**4.2 Default-mode network dysfunction in Multiple Sclerosis**

Cognitive impairment is frequently observed in MS pathology (Benedict et al., 2006; Rao et al., 1991) and fMRI activation studies in MS patients with cognitive impairment have suggested that cerebral reorganisation (Filippi & Rocca, 2004; Mainero et al., 2004) and recruitment of non impaired cortical regions may occur as a compensatory mechanism to limit the cognitive consequences of tissue damage (Filippi & Rocca, 2004; Wishart et al., 2004).

Fig. 4. ALS disease-by-age interaction in the DMN (left panel) and RFPN (right panel). Upper panels: F-map of disease by age interaction effects (P=0.05, cluster-level corrected) overlaid on the average Talairach-transformed T1 image (coronal and axial cuts). Lower panels: Regional ICA z-scores vs age in the PCC (left) and in the MFG (right).

Thereby, rs-fMRI is an attractive way to explore the spatio-temporal distribution of the spontaneous coherent fluctuations of BOLD signals within and between different regions throughout the entire human brain in different functional domains.

RS-FMRI studies have reported DMN alterations in both relapsing-remitting (RR) and progressive MS patients, when comparing MS patient groups with age and sex-matched healthy controls (Bonavita et al., 2011; Rocca et al., 2010).

The DMN connectivity distribution in RR MS patients may deviate from the control group both in the anterior node (in the ACC), that is substantially suppressed in the RR MS patient groups, and in the posterior nodes (in the PCC and, bilaterally, in the IPC), where a more distributed spatial re-organization seems to occur. Figure 5 shows a DMN comparisons map between a group of RR MS patients and a control group which clearly indicates that rs-fMRI coherent fluctuations within the DMN are reduced in RR MS patients close to the midline, both in the ACC and in the PCC, but also that, RR MS patients exhibit spots of more

Neuronal Networks Observed with Resting State

Functional Magnetic Resonance Imaging in Clinical Populations 119

with relatively fewer connections. Actually, there is evidence from histopathological studies that the cingulate gyrus shows a higher prevalence of cortical demyelinated lesions than other areas (Bo et al., 2003; Kutzelnigg & Lassmann, 2006) and therefore it is likely that these regions

Fig. 6. Comparison between a group of RR MS patients and healthy controls (HCs). The clusters of significant differential activity are displayed as reconstructed as 3D volumes.

Fig. 7. Comparison between the separate groups of cognitive preserved (CP) (left) and cognitive impaired (CI) (right) RR MS patients and healthy controls (HC). The clusters of

significant activity are displayed reconstructed as 3D volumes.

are intrinsically more vulnerable and more directly involved by the disease.

coherent fluctuations far from the midline, at the periphery of the PCC and toward the parieto-occipital regions of the DMN.

Fig. 5. Comparison between a group of RR MS patients and healthy controls (HCs). The clusters of significant differential activity are overlaid on two orthogonal slices of the averaged normalized anatomy.

A better display of the differences in the DMN functional connectivity distribution between the RR-MS and control groups is visible in figure 6, where all clusters with statistically significant differential effects are reconstructed as 3D volumes with separate colours in relation to the sign of the differences.

The comparison between RR-MS patients and normal controls becomes certainly more interesting if cognitive impaired (CI) and cognitive preserved (CP) subgroups are separately compared. Figure 7 shows this comparison and the 3D maps suggest that, while the suppression of the ACC node is a common aspect to both CI and CP RR MS patients, the reorganization of the functional connectivity in the posterior DMN can be different depending on the cognitive impairment of RR MS patients.

In summary, RR MS patients, regardless of their cognitive status exhibit a weaker DMN connectivity at the level of the ACC and the central/midline region of the PCC, together with an expanded connectivity at the level of the peripheral portions of the PCC and bilateral IPC. However, distribution changes in the posterior DMN appear with different lay outs in CI and CP patients and may thus be associated with the cognitive status of RRMS patients.

As for the other MS forms, progressive MS patients also exhibit reduced DMN connectivity, but mainly in the anterior part of the DMN (Rocca et al., 2011), where as clinically isolated syndrome (CIS) suggestive of MS seem to have increased DMN connectivity in the PCC node when compared to RR MS patients (Roosendaal et al., 2010), thus suggesting that the possible compensatory mechanism observed in the posterior DMN might be visible quite early in the disease course.

With respect to the selective involvement of the ACC in MS, one should consider that the ACC has extensive associative connections with other areas (Paus, 2001). Thereby, if cortico-cortical functional connectivity reduction is the result of axonal transection by white matter lesions, then highly connected (and distant) regions like ACC should be more vulnerable than regions

coherent fluctuations far from the midline, at the periphery of the PCC and toward the

Fig. 5. Comparison between a group of RR MS patients and healthy controls (HCs). The clusters of significant differential activity are overlaid on two orthogonal slices of the

A better display of the differences in the DMN functional connectivity distribution between the RR-MS and control groups is visible in figure 6, where all clusters with statistically significant differential effects are reconstructed as 3D volumes with separate colours in

The comparison between RR-MS patients and normal controls becomes certainly more interesting if cognitive impaired (CI) and cognitive preserved (CP) subgroups are separately compared. Figure 7 shows this comparison and the 3D maps suggest that, while the suppression of the ACC node is a common aspect to both CI and CP RR MS patients, the reorganization of the functional connectivity in the posterior DMN can be different depending

In summary, RR MS patients, regardless of their cognitive status exhibit a weaker DMN connectivity at the level of the ACC and the central/midline region of the PCC, together with an expanded connectivity at the level of the peripheral portions of the PCC and bilateral IPC. However, distribution changes in the posterior DMN appear with different lay outs in CI and

As for the other MS forms, progressive MS patients also exhibit reduced DMN connectivity, but mainly in the anterior part of the DMN (Rocca et al., 2011), where as clinically isolated syndrome (CIS) suggestive of MS seem to have increased DMN connectivity in the PCC node when compared to RR MS patients (Roosendaal et al., 2010), thus suggesting that the possible compensatory mechanism observed in the posterior DMN might be visible quite

With respect to the selective involvement of the ACC in MS, one should consider that the ACC has extensive associative connections with other areas (Paus, 2001). Thereby, if cortico-cortical functional connectivity reduction is the result of axonal transection by white matter lesions, then highly connected (and distant) regions like ACC should be more vulnerable than regions

CP patients and may thus be associated with the cognitive status of RRMS patients.

parieto-occipital regions of the DMN.

averaged normalized anatomy.

early in the disease course.

relation to the sign of the differences.

on the cognitive impairment of RR MS patients.

with relatively fewer connections. Actually, there is evidence from histopathological studies that the cingulate gyrus shows a higher prevalence of cortical demyelinated lesions than other areas (Bo et al., 2003; Kutzelnigg & Lassmann, 2006) and therefore it is likely that these regions are intrinsically more vulnerable and more directly involved by the disease.

Fig. 6. Comparison between a group of RR MS patients and healthy controls (HCs). The clusters of significant differential activity are displayed as reconstructed as 3D volumes.

Fig. 7. Comparison between the separate groups of cognitive preserved (CP) (left) and cognitive impaired (CI) (right) RR MS patients and healthy controls (HC). The clusters of significant activity are displayed reconstructed as 3D volumes.

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### **5. Conclusion**

The present chapter has highlighted the importance of observing RSN in clinical populations in relation to both physiological and pathological factors and the potential impact of rs-fMRI as a non-invasive technique to explore whole-brain functional connectivity in neurological diseases for which the biological mechanisms are not completely understood. Particularly, since rs-fMRI does not require patient interaction, it will be possible to apply the present functional neuroimaging methodology to patients at highly advanced stages of the disease and eventually allow for longitudinal investigations.

Besides potentially shedding light on the pathological mechanisms occurring in certain neurological disorders, the clinical applications may also favor a better understanding of RSN functional connectivity in the context of brain neurophysiology, especially when the rsfMRI patterns are carefully examined in relation to physiological and anatomical factors and to the possible interaction between these and the temporal course of a disease.

#### **6. References**


Van den Heuvel et al. (van den Heuvel et al., 2008) have investigated the structural connection of the DMN by combining diffusion tensor imaging and rs-fMRI data and found that the microstructural organization of the interconnecting cingulum tract, as measured by fractional anisotropy, is directly associated with the level of functional connectivity of the DMN, in particular the cingulum tract is confirmed to interconnect the PCC to the ACC of the DMN. This direct anatomical connection reflects a vast number of axonal connections between the posterior node/PCC and anterior node/ACC, responsible for the facilitation of neuronal communication between these regions. The cingulum tract is a thin white matter association bundle that is located just above and all along the corpus callosum, therefore it is expected to be frequently involved by WM lesions of MS. Thereby, if white matter MS plaques significantly contribute in determining the disconnection phenomena observed between the PCC and the ACC with the net functional loss of the ACC in the DMN of RRMS subjects, it is likely that DMN distribution changes in the posterior node represent a

The present chapter has highlighted the importance of observing RSN in clinical populations in relation to both physiological and pathological factors and the potential impact of rs-fMRI as a non-invasive technique to explore whole-brain functional connectivity in neurological diseases for which the biological mechanisms are not completely understood. Particularly, since rs-fMRI does not require patient interaction, it will be possible to apply the present functional neuroimaging methodology to patients at highly advanced stages of the disease and eventually allow for longitudinal investigations. Besides potentially shedding light on the pathological mechanisms occurring in certain neurological disorders, the clinical applications may also favor a better understanding of RSN functional connectivity in the context of brain neurophysiology, especially when the rsfMRI patterns are carefully examined in relation to physiological and anatomical factors and

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**7** 

*Chiba University* 

*Japan* 

**Resting State Blood Flow and Glucose** 

Nobuhisa Kanahara, Eiji Shimizu, Yoshimoto Sekine and Masaomi Iyo

Over the last 20 years, SPECT and PET, along with CT and MRI have been the main methodologies used in studies investigating psychiatric disorders. The structural alterations in patients' brains found by CT and MRI are usually quite subtle, while those found by the nuclear imaging modalities (PET and SPECT) are more pronounced. Partly for this reason, the latter methods have led to discoveries in a wide range of psychiatric disorders. In the 90s, region of interest (ROI) method provided only sketchy results due to the low spatial resolution of the nuclear imaging, but rapid progression in analytic and statistical methods in the 2000s had led to more detailed and accurate determinations of the differences in regional cerebral blood flow (rCBF) and glucose metabolic ratios (rGMR) between patients and comparison subjects. On the other hand, whereas an improved understanding of the etiology of psychiatric disorders has led to significant progress in multiple research areas, SPECT and PET studies measuring only the rCBF/rGMR distribution at rest have come to face some limitations for elucidation of the disease pathophysiology. Accordingly, at resting studies using SPECT/PET have tended to focus on certain kinds of clinical information, such as symptomatology and treatment. This review summarizes the history of at rest SPECT and PET studies, and provides a comprehensive survey in psychiatric disorders including schizophrenia, major depressive disorder, bipolar disorder and obsessive-

Functional neuroimaging has been used to elucidate patterns of increased or decreased activity within the brains of schizophrenic and normal subjects during rest and various assigned tasks, revealing that the affected parts of the central nervous system are not contained within a single brain region, but rather lie within neural networks over several brain regions. Numerous structural brain researches studies employing CT and MRI have demonstrated significant volume reductions in key brain regions such as the lateral prefrontal cortex, anterior cingulate cortex (ACC), superior temporal cortex, hippocampus/parahippocampus, striatum and thalamus in patients with schizophrenia relative to normal subjects (Shenton et al., 2001). In support of these structural alterations, functional neuroimaging studies have produced representations of abnormalities in and across these regions. Taking these results together, a variety of symptoms, including

**1. Introduction** 

compulsive disorder.

**2. Schizophrenia** 

**Metabolism in Psychiatric Disorders** 

