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Brain & Heart Application of the neural networks surgery

In the 21 century, this field is commonly described
st
as the developmental consequence of three dimensions
(anatomy and cognitive discovery of the brain, medical
imaging innovations, and medical devices). The history
of neurosurgery can be divided into three stages: classical
neurosurgery, microsurgery, and minimally invasive
neurosurgery. Research on neural networks and advances
in digital stereometric brain imaging today have led to the
[1]
emergence of the field of neural networks surgery .
In the last decades, with the development and
application of advanced imaging equipment, multiple
imaging techniques, including computed tomography
(CT), magnetic resonance imaging (MRI), digital
subtraction angiography (DSA), single photon emission
computed tomography (SPECT), and positron emission Figure 1. A general map of brain networks. Human behavior requires the
tomography (PET), have made great contributions to interaction of multiple networks.
both clinical and fundamental research. Meanwhile,
a combination of techniques that reflects the cerebral
anatomical structure and the brain function has
been introduced; this new concept is known as brain
networks . Unlike the localizationist theory, which
[2]
proposes that one cortical area executes a specific function
discretely and separately, such as the Broca’s area for motor
images of speech and the Wernicke’s area for sensory
images of words, the brain network model is related to
functional segregation and integration. It implies that
a significant part of human behavior is determined by
global communication (Figure 1) [3,4] . Following extensive
research on brain networks, this complex network has
gained recognition as the physiological basis of cerebral
information management and cognitive expression. As
the potential of brain networks in maintaining cognitive Figure 2. General structure of modules and hubs in a network. The
function becomes more apparent, scientists have put internal module connections are identified in dashed circles. The degree
of nodes is reflected by their size (the number of connections that are
forward the concept of human connectome (Table 1). For maintained by a node). Provincial hubs mainly connect nodes within their
now, advanced medical techniques are used in human own module, and connector hubs are important in the interconnection of
connectome research to construct individual structural modules.
and functional connectivity (FC), and the brain, as a
complex functional system with topological feature, has Table 1. Difference between human connectome and brain
been modeled based on the network analysis method networks
and the graph theory . The topological feature of brain Human connectome Brain networks
[5]
networks is another theoretical basis for raising the concept The functional and structural The working pattern of the brain is
of neural networks surgery; the investigation of other connections of the brain. abstracted into a connection of nodes
deuterogenic discoveries, including hubs, module, and by edges.
default mode network (DMN), helps in the exploration
of network connective rules (Figure 2). Understanding study have indicated an increase in stroke-related mortality
the mechanism of lesion and plasticity plays a critical and other worldwide epidemiological metrics from 1990
role in condition assessment, prognosis prediction, and to 2019; in China, the incidence, prevalence rate, and
even cerebral function protection in surgery [3,6,7] . Patients mortality of stroke increased by 86%, 106%, and 32.3%,
with cerebrovascular disease often presents with stroke, of respectively; more importantly, the age-standardized
which 85% of stroke cases are ischemic stroke, while 15% rates decreased during this period . Related studies
[10]
are hemorrhagic . The occurrence of stroke is affected by have listed ten modifiable risk factors that have over 90%
[8]
various factors . Data from the Global Burden of Disease population-attributable stroke risk globally . Due to the
[9]
[11]
Volume 1 Issue 1 (2023) 2 https://doi.org/10.36922/bh.v1i1.223