Is There a Brain Microbiome?

Ground Truth ◽

Healthy Human ◽

Strong Motivation ◽

The Many ◽

Numerous studies have identified microbial sequences or epitopes in pathological and non-pathological human brain samples. It has not been resolved if these observations are artifactual, or truly represent population of the brain by microbes. Given the tempting speculation that resident microbes could play a role in the many neuropsychiatric and neurodegenerative diseases that currently lack clear etiologies, there is a strong motivation to determine the “ground truth” of microbial existence in living brains. Here I argue that the evidence for the presence of microbes in diseased brains is quite strong, but a compelling demonstration of resident microbes in the healthy human brain remains to be done. Dedicated animal models studies may be required to determine if there is indeed a “brain microbiome.”

Comparing supervised and unsupervised approaches to emotion categorization in the human brain, body, and subjective experience.

10.31234/osf.io/egh2t ◽

2020 ◽

Author(s):

Bahar Azari ◽

Christiana Westlin ◽

Ajay Satpute ◽

J. Benjamin Hutchinson ◽

Philip A. Kragel ◽

...

Keyword(s):

Human Brain ◽

Subjective Experience ◽

A Priori ◽

Ground Truth ◽

Test Case ◽

Physical Measurements ◽

Supervised Classifiers ◽

Emotional Episodes ◽

Emotion Labels ◽

Machine learning methods provide powerful tools to map physical measurements to scientific categories. But are such methods suitable for discovering the ground truth about psychological categories? We use the science of emotion as a test case to explore this question. In studies of emotion, researchers use supervised classifiers, guided by emotion labels, to attempt to discover biomarkers in the brain or body for the corresponding emotion categories. This practice relies on the assumption that the labels refer to objective categories that can be discovered. Here, we critically examine this approach across three distinct datasets collected during emotional episodes- measuring the human brain, body, and subjective experience- and compare supervised classification studies with those from unsupervised clustering in which no a priori labels are assigned to the data. We conclude with a set of recommendations to guide researchers towards meaningful, data-driven discoveries in the science of emotion and beyond.

Splendours and miseries of the brain

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.1999.0543 ◽

1999 ◽

Vol 354 (1392) ◽

pp. 2053-2065 ◽

Cited By ~ 12

Author(s):

S. Zeki

Keyword(s):

Human Brain ◽

Daily Lives ◽

Evolutionary Selection ◽

Evolutionary Success ◽

The Many ◽

The Brain ◽

Enormous Success

In this speculative essay, I examine two evolutionary developments underlying the enormous success of the human brain: its capacity to acquire knowledge and its variability across individuals. A feature of an efficient knowledge–acquiring system is, I believe, its capacity to abstract and to formulate ideals. Both attributes carry with them a clash between experience of the particular and what the brain has developed from experience of the many. Both therefore can lead to much disappointment in our daily lives. This disappointment is heightened by the fact that both abstraction and ideals are subject to variability in time within an individual and between individuals. Variability, which is a cherished source for evolutionary selection, can also be an isolating and individualizing feature in society. Thus the very features of the human brain which underlie our enormous evolutionary success can also be a major source of our misery.

The Many Sides of Hemispheric Asymmetry: A Selective Review and Outlook

Journal of the International Neuropsychological Society ◽

10.1017/s1355617717000376 ◽

2017 ◽

Vol 23 (9-10) ◽

pp. 710-718 ◽

Cited By ~ 11

Author(s):

Michael C. Corballis ◽

Isabelle S. Häberling

Keyword(s):

Human Brain ◽

Social Life ◽

Hemispheric Asymmetry ◽

Brain Asymmetry ◽

Dual System ◽

Animal Kingdom ◽

Internal Organs ◽

The Many ◽

Two Sides ◽

AbstractHemispheric asymmetry is commonly viewed as a dual system, unique to humans, with the two sides of the human brain in complementary roles. To the contrary, modern research shows that cerebral and behavioral asymmetries are widespread in the animal kingdom, and that the concept of duality is an oversimplification. The brain has many networks serving different functions; these are differentially lateralized, and involve many genes. Unlike the asymmetries of the internal organs, brain asymmetry is variable, with a significant minority of the population showing reversed asymmetries or the absence of asymmetry. This variability may underlie the divisions of labor and the specializations that sustain social life. (JINS, 2017, 23, 710–718)

The Role of the Human Brain Neuron–Glia–Synapse Composition in Forming Resting-State Functional Connectivity Networks

Brain Sciences ◽

10.3390/brainsci11121565 ◽

2021 ◽

Vol 11 (12) ◽

pp. 1565

Author(s):

Sayan Kahali ◽

Marcus E Raichle ◽

Dmitriy A Yablonskiy

Keyword(s):

Human Brain ◽

Resting State ◽

Functional Networks ◽

Bold Signal ◽

Resting State Functional Connectivity ◽

Healthy Human ◽

Neuronal Density ◽

Wide Range ◽

Functional Units ◽

While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain’s cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood–oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional units’ connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents. These mechanisms lead to a rather broad distribution of resting-state functional network properties. Visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of the BOLD signal as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but with a remarkably balanced cellular contents, enabling DMN to have a prominent role in the overall organization of the brain and hierarchy of functional networks.

Animal Models of Neurodegenerative Diseases

10.1093/med/9780190233563.003.0014 ◽

2016 ◽

Author(s):

David Baglietto-Vargas ◽

Rahasson R. Ager ◽

Rodrigo Medeiros ◽

Frank M. LaFerla

Keyword(s):

Animal Models ◽

Life Expectancy ◽

Neurodegenerative Disorders ◽

Human Disease ◽

Molecular Mechanisms ◽

Preclinical Studies ◽

Pathological Features ◽

The Past ◽

The incidence and prevalence of neurodegenerative disorders (e.g., Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD), etc.) are growing rapidly due to increasing life expectancy. Researchers over the past two decades have focused their efforts on the development of animal models to dissect the molecular mechanisms underlying neurodegenerative disorders. Existing models, however, do not fully replicate the symptomatic and pathological features of human diseases. This chapter focuses on animal models of AD, as this disorder is the most prevalent of the brain degenerative conditions afflicting society. In particular, it briefly discusses the current leading animal models, the translational relevance of the preclinical studies using such models, and the limitations and shortcomings of using animals to model human disease. It concludes with a discussion of potential means to improve future models to better recapitulate human conditions.

Comparing supervised and unsupervised approaches to emotion categorization in the human brain, body, and subjective experience

Scientific Reports ◽

10.1038/s41598-020-77117-8 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Bahar Azari ◽

Christiana Westlin ◽

Ajay B. Satpute ◽

J. Benjamin Hutchinson ◽

Philip A. Kragel ◽

...

Keyword(s):

Human Brain ◽

Subjective Experience ◽

Ground Truth ◽

Test Case ◽

Machine Learning Methods ◽

Physical Measurements ◽

Supervised Classifiers ◽

Emotional Episodes ◽

Emotion Labels ◽

AbstractMachine learning methods provide powerful tools to map physical measurements to scientific categories. But are such methods suitable for discovering the ground truth about psychological categories? We use the science of emotion as a test case to explore this question. In studies of emotion, researchers use supervised classifiers, guided by emotion labels, to attempt to discover biomarkers in the brain or body for the corresponding emotion categories. This practice relies on the assumption that the labels refer to objective categories that can be discovered. Here, we critically examine this approach across three distinct datasets collected during emotional episodes—measuring the human brain, body, and subjective experience—and compare supervised classification solutions with those from unsupervised clustering in which no labels are assigned to the data. We conclude with a set of recommendations to guide researchers towards meaningful, data-driven discoveries in the science of emotion and beyond.

FRACTAL DIMENSION AND LACUNARITY OF TRACTOGRAPHY IMAGES OF THE HUMAN BRAIN

Fractals ◽

10.1142/s0218348x09004284 ◽

2009 ◽

Vol 17 (02) ◽

pp. 181-189 ◽

Cited By ~ 23

Author(s):

P. KATSALOULIS ◽

D. A. VERGANELAKIS ◽

A. PROVATA

Keyword(s):

Fractal Dimension ◽

Human Brain ◽

Fractal Dimensions ◽

Resonance Imaging ◽

Self Similarity ◽

Healthy Human ◽

Box Counting ◽

Self Similar ◽

Box Method ◽

Tractography images produced by Magnetic Resonance Imaging scans have been used to calculate the topology of the neuron tracts in the human brain. This technique gives neuroanatomical details, limited by the system resolution properties. In the observed scales the images demonstrated the statistical self-similar structure of the neuron axons and its fractal dimensions were estimated using the classic Box Counting technique. To assess the degree of clustering in the neural tracts network, lacunarity was calculated using the Gliding Box method. The two-dimensional tractography images were taken from four subjects using various angles and different parts in the brain. The results demonstrated that the average estimated fractal dimension of tractography images is approximately Df = 1.60 with standard deviation 0.11 for healthy human-brain tissues, and it presents statistical self-similarity features similar to many other biological root-like structures.

Human brain mitochondrial-nuclear cross-talk is cell-type specific and is perturbed by neurodegeneration

10.1101/2021.02.04.429781 ◽

2021 ◽

Author(s):

Aine Fairbrother-Browne ◽

Aminah T. Ali ◽

Regina H. Reynolds ◽

Sonia Garcia-Ruiz ◽

David Zhang ◽

...

Keyword(s):

Central Nervous System ◽

Nervous System ◽

Mitochondrial Genome ◽

Human Brain ◽

System Analysis ◽

Nuclear Gene ◽

Cell Type ◽

Human Brain Tissue ◽

Healthy Human

AbstractMitochondrial dysfunction contributes to the pathogenesis of many neurodegenerative diseases as mitochondria are essential to neuronal function. The mitochondrial genome encodes a small number of core respiratory chain proteins, whereas the vast majority of mitochondrial proteins are encoded by the nuclear genome. Here we focus on establishing a profile of nuclear-mitochondrial transcriptional relationships in healthy human central nervous system tissue data, before examining perturbations of these processes in Alzheimer&#8217s disease using transcriptomic data originating from affected human brain tissue. Through cross-central nervous system analysis of mitochondrial-nuclear gene pair relationships, we find that the cell type composition underlies regional variation, and variation is driven at the subcellular level by heterogeneity of nuclear-mitochondrial coordination in post-synaptic regions. We show that nuclear genes causally implicated in sporadic Parkinson&#8217s disease and Alzheimer&#8217s disease show much stronger relationships with the mitochondrial genome than expected by chance, and that nuclear-mitochondrial relationships are significantly perturbed in Alzheimer&#8217s disease cases, particularly amongst genes involved in synaptic and lysosomal pathways. Finally, we present MitoNuclearCOEXPlorer, a web tool designed to allow users to interrogate and visualise key mitochondrial-nuclear relationships in multi-dimensional brain data. We conclude that mitochondrial-nuclear relationships differ significantly across regions of the healthy brain, which appears to be driven by the functional specialisation of different cell types. We also find that mitochondrial-nuclear co-expression in critical pathways is disrupted in Alzheimer&#8217s disease, potentially implicating the regulation of energy balance and removal of dysfunctional mitochondria in the etiology or progression of the disease and making the case for the relevance of bi-genomic co-ordination in the pathogenesis of neurodegenerative diseases.

Cryo-EM structures of amyloid-β 42 filaments from human brains

Science ◽

10.1126/science.abm7285 ◽

2022 ◽

Vol 375 (6577) ◽

pp. 167-172

Author(s):

Yang Yang ◽

Diana Arseni ◽

Wenjuan Zhang ◽

Melissa Huang ◽

Sofia Lövestam ◽

...

Keyword(s):

Electron Microscopy ◽

Animal Models ◽

Human Brain ◽

Amyloid Β ◽

Aβ Peptides ◽

Cryo Electron Microscopy ◽

Specificity And Sensitivity ◽

Human Brains ◽

Hi-res view of human Aβ42 filaments Alzheimer’s disease is characterized by a loss of memory and other cognitive functions and the filamentous assembly of Aβ and tau in the brain. The assembly of Aβ peptides into filaments that end at residue 42 is a central event. Yang et al . used electron cryo–electron microscopy to determine the structures of Aβ42 filaments from human brain (see the Perspective by Willem and Fändrich). They identified two types of related S-shaped filaments, each consisting of two identical protofilaments. These structures will inform the development of better in vitro and animal models, inhibitors of Aβ42 assembly, and imaging agents with increased specificity and sensitivity. —SMH

TRIM28 regulates the nuclear accumulation and toxicity of both alpha-synuclein and tau

eLife ◽

10.7554/elife.19809 ◽

2016 ◽

Vol 5 ◽

Cited By ~ 34

Author(s):

Maxime WC Rousseaux ◽

Maria de Haro ◽

Cristian A Lasagna-Reeves ◽

Antonia De Maio ◽

Jeehye Park ◽

...

Keyword(s):

Animal Models ◽

Alpha Synuclein ◽

Nuclear Accumulation ◽

Model Organisms ◽

Gain Of Function ◽

Entry Points ◽

Specific Proteins ◽

The Brain ◽

Lines Of Evidence

Several neurodegenerative diseases are driven by the toxic gain-of-function of specific proteins within the brain. Elevated levels of alpha-synuclein (α-Syn) appear to drive neurotoxicity in Parkinson's disease (PD); neuronal accumulation of tau is a hallmark of Alzheimer's disease (AD); and their increased levels cause neurodegeneration in humans and model organisms. Despite the clinical differences between AD and PD, several lines of evidence suggest that α-Syn and tau overlap pathologically. The connections between α-Syn and tau led us to ask whether these proteins might be regulated through a shared pathway. We therefore screened for genes that affect post-translational levels of α-Syn and tau. We found that TRIM28 regulates α-Syn and tau levels and that its reduction rescues toxicity in animal models of tau- and α-Syn-mediated degeneration. TRIM28 stabilizes and promotes the nuclear accumulation and toxicity of both proteins. Intersecting screens across comorbid proteinopathies thus reveal shared mechanisms and therapeutic entry points.