**1. Introduction**

Parkinson's disease (PD) is the second commonest neurodegenerative disease affecting both motor and non-motor domains [1]. It affects 1 to 2% of persons over the age of 60 years [2]. At present, no treatment is available to stop or slow down disease progression. However, currently available therapies can offer symptomatic relief to the patients [1]. In general, with the use of oral dopaminergic treatment, their symptoms can be controlled for a few years after symptom onset before developing motor and non-motor complications [1, 3]. Device-aided therapies, especially deep brain stimulation (DBS), have been used in the management of advanced PD when oral pharmacological treatment is no longer sufficient to control the symptoms or when the patients cannot tolerate the drugs [4–9].

The success of DBS surgery depends on appropriate candidate selection, accuracy of localization of electrodes and optimal DBS programming and medication titration [10, 11]. Okun et al. reported that 46% of patients with referred DBS failure were found to have suboptimal lead placement. Among these patients with lead misplacement, 52% improved with lead replacement [10]. This highlights the importance of precise electrode localization in DBS surgery.

Historically, subthalamic nucleus (STN) and globus pallidus internus (GPi) are common surgical targets in PD patients undergoing DBS surgery [12–18]. Although neurostimulation at these surgical targets can improve motor function and may lead to a reduction in dopaminergic medication dosage, a few issues have been reported with the implantation of neurostimulators at STN and GPi. First, these surgical targets such as STN, though small, were found to be divided into functional subzones [19–21]. Therefore, even with precise electrode localization, patients undergoing DBS surgeries can develop neuropsychiatric complications. Lambert et al. showed that the STN was divided into 3 functional subzones (anterior: "limbic" subzone; middle: "associative" subzone; posterior: "motor" subzone) with the use of diffusion weighted imaging (DWI) [19]. Ewert et al. revealed that the GPi can divided into 7 subzones (motor, premotor, sensory, prefrontal, posterior parietal, temporal and occipital), of which motor, premotor and sensory subzones are grouped together as the sensorimotor functional zone and lie in the posterior third of the GPi [21]. Second, these surgical targets are small and close to other salient anatomical structures in the brain. Let us take the STN as an example. The STN is small (12 × 5 × 3 mm3 ) and lies next to structures such as internal capsule, medial lemniscus, corticospinal tract, and red nucleus. With suboptimal electrode placement or overstimulation, electrical current can be spread to these adjacent structures, resulting in side effects (**Table 1**) [22]. Third, even though STN and GPi are known to be effective targets in relieving PD symptoms, different symptom may have small difference in the site for effective neurostimulation [23]. On the contrary, lesions from different brain locations can result in similar symptoms [24]. Therefore, PD DBS surgeries at these conventional surgical targets, even if the localization is accurate, can vary in treatment response. Furthermore, a PD patient may have more than one symptom, either motor or non-motor symptom, and so neurostimulation at one surgical target may not be sufficient to alleviate his symptoms.


#### **Table 1.**

*Side effects of STN / GPi DBS with respect to the anatomy of the surgical targets [22].*

*Perspective Chapter: Functional Human Brain Connectome in Deep Brain Stimulation (DBS)… DOI: http://dx.doi.org/10.5772/intechopen.109855*

To better control symptoms with DBS surgery, researchers have explored the possibility of better localizing the sites responsible for patients' symptoms and linking these sites together to form a circuit or network. It has been postulated that if a circuit connecting these sites can be mapped out for each patient individually, stimulating the circuit, instead of the traditional way of stimulating the anatomical structure, may be a better therapeutic option.

In this review, we will discuss


## **2. The concept of human connectome**

According to the classical teaching, localization of lesions in the nervous system accounts for most of the neurological features. In reality, we found that this approach has some limitations. First, lesion-based localization approach is occasionally unclear. Lesions causing the same symptom can occur in various parts in the brain, whereas one cerebral lesion can result in different neurological symptoms. As a result, the relationship between neurological symptoms and lesion location is not often straightforward [25–27]. Second, it is not uncommon to have patients with complex neurological and psychiatric symptoms unable to find obvious cerebral lesions from neuroimaging [27]. Therefore, it has been speculated that these neurological symptoms, instead of resulting from overt lesions in the nervous system, may be caused by disruption of anatomical and functional networks created by interacting neural elements, which are at a more microscopic level.

To study the human brain network, we have to understand the concept of human connectome. The human connectome is defined as "a comprehensive structural description of the network and connections forming the human brain" [25, 26]. In general, the term "connectome" has three major components.

First, the connectome is a description of structures and studies the set of physical links between neural elements. To examine the connections between neural elements, we need to look at both *structural* and *functional connectivity*.

*Structural connectivity* offers a consistent anatomical description of structural connections within the nervous system. At the micro- and meso-scales, structural connectivity reveals synaptic coupling between cells or long-distance axonal projections between neuronal populations [28, 29]. On the other hand, at the macroscale, structural connectivity points to large, myelinated white matter fiber bundles, which can be visualized with diffusion-weighted MRI data using the tractography software packages [30, 31].

As for *functional connectivity*, it means correlations in activation among spatially distinct brain regions, either in a resting state or with external stimuli, and can be measured as the bivariate correlation of their activities when using functional MRI data [26, 32–34].

Second, the connectome is merely a description of brain connectivity across multiple spatial scales. However, it does not offer all the information of cells and synapses at the microscale level [26].

Thirdly and most importantly, the concept of the connectome is that it is a description of a neural network [26]. With the use of mathematical and statistical approaches, the connectome is an object that fits within a larger theoretical framework, thereby linking neuroscience to network science and complex systems [26].
