Critical period regulation across multiple timescales

Brain plasticity is dynamically regulated across the life span, peaking during windows of early life. Typically assessed in the physiological range of milliseconds (real time), these trajectories are also influenced on the longer timescales of developmental time (nurture) and evolutionary time (nature), which shape neural architectures that support plasticity. Properly sequenced critical periods of circuit refinement build up complex cognitive functions, such as language, from more primary modalities. Here, we consider recent progress in the biological basis of critical periods as a unifying rubric for understanding plasticity across multiple timescales. Notably, the maturation of parvalbumin-positive (PV) inhibitory neurons is pivotal. These fast-spiking cells generate gamma oscillations associated with critical period plasticity, are sensitive to circadian gene manipulation, emerge at different rates across brain regions, acquire perineuronal nets with age, and may be influenced by epigenetic factors over generations. These features provide further novel insight into the impact of early adversity and neurodevelopmental risk factors for mental disorders.

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The Concept and Application of Early Economic Period Threshold: The Case of DCPA in Onions (Allium Cepa)

Weed Science ◽

10.1017/s0043174500081753 ◽

1995 ◽

Vol 43 (4) ◽

pp. 634-639 ◽

Cited By ~ 17

Author(s):

Claudio M. Dunan ◽

Philip Westra ◽

Edward E. Schweizer ◽

Donald W. Lybecker ◽

Frank D. Moore

Keyword(s):

Weed Control ◽

Critical Period ◽

Crop Yields ◽

Economic Feasibility ◽

Control Measures ◽

Economic Losses ◽

Weed Competition ◽

Critical Periods ◽

Control Efficacy ◽

The Impact

The question of when to control weeds traditionally has been approached with the calculation of critical periods (CP) based on crop yields. The concept of economic critical period (ECP) and early (EEPT) and late (LEFT) economic period thresholds are presented as a comprehensive approach to answer the same question based on economic losses and costs of control. ECP is defined as the period when the benefit of controlling weeds is greater than its cost. EEPT and LEFT are the limits of the ECP and can be used to determine when first and last weed control measures should be performed. Calculation of EEPT accounts for the economic losses due to weed competition that occur between planting and postemergence weed control. In this way it is possible to better evaluate the economic feasibility of using preplant or preemergence control tactics. The EEPT for DCPA application is analyzed in the context of onion production in Colorado. The EEPT for DCPA application was calculated from an empirical regression model that assessed the impact of weed load and time of weed removal on onion yields. The EEPT was affected by control efficacy, weed-free yield, DCPA cost, and onion price. DCPA application was economically advisable in only one of 20 fields analyzed because of the tow DCPA efficacy (60%).

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Drp1 widely, yet heterogeneously distributes in mice central nervous system

10.21203/rs.3.rs-18926/v1 ◽

2020 ◽

Author(s):

Ting-Ting Luo ◽

Chun-Qiu Dai ◽

Jia-Qi Wang ◽

Zheng-Mei Wang ◽

Yi Yang ◽

...

Keyword(s):

Central Nervous System ◽

Nervous System ◽

Malignant Glioma ◽

Expression Patterns ◽

Brain Regions ◽

Inhibitory Neurons ◽

Heterogeneous Distribution ◽

Human Malignant Glioma ◽

The Impact ◽

The Relationship

Abstract Objectives: Drp1 is wildly expressed and plays a role in inducing mitochondrial fission process. It is confirmed that many diseases are associated with Drp1 and mitochondria. However, since the exact Drp1 is not specifically distributed, it is hard to determine the impact of anti-Drp1 molecules on human body and where the Drp1 inhibitor functions. Methods: We visualized distribution of Drp1 in different brain regions, and explicated the relationship between Drp1 and mitochondria. GAD67-GFP knock-in mice were utilized to detect the expression patterns of Drp1 on the GABAergic neurons. And we further analyzed Drp1 expression in human malignant glioma tissue. Results: Drp1 widely but heterogeneously distributed in central nervous system. Further observation indicated that Drp1 was highly and heterogeneously expressed in inhibitory neurons. Under transmission electron microscope, Drp1 distribution in dendrites was higher than other areas in neurons and only a small amount of Drp1 was located on mitochondria. In human malignant glioma, Drp1 fluorescence intensity increased from grade I-III, while grade IV showed the descending trend. Conclusion: In this study, we observed Drp1 widely yet heterogeneously distributed in central nervous system. Drp1 heterogeneous distribution may be related with the occurrence and development of neurologic disease. We hope that the relationship between Drp1 and mitochondria may give the therapeutic guidance.

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Integration of Broadband Conductance Input in Rat Somatosensory Cortical Inhibitory Interneurons: An Inhibition-Controlled Switch Between Intrinsic and Input-Driven Spiking in Fast-Spiking Cells

Journal of Neurophysiology ◽

10.1152/jn.91057.2008 ◽

2009 ◽

Vol 101 (2) ◽

pp. 1056-1072 ◽

Cited By ~ 9

Author(s):

T. Tateno ◽

H.P.C. Robinson

Keyword(s):

Cell Types ◽

Gamma Oscillations ◽

External Input ◽

Spike Timing ◽

Cortical Network ◽

Inhibitory Neurons ◽

Dependent Manner ◽

Input Output ◽

Complex Activity ◽

Fast Spiking

Quantitative understanding of the dynamics of particular cell types when responding to complex, natural inputs is an important prerequisite for understanding the operation of the cortical network. Different types of inhibitory neurons are connected by electrical synapses to nearby neurons of the same type, enabling the formation of synchronized assemblies of neurons with distinct dynamical behaviors. Under what conditions is spike timing in such cells determined by their intrinsic dynamics and when is it driven by the timing of external input? In this study, we have addressed this question using a systematic approach to characterizing the input–output relationships of three types of cortical interneurons (fast spiking [FS], low-threshold spiking [LTS], and nonpyramidal regular-spiking [NPRS] cells) in the rat somatosensory cortex, during fluctuating conductance input designed to mimic natural complex activity. We measured the shape of average conductance input trajectories preceding spikes and fitted a two-component linear model of neuronal responses, which included an autoregressive term from its own output, to gain insight into the input–output relationships of neurons. This clearly separated the contributions of stimulus and discharge history, in a cell-type dependent manner. Unlike LTS and NPRS cells, FS cells showed a remarkable switch in dynamics, from intrinsically driven spike timing to input-fluctuation–controlled spike timing, with the addition of even a small amount of inhibitory conductance. Such a switch could play a pivotal role in the function of FS cells in organizing coherent gamma oscillations in the local cortical network. Using both pharmacological perturbations and modeling, we show how this property is a consequence of the particular complement of voltage-dependent conductances in these cells.

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Synapse-selective control of cortical maturation and plasticity engages an interneuron-autonomous synaptic switch

10.1101/382614 ◽

2018 ◽

Author(s):

Adema Ribic ◽

Michael C. Crair ◽

Thomas Biederer

Keyword(s):

Visual Cortex ◽

Critical Period ◽

Visual Experience ◽

Cortical Plasticity ◽

Brain Plasticity ◽

Cortical Inhibition ◽

Specific Cell ◽

List Type ◽

Critical Periods ◽

Age Related

HighlightsThe synaptogenic molecule SynCAM 1 is selectively regulated by visual experienceSynCAM 1 controls thalamic input onto cortical Parvalbumin (PV+) interneuronsPV+-specific knockdown of SynCAM 1 arrests maturation of cortical inhibitionThalamic excitation onto PV+ interneurons is essential for critical period closureeTOC BlurbRibic et al. show that network plasticity in both young and adult cortex is restricted by the synapse organizing molecule SynCAM 1. On a cellular level, it functions in Parvalbumin-positive interneurons to recruit thalamocortical terminals. This controls the maturation of inhibitory drive and restricts plasticity in the cortex. These results reveal the synaptic locus of cortical plasticity and identify the first cell-autonomous synaptic factor for closure of cortical critical periods.SummaryBrain plasticity peaks early in life and tapers in adulthood. This is exemplified in the primary visual cortex, where brief loss of vision to one eye abrogates cortical responses to inputs from that eye during the critical period, but not in adulthood. The synaptic locus of critical period plasticity and the cell-autonomous synaptic factors timing these periods remain unclear. We here demonstrate that the immunoglobulin protein Synaptic Cell Adhesion Molecule 1 (SynCAM 1/Cadm1) is regulated by visual experience and limits visual cortex plasticity. SynCAM 1 selectively controls the number of excitatory thalamocortical (TC) inputs onto Parvalbumin (PV+) interneurons and loss of SynCAM 1 in turn impairs the maturation of TC-driven feed-forward inhibition. SynCAM 1 acts in cortical PV+ interneurons to perform these functions and its PV+-specific knockdown prevents the age-related plasticity decline. These results identify a synapse type-specific, cell-autonomous mechanism that governs circuit maturation and closes the visual critical period.

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The Exercising Brain: Changes in Functional Connectivity Induced by an Integrated Multimodal Cognitive and Whole-Body Coordination Training

Neural Plasticity ◽

10.1155/2016/8240894 ◽

2016 ◽

Vol 2016 ◽

pp. 1-11 ◽

Cited By ~ 21

Author(s):

Traute Demirakca ◽

Vita Cardinale ◽

Sven Dehn ◽

Matthias Ruf ◽

Gabriele Ende

Keyword(s):

Functional Connectivity ◽

Brain Plasticity ◽

Brain Regions ◽

Posterior Cingulate Cortex ◽

Whole Body ◽

Before And After ◽

Coordination Training ◽

Brain Changes ◽

The Impact ◽

The Brain

This study investigated the impact of “life kinetik” training on brain plasticity in terms of an increased functional connectivity during resting-state functional magnetic resonance imaging (rs-fMRI). The training is an integrated multimodal training that combines motor and cognitive aspects and challenges the brain by introducing new and unfamiliar coordinative tasks. Twenty-one subjects completed at least 11 one-hour-per-week “life kinetik” training sessions in 13 weeks as well as before and after rs-fMRI scans. Additionally, 11 control subjects with 2 rs-fMRI scans were included. The CONN toolbox was used to conduct several seed-to-voxel analyses. We searched for functional connectivity increases between brain regions expected to be involved in the exercises. Connections to brain regions representing parts of the default mode network, such as medial frontal cortex and posterior cingulate cortex, did not change. Significant connectivity alterations occurred between the visual cortex and parts of the superior parietal area (BA7). Premotor area and cingulate gyrus were also affected. We can conclude that the constant challenge of unfamiliar combinations of coordination tasks, combined with visual perception and working memory demands, seems to induce brain plasticity expressed in enhanced connectivity strength of brain regions due to coactivation.

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Neural Dynamics and Gamma Oscillation on a Hybrid Excitatory-Inhibitory Complex Network (Student Abstract)

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i10.7251 ◽

2020 ◽

Vol 34 (10) ◽

pp. 13957-13958

Author(s):

Yuan Wang ◽

Xia Shi ◽

Bo Cheng ◽

Junliang Chen

Keyword(s):

Complex Network ◽

Small World ◽

Gamma Oscillations ◽

Gamma Oscillation ◽

Inhibitory Neurons ◽

Critical Parameters ◽

Neural Dynamics ◽

Gamma Rhythm ◽

Excitatory Neurons ◽

Fast Spiking

This paper investigates the neural dynamics and gamma oscillation on a complex network with excitatory and inhibitory neurons (E-I network), as such network is ubiquitous in the brain. The system consists of a small-world network of neurons, which are emulated by Izhikevich model. Moreover, mixed Regular Spiking (RS) and Chattering (CH) neurons are considered to imitate excitatory neurons, and Fast Spiking (FS) neurons are used to mimic inhibitory neurons. Besides, the relationship between synchronization and gamma rhythm is explored by adjusting the critical parameters of our model. Experiments visually demonstrate that the gamma oscillations are generated by synchronous behaviors of our neural network. We also discover that the Chattering(CH) excitatory neurons can make the system easier to synchronize.

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Newly Generated and Non-Newly Generated “Immature” Neurons in the Mammalian Brain: A Possible Reservoir of Young Cells to Prevent Brain Aging and Disease?

Journal of Clinical Medicine ◽

10.3390/jcm8050685 ◽

2019 ◽

Vol 8 (5) ◽

pp. 685 ◽

Cited By ~ 10

Author(s):

Chiara La Rosa ◽

Marco Ghibaudi ◽

Luca Bonfanti

Keyword(s):

Neurological Disorders ◽

Brain Aging ◽

Brain Plasticity ◽

Brain Regions ◽

Mammalian Brain ◽

Brain Health ◽

Immature Neurons ◽

Potential Reservoir ◽

The Impact ◽

Stem Cell Niches

Brain plasticity is important for translational purposes since most neurological disorders and brain aging problems remain substantially incurable. In the mammalian nervous system, neurons are mostly not renewed throughout life and cannot be replaced. In humans, the increasing life expectancy explains the increase in brain health problems, also producing heavy social and economic burden. An exception to the “static” brain is represented by stem cell niches leading to the production of new neurons. Such adult neurogenesis is dramatically reduced from fish to mammals, and in large-brained mammals with respect to rodents. Some examples of neurogenesis occurring outside the neurogenic niches have been reported, yet these new neurons actually do not integrate in the mature nervous tissue. Non-newly generated, “immature” neurons (nng-INs) are also present: Prenatally generated cells continuing to express molecules of immaturity (mostly shared with the newly born neurons). Of interest, nng-INs seem to show an inverse phylogenetic trend across mammals, being abundant in higher-order brain regions not served by neurogenesis and providing structural plasticity in rather stable areas. Both newly generated and nng-INs represent a potential reservoir of young cells (a “brain reserve”) that might be exploited for preventing the damage of aging and/or delay the onset/reduce the impact of neurological disorders.

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Hyperexcitability and Homeostasis in Fragile X Syndrome

Frontiers in Molecular Neuroscience ◽

10.3389/fnmol.2021.805929 ◽

2022 ◽

Vol 14 ◽

Author(s):

Xiaopeng Liu ◽

Vipendra Kumar ◽

Nien-Pei Tsai ◽

Benjamin D. Auerbach

Keyword(s):

Fragile X Syndrome ◽

Fragile X ◽

Inhibitory Neuron ◽

Cell Types ◽

Developmental Time ◽

Brain Regions ◽

Synaptic Function ◽

Homeostatic Plasticity ◽

Neuron Activity ◽

The Impact

Fragile X Syndrome (FXS) is a leading inherited cause of autism and intellectual disability, resulting from a mutation in the FMR1 gene and subsequent loss of its protein product FMRP. Despite this simple genetic origin, FXS is a phenotypically complex disorder with a range of physical and neurocognitive disruptions. While numerous molecular and cellular pathways are affected by FMRP loss, there is growing evidence that circuit hyperexcitability may be a common convergence point that can account for many of the wide-ranging phenotypes seen in FXS. The mechanisms for hyperexcitability in FXS include alterations to excitatory synaptic function and connectivity, reduced inhibitory neuron activity, as well as changes to ion channel expression and conductance. However, understanding the impact of FMR1 mutation on circuit function is complicated by the inherent plasticity in neural circuits, which display an array of homeostatic mechanisms to maintain activity near set levels. FMRP is also an important regulator of activity-dependent plasticity in the brain, meaning that dysregulated plasticity can be both a cause and consequence of hyperexcitable networks in FXS. This makes it difficult to separate the direct effects of FMR1 mutation from the myriad and pleiotropic compensatory changes associated with it, both of which are likely to contribute to FXS pathophysiology. Here we will: (1) review evidence for hyperexcitability and homeostatic plasticity phenotypes in FXS models, focusing on similarities/differences across brain regions, cell-types, and developmental time points; (2) examine how excitability and plasticity disruptions interact with each other to ultimately contribute to circuit dysfunction in FXS; and (3) discuss how these synaptic and circuit deficits contribute to disease-relevant behavioral phenotypes like epilepsy and sensory hypersensitivity. Through this discussion of where the current field stands, we aim to introduce perspectives moving forward in FXS research.

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Systematic Analysis of Environmental Chemicals That Dysregulate Critical Period Plasticity-Related Gene Expression Reveals Common Pathways That Mimic Immune Response to Pathogen

Neural Plasticity ◽

10.1155/2020/1673897 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Milo R. Smith ◽

Priscilla Yevoo ◽

Masato Sadahiro ◽

Ben Readhead ◽

Brian Kidd ◽

...

Keyword(s):

Immune Response ◽

Critical Period ◽

Enrichment Analysis ◽

Environmental Chemicals ◽

Molecular Signatures ◽

Critical Periods ◽

Systematic Analysis ◽

Synthetic Chemicals ◽

Chemically Induced ◽

The Impact

The tens of thousands of industrial and synthetic chemicals released into the environment have an unknown but potentially significant capacity to interfere with neurodevelopment. Consequently, there is an urgent need for systematic approaches that can identify disruptive chemicals. Little is known about the impact of environmental chemicals on critical periods of developmental neuroplasticity, in large part, due to the challenge of screening thousands of chemicals. Using an integrative bioinformatics approach, we systematically scanned 2001 environmental chemicals and identified 50 chemicals that consistently dysregulate two transcriptional signatures of critical period plasticity. These chemicals included pesticides (e.g., pyridaben), antimicrobials (e.g., bacitracin), metals (e.g., mercury), anesthetics (e.g., halothane), and other chemicals and mixtures (e.g., vehicle emissions). Application of a chemogenomic enrichment analysis and hierarchical clustering across these diverse chemicals identified two clusters of chemicals with one that mimicked an immune response to pathogen, implicating inflammatory pathways and microglia as a common chemically induced neuropathological process. Thus, we established an integrative bioinformatics approach to systematically scan thousands of environmental chemicals for their ability to dysregulate molecular signatures relevant to critical periods of development.

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An Extracellular Perspective on CNS Maturation: Perineuronal Nets and the Control of Plasticity

International Journal of Molecular Sciences ◽

10.3390/ijms22052434 ◽

2021 ◽

Vol 22 (5) ◽

pp. 2434

Author(s):

Daniela Carulli ◽

Joost Verhaagen

Keyword(s):

Critical Period ◽

Brain Plasticity ◽

Time Windows ◽

Adult Brain ◽

Mammalian Brain ◽

Postnatal Life ◽

Perineuronal Nets ◽

Critical Periods ◽

Perineuronal Net ◽

Memory Processes

During restricted time windows of postnatal life, called critical periods, neural circuits are highly plastic and are shaped by environmental stimuli. In several mammalian brain areas, from the cerebral cortex to the hippocampus and amygdala, the closure of the critical period is dependent on the formation of perineuronal nets. Perineuronal nets are a condensed form of an extracellular matrix, which surrounds the soma and proximal dendrites of subsets of neurons, enwrapping synaptic terminals. Experimentally disrupting perineuronal nets in adult animals induces the reactivation of critical period plasticity, pointing to a role of the perineuronal net as a molecular brake on plasticity as the critical period closes. Interestingly, in the adult brain, the expression of perineuronal nets is remarkably dynamic, changing its plasticity-associated conditions, including memory processes. In this review, we aimed to address how perineuronal nets contribute to the maturation of brain circuits and the regulation of adult brain plasticity and memory processes in physiological and pathological conditions.

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