**4. Resting state networks in clinical populations**

The observational study of RSN functional connectivity in normal and clinical populations allows generating a comprehensive picture of brain functions and dysfunctions by the sole analysis of resting state fMRI activity, i. e. without relying on an active performance or engagement of the patient. This aspect is particularly attractive when studying uncooperative populations, but is generally suited to all cases where behaviors and performances are pathologically impaired. For this reason many research groups have studied RSN functional connectivity in different neurological and psychiatry disorders, detected differences between patients and controls and correlated these measures to clinical variables.

The largest numbers of studies and the most consistent results have been obtained for disorders like Alzheimer disease (AD) (Greicius et al., 2004; Petrella et al., 2011; Rombouts et al., 2005; Sorg et al., 2007; Supekar et al., 2008; Wang et al., 2007; Wang et al., 2006; Zhang et al., 2010; Zhang et al., 2009) and schizophrenia (Bates et al., 2009; Bluhm et al., 2007; Foucher et al., 2005; Greicius, 2008; Hoptman et al., 2010; Jang et al., 2011; Lagioia et al., 2010; Lynall et al., 2010; Mannell et al., ; Ongur et al., 2010; Repovs et al., 2011; Rotarska-Jagiela et al., 2010; Shen et al., ; Skudlarski et al., ; van den Heuvel & Hulshoff Pol, ; Woodward et al., 2011; Zhou et al., 2008). In this chapter, we present two examples of clinical RSN study, applied to ALS and MS.

#### **4.1 Resting state networks in Amyotrophic Lateral Sclerosis**

ALS is a chronic progressive disease that predominantly affects the motor system (Turner et al., 2009b), but neurodegeneration may also extend beyond motor areas (Geser et al., 2008; Geser et al., 2009; Murphy et al., 2007; Turner et al., 2009a). In fact, ALS patients often exhibit variable degrees of cognitive impairment with rather typical involvement of frontal executive functions (Grossman et al., 2008; Murphy et al., 2007). Thereby, studying the SMN, but also the DMN and the FPN, is crucially important to elucidate both motor and extramotor involvement in ALS, to examine the possible interaction between physiologically sensitive and disease modified rs-fMRI parameters and to compare these functional measures with the clinical and MRI structural aspects of the neurodegenerative process.

The fact that rs-fMRI allows exploring whole-brain functional connectivity in all these RSNs with minimal bias towards a specific motor or cognitive function is particularly attractive for studying ALS patients, whose degree of cooperation normally introduces substantial variability in their performances.

The rs-FMRI fluctuations within the SMN network are reduced or even suppressed in ALS patients compared to age- and sex-matched normal controls (Mohammadi et al., 2009; Tedeschi et al., 2010). For instance, comparing the SMN maps on a voxel by voxel basis has shown statistically significant group differences bilaterally in the primary motor cortex (PMC) (figure 2).

ALS has long been characterized as a neurodegenerative disorder affecting the motor system, therefore, the observation that the coherent RS-fMRI fluctuations within the SMN

2001a; Zuo et al., 2010) are based on temporal concatenation and assume "common" ICA maps for all subjects in the first level analysis. A population analysis is then performed retrospectively determining the individual ICA components from the group ICA components. Thereby, all these methods implicitly assume that a given component is really

The observational study of RSN functional connectivity in normal and clinical populations allows generating a comprehensive picture of brain functions and dysfunctions by the sole analysis of resting state fMRI activity, i. e. without relying on an active performance or engagement of the patient. This aspect is particularly attractive when studying uncooperative populations, but is generally suited to all cases where behaviors and performances are pathologically impaired. For this reason many research groups have studied RSN functional connectivity in different neurological and psychiatry disorders, detected differences between

The largest numbers of studies and the most consistent results have been obtained for disorders like Alzheimer disease (AD) (Greicius et al., 2004; Petrella et al., 2011; Rombouts et al., 2005; Sorg et al., 2007; Supekar et al., 2008; Wang et al., 2007; Wang et al., 2006; Zhang et al., 2010; Zhang et al., 2009) and schizophrenia (Bates et al., 2009; Bluhm et al., 2007; Foucher et al., 2005; Greicius, 2008; Hoptman et al., 2010; Jang et al., 2011; Lagioia et al., 2010; Lynall et al., 2010; Mannell et al., ; Ongur et al., 2010; Repovs et al., 2011; Rotarska-Jagiela et al., 2010; Shen et al., ; Skudlarski et al., ; van den Heuvel & Hulshoff Pol, ; Woodward et al., 2011; Zhou et al., 2008). In this chapter, we present two examples of clinical RSN study,

ALS is a chronic progressive disease that predominantly affects the motor system (Turner et al., 2009b), but neurodegeneration may also extend beyond motor areas (Geser et al., 2008; Geser et al., 2009; Murphy et al., 2007; Turner et al., 2009a). In fact, ALS patients often exhibit variable degrees of cognitive impairment with rather typical involvement of frontal executive functions (Grossman et al., 2008; Murphy et al., 2007). Thereby, studying the SMN, but also the DMN and the FPN, is crucially important to elucidate both motor and extramotor involvement in ALS, to examine the possible interaction between physiologically sensitive and disease modified rs-fMRI parameters and to compare these functional measures with the clinical and MRI structural aspects of the neurodegenerative process. The fact that rs-fMRI allows exploring whole-brain functional connectivity in all these RSNs with minimal bias towards a specific motor or cognitive function is particularly attractive for studying ALS patients, whose degree of cooperation normally introduces substantial

The rs-FMRI fluctuations within the SMN network are reduced or even suppressed in ALS patients compared to age- and sex-matched normal controls (Mohammadi et al., 2009; Tedeschi et al., 2010). For instance, comparing the SMN maps on a voxel by voxel basis has shown statistically significant group differences bilaterally in the primary motor cortex

ALS has long been characterized as a neurodegenerative disorder affecting the motor system, therefore, the observation that the coherent RS-fMRI fluctuations within the SMN

present with exactly the same layout in all the subjects.

applied to ALS and MS.

variability in their performances.

(PMC) (figure 2).

**4. Resting state networks in clinical populations** 

patients and controls and correlated these measures to clinical variables.

**4.1 Resting state networks in Amyotrophic Lateral Sclerosis** 

are strongly reduced can be easily linked to most existing animal models of ALS explaining motor neuron degeneration both at the cellular and molecular levels (Dal Canto et al., 1995; Wong et al., 1995; Wils et al., 2010).

Fig. 2. ALS disease effects in the SMN. Upper panel: F-map of statistically significant disease effects within the SMN network (P=0.05, cluster-level corrected) overlaid on the average Talairach-transformed T1 image (coronal and axial cuts). Lower panel: Scatter plots of the regional ICA z-scores vs age in the R-PMC (left) and in the L-PMC (right). PMC = primary motor cortex. ALS = amyotrophic lateral sclerosis patients. CTL = control subjects.

The RFPN network is also partially suppressed in ALS patients. Figure 3 shows the localization of two regions within this network, in the superior frontal gyrus (SFG) and in the supra-marginal gyrus (SMG), where the network-specific RS-fMRI fluctuations resulted suppressed in ALS compared to controls. These effects in a cognitive executive network like the RFPN likely reflect a rather typical frontal cortex dysfunction observed in ALS patients (Abrahams et al., 1996; Hatazawa et al., 1988; Rule et al., 2010; Vercelletto et al., 1999).

Observing RSNs in ALS patients over an extended range of age has highlighted the possible interaction between aging and neurodegeneration (Tedeschi et al., 2010). Previous work has reported a significant effect of aging on DMN regions in the normal population (Esposito et al., 2008; Grady et al., 2006; Greicius et al., 2004; Koch et al., 2009; Persson et al., 2007). In ALS patients, the DMN network has shown an age-by-disease interaction effect in the PCC (figure 4), with the strength of the RS-fMRI fluctuations relatively increased rather than reduced with increasing age (and disease duration). In addition, there was also a group-byage interaction effect in RFPN, and more precisely the middle frontal gyrus (MFG) (figure

Neuronal Networks Observed with Resting State

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

consequences of tissue damage (Filippi & Rocca, 2004; Wishart et al., 2004).

Functional Magnetic Resonance Imaging in Clinical Populations 117

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

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

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

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

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

panels: Regional ICA z-scores vs age in the PCC (left) and in the MFG (right).

throughout the entire human brain in different functional domains.

healthy controls (Bonavita et al., 2011; Rocca et al., 2010).

4), further reflecting a possible attempt of the ALS brain to compensate the motor neuron degeneration by reorganizing the functional connectivity in cognitive networks within unaffected (or less affected) domains.

Fig. 3. ALS disease effects in the RFPN network. Upper panel: F-map of statistically significant disease effects within the R-FPN network (P=0.05, cluster-level corrected) overlaid on the average Talairach-transformed T1 image (two right sagittal cuts and one axial cut). Lower panel: Scatter plot of the regional ICA z-scores vs age in the SMG (left) and in the SFG (right). SMG = supramarginal gyrus. SFG = superior frontal gyrus. ALS = amyotrophic lateral sclerosis patients. CTL = control subjects.

This age compensatory effect on the functional connectivity can also be linked to biological processes of neuronal aging and degeneration. In fact, a few studies based on animal and cellular models of ALS pathophysiology (see, e. g., (Madeo et al., 2009)) have linked neurodegeneration and aging to specific strategies of neuroprotection by which the cell damage is contrasted with adaptive mechanisms against the physiological stress implied by aging. Thereby, these interaction patterns might represent the functional expression of the interaction between a widespread brain neurodegeneration and a physiological mechanism activated by aging. Particularly, the observed positive correlation between aging and spontaneous functional connectivity might be the result of a specific change in the default system to counteract the physiologically driven decline with age, given that ALS patients continuously alert the default system for performing any task potentially requested and made possible by the residual motor capabilities.

4), further reflecting a possible attempt of the ALS brain to compensate the motor neuron degeneration by reorganizing the functional connectivity in cognitive networks within

Fig. 3. ALS disease effects in the RFPN network. Upper panel: F-map of statistically significant disease effects within the R-FPN network (P=0.05, cluster-level corrected) overlaid on the average Talairach-transformed T1 image (two right sagittal cuts and one axial cut). Lower panel: Scatter plot of the regional ICA z-scores vs age in the SMG (left) and

in the SFG (right). SMG = supramarginal gyrus. SFG = superior frontal gyrus. ALS =

This age compensatory effect on the functional connectivity can also be linked to biological processes of neuronal aging and degeneration. In fact, a few studies based on animal and cellular models of ALS pathophysiology (see, e. g., (Madeo et al., 2009)) have linked neurodegeneration and aging to specific strategies of neuroprotection by which the cell damage is contrasted with adaptive mechanisms against the physiological stress implied by aging. Thereby, these interaction patterns might represent the functional expression of the interaction between a widespread brain neurodegeneration and a physiological mechanism activated by aging. Particularly, the observed positive correlation between aging and spontaneous functional connectivity might be the result of a specific change in the default system to counteract the physiologically driven decline with age, given that ALS patients continuously alert the default system for performing any task potentially requested and

amyotrophic lateral sclerosis patients. CTL = control subjects.

made possible by the residual motor capabilities.

unaffected (or less affected) domains.
