-
Current Opinion in Neurobiology Oct 2013It has been known since the 1970s that the suprachiasmatic nucleus (SCN) is the brain's main biological clock, and since the 1990s that it uses a genetic clock based on... (Review)
Review
It has been known since the 1970s that the suprachiasmatic nucleus (SCN) is the brain's main biological clock, and since the 1990s that it uses a genetic clock based on transcriptional-translational loops to tell time. However, the recent demonstration that many other cells in the brain and the body also make use of the same genetic clock raises the question of how the SCN synchronizes all of the other clocks to arrive at a coherent circadian profile of physiology and behavior. In this review, we re-examine the evidence that the SCN clock is necessary for bringing order to the body's biological rhythms, and the circuitry of the circadian timing system by which it accomplishes this goal. Finally, we review the evidence that under conditions of restricted food availability, other clocks may be able to take over from the SCN to determine rhythms of behavior and physiology.
Topics: Animals; Brain; Circadian Clocks; Circadian Rhythm; Humans; Suprachiasmatic Nucleus
PubMed: 23706187
DOI: 10.1016/j.conb.2013.04.004 -
Cell Nov 2021Our immune system and brain interact on multiple scales, but how the brain represents and remembers immune challenges remains unclear. In this issue of Cell, Koren...
Our immune system and brain interact on multiple scales, but how the brain represents and remembers immune challenges remains unclear. In this issue of Cell, Koren et al. (2021) reveal that the brain's insular cortex stores information about inflammation in the body. Strikingly, these immunological "memory engrams" can restore the initial disease state when reactivated.
Topics: Brain; Humans; Immune System; Inflammation; Insular Cortex
PubMed: 34822782
DOI: 10.1016/j.cell.2021.11.002 -
Scientific Reports Jun 2021Despite remarkable advances, research into neurodegeneration and Alzheimer Disease (AD) has nonetheless been dominated by inconsistent and conflicting theory. Basic...
Despite remarkable advances, research into neurodegeneration and Alzheimer Disease (AD) has nonetheless been dominated by inconsistent and conflicting theory. Basic questions regarding how and why the brain changes over time remain unanswered. In this work, we lay novel foundations for a consistent, integrated view of the aging brain. We develop neural economics-the study of the brain's infrastructure, brain capital. Using mathematical modeling, we create ABC (Aging Brain Capital), a simple linear simultaneous-equation model that unites aspects of neuroscience, economics, and thermodynamics to explain the rise and fall of brain capital, and thus function, over the human lifespan. Solving and simulating this model, we show that in each of us, the resource budget constraints of our finite brains cause brain capital to reach an upper limit. The thermodynamics of our working brains cause persistent pathologies to inevitably accumulate. With time, the brain becomes damaged causing brain capital to depreciate and decline. Using derivative models, we suggest that this endogenous aging process underpins the pathogenesis and spectrum of neurodegenerative disease. We develop amyloid-tau interaction theory, a paradigm that bridges the unnecessary conflict between amyloid- and tau-centered hypotheses of AD. Finally, we discuss profound implications for therapeutic strategy and development.
Topics: Aging; Brain; Humans; Models, Neurological; Neurodegenerative Diseases; Neurons
PubMed: 34108560
DOI: 10.1038/s41598-021-91621-5 -
PLoS Computational Biology Nov 2022The connectivity of Artificial Neural Networks (ANNs) is different from the one observed in Biological Neural Networks (BNNs). Can the wiring of actual brains help...
The connectivity of Artificial Neural Networks (ANNs) is different from the one observed in Biological Neural Networks (BNNs). Can the wiring of actual brains help improve ANNs architectures? Can we learn from ANNs about what network features support computation in the brain when solving a task? At a meso/macro-scale level of the connectivity, ANNs' architectures are carefully engineered and such those design decisions have crucial importance in many recent performance improvements. On the other hand, BNNs exhibit complex emergent connectivity patterns at all scales. At the individual level, BNNs connectivity results from brain development and plasticity processes, while at the species level, adaptive reconfigurations during evolution also play a major role shaping connectivity. Ubiquitous features of brain connectivity have been identified in recent years, but their role in the brain's ability to perform concrete computations remains poorly understood. Computational neuroscience studies reveal the influence of specific brain connectivity features only on abstract dynamical properties, although the implications of real brain networks topologies on machine learning or cognitive tasks have been barely explored. Here we present a cross-species study with a hybrid approach integrating real brain connectomes and Bio-Echo State Networks, which we use to solve concrete memory tasks, allowing us to probe the potential computational implications of real brain connectivity patterns on task solving. We find results consistent across species and tasks, showing that biologically inspired networks perform as well as classical echo state networks, provided a minimum level of randomness and diversity of connections is allowed. We also present a framework, bio2art, to map and scale up real connectomes that can be integrated into recurrent ANNs. This approach also allows us to show the crucial importance of the diversity of interareal connectivity patterns, stressing the importance of stochastic processes determining neural networks connectivity in general.
Topics: Brain; Neural Networks, Computer; Connectome; Machine Learning
PubMed: 36383563
DOI: 10.1371/journal.pcbi.1010639 -
Physiological Reviews Jan 2008Estradiol is the most potent and ubiquitous member of a class of steroid hormones called estrogens. Fetuses and newborns are exposed to estradiol derived from their... (Review)
Review
Estradiol is the most potent and ubiquitous member of a class of steroid hormones called estrogens. Fetuses and newborns are exposed to estradiol derived from their mother, their own gonads, and synthesized locally in their brains. Receptors for estradiol are nuclear transcription factors that regulate gene expression but also have actions at the membrane, including activation of signal transduction pathways. The developing brain expresses high levels of receptors for estradiol. The actions of estradiol on developing brain are generally permanent and range from establishment of sex differences to pervasive trophic and neuroprotective effects. Cellular end points mediated by estradiol include the following: 1) apoptosis, with estradiol preventing it in some regions but promoting it in others; 2) synaptogenesis, again estradiol promotes in some regions and inhibits in others; and 3) morphometry of neurons and astrocytes. Estradiol also impacts cellular physiology by modulating calcium handling, immediate-early-gene expression, and kinase activity. The specific mechanisms of estradiol action permanently impacting the brain are regionally specific and often involve neuronal/glial cross-talk. The introduction of endocrine disrupting compounds into the environment that mimic or alter the actions of estradiol has generated considerable concern, and the developing brain is a particularly sensitive target. Prostaglandins, glutamate, GABA, granulin, and focal adhesion kinase are among the signaling molecules co-opted by estradiol to differentiate male from female brains, but much remains to be learned. Only by understanding completely the mechanisms and impact of estradiol action on the developing brain can we also understand when these processes go awry.
Topics: Animals; Animals, Newborn; Brain; Estradiol; Female; Male; Nervous System; Receptors, Estradiol; Sex Characteristics; Signal Transduction
PubMed: 18195084
DOI: 10.1152/physrev.00010.2007 -
Philosophical Transactions of the Royal... Dec 2015Large, complex brains have evolved independently in several lineages of protostomes and deuterostomes. Sensory centres in the brain increase in size and complexity in... (Review)
Review
Large, complex brains have evolved independently in several lineages of protostomes and deuterostomes. Sensory centres in the brain increase in size and complexity in proportion to the importance of a particular sensory modality, yet often share circuit architecture because of constraints in processing sensory inputs. The selective pressures driving enlargement of higher, integrative brain centres has been more difficult to determine, and may differ across taxa. The capacity for flexible, innovative behaviours, including learning and memory and other cognitive abilities, is commonly observed in animals with large higher brain centres. Other factors, such as social grouping and interaction, appear to be important in a more limited range of taxa, while the importance of spatial learning may be a common feature in insects with large higher brain centres. Despite differences in the exact behaviours under selection, evolutionary increases in brain size tend to derive from common modifications in development and generate common architectural features, even when comparing widely divergent groups such as vertebrates and insects. These similarities may in part be influenced by the deep homology of the brains of all Bilateria, in which shared patterns of developmental gene expression give rise to positionally, and perhaps functionally, homologous domains. Other shared modifications of development appear to be the result of homoplasy, such as the repeated, independent expansion of neuroblast numbers through changes in genes regulating cell division. The common features of large brains in so many groups of animals suggest that given their common ancestry, a limited set of mechanisms exist for increasing structural and functional diversity, resulting in many instances of homoplasy in bilaterian nervous systems.
Topics: Animals; Behavior, Animal; Biological Evolution; Brain; Gene Expression Regulation, Developmental; Sense Organs
PubMed: 26554044
DOI: 10.1098/rstb.2015.0054 -
Annals of the New York Academy of... Oct 2014Although the study of time has been central to physics and philosophy for millennia, questions of how time is represented in the brain and how this representation is... (Review)
Review
Although the study of time has been central to physics and philosophy for millennia, questions of how time is represented in the brain and how this representation is related to time perception have only recently started to be addressed. Emerging evidence subtly yet profoundly challenges our intuitive notions of time over short scales, offering insight into the nature of the brain's representation of time. Numerous different models, specified at the neural level, of how the brain may keep track of time have been proposed. These models differ in various ways, such as whether time is represented by a centralized or distributed neural system, or whether there are neural systems dedicated to the problem of timing. This paper reviews the insight offered by behavioral experiments and how these experiments refute and guide some of the various models of the brain's representation of time.
Topics: Brain; Humans; Models, Neurological; Neural Pathways; Time Perception
PubMed: 25257798
DOI: 10.1111/nyas.12545 -
Neuron Oct 2017We summarize the current state of knowledge of the brain's reading circuits, and then we describe opportunities to use quantitative and reproducible methods for... (Review)
Review
We summarize the current state of knowledge of the brain's reading circuits, and then we describe opportunities to use quantitative and reproducible methods for diagnosing these circuits. Neural circuit diagnostics-by which we mean identifying the locations and responses in an individual that differ significantly from measurements in good readers-can help parents and educators select the best remediation strategy. A sustained effort to develop and share diagnostic methods can support the societal goal of improving literacy.
Topics: Brain; Brain Mapping; Humans; Magnetic Resonance Imaging; Nerve Net; Reading; Retinal Ganglion Cells
PubMed: 29024656
DOI: 10.1016/j.neuron.2017.08.007 -
European Neuropsychopharmacology : the... Jan 2013Over the past three decades numerous imaging studies have revealed structural and functional brain abnormalities in patients with neuropsychiatric diseases. These... (Review)
Review
Over the past three decades numerous imaging studies have revealed structural and functional brain abnormalities in patients with neuropsychiatric diseases. These structural and functional brain changes are frequently found in multiple, discrete brain areas and may include frontal, temporal, parietal and occipital cortices as well as subcortical brain areas. However, while the structural and functional brain changes in patients are found in anatomically separated areas, these are connected through (long distance) fibers, together forming networks. Thus, instead of representing separate (patho)-physiological entities, these local changes in the brains of patients with psychiatric disorders may in fact represent different parts of the same 'elephant', i.e., the (altered) brain network. Recent developments in quantitative analysis of complex networks, based largely on graph theory, have revealed that the brain's structure and functions have features of complex networks. Here we briefly introduce several recent developments in neural network studies relevant for psychiatry, including from the 2013 special issue on Neural Networks in Psychiatry in European Neuropsychopharmacology. We conclude that new insights will be revealed from the neural network approaches to brain imaging in psychiatry that hold the potential to find causes for psychiatric disorders and (preventive) treatments in the future.
Topics: Brain; Genetic Predisposition to Disease; Humans; Mental Disorders; Nerve Net; Neural Pathways; Neuroimaging; Neuropsychiatry
PubMed: 23394870
DOI: 10.1016/j.euroneuro.2012.12.004 -
NeuroImage Nov 2022Most neuroimaging studies of brain function analyze data in normalized space to identify regions of common activation across participants. These studies treat... (Review)
Review
Most neuroimaging studies of brain function analyze data in normalized space to identify regions of common activation across participants. These studies treat interindividual differences in brain organization as noise, but this approach can obscure important information about the brain's functional architecture. Recently, a number of studies have adopted a person-specific approach that aims to characterize these individual differences and explore their reliability and implications for behavior. A subset of these studies has taken a precision imaging approach that collects multiple hours of data from each participant to map brain function on a finer scale. In this review, we provide a broad overview of how person-specific and precision imaging techniques have used resting-state measures to examine individual differences in the brain's organization and their impact on behavior, followed by how task-based activity continues to add detail to these discoveries. We argue that person-specific and precision approaches demonstrate substantial promise in uncovering new details of the brain's functional organization and its relationship to behavior in many areas of cognitive neuroscience. We also discuss some current limitations in this new field and some new directions it may take.
Topics: Humans; Magnetic Resonance Imaging; Connectome; Reproducibility of Results; Brain; Neuroimaging
PubMed: 36030062
DOI: 10.1016/j.neuroimage.2022.119589