Overview of Visualization in Biology and Medicine - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 202

of biological and medical research. This underlines the high practical relevance of
the on-going quest in visualization to find the optimal tool for human insight. Even
as various issues become solved problems, further developments in technology and
new questions posed by researchers require an unceasing and continuous spectrum
of research in the fields of data acquisition, management, analysis, and visualization
in order to achieve further insight.
Chapter 21 provides a general overview of the emerging field of connectomics .
Connectomics is a branch of neuroscience that attempts to create a connectome ,
that is, a complete map of the neuronal system and all connections between neu-
ronal structures. Such a holistic representation can then be used to understand how
functional brain states emerge from their underlying anatomical structures and how
dysfunction and neuronal diseases arise.
The notion of brain connectivity by itself is not straightforward. In fact, different
types of connectivity can be distinguished at different spatial scales. Structural or
anatomical connectivity usually refers to the physical connections between neural
elements. Functional connectivity refers to the temporal correlation between spa-
tially remote neurophysiological events; it does not necessarily imply an anatomical
connection. Finally, effective connectivity concerns causal interactions between dis-
tinct unitswithin a nervous system. One can also differentiate betweenmacro-, meso-,
and microscale connectomes. At the macroscale , a whole brain can be divided into
anatomically distinct areas with specific patterns of connectivity. One order of mag-
nitude smaller is the mesoscale connectome that describes local neuronal circuits,
such as, cortical columns. At the finest microscale , the connectome involves mapping
single neuronal cells and their connectivity patterns. Ultimately, connectomes from
all scales should be merged into one hierarchical representation.
Since the field of connectomics is to a large extent based on image data, visual-
ization is an important task for the analysis of brain structures and their functional
connections. Therefore, this chapter reviews the current state-of-the-art of visualiza-
tion and image processing techniques in the field of connectomics and associated
challenges. This chapter first presents some biological background into the con-
cepts of neural systems and model systems. Relevant imaging modalities are also
introduced, including electroencephalography, magnetoencephalography, magnetic
resonance imaging, positron emission tomography, and diffusion-weighted imag-
ing. Then, current techniques to extract connectivity information from the image
data at the macro-, meso-, and microscale are reviewed. Based on this extraction,
integration of the data for the important topics of brain mapping and neural network
modeling by reverse engineering are discussed. Lastly, techniques for visual analysis,
measurements, and comparative visualization are discussed.
Chapter 22 concerns visualization in biology. Similar to Chap. 21 , the notion of
scale is very important. Basic biological research spans a huge range of scales, from
the genome level up to the cellular and population level. Advances in high-throughput
measuring devices such as genome sequencers and the public availability of large
amounts of data have fundamentally changed the way that biologists conduct
research. Access to this data has made visualization a key component in almost
every biological discovery workflow.