural circuits did a better job of explaining the altered neural activity seen in the mice. O’Donnell et al. propose that this more advanced multi-dimensional model of changes in neural circuits could be used to screen candidate drugs before testing them in patients. In principle, the model could even help with designing drugs or other interventions by making it easier for researchers to target more precisely the changes in neural circuits that occur in brain disorders.
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Affiliation(s)
- Cian O'Donnell
- Department of Computer Science, University of Bristol, Bristol, United Kingdom.,Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, United States
| | - J Tiago Gonçalves
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, United States.,Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, United States
| | - Carlos Portera-Cailliau
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, United States.,Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, United States
| | - Terrence J Sejnowski
- Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, United States.,Division of Biological Sciences, University of California at San Diego, La Jolla, United States
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Tactile Defensiveness and Impaired Adaptation of Neuronal Activity in the Fmr1 Knock-Out Mouse Model of Autism. J Neurosci 2017; 37:6475-6487. [PMID: 28607173 DOI: 10.1523/jneurosci.0651-17.2017] [Citation(s) in RCA: 80] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 05/17/2017] [Accepted: 05/24/2017] [Indexed: 11/21/2022] Open
Abstract
Sensory hypersensitivity is a common symptom in autism spectrum disorders (ASDs), including fragile X syndrome (FXS), and frequently leads to tactile defensiveness. In mouse models of ASDs, there is mounting evidence of neuronal and circuit hyperexcitability in several brain regions, which could contribute to sensory hypersensitivity. However, it is not yet known whether or how sensory stimulation might trigger abnormal sensory processing at the circuit level or abnormal behavioral responses in ASD mouse models, especially during an early developmental time when experience-dependent plasticity shapes such circuits. Using a novel assay, we discovered exaggerated motor responses to whisker stimulation in young Fmr1 knock-out (KO) mice (postnatal days 14-16), a model of FXS. Adult Fmr1 KO mice actively avoided a stimulus that was innocuous to wild-type controls, a sign of tactile defensiveness. Using in vivo two-photon calcium imaging of layer 2/3 barrel cortex neurons expressing GCaMP6s, we found no differences between wild-type and Fmr1 KO mice in overall whisker-evoked activity, though 45% fewer neurons in young Fmr1 KO mice responded in a time-locked manner. Notably, we identified a pronounced deficit in neuronal adaptation to repetitive whisker stimulation in both young and adult Fmr1 KO mice. Thus, impaired adaptation in cortical sensory circuits is a potential cause of tactile defensiveness in autism.SIGNIFICANCE STATEMENT We use a novel paradigm of repetitive whisker stimulation and in vivo calcium imaging to assess tactile defensiveness and barrel cortex activity in young and adult Fmr1 knock-out mice, the mouse model of fragile X syndrome (FXS). We describe evidence of tactile defensiveness, as well as a lack of L2/3 neuronal adaptation in barrel cortex, during whisker stimulation. We propose that a defect in sensory adaptation within local neuronal networks, beginning at a young age and continuing into adulthood, likely contributes to sensory overreactivity in FXS and perhaps other ASDs.
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