Role of Graph Theory in Computational Neuroscience

2022 ◽  
pp. 86-97
Author(s):  
Hitesh Marwaha ◽  
Anurag Sharma ◽  
Vikrant Sharma
Keyword(s):  
Graph Theory ◽  
Human Brain ◽  
Computational Neuroscience ◽  
Cognitive Functions ◽  
Special Focus ◽  
Meaningful Information ◽  
Different Types ◽  
The Brain ◽  
Vertex Centrality

Neuroscience is the study of the brain and its impact on behavior and cognitive functions. Computational neuroscience is the subfield that deals with the study of the ability of the brain to think and compute. It also analyzes various electrical and chemical signals that take place in the brain to represent and process the information. In this chapter, a special focus will be given on the processing of signals by the brain to solve the problems. In the second section of the chapter, the role of graph theory is discussed to analyze the pattern of neurons. Graph-based analysis reveals meaningful information about the topological architecture of human brain networks. The graph-based analysis also discloses the networks in which most nodes are not neighbors of each other but can be reached from every other node by a small number of steps. In the end, it is concluded that by using the various operations of graph theory, the vertex centrality, betweenness, etc. can be computed to identify the dominant neurons for solving different types of computational problems.

scholarly journals The modular and integrative functional architecture of the human brain

2015 ◽  
Vol 112 (49) ◽  
pp. E6798-E6807 ◽  
Author(s):  
Maxwell A. Bertolero ◽  
B. T. Thomas Yeo ◽  
Mark D’Esposito
Keyword(s):  
Human Brain ◽  
Cognitive Functions ◽  
Topic Model ◽  
Brain Activity ◽  
Modular Function ◽  
Imaging Data ◽  
Functional Architecture ◽  
Brain Imaging Data ◽  
The Brain

Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules’ processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author–topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network’s modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules’ functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain’s modular yet integrated implementation of cognitive functions.

The human brain: Chairman’s introduction

1981 ◽  
Vol 292 (1057) ◽  
pp. 151-153
Keyword(s):  
Human Brain ◽  
Cultural Evolution ◽  
Positive Feedback ◽  
Time Scale ◽  
Biological Evolution ◽  
Internal Models ◽  
Adaptive Behaviour ◽  
Myelin Sheaths ◽  
The Brain

Much has been said at the symposium about the pre-eminent role of the brain in the continuing emergence of man. Tobias has spoken of its explosive enlargement during the last 1 Ma, and how much of its enlargement in individual ontogeny is postnatal. We are born before our brains are fully grown and ‘wired up ’. During our long adolescence we build up internal models of the outside world and of the relations of parts of our bodies to it and to one another. Neurons that are present at birth spread their dendrites and project axons which acquire their myelin sheaths, and establish innumerable contacts with other neurons, over the years. New connections are formed; genetically endowed ones are stamped in or blanked off. People born without arms may grow up to use their toes in skills that are normally manual. Tobias, Darlington and others have stressed the enormous survival value of adaptive behaviour and the ‘positive feedback’ relation between biological and cultural evolution. The latter, the unique product of the unprecedentedly rapid biological evolution of big brains, advances on a time scale unknown to biological evolution.

scholarly journals Low Frequency Noise Remove from EEG Signal

2020 ◽  
Vol 9 (1) ◽  
pp. 1510-1513
Keyword(s):  
Human Brain ◽  
Random Noise ◽  
Low Frequency ◽  
Frequency Noise ◽  
Eeg Signal ◽  
Low Frequency Noise ◽  
Frequency Range ◽  
Average Value ◽  
Different Types ◽  
The Brain

The electrical activity of the brain recorded by EEG which used to detect different types of diseases and disorders of the human brain. There is contained a large amount of random noise present during EEG recording, such as artifacts and baseline changes. These noises affect the low -frequency range of the EEG signal. These artifacts hiding some valuable information during analyzing of the EEG signal. In this paper we used the FIR filter for removing low -frequency noise(<1Hz) from the EEG signal. The performance is measured by calculating the SNR and the RMSE. We obtained RMSE average value from the test is 0.08 and the SNR value at frequency(<1Hz) is 0.0190.

Love, the Brain, and Becoming Human

2019 ◽  
pp. 44-71
Author(s):  
Riane Eisler
Keyword(s):  
Human Brain ◽  
Human Development ◽  
Human Evolution ◽  
Evolutionary History ◽  
Negative Effects ◽  
New Perspective ◽  
The Brain ◽  
The Continuum

This chapter introduces a new perspective on the role of love in human evolution and human development. The bonds of love, whether between parent and child, lovers, or close friends, may all have a common biological root, activating neurochemicals that make us feel good. Like other human capacities, such as consciousness, learning, and creativity, love has a long and fascinating evolutionary history. Indeed, the evolution of love appears to be integral to the development of our human brain and hence to much that distinguishes us from other species. Moreover, love plays a vital, though still largely unrecognized, role in human development, with evidence accumulating about the negative effects of love deprivation as well as the benefits of love. But whether or not our needs for meaning and love are met, and whether or not our capacities for creativity and love are expressed, are largely determined by the interaction of biology and culture—specifically, the degree to which a culture or subculture orients to the partnership or domination end of the continuum.

Is Artistic Composition in Abstract Art Detected Automatically?

2021 ◽  
pp. 102-106
Author(s):  
Claudia Menzel ◽  
Gyula Kovács ◽  
Gregor U. Hayn-Leichsenring ◽  
Christoph Redies
Keyword(s):  
Human Brain ◽  
Significant Role ◽  
Mismatch Negativity ◽  
Brain Activity ◽  
Perceptual Processing ◽  
Abstract Art ◽  
Electrical Brain Activity ◽  
Image Set ◽  
The Brain

Most artists who create abstract paintings place the pictorial elements not at random, but arrange them intentionally in a specific artistic composition. This arrangement results in a pattern of image properties that differs from image versions in which the same pictorial elements are randomly shuffled. In the article under discussion, the original abstract paintings of the author’s image set were rated as more ordered and harmonious but less interesting than their shuffled counterparts. The authors tested whether the human brain distinguishes between these original and shuffled images by recording electrical brain activity in a particular paradigm that evokes a so-called visual mismatch negativity. The results revealed that the brain detects the differences between the two types of images fast and automatically. These findings are in line with models that postulate a significant role of early (low-level) perceptual processing of formal image properties in aesthetic evaluations.

Is the human brain only responsive?

1995 ◽  
Vol 18 (2) ◽  
pp. 365-366
Author(s):  
Rumyana Kristeva-Feige ◽  
Bernd Feige
Keyword(s):  
Human Brain ◽  
Spontaneous Activity ◽  
Cognitive Functions ◽  
Evoked Potential ◽  
Imaging Techniques ◽  
Brain Activity ◽  
External Events ◽  
Potential Methods ◽  
The Brain

AbstractPosner & Raichle's (1994) book is a fascinating and readable account of the studies the authors have conducted on the localization of cognitive functions in the brain mainly using PET and EEC evoked potential methods. Our criticism concerns the underrepresentation of some imaging techniques (magnetoencephalography) and some forms of brain activity (spontaneous activity). Furthermore, the book leaves the reader with the impression that the brain only responds to external events.

scholarly journals Facephenes and rainbows: Causal evidence for functional and anatomical specificity of face and color processing in the human brain

2017 ◽  
Vol 114 (46) ◽  
pp. 12285-12290 ◽  
Author(s):  
Gerwin Schalk ◽  
Christoph Kapeller ◽  
Christoph Guger ◽  
Hiroshi Ogawa ◽  
Satoru Hiroshima ◽  
...  
Keyword(s):  
Human Brain ◽  
Mental Process ◽  
Color Processing ◽  
Face Area ◽  
Neurosurgical Patient ◽  
Patient Reported ◽  
Stimulus Classes ◽  
Cortical Regions ◽  
The Brain

Neuroscientists have long debated whether some regions of the human brain are exclusively engaged in a single specific mental process. Consistent with this view, fMRI has revealed cortical regions that respond selectively to certain stimulus classes such as faces. However, results from multivoxel pattern analyses (MVPA) challenge this view by demonstrating that category-selective regions often contain information about “nonpreferred” stimulus dimensions. But is this nonpreferred information causally relevant to behavior? Here we report a rare opportunity to test this question in a neurosurgical patient implanted for clinical reasons with strips of electrodes along his fusiform gyri. Broadband gamma electrocorticographic responses in multiple adjacent electrodes showed strong selectivity for faces in a region corresponding to the fusiform face area (FFA), and preferential responses to color in a nearby site, replicating earlier reports. To test the causal role of these regions in the perception of nonpreferred dimensions, we then electrically stimulated individual sites while the patient viewed various objects. When stimulated in the FFA, the patient reported seeing an illusory face (or “facephene”), independent of the object viewed. Similarly, stimulation of color-preferring sites produced illusory “rainbows.” Crucially, the patient reported no change in the object viewed, apart from the facephenes and rainbows apparently superimposed on them. The functional and anatomical specificity of these effects indicate that some cortical regions are exclusively causally engaged in a single specific mental process, and prompt caution about the widespread assumption that any information scientists can decode from the brain is causally relevant to behavior.

scholarly journals Dissociated Expression of Mitochondrial and Cytosolic Creatine Kinases in the Human Brain: A New Perspective on the Role of Creatine in Brain Energy Metabolism

2013 ◽  
Vol 33 (8) ◽  
pp. 1295-1306 ◽  
Author(s):  
Matthew TJ Lowe ◽  
Eric H Kim ◽  
Richard LM Faull ◽  
David L Christie ◽  
Henry J Waldvogel
Keyword(s):  
Energy Metabolism ◽  
Human Brain ◽  
High Energy ◽  
Cellular Energy ◽  
Neuronal Populations ◽  
Neurologic Function ◽  
New Perspective ◽  
The Brain ◽  
Brain Energy

The phosphocreatine/creatine kinase (PCr/CK) system in the brain is defined by the expression of two CK isozymes: the cytosolic brain-type CK (BCK) and the ubiquitous mitochondrial CK (uMtCK). The system plays an important role in supporting cellular energy metabolism by buffering adenosine triphosphate (ATP) consumption and improving the flux of high-energy phosphoryls around the cell. This system is well defined in muscle tissue, but there have been few detailed studies of this system in the brain, especially in humans. Creatine is known to be important for neurologic function, and its loss from the brain during development can lead to mental retardation. This study provides the first detailed immunohistochemical study of the expression pattern of BCK and uMtCK in the human brain. A strikingly dissociated pattern of expression was found: uMtCK was found to be ubiquitously and exclusively expressed in neuronal populations, whereas BCK was dominantly expressed in astrocytes, with a low and selective expression in neurons. This pattern indicates that the two CK isozymes are not widely coexpressed in the human brain, but rather are selectively expressed depending on the cell type. These results suggest that the brain cells may use only certain properties of the PCr/CK system depending on their energetic requirements.

Tractography of White Matter Fibers Using Diffusion MRI

2022 ◽  
pp. 98-112
Author(s):  
Strivathsav Ashwin Ramamoorthy
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Diffusion Mri ◽  
Neural Circuits ◽  
Water Molecules ◽  
Neural Connectivity ◽  
Non Invasive ◽  
Diffusion Weighted Images ◽  
Different Types ◽  
The Brain

To understand more about the human brain and how it works, it is vital to understand how the neural circuits connect different regions of the brain. The human brain is filled predominantly with water and the majority of the water molecules undergo diffusion which can be captured with the help of diffusion MRI. Diffusion weighted images enable us to reconstruct the neural circuits in a non-invasive manner, and this procedure is referred to as tractography. Tractography aids neurosurgeons to understand the neural connectivity of the patient. This chapter attempts to explain the procedure of tractography and different types of algorithms.

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