Age-dependent effects of brain stimulation on network centrality
Introduction
Non-invasive brain stimulation techniques constitute promising approaches to investigate the relationship between brain structure and function and to develop cognitive enhancement strategies (Fertonani and Miniussi, 2016; Kuo and Nitsche, 2012; Nitsche et al., 2015). Importantly, such techniques have been discussed as a potential intervention to counteract age-related cognitive decline and reduced neural efficacy (Mameli et al., 2014; Perceval et al., 2016).
Here, transcranial direct current stimulation (tDCS) has proven to be the most feasible method, because of its relative low costs, few contraindications and adverse effects and its simplicity for concurrent application during task execution (Polania et al., 2018; Woods et al., 2016). When applied concurrent to cognitive training over multiple days, tDCS has been found to induce sustained performance improvement of trained and untrained functions (Antonenko et al., 2018; Berryhill, 2017; Kuo and Nitsche, 2012). In addition to its additive effect on training interventions, there is a large number of studies using single session tDCS to establish brain-behavior relationships and study underlying neural effects (Perceval et al., 2016; Polania et al., 2018). At the neural level, acute tDCS effects are modulation of cortical excitability by de- or hyperpolarizing resting membrane potentials (Nitsche and Paulus, 2000; Polania et al., 2018). Applied over a longer time interval, tDCS effects have been suggested to include synaptic mechanisms leading to long-term potentiation- (LTP) and depression-like plasticity (Monte-Silva et al., 2013; Nitsche and Paulus, 2001; Stagg and Nitsche, 2011). In particular, LTP-like effects induced by anodal tDCS can extend to interconnected brain areas, exerting network-based neurophysiological modulation that is evident during current application and can last up to an hour after the stimulation ends (Polania et al., 2018; Sehm et al., 2012; Stagg and Nitsche, 2011). Importantly, magnitude and direction of neurophysiological and behavioral effects of tDCS may not only depend on external methodological factors (e.g., stimulation parameters including electrode montage, current strength and stimulation duration), but also on inter-individual (e.g., genotype, baseline performance and education) and intra-individual factors (e.g., brain state) (Krause and Cohen Kadosh, 2014; Polania et al., 2018; Stephens et al., 2017).
In order to investigate effects on neural processing, brain stimulation can be combined with brain imaging techniques (for an overview, see Bergmann et al., 2016; Siebner et al., 2009). These include electroencephalography, magnetoencephalography, functional near-infrared spectroscopy and functional magnetic resonance imaging (fMRI) – each having its advantages, limits and technical challenges regarding the temporal and spatial resolution with which they can map certain neural patterns (Bolognini and Miniussi, 2016; Jones et al., 2015; Miniussi et al., 2012). The main advantage of fMRI over other techniques is that it can provide whole-brain information of stimulation effects on both local activity and large scale functional network with high spatial and sufficient temporal resolution (Antal et al., 2011; Johnstone et al., 2016; Siebner et al., 2009; Woods et al., 2016).
Using fMRI assessment, several studies have described tDCS-induced modulations of functional brain networks comprising effects in areas proximal and distant to the stimulation electrodes using both task-dependent and resting-state fMRI assessments in young adults (Bachtiar et al., 2015; Lindenberg et al., 2016; Martin et al., 2017; Meinzer et al., 2012; Sehm et al., 2012). Investigations of tDCS-induced functional modulation in older adults are scarce but essential, given differential effects in young versus older cohorts due to prominent age-related reorganization (cf. Perceval et al., 2016; Summers et al., 2016). Studies with older participants, in fact, allow to anticipate age-specific patterns of tDCS-induced modulations (Antonenko et al., 2017; Lindenberg et al., 2013). For instance, in a recent study we found that functional connectivity in the sensorimotor network is reduced due to anodal tDCS in older participants (Antonenko et al., 2017), as compared to an increase previously reported in young adults (Bachtiar et al., 2015).
Only one study to date included both older and young adults and compared the effects of tDCS on underlying functional connectivity during a semantic word generation task (Martin et al., 2017). The authors found performance improvements during tDCS administered to the left sensorimotor cortex and overlapping functional network modulations as assessed by independent component analysis during the task in both age groups. Only older adults showed increased lateralization of language related networks during anodal tDCS. Thus, tDCS resulted in partially different effects in both age groups. Effects on blood-oxygenated level-dependent (BOLD) task fMRI were related to the experimental paradigm, stimulus input and behavioral output. Here, task-independent resting-state BOLD fMRI not only offers a promising approach avoiding confounds related to the interaction of brain activity during task performance, but may also facilitate the understanding of complex network organization and stimulation-induced neuromodulation in aging (Ferreira and Busatto, 2013; Fox and Raichle, 2007).
The present study compared brain stimulation response in groups of older and young participants during task-free resting-state fMRI. Specifically, we administered anodal, cathodal and sham tDCS over the left sensorimotor cortex (SM1) with a right supraorbital (SO) reference electrode using a within-subjects design. Resting-state fMRI was acquired in all tDCS conditions during stimulation. For connectivity analysis, we chose the established graph theory-based eigenvector centrality mapping (ECM) approach, because it is purely data-driven and allows characterization of whole-brain functional connectivity without requiring a priori assumptions about anatomical or functional network organization or regions-of-interest specification (Bonacich, 2007; Lohmann et al., 2010; Nierhaus et al., 2012; Zuo et al., 2012). In addition, this approach has successfully been used to map tDCS-induced modulations of resting-state functional connectivity in several previous studies in young or older adults (Lindenberg et al., 2013, 2016; Meinzer et al., 2012, 2015; Sehm et al., 2012).
Based on substantial evidence of age-related brain network reorganization (Ferreira and Busatto, 2013; Geerligs et al., 2015; Sala-Llonch et al., 2015) and previous fMRI studies that pointed towards age group-specific patterns of neural tDCS effects on brain activity and connectivity (Lindenberg et al., 2013; Martin et al., 2017; Meinzer et al., 2012), we aimed to investigate the interaction between stimulation condition and age group. Thus, we focused on differences in whole-brain spatial distribution of tDCS-induced neural effects with the aim to explore which regions showed modulatory patterns in different directions in older and young adults. Based on available preliminary data described above, we expected differential large-scale network modulations in both age groups with inter-regional connectivity of areas surrounding the targeted sensorimotor cortex to be increased during anodal stimulation in young adults (Bachtiar et al., 2015; Lindenberg et al., 2016) and to be decreased in older adults (Antonenko et al., 2017).
Section snippets
Participants and study design
The study sample comprised sixty participants, 30 older (16 f, mean/SD age: 63/7, mean/SD education: 16/3 years) and 30 young adults (16 f, mean/SD age: 24/4, mean/SD education: 16/3 years). All were native German speakers and had no history of neurological or psychiatric disorders. Intake of medication affecting the central nervous-system was treated as an exclusion criterion. Smoking was not an exclusion criterion, but the proportion of smokers in the study sample was low (n = 2 in each age
Electric field simulations
The modeling results indicate that this conventional electrode montage induced electric fields with maximum intensity between the two electrodes, but also high intensities around the intended target area. More specifically, in both age groups, high electric field intensities occurred in the vicinity of the left-hemispheric paracentral lobe, at the precentral gyrus and central sulcus (Fig. 1A). On average, the spatial distribution of the electric field strength is highly similar between age
Discussion
The present study explored the difference in tDCS effects on functional connectivity between older and young adults. We used a counterbalanced, cross-over design with anodal, cathodal and sham stimulation targeting the sensorimotor network. Functional network analysis revealed neuromodulatory effects of tDCS in brain regions under the anode, but also distant to the stimulation site. We observed differential effects of anodal stimulation on centrality in left paracentral, right superior parietal
Conclusions
This is the first systematic investigation of age-related differences in tDCS-induced modulation of resting-state functional network connectivity. We confirm and extend previous evidence for neuromodulatory effects in the aging brain by providing a detailed picture of distinct stimulation-induced global brain network reorganization. Importantly, we observed an interaction between the effect of anodal stimulation and age group, reflecting opposite patterns of network centrality modulation in
Acknowledgements
The authors thank Semiha Aydin, Florian Bohm, and Angelica Sousa for help with data acquisition and Dr. Ulrike Grittner for statistical assistance. This work was supported by the “Bundesministerium für Bildung und Forschung” [01GQ1424A]. Conflicts of interest: none.
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2021, NeuroImageCitation Excerpt :However, anatomical variations are mostly neglected in brain stimulation research with healthy participants and patients, but can be a core factor causing the variability in empirical findings (Kim et al., 2014; Laakso et al., 2015; Liu et al., 2018). Given that age-related brain atrophy affects tissue volumes in an inter-individually variable extent (Grady, 2012; Reuter-Lorenz and Park, 2014), its effects on altered current distribution induced by brain stimulation may be particularly relevant in studies with older populations (Antonenko et al., 2018; Mahdavi et al., 2018; Thomas et al., 2017). The development of accessible computational modeling approaches has advanced the understanding of physical principles and neurophysiological effects of electrical current on the human brain (Hartwigsen et al., 2015; Peterchev, 2017; Thielscher et al., 2015).