scholarly journals Brown-Séquard: On neural networks and brain localization of functions

2014 ◽  
Vol 8 (1) ◽  
pp. 79-82
Author(s):  
Eliasz Engelhardt
Keyword(s):  
Functional Organization ◽  
Body Of Knowledge ◽  
Current State ◽  
Brain Localization ◽  
Physical Functions ◽  
Action At A Distance ◽  
The Rich ◽  
The 19Th Century ◽  
The Brain ◽  
Neuroimaging Techniques

ABSTRACT The notion that the brain (encephalon) is a network of interconnected neurons has a long and memorable history. Cytoarchitectonic and hodological studies coupled with advanced neuroimaging techniques have produced a substantial body of knowledge on structural and functional organization. Acquiring the rich knowledge held today took a long and winding journey. Important advancements were made in the 19th century, with the remarkable Brown-Séquard figuring as one of the protagonists. Regarding the brain, he proposed nine mental and physical functions (organs) related to distributed cell clusters, interconnected according to their roles, the "network of anastomosing cells", dynamically submitted to "dynamogenic and inhibitory activities", and "action at a distance" concepts, the latter also related to his notion of "recovery". It is remarkable that someone was able to propose, ahead of his time, and with the limited technical resources available, such significant concepts that paved the way for the current state of knowledge.

History of Functional Brain Imaging

2020 ◽  
Author(s):  
Michael A. Cole ◽  
Christopher N. Sozda ◽  
Mark D'Esposito
Keyword(s):  
Functional Organization ◽  
Functional Neuroimaging ◽  
Empirical Support ◽  
Normal Subjects ◽  
Functional Brain Imaging ◽  
Technological Advances ◽  
The 1960S ◽  
Effective Use ◽  
The 19Th Century ◽  
The Brain

Modern functional neuroimaging techniques can be dated to the 1960s, although humans have been trying to understand the functional organization of the brain for millennia. Precursors of modern techniques were quite crude and date roughly to the 19th century. Rapid technological advances during the end of the 20th century provided researchers with tools capable of measuring hemodynamic activity within the brain, such as changes in blood flow and metabolism, and these techniques quickly became core methodological approaches in the disciplines of cognitive and clinical neuroscience. Notably, clinicians and researchers were significantly aided in their ability to examine diffuse neural networks underlying complex cognitive functions such as working memory, learning, and attention in normal subjects and patient populations. Although the clinical application of functional neuroimaging methodologies have been limited to date, research in this area is rapidly growing and empirical support exists for effective use of techniques such as fMRI and PET, for instance, in presurgical mapping and early detection of Alzheimer’s disease.

scholarly journals Blood-Based Biomarkers: A Forgotten Friend of Hyperacute Ischemic Stroke

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhilan Liu ◽  
Cui Yang ◽  
Xiaoming Wang ◽  
Yang Xiang
Keyword(s):  
Oxidative Stress ◽  
Ischemic Stroke ◽  
Vascular Injury ◽  
Glial Activation ◽  
Future Directions ◽  
Biochemical Alterations ◽  
Current State ◽  
The Brain ◽  
Diagnostic And Prognostic Value ◽  
Neuroimaging Techniques

Ischemic stroke (IS) is the second leading cause of death worldwide. Multimodal neuroimaging techniques that have significantly facilitated the diagnosis of hyperacute IS are not widely used in underdeveloped areas and community hospitals owing to drawbacks such as high cost and lack of trained operators. Moreover, these methods do not have sufficient resolution to detect changes in the brain at the cellular and molecular levels after IS onset. In contrast, blood-based biomarkers can reflect molecular and biochemical alterations in both normal and pathophysiologic processes including angiogenesis, metabolism, inflammation, oxidative stress, coagulation, thrombosis, glial activation, and neuronal and vascular injury, and can thus provide information complementary to findings from routine examinations and neuroimaging that is useful for diagnosis. In this review, we summarize the current state of knowledge on blood-based biomarkers of hyperacute IS including those associated with neuronal injury, glial activation, inflammation and oxidative stress, vascular injury and angiogenesis, coagulation and thrombosis, and metabolism as well as genetic and genomic biomarkers. Meanwhile, the blood sampling time of the biomarkers which are cited and summarized in the review is within 6 h after the onset of IS. Additionally, we also discuss the diagnostic and prognostic value of blood-based biomarkers in stroke patients, and future directions for their clinical application and development.

scholarly journals Unraveling reproducible dynamic states of individual brain functional parcellation

2020 ◽  
pp. 1-28 ◽  
Author(s):  
Amal Boukhdhir ◽  
Yu Zhang ◽  
Max Mignotte ◽  
Pierre Bellec
Keyword(s):  
Functional Organization ◽  
Time Windows ◽  
Brain Networks ◽  
Anterior Cingulate ◽  
Fmri Data ◽  
Network Analyses ◽  
Stability Maps ◽  
The Rich ◽  
The Brain ◽  
Dynamic States

Data-driven parcellations are widely used for exploring the functional organization of the brain, and also for reducing the high dimensionality of fMRI data. Despite the flurry of methods proposed in the literature, functional brain parcellations are not highly reproducible at the level of individual subjects, even with very long acquisitions. Some brain areas are also more difficult to parcellate than others, with association heteromodal cortices being the most challenging. An important limitation of classical parcellations is that they are static, that is, they neglect dynamic reconfigurations of brain networks. In this paper, we proposed a new method to identify dynamic states of parcellations, which we hypothesized would improve reproducibility over static parcellation approaches. For a series of seed voxels in the brain, we applied a cluster analysis to regroup short (3 min) time windows into “states” with highly similar seed parcels. We splitted individual time series of the Midnight scan club sample into two independent sets of 2.5 hr (test and retest). We found that average within-state parcellations, called stability maps, were highly reproducible (over 0.9 test-retest spatial correlation in many instances) and subject specific (fingerprinting accuracy over 70% on average) between test and retest. Consistent with our hypothesis, seeds in heteromodal cortices (posterior and anterior cingulate) showed a richer repertoire of states than unimodal (visual) cortex. Taken together, our results indicate that static functional parcellations are incorrectly averaging well-defined and distinct dynamic states of brain parcellations. This work calls to revisit previous methods based on static parcellations, which includes the majority of published network analyses of fMRI data. Our method may, thus, impact how researchers model the rich interactions between brain networks in health and disease.

scholarly journals Unraveling reproducible dynamic states of individual brain functional parcellation

2020 ◽  
Author(s):  
Amal Boukhdhir ◽  
Yu Zhang ◽  
Max Mignotte ◽  
Pierre Bellec
Keyword(s):  
Functional Organization ◽  
Time Windows ◽  
Brain Networks ◽  
Anterior Cingulate ◽  
Fmri Data ◽  
Network Analyses ◽  
Stability Maps ◽  
The Rich ◽  
The Brain ◽  
Dynamic States

AbstractData-driven parcellations are widely used for exploring the functional organization of the brain, and also for reducing the high dimensionality of fMRI data. Despite the flurry of methods proposed in the literature, functional brain parcellations are not highly reproducible at the level of individual subjects, even with very long acquisitions. Some brain areas are also more difficult to parcellate than others, with association heteromodal cortices being the most challenging. An important limitation of classical parcellations is that they are static, i.e. they neglect dynamic reconfigurations of brain networks. In this paper, we proposed a new method to identify dynamic states of parcellations, which we hypothesized would improve reproducibility over static parcellation approaches. For a series of seed voxels in the brain, we applied a cluster analysis to regroup short (3 minutes) time windows into “states” with highly similar seed parcels. We splitted individual time series of the Midnight scan club sample into two independent sets of 2.5 hours (test and retest). We found that average within-state parcellations, called stability maps, were highly reproducible (over .9 test-retest spatial correlation in many instances) and subject specific (fingerprinting accuracy over 70% on average) between test and retest. Consistent with our hypothesis, seeds in heteromodal cortices (posterior and anterior cingulate) showed a richer repertoire of states than unimodal (visual) cortex. Taken together, our results indicate that static functional parcellations are incorrectly averaging well-defined and distinct dynamic states of brain parcellations. This work calls to revisit previous methods based on static parcellations, which includes the majority of published network analyses of fMRI data. Our method may, thus, impact how researchers model the rich interactions between brain networks in health and disease.

From many to one: Meditation and the plasticity of the predictive mind

2020 ◽  
Author(s):  
Ruben Laukkonen ◽  
Heleen A Slagter
Keyword(s):  
Cognitive Enhancement ◽  
The Self ◽  
Predictive Processing ◽  
Focused Attention ◽  
Conceptual Processing ◽  
Current State ◽  
Contemplative Science ◽  
Open Monitoring ◽  
Living Organisms ◽  
The Brain

How profoundly can humans change their own minds? In this paper we offer a unifying account of meditation under the predictive processing view of living organisms. We start from relatively simple axioms. First, the brain is an organ that serves to predict based on past experience, both phylogenetic and ontogenetic. Second, meditation serves to bring one closer to the here and now by disengaging from anticipatory processes. We propose that practicing meditation therefore gradually reduces predictive processing, in particular counterfactual cognition—the tendency to construct abstract and temporally deep representations—until all conceptual processing falls away. Our Many- to-One account also places three main styles of meditation (focused attention, open monitoring, and non-dual meditation) on a single continuum, where each technique progressively relinquishes increasingly engrained habits of prediction, including the self. This deconstruction can also make the above processes available to introspection, permitting certain insights into one’s mind. Our review suggests that our framework is consistent with the current state of empirical and (neuro)phenomenological evidence in contemplative science, and is ultimately illuminating about the plasticity of the predictive mind. It also serves to highlight that contemplative science can fruitfully go beyond cognitive enhancement, attention, and emotion regulation, to its more traditional goal of removing past conditioning and creating conditions for potentially profound insights. Experimental rigor, neurophenomenology, and no-report paradigms combined with neuroimaging are needed to further our understanding of how different styles of meditation affect predictive processing and the self, and the plasticity of the predictive mind more generally.

Umbral Calculus

10.37236/24 ◽  
2002 ◽  
Vol 1000 ◽  
Author(s):  
A. Di Bucchianico ◽  
D. Loeb
Keyword(s):  
19Th Century ◽  
Finite Differences ◽  
State Of The Art ◽  
Umbral Calculus ◽  
Current State ◽  
Logical Foundation ◽  
Complete Bibliography ◽  
The 19Th Century ◽  
Mathematical Literature

We survey the mathematical literature on umbral calculus (otherwise known as the calculus of finite differences) from its roots in the 19th century (and earlier) as a set of “magic rules” for lowering and raising indices, through its rebirth in the 1970’s as Rota’s school set it on a firm logical foundation using operator methods, to the current state of the art with numerous generalizations and applications. The survey itself is complemented by a fairly complete bibliography (over 500 references) which we expect to update regularly.

scholarly journals The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rossana Mastrandrea ◽  
Fabrizio Piras ◽  
Andrea Gabrielli ◽  
Nerisa Banaj ◽  
Guido Caldarelli ◽  
...  
Keyword(s):  
Resting State ◽  
Functional Organization ◽  
Functional Integration ◽  
Brain Network ◽  
Modular Organization ◽  
Node Degree ◽  
Imaging Data ◽  
Brain Disorder ◽  
Functional Connections ◽  
The Brain

AbstractNetwork neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization’s basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions.

scholarly journals The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Camille Fauchon ◽  
David Meunier ◽  
Isabelle Faillenot ◽  
Florence B Pomares ◽  
Hélène Bastuji ◽  
...  
Keyword(s):  
Information Integration ◽  
Functional Organization ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Modular Organization ◽  
Noxious Heat ◽  
Intracranial Eeg ◽  
Brain Connectome ◽  
Posterior Parietal ◽  
The Brain

Abstract Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models, remains unknown. Here, we used graph theory with modular analysis of fMRI data from 60 healthy participants experiencing noxious heat stimuli, of whom 36 also received audio stimulation. Brain connectivity during pain was organized in four modules matching those identified through iEEG, namely: 1) sensorimotor (SM), 2) medial fronto-cingulo-parietal (default mode-like), 3) posterior parietal-latero-frontal (central executive-like), and 4) amygdalo-hippocampal (limbic). Intrinsic overlaps existed between the pain and audio conditions in high-order areas, but also pain-specific higher small-worldness and connectivity within the sensorimotor module. Neocortical modules were interrelated via “connector hubs” in dorsolateral frontal, posterior parietal, and anterior insular cortices, the antero-insular connector being most predominant during pain. These findings provide a mechanistic picture of the brain networks architecture and support fractal-like similarities between the micro-and macrotemporal dynamics associated with pain. The anterior insula appears to play an essential role in information integration, possibly by determining priorities for the processing of information and subsequent entrance into other points of the brain connectome.

scholarly journals Pain Detection and the Privacy of Subjective Experience

2007 ◽  
Vol 33 (2-3) ◽  
pp. 433-456 ◽  
Author(s):  
Adam J. Kolber
Keyword(s):  
Subjective Experience ◽  
Brain Regions ◽  
Physical Pain ◽  
Medical Evidence ◽  
Functional Magnetic Resonance ◽  
Positron Emission ◽  
Pain Symptoms ◽  
The Brain ◽  
Insight Into ◽  
Neuroimaging Techniques

A neurologist with abdominal pain goes to see a gastroenterologist for treatment. The gastroenterologist asks the neurologist where it hurts. The neurologist replies, “In my head, of course.” Indeed, while we can feel pain throughout much of our bodies, pain signals undergo most of their processing in the brain. Using neuroimaging techniques like functional magnetic resonance imaging (“fMRI”) and positron emission tomography (“PET”), researchers have more precisely identified brain regions that enable us to experience physical pain. Certain regions of the brain's cortex, for example, increase in activation when subjects are exposed to painful stimuli. Furthermore, the amount of activation increases with the intensity of the painful stimulus. These findings suggest that we may be able to gain insight into the amount of pain a particular person is experiencing by non-invasively imaging his brain.Such insight could be particularly valuable in the courtroom where we often have no definitive medical evidence to prove or disprove claims about the existence and extent of pain symptoms.

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