Gene expression profiling in the neuroendocrine brain of male goldfish (Carassius auratus) exposed to 17α-ethinylestradiol

2006 ◽  
Vol 27 (3) ◽  
pp. 328-336 ◽  
Author(s):  
Christopher J. Martyniuk ◽  
Huiling Xiong ◽  
Kate Crump ◽  
Suzanne Chiu ◽  
Ravinder Sardana ◽  
...  
Keyword(s):  
Large Scale ◽  
Cell Metabolism ◽  
Endocrine Disrupting Chemicals ◽  
Cdna Array ◽  
Adult Brain ◽  
Intact Male ◽  
Mature Adult ◽  
Goldfish Carassius Auratus ◽  
Brain Aromatase ◽  
The Brain

17-α Ethinylestradiol (EE2), a pharmaceutical estrogen, is detectable in water systems worldwide. Although studies report on the effects of xenoestrogens in tissues such as liver and gonad, few studies to date have investigated the effects of EE2 in the vertebrate brain at a large scale. The purpose of this study was to develop a goldfish brain-enriched cDNA array and use this in conjunction with a mixed tissue carp microarray to study the genomic response to EE2 in the brain. Gonad-intact male goldfish were exposed to nominal concentrations of 0.1 nM (29.6 ng/l) and 1.0 nM (296 ng/l) EE2 for 15 days. Male goldfish treated with the higher dose of EE2 had significantly smaller gonads compared with controls. Males also had a significantly reduced level of circulating testosterone (T) and 17β-estradiol (E2) in both treatment groups. Candidate genes identified by microarray analysis fall into functional categories that include neuropeptides, cell metabolism, and transcription/translation factors. Differentially expressed genes verified by real-time RT-PCR included brain aromatase, secretogranin-III, and interferon-related developmental regulator 1. Our results suggest that the expression of genes in the sexually mature adult brain appears to be resistant to low EE2 exposure but is affected significantly at higher doses of EE2. This study demonstrates that microarray technology is a useful tool to study the effects of endocrine disrupting chemicals on neuroendocrine function and suggest that exposure to EE2 may have significant effects on localized E2 synthesis in the brain by affecting transcription of brain aromatase.

Arithmetic in the Child and Adult Brain

2014 ◽  
Author(s):  
Vinod Menon
Keyword(s):  
Skill Acquisition ◽  
Temporal Cortex ◽  
Occipital Cortex ◽  
Building Blocks ◽  
Memory Systems ◽  
Adult Brain ◽  
Long Term Memory ◽  
Neural Basis ◽  
Mature Adult ◽  
The Brain

This review examines brain and cognitive processes involved in arithmetic. I take a distinctly developmental perspective because neither the cognitive nor the brain processes involved in arithmetic can be adequately understood outside the framework of how developmental processes unfold. I review four basic neurocognitive processes involved in arithmetic, highlighting (1) the role of core dorsal parietal and ventral temporal-occipital cortex systems that form basic building blocks from which number form and quantity representations are constructed in the brain; (2) procedural and working memory systems anchored in the basal ganglia and frontoparietal circuits, which create short-term representations that allow manipulation of multiple discrete quantities over several seconds; (3) episodic and semantic memory systems anchored in the medial and lateral temporal cortex that play an important role in long-term memory formation and generalization beyond individual problem attributes; and (4) prefrontal cortex control processes that guide allocation of attention resources and retrieval of facts from memory in the service of goal-directed problem solving. Next I examine arithmetic in the developing brain, first focusing on studies comparing arithmetic in children and adults, and then on studies examining development in children during critical stages of skill acquisition. I highlight neurodevelopmental models that go beyond parietal cortex regions involved in number processing, and demonstrate that brain systems and circuits in the developing child brain are clearly not the same as those seen in more mature adult brains sculpted by years of learning. The implications of these findings for a more comprehensive view of the neural basis of arithmetic in both children and adults are discussed.

Nerve and Brain

Mind Shift ◽  
2021 ◽  
pp. 63-79
Author(s):  
John Parrington
Keyword(s):  
Human Brain ◽  
Glial Cells ◽  
Large Scale ◽  
Brain Size ◽  
Adult Brain ◽  
The Other ◽  
Basic Unit ◽  
The Brain ◽  
Size And Structure

This chapter evaluates the basic unit of the human brain: the nerve cell, or neuron. These cells are also the main units of the peripheral nervous system, which sends messages from the brain to the other tissues and organs that make up our bodies. Neurons are the most well-known cells in the brain but they are not the only type of cell in this organ. The other main types are the glial cells, also known as neuroglia. Recent studies of the role of glial cells in the brain are revealing potentially important differences between humans and other species in the functions of these cells. The chapter then turns to the large-scale structure of the brain. The most dramatic changes in brain size and structure occurred in the final phase of human evolutionary change. Indeed, Neanderthals had brains similar in size to those of modern humans. An important feature of the human brain is that a larger fraction of its growth occurs outside the womb. Although humans reach adult brain size in childhood, brain development continues for decades afterwards.

scholarly journals Constant neuropilar ratio in the insect brain

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Alexey A. Polilov ◽  
Anastasia A. Makarova
Keyword(s):  
Cell Body ◽  
Large Scale ◽  
Relative Volume ◽  
Adult Brain ◽  
Morphometric Study ◽  
Insect Brain ◽  
Size Groups ◽  
Brain Changes ◽  
Allometric Analysis ◽  
The Brain

AbstractRevealing scaling rules is necessary for understanding the morphology, physiology and evolution of living systems. Studies of animal brains have revealed both general patterns, such as Haller's rule, and patterns specific for certain animal taxa. However, large-scale studies aimed at studying the ratio of the entire neuropil and the cell body rind in the insect brain have never been performed. Here we performed morphometric study of the adult brain in 37 insect species of 26 families and ten orders, ranging in volume from the smallest to the largest by a factor of more than 4,000,000, and show that all studied insects display a similar ratio of the volume of the neuropil to the cell body rind, 3:2. Allometric analysis for all insects shows that the ratio of the volume of the neuropil to the volume of the brain changes strictly isometrically. Analyses within particular taxa, size groups, and metamorphosis types also reveal no significant differences in the relative volume of the neuropil; isometry is observed in all cases. Thus, we establish a new scaling rule, according to which the relative volume of the entire neuropil in insect brain averages 60% and remains constant.

scholarly journals Brain Aromatase and the Regulation of Sexual Activity in Male Mice

Endocrinology ◽  
2020 ◽  
Vol 161 (10) ◽  
Author(s):  
David C Brooks ◽  
John S Coon V ◽  
Cihangir M Ercan ◽  
Xia Xu ◽  
Hongxin Dong ◽  
...  
Keyword(s):  
Sexual Behavior ◽  
Sexual Activity ◽  
Adult Brain ◽  
Whole Body ◽  
Male Mice ◽  
Negative Feedback Regulation ◽  
Male Sexual Behavior ◽  
Brain Physiology ◽  
Brain Aromatase ◽  
The Brain

Abstract The biologically active estrogen estradiol has important roles in adult brain physiology and sexual behavior. A single gene, Cyp19a1, encodes aromatase, the enzyme that catalyzes the conversion of testosterone to estradiol in the testis and brain of male mice. Estradiol formation was shown to regulate sexual activity in various species, but the relative contributions to sexual behavior of estrogen that arises in the brain versus from the gonads remained unclear. To determine the role of brain aromatase in regulating male sexual activity, we generated a brain-specific aromatase knockout (bArKO) mouse. A newly generated whole-body total aromatase knockout mouse of the same genetic background served as a positive control. Here we demonstrate that local aromatase expression and estrogen production in the brain is partially required for male sexual behavior and sex hormone homeostasis. Male bArKO mice exhibited decreased sexual activity in the presence of strikingly elevated circulating testosterone. In castrated adult bArKO mice, administration of testosterone only partially restored sexual behavior; full sexual behavior, however, was achieved only when both estradiol and testosterone were administered together. Thus, aromatase in the brain is, in part, necessary for testosterone-dependent male sexual activity. We also found that brain aromatase is required for negative feedback regulation of circulating testosterone of testicular origin. Our findings suggest testosterone activates male sexual behavior in part via conversion to estradiol in the brain. These studies provide foundational evidence that sexual behavior may be modified through inhibition or enhancement of brain aromatase enzyme activity and/or utilization of selective estrogen receptor modulators.

Implantable neural interfaces

2018 ◽  
Author(s):  
Stefano Vassanelli
Keyword(s):  
Brain Function ◽  
Large Scale ◽  
Ionic Channels ◽  
Patch Clamp Technique ◽  
Advantages And Disadvantages ◽  
Optogenetic Stimulation ◽  
Physical Interfaces ◽  
The Brain

Establishing direct communication with the brain through physical interfaces is a fundamental strategy to investigate brain function. Starting with the patch-clamp technique in the seventies, neuroscience has moved from detailed characterization of ionic channels to the analysis of single neurons and, more recently, microcircuits in brain neuronal networks. Development of new biohybrid probes with electrodes for recording and stimulating neurons in the living animal is a natural consequence of this trend. The recent introduction of optogenetic stimulation and advanced high-resolution large-scale electrical recording approaches demonstrates this need. Brain implants for real-time neurophysiology are also opening new avenues for neuroprosthetics to restore brain function after injury or in neurological disorders. This chapter provides an overview on existing and emergent neurophysiology technologies with particular focus on those intended to interface neuronal microcircuits in vivo. Chemical, electrical, and optogenetic-based interfaces are presented, with an analysis of advantages and disadvantages of the different technical approaches.

What Has Direct Cortical and Subcortical Electrostimulation Taught Us about Neurolinguistics?

2019 ◽  
pp. 185-211
Author(s):  
Hugues Duffau
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Great Accuracy ◽  
Subcortical White Matter ◽  
Cerebral Lesions ◽  
Physiological Basis ◽  
Postoperative Mri ◽  
The Brain

Investigating the neural and physiological basis of language is one of the most important challenges in neurosciences. Direct electrical stimulation (DES), usually performed in awake patients during surgery for cerebral lesions, is a reliable tool for detecting both cortical and subcortical (white matter and deep grey nuclei) regions crucial for cognitive functions, especially language. DES transiently interacts locally with a small cortical or axonal site, but also nonlocally, as the focal perturbation will disrupt the entire subnetwork sustaining a given function. Thus, in contrast to functional neuroimaging, DES represents a unique opportunity to identify with great accuracy and reproducibility, in vivo in humans, the structures that are actually indispensable to the function, by inducing a transient virtual lesion based on the inhibition of a subcircuit lasting a few seconds. Currently, this is the sole technique that is able to directly investigate the functional role of white matter tracts in humans. Thus, combining transient disturbances elicited by DES with the anatomical data provided by pre- and postoperative MRI enables to achieve reliable anatomo-functional correlations, supporting a network organization of the brain, and leading to the reappraisal of models of language representation. Finally, combining serial peri-operative functional neuroimaging and online intraoperative DES allows the study of mechanisms underlying neuroplasticity. This chapter critically reviews the basic principles of DES, its advantages and limitations, and what DES can reveal about the neural foundations of language, that is, the large-scale distribution of language areas in the brain, their connectivity, and their ability to reorganize.

scholarly journals Content-Based Estimation of Brain MRI Tilt in Three Orthogonal Directions

2021 ◽  
Author(s):  
Pooja Prabhu ◽  
A. K. Karunakar ◽  
Sanjib Sinha ◽  
N. Mariyappa ◽  
G. K. Bhargava ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Mri ◽  
Similarity Measures ◽  
Principal Component ◽  
Brain Anatomy ◽  
Morphological Operations ◽  
Mr Images ◽  
Tilt Correction ◽  
Brain Mr Images ◽  
The Brain

AbstractIn a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 ± 0.09°, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 ± 3.94, 2.35 ± 2.61, and 5 ± 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.

scholarly journals An architectonic type principle in the development of laminar patterns of cortico-cortical connections

2021 ◽  
Author(s):  
Sarah F. Beul ◽  
Alexandros Goulas ◽  
Claus C. Hilgetag
Keyword(s):  
Structural Connectivity ◽  
Macaque Monkey ◽  
Brain Regions ◽  
Adult Brain ◽  
Mammalian Brain ◽  
Cortical Connections ◽  
Cortical Projections ◽  
Structural Connections ◽  
High Degree ◽  
The Brain

AbstractStructural connections between cortical areas form an intricate network with a high degree of specificity. Many aspects of this complex network organization in the adult mammalian cortex are captured by an architectonic type principle, which relates structural connections to the architectonic differentiation of brain regions. In particular, the laminar patterns of projection origins are a prominent feature of structural connections that varies in a graded manner with the relative architectonic differentiation of connected areas in the adult brain. Here we show that the architectonic type principle is already apparent for the laminar origins of cortico-cortical projections in the immature cortex of the macaque monkey. We find that prenatal and neonatal laminar patterns correlate with cortical architectonic differentiation, and that the relation of laminar patterns to architectonic differences between connected areas is not substantially altered by the complete loss of visual input. Moreover, we find that the degree of change in laminar patterns that projections undergo during development varies in proportion to the relative architectonic differentiation of the connected areas. Hence, it appears that initial biases in laminar projection patterns become progressively strengthened by later developmental processes. These findings suggest that early neurogenetic processes during the formation of the brain are sufficient to establish the characteristic laminar projection patterns. This conclusion is in line with previously suggested mechanistic explanations underlying the emergence of the architectonic type principle and provides further constraints for exploring the fundamental factors that shape structural connectivity in the mammalian brain.

A new method to predict anomaly in brain network based on graph deep learning

2020 ◽  
Vol 31 (6) ◽  
pp. 681-689
Author(s):  
Jalal Mirakhorli ◽  
Hamidreza Amindavar ◽  
Mojgan Mirakhorli
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Brain Plasticity ◽  
Brain Network ◽  
High Order ◽  
Brain Diseases ◽  
Simultaneous Occurrence ◽  
Generative Adversarial Network ◽  
The Brain ◽  
Brain Connections

AbstractFunctional magnetic resonance imaging a neuroimaging technique which is used in brain disorders and dysfunction studies, has been improved in recent years by mapping the topology of the brain connections, named connectopic mapping. Based on the fact that healthy and unhealthy brain regions and functions differ slightly, studying the complex topology of the functional and structural networks in the human brain is too complicated considering the growth of evaluation measures. One of the applications of irregular graph deep learning is to analyze the human cognitive functions related to the gene expression and related distributed spatial patterns. Since a variety of brain solutions can be dynamically held in the neuronal networks of the brain with different activity patterns and functional connectivity, both node-centric and graph-centric tasks are involved in this application. In this study, we used an individual generative model and high order graph analysis for the region of interest recognition areas of the brain with abnormal connection during performing certain tasks and resting-state or decompose irregular observations. Accordingly, a high order framework of Variational Graph Autoencoder with a Gaussian distributer was proposed in the paper to analyze the functional data in brain imaging studies in which Generative Adversarial Network is employed for optimizing the latent space in the process of learning strong non-rigid graphs among large scale data. Furthermore, the possible modes of correlations were distinguished in abnormal brain connections. Our goal was to find the degree of correlation between the affected regions and their simultaneous occurrence over time. We can take advantage of this to diagnose brain diseases or show the ability of the nervous system to modify brain topology at all angles and brain plasticity according to input stimuli. In this study, we particularly focused on Alzheimer’s disease.

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