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This book provides an essential overview of the broad range of functional brain imaging techniques, as well as neuroscientific methods suitable for various scientific tasks in fundamental and clinical neuroscience. It also shares information on novel methods in computational neuroscience, mathematical algorithms, image processing, and applications to neuroscience.

The mammalian brain is a huge and complex network that consists of billions of neural and glial cells. Decoding how information is represented and processed by this neural network requires the ability to monitor the dynamics of large numbers of neurons at high temporal and spatial resolution over a large part of the brain. Functional brain optical imaging has seen more than thirty years of intensive development. Current light-using methods provide good sensitivity to functional changes through intrinsic contrast and are rapidly exploiting the growing availability of exogenous fluorescence probes. In addition, various types of functional brain optical imaging are now being used to reveal the brain’s microanatomy and physiology.

Inhaltsverzeichnis

Frontmatter

Principles of Functional Brain Imaging

Frontmatter

General Descriptions on MRI

Abstract
MRI is an abbreviation for Magnetic Resonance Imaging. The magnetic resonance imaging represents measurement equipment and a method to obtain an image of magnetic resonance signals.
Hidenao Fukuyama, Tomohiro Ueno, Hector Sanchez Lopez

Neurons and Plasticity: What Do Glial Cells Have to Do with This?

Abstract
It has long been the view that the neurons in the brain are responsible for its ability to process information from external cues and adapt accordingly. The key to this is the brain’s ability to change its internal structure in an activity-dependent manner over several timescales. Synapses are the key sites where changes, both structurally ad functionally, such take place. The neurons in the mammalian brain, however, only make up half the number of cells. The remaining cells are collectively called glial cells, a family of cells that are comprised of astrocytes, oligodendrocytes, ependymal cells and radial glia. Historically, these cells were believed to only support the maintenance and wellbeing of neurons, playing no role in information processing, however, over the last twenty years there is mounting evidence illustrating that this is not the case. Currently, experiments have shown that glial cells are directly involved in transmission and modulation of neurotransmitters, synaptic plasticity and have also been implicated in brain disorders, such as epilepsy. To this end, the traditional picture of a synapse being composed of a pre-synaptic terminal, a small extracellular gap and a post-synaptic spine needs revision to include both glial cell and extracellular matrix components. To this end, computational investigations of neural-glial signaling and their impact on synaptic plasticity and spiking neural network dynamics has been sorely lacking. It is the authors’ aspiration that this will inspire future researcher to investigate the complex interactions between neurons and glial cells.
Nicolangelo Iannella, Michel Condemine

Molecular Brain Imaging

Frontmatter

Transcranial Dynamic Fluorescence Imaging for the Study of the Epileptic Seizures

Abstract
In last decade functional brain mapping has made significant strides through development of advanced methods, culminating into revolutionary diagnostic imaging and therapeutic applications of neurophotonics. Imaging technologies include intrinsic optical imaging, voltage-sensitive dye, photoacoustic, optical coherence tomography, multi-spectral imaging, UV, yellow light, thermal and near-infrared spectroscopy. Some of these technologies are not only used in animal studies of the model of epileptic seizures but also been in clinical trials. However, translation of such basic science application of brain mapping technologies into clinical setting remains challenging. In this paper we review current advances in the field, along with one clear focus on laser speckle contrast imaging and its application in epilepsy. Our conclusion is that functional brain optical imaging could play a key role in bridging between morphology and functional activity of the brain, and thus contribute to more accurate diagnostics and improved efficacy of the therapy. Coupling brain optical imaging with measurements of disease biomarkers and adding as well as other neuroscience techniques is making early diagnosis more effective and applicable for variable clinical tasks.
Vyacheslav Kalchenko, Alon Harmelin, David Israeli, Babak Kateb, Igor Meglinski, Qinggong Tang, Nitish V. Thakor, Alla Ignashchenkova, Anna Volnova, Vassiliy Tsytsarev

Critical Elements for Connectivity Analysis of Brain Networks

Abstract
In recent years, new and important perspectives were introduced in the field of neuroimaging with the emergence of the connectionist approach [136]. In this new context, it is important to know not only which brain areas are activated by a particular stimulus but, mainly, how these areas are structurally and functionally connected, distributed, and organized in relation to other areas. In addition, the arrangement of the network elements, i.e., its topology, and the dynamics they give rise to are also important. This new approach is called connectomics [15]. It brings together a series of techniques and methodologies capable of systematizing, from the different types of signals and images of the nervous system, how neuronal units to brain areas are connected. Through this approach, the different patterns of connectivity can be graphically and mathematically represented by the so-called connectomes [115].
Jean Faber, Priscila C. Antoneli, Noemi S. Araújo, Daniel J. L. L. Pinheiro, Esper Cavalheiro

Brain Optical Imaging

Frontmatter

Intrinsic Signal Optical Imaging (ISOI): State-of-the-Art with Emphasis on Pre-clinical and Clinical Studies

Abstract
Intrinsic signal optical imaging (ISOI) remains one of the most exciting functional imaging techniques for functional mapping. It is routinely employed for basic research and has also been slowly adopted in recent years in preclinical and clinical research.
Ron D. Frostig

Implantable CMOS Fluorescent Imaging Devices

Abstract
Optical techniques are one of the most useful methods for elucidating how the brain works. In particular, by using a potential-sensitive dye [1] or a calcium probe, potential changes in cell membrane or Ca2+ ion concentration associated with neural activities can be converted to fluorescence intensity. Visualizing neural activity by combining these and microscopic techniques is widely used in recent neurosciences.
Kiyotaka Sasagawa, Makito Haruta, Yasumi Ohta, Hironari Takehara, Takashi Tokuda, Jun Ohta

Neural Computation and Data Analysis

Frontmatter

Data Analysis Method for Neuroimaging Data: Task-Related Component Analysis and Its Applications to fNIRS Data

Abstract
Experimental results should guarantee their reproducibility for the objective nature of science. Neuroimaging data, however, often contain artifactual components that are not pertinent directly to neural activations in question, thereby impeding the reproducibility of experimental results. Signal processing or data analysis methods play a crucial role in removing such artifactual components and extracting relevant neural activations. We here provide a concise overview of data analysis methods with an emphasis on functional near-infrared spectroscopy (fNIRS) and discuss their advantages and disadvantages. Then our analysis method, task-related component analysis (TRCA), that maximizes the block-by-block reproducibility of a signal in one condition is proposed. TRCA is formulated as a generalized eigenvalue problem and is extended to several useful forms including an online recursive algorithm and one that takes channel-by-channel delays into account. Finally extensive applications of TRCA to synthetic data and fNIRS data of a finger-tapping task and a working-memory task are presented. Although originally motivated for fNIRS data analysis, the concept of signal reproducibility has a broad implication and we expect that TRCA has a wide range of applications in biophysical data analysis.
Hirokazu Tanaka, Takusige Katura, Hiroki Sato

Towards Automated Processing and Analysis of Neuronal Big Data Acquired Using High-Resolution Brain-Chip Interfaces

Abstract
Innovation of neurotechnological tools during the last two decades, especially in the realm of micro-and-nano-machined devices, has allowed the neuroscientific community to study the brain with neuronal probes having thousands of recording sites integrated at very high spatial resolution. The capability of these next generation probes is not only limited to simultaneous recording from a large number of channels, but also to provide activity dependent stimulation. Given that the parallel recording of signals at multiple scales generates a huge amount of data, to intelligently mine these data and decode brain functions, diagnose diseases, and devise treatments is one of the biggest challenges the community is currently facing. Responding to that challenge, many automated and intelligent tools have been reported for the processing and analysis of this gigantic amount of data. Taking this into consideration, this chapter lays out an overview of different generations of high-resolution neural probes capable of providing high spatio-temporal electrical imaging of neuronal population activities; and a number of possible methods to automatically analyse the recorded signals.
Mufti Mahmud, Claudia Cecchetto, Marta Maschietto, Roland Thewes, Stefano Vassanelli

Conclusion and Future Work

Frontmatter

Conclusion and Future Work

Abstract
All achievements of mankind in science, art and technology exist thanks to the mind container which is the brain. All products of our civilization are adapted and limited by physiological properties of the brain. The brain is able to receive only certain types of information, process it only in limited volume and with limited velocity, but in the world we live in with all of our scientific and technological advances in the modern neurobiology, we are still limited in our understanding of how the brain works in normal and pathological mode.
Vassiliy Tsytsarev
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