The approximately 50 Brodmann areas depicting histologically based different areas were reported over 100 years ago by the anatomist Korbinian Brodmann in 1909, and these are still used extensively today. More recently, newer functional neuroimaging capabil
ities by DTI and functional MRI intrinsic connectivity network analysis has allowed the delineation of four principal intrinsic connectivity networks by independent component analysis. These included the default mode network, salience network, dorsal attention network, and motor network [2]. In an ambitious study of 1000 healthy young adults, Yeo et al. assessed the human cortical networks by intrinsic functional connectivity MRI (fcMRI) for the purposes of providing contemporary reference maps. Spatial measure
ment applications may be performed by using DTI which measures diffusion of water with noninvasive mapping of white matter tracts, and fcMRI, which measures intrinsic functional correlations among the various brain regions. A seven network system was derived from these measurements, which included sensory visual and somatomotor cortices. The associated cortical networks included the dorsal attention, ventral attention, frontoparietal, limbic, and default mode networks. A 17 network classification was also reported that was derived by separating the basic seven networks into smaller subnet
works. These measurements have revealed that secondary and tertiary association cor
tices comprise the vast majority of the human cerebral cortex of multiple functionally coupled networks [3]. An even more ambitious project has redefined the brain map from 52 Brodmann areas to 360 areas [4].
The ground zero of human functional connectivity expansion appears to be in the mid
line. The most impactful lesions on brain connectivity have been recorded when medially placed cerebral lesions occur that affect the temporoparietal junction (BA 5 and 7) and the prefrontal cortex and frontal eye field areas (BA 46 and 8). Using diffusion imaging noninvasive mapping of highly connected networks, a densely connected structural core of the human brain emerged, with critical components being the posterior medial cortex
139 Mapping Brain Connectivity
and parietal cortical regions. There are links from there through a multitude of connector hubs that are linked with frontal and temporal cortices, which are regarded as playing a crucial role in integrating cerebral information processes. Using six different network measures, Hagmann et al. were able to identify eight different anatomical subregions that composed the structural core network. These were the cuneus, precuneus, the paracentral lobe, superior temporal sulci, cingulate isthmus, superior parietal cortex, and inferior parietal cortex in both hemispheres [5]. This correlates with evidence of the precuneus, in particular, having the highest energy consumption of any part of the cortex [6]. This core region probably represents the substrate for influencing other large scale cerebral networks and integrating these with many other networks [7,8] (Figure 8.1).
Network Imaging by Intrinsic Functional Connectivity
Network imaging by intrinsic functional connectivity is able to decipher objective abnor
mality in most neurological diseases. In many neurological diseases, normal structural MRI brain imaging frequently confounds the diagnostic process. Newer MRI based net
work imaging has had a number of significant impacts. So far evidence for improved diagnosis, early diagnosis, and more sensitive diagnoses have been reported for traumatic brain injury (TBI), multiple sclerosis, depression, Alzheimer’s disease, Parkinson’s dis
ease, frontotemporal lobe dementia, and migraine. Management may also be improved and be more accurate in understanding network analyses, which has been helpful in providing critical information for epilepsy surgery, for example [9]. The importance of detecting these network changes lies in the supposition that these may be the most sensi
tive and earliest surrogate markers for recovery. A new understanding of the connectome is that the network dysfunction also affects the intact, non lesioned hemisphere. Already,
Figure 8.1 A densely connected structural core of highly connected networks in the human brain. The highest “network score” was recorded for the posterior cingulate, precuneus, cingulate isthmus, and paracentral lobules in both hemispheres. Left, anterior posterior; right, sagittal depiction.
Source: Hagmann P, Cammoun L, Gigandet X, et al. Mapping the structural core of human cerebral cortex.
PLoS Biol 2008;6(7):e159. https://doi.org//10.1371/journal.pbio.0060159 Reproduced under the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/
rodent data have demonstrated an increase in the “small worldness” of a sensory network within three days post stroke, becoming normal at about two months [1]. These obser
vations have prompted the concept of an additional subtype of diaschisis, connectomal diaschisis. The small world impairment has also been seen clinically in TBI patients [10].
In Parkinson’s disease two different dynamic functional connectivity patterns were iden
tified that correlated with disease severity [11].
Interactions between Complex Networks and the Brain
Many other very complex networks interact with the brain networks. The various “omics,”
including genomics, proteinomics, lipidomics, epileptomics, as well as matrisomes and microbiomes, are immensely complex systems that interact with the human con
nectome [12].
Following the era of genomics, then proteomics, more recently the era of lipidomics has yielded many critical insights for the study of the lipidome, lipid messengers such as prostaglandins and in the understanding of signaling between neurons, astrocytes, oligo
dendrocytes, and microglia. The retina and brain have the highest concentrations of DHA of any tissue, and it is especially abundant in photoreceptors and synapses. DHA is a key component in mechanisms providing neuroprotection, anti inflammatory effects, vision, and memory processing. These critical processes have given rise to the concept of DHA signalolipidomics, which relates synaptic functions and neuroprotection (via NPD1) and neurotrophin agonists [13–15].
For example, cerebral small vessel disease (SVD) is the most proximate, responsible mechanism in 25–30 percent of people with stroke and the number one cause of decline and disability among the adult population. Cerebral SVD is due to a complex interaction of environmental and genetic factors. Matrisome refers to the aggregate of proteins that constitute the extracellular matrix (ECM). This comprises a complexity of cross linked proteins whose functions include binding to cell surfaces via adhesion receptors by pro
teins such as integrins and the regulation of various growth and cellular secretory factors.
The matrisome of the cerebral blood vessels includes the basement membrane, a critical interface structure between the brain and the microvasculature. Derangements of this part of the matrisome are now considered a major cause of SVD, both acquired and familial.
The latter includes inherited conditions such as CADASIL, CARASIL, HANAC, COL4A1, and COL4A2. As the major proportion of matrisome protein is expressed in the endothe
lial basement membrane, which also interacts with pericytes and astrocytes, it occupies a strategic position as part of the neuro gliovascular unit [16]. It comes as no surprise, therefore, that vascular dysregulation precedes that of A beta deposition in dementias such as Alzheimer’s disease, ascribed to impaired clearance as opposed to an A Beta over
production. Vascular dysregulation has been touted as the causal role for Alzheimer’s dis
ease since 1900, in contradistinction to the amyloid hypothesis. Also, an age dependent BBB (blood–brain barrier) breakdown with misfolded protein deposition and related tox
icity with increased permeability correlates with clinical cognitive dysfunction [17].
Microbiome Insights
Our bodies and our resident microbes work together, both in sickness and in health. The extensive host microbiome interaction within our bodies occurs at the genomic, intra
cellular, intercellular, and cerebral network levels. Our gut–brain axis has an epigenetic