ORIGINAL RESEARCH published: 17 January 2020 doi: 10.3389/fnins.2019.01440 Differential tDCS and tACS Effects on Working Memory-Related Neural Activity and Resting-State Connectivity Kilian Abellaneda-Pérez 1,2 , Lídia Vaqué-Alcázar 1,2 , Ruben Perellón-Alfonso 1,2 , Núria Bargalló 3,4 , Min-Fang Kuo 5 , Alvaro Pascual-Leone 6,7,8 , Michael A. Nitsche 5,9 and David Bartrés-Faz 1,2,8* 1 Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain, 2 Institute of Biomedical Research August Pi i Sunyer, Barcelona, Spain, 3 Hospital Clínic de Barcelona, Magnetic Resonance Image Core Facility, Institute of Biomedical Research August Pi i Sunyer, Barcelona, Spain, 4 Hospital Clínic de Barcelona, Neuroradiology Section, Radiology Service, Centre de Diagnòstic per la Imatge, Barcelona, Spain, 5 Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany, 6 Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, United States, 7 Department of Neurology, Harvard Medical School, Boston, MA, United States, 8 Guttmann Brain Health Institute, Institut Universitari de Neurorehabilitació Guttmann, Autonomous University of Barcelona, Bellaterra, Spain, 9 Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany Edited by: Transcranial direct and alternating current stimulation (tDCS and tACS, respectively) Oscar Arias-Carrión, entail capability to modulate human brain dynamics and cognition. However, the Hospital General Dr. Manuel Gea Gonzalez, Mexico comparability of these approaches at the level of large-scale functional networks has Reviewed by: not been thoroughly investigated. In this study, 44 subjects were randomly assigned to Silmar Teixeira, receive sham (N = 15), tDCS (N = 15), or tACS (N = 14). The first electrode (anode in Federal University of Piauí, Brazil Daniel Keeser, tDCS) was positioned over the left dorsolateral prefrontal cortex, the target area, and Ludwig Maximilian University the second electrode (cathode in tDCS) was placed over the right supraorbital region. of Munich, Germany tDCS was delivered with a constant current of 2 mA. tACS was fixed to 2 mA peak-to- *Correspondence: peak with 6 Hz frequency. Stimulation was applied concurrently with functional magnetic David Bartrés-Faz dbartres@ub.edu resonance imaging (fMRI) acquisitions, both at rest and during the performance of a verbal working memory (WM) task. After stimulation, subjects repeated the fMRI Specialty section: This article was submitted to WM task. Our results indicated that at rest, tDCS increased functional connectivity Brain Imaging Methods, particularly within the default-mode network (DMN), while tACS decreased it. When a section of the journal comparing both fMRI WM tasks, it was observed that tDCS displayed decreased brain Frontiers in Neuroscience activity post-stimulation as compared to online. Conversely, tACS effects were driven Received: 13 September 2019 Accepted: 20 December 2019 by neural increases online as compared to post-stimulation. Interestingly, both effects Published: 17 January 2020 primarily occurred within DMN-related areas. Regarding the differences in each fMRI Citation: WM task, during the online fMRI WM task, tACS engaged distributed neural resources Abellaneda-Pérez K, Vaqué-Alcázar L, Perellón-Alfonso R, which did not overlap with the WM-dependent activity pattern, but with some posterior Bargalló N, Kuo M-F, DMN regions. In contrast, during the post-stimulation fMRI WM task, tDCS strengthened Pascual-Leone A, Nitsche MA and prefrontal DMN deactivations, being these activity reductions associated with faster Bartrés-Faz D (2020) Differential tDCS and tACS Effects on Working responses. Furthermore, it was observed that tDCS neural responses presented certain Memory-Related Neural Activity consistency across distinct fMRI modalities, while tACS did not. In sum, tDCS and tACS and Resting-State Connectivity. Front. Neurosci. 13:1440. modulate fMRI-derived network dynamics differently. However, both effects seem to doi: 10.3389/fnins.2019.01440 focus on DMN regions and the WM network-DMN shift, which are highly affected in Frontiers in Neuroscience | www.frontiersin.org 1 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI aging and disease. Thus, albeit exploratory and needing further replication with larger samples, our results might provide a refined understanding of how the DMN functioning can be externally modulated through commonly used non-invasive brain stimulation techniques, which may be of eventual clinical relevance. Keywords: transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), resting-state functional magnetic resonance imaging (rs-fMRI), task-based functional magnetic resonance imaging (tb-fMRI), working memory (WM) INTRODUCTION Hoy et al., 2015; Alekseichuk et al., 2016; Dedoncker et al., 2016). Nevertheless, and despite this promising developments, Working memory (WM) provides temporary storage and data is still inconclusive, particularly in healthy populations manipulation of information required for a variety of complex (Tremblay et al., 2014; Hsu et al., 2015; Nilsson et al., 2015; cognitive tasks (Baddeley, 1992, 2010). WM capacity plays a Mancuso et al., 2016; Hill et al., 2017; Medina and Cason, 2017; central role in daily life activities and is predictive for a wide- Imburgio and Orr, 2018). range of higher-level cognitive measures (Johnson et al., 2013; Among tES techniques, transcranial direct current stimulation Unsworth et al., 2014). Impairments in WM entail functionally (tDCS) and transcranial alternating current stimulation (tACS) disabling symptoms in advanced age (Park et al., 2002; Park are the most commonly used (Polanía et al., 2018). tDCS delivers and Reuter-Lorenz, 2009; Anderson and Craik, 2017) and weak tonic currents to the scalp. During tDCS, neural membrane in several neuropsychiatric conditions (Lee and Park, 2005; potentials are depolarized under the anode, leading to an increase Nakao et al., 2009). in cortical excitability, while neural membrane hyperpolarization The WM network (WMN) includes a fronto-parietal loop develops under the cathode, thereby diminishing cortical (Owen et al., 2005), where the dorsolateral prefrontal cortex excitability (Purpura and McMurtry, 1965; Nitsche and Paulus, (dlPFC) is of particular relevance (Curtis and D’Esposito, 2003; 2000; Nitsche et al., 2008). On the other hand, tACS applies a Barbey et al., 2013). This fronto-parietal circuit shows a negative sinusoidal current to the scalp at specific frequencies, exerting an correlation with the default-mode network (DMN; Fox et al., exogenous modulation of ongoing brain oscillations (Zaghi et al., 2005; Buckner et al., 2008; Raichle, 2015). The DMN has 2010a; Ali et al., 2013; Antal and Paulus, 2013; Herrmann et al., been shown to be consistently activated during rest, while 2013; Reato et al., 2013; Antal and Herrmann, 2016; Moisa et al., its nodes are inhibited during externally oriented tasks (Fox 2016). Beyond their immediate impact, both techniques display et al., 2005; Pfefferbaum et al., 2011). Thus, the brain may after-effects that can outlast the period of stimulation, probably shift between two modes of information processing, one that due to their capability to induce neuroplasticity-like processes puts the attentional focus on external stimuli and another one (Nitsche and Paulus, 2001; Liebetanz et al., 2002; Nitsche et al., that relates to internally directed processing (Buckner et al., 2003; Monte-Silva et al., 2013; Vossen et al., 2015; Kasten et al., 2008). At the electrophysiological level, it has been shown that 2016; Wischnewski et al., 2019). WM processes are mediated by synchronous firing of neural In this context, only two studies have explored the differential populations at distinct frequencies as well as via cross-frequency impact of tDCS and tACS on WM performance (Hoy et al., 2015; coupling (Sarnthein et al., 1998; Howard et al., 2003; Sauseng Röhner et al., 2018), indicating a more relevant effect of tACS et al., 2005; Jensen and Colgin, 2007; Lisman and Jensen, 2013; as compared to tDCS. However, the physiological underpinnings Roux and Uhlhaas, 2014). A large body of literature indicates of those protocols over large-scale neural systems supporting the that the coupling of theta and gamma oscillations mediates WM function remain understudied. Further, to our knowledge, communication within and between brain networks in general a direct comparison of the effects of these different stimulation and during WM tasks in particular, possibly accounting for WM protocols at the functional magnetic resonance imaging (fMRI)- processing and capacity demands (for a review see Lisman and derived network level has not been so far investigated. Since Jensen, 2013; Hanslmayr et al., 2019). aging and various neuropsychiatric disorders show alterations in Despite the fact that neuroimaging and neurophysiological WM circuits and may benefit from their modulation, a better investigations have been providing relevant data on the insight on tES impact on the brain’s WMN and its linked anatomo-functional correlates of WMN and its anticorrelated neural systems, such as the DMN, would likely have clinical systems (Nee et al., 2013; Roux and Uhlhaas, 2014; Eriksson translational relevance. et al., 2015; Raichle, 2015), the cognitive benefits derived from interventional approaches aimed to improve WM functioning have been limited. Notwithstanding, new methodologies, MATERIALS AND METHODS such as transcranial electrical stimulation (tES), have recently shown potential to enhance WM performance Participants by targeting its critical network hubs, such as the dlPFC Forty-four healthy young subjects [age mean ± standard (Fregni et al., 2005; Ohn et al., 2008; Zaehle et al., 2011; deviation (SD), 25.25 ± 4.22 years; age range, 19–37 years; 20 Brunoni and Vanderhasselt, 2014; Meiron and Lavidor, 2014; females; years of education mean ± SD, 21.11 ± 3.40 years; Frontiers in Neuroscience | www.frontiersin.org 2 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI 36 right-handed] naive to tES were recruited from the general the experimental session [adapted from Brunoni et al., 2011; population and provided informed consent to participate in this Figure 1C; see also Supplementary Material (SM)]. study, in accordance with the Declaration of Helsinki (1964, last revision 2013). All study procedures were approved by the Institutional Review Board (IRB 00003099). None of the Transcranial Electrical Stimulation (tES) participants reported a diagnosis of a neurological or psychiatric Parameters disorder. For all participants, MRI images were examined Stimulation was delivered using a battery-driven MRI- by a senior neuroradiologist for any clinically significant compatible DC-Stimulator Plus (neuroConn GmbH, Ilmenau, pathology (none found). Germany) and was transferred by two MRI-compatible conductive rubber electrodes (7 cm × 5 cm) positioned in a Experimental Design room adjacent to the MRI scanner. The same montage was The present study was conducted in a randomized between- used in all groups, as applied in similar recent comparative subjects placebo-controlled design. Online effects of prefrontal studies (Lang et al., 2019). According to the international 10–10 tDCS and tACS on resting-state fMRI (rs-fMRI) were assessed. system of measurement, the first electrode (anode in tDCS) Furthermore, the online and post-stimulation impact of was positioned over the F3 (l-dlPFC) and the second electrode these intervention protocols on WM-related neural activity (cathode in tDCS) was placed over the FP2 (right supraorbital and performance was explored, using a similar experimental area). This is one of the standard montages frequently employed setting as described elsewhere (i.e., Meiron and Lavidor, to stimulate the l-dlPFC (Fregni et al., 2005; Nitsche et al., 2008; 2014; Brauer et al., 2018). Participants were randomly Ohn et al., 2008), the target area. In all groups, the current was assigned to receive sham stimulation (N = 15), anodal initially increased and finally decreased in a ramp-like fashion of tDCS (N = 15) or theta tACS (N = 14; Figure 1A) over 15 s. In the sham condition, the current delivery was terminated the left dlPFC (l-dlPFC; Figure 1B; see also see section after 30 s of stimulation with no further blinding processes. In “Transcranial Electrical Stimulation (tES) Parameters”). A simple the real stimulation groups, the current was supplied during randomization procedure was used (Altman and Bland, 1999; 20 min, which covered the rs-fMRI acquisition and the first Kang et al., 2008). tb-fMRI sequence. tDCS was delivered with a constant current of First, a brief cognitive assessment was conducted to obtain an 2 mA. tACS was fixed to 2 mA peak-to-peak in a 6 Hz frequency. estimation of the intelligence quotient (IQ) of the participants, We selected 6 Hz as this frequency has been widely used in recent using the vocabulary subtest of the Wechsler Adult Intelligence tACS WM investigations (i.e., Polanía et al., 2012; Alekseichuk Scale-IV (WAIS-IV). Subsequently and within the same et al., 2016; Violante et al., 2017; Brauer et al., 2018; Röhner et al., experimental day, tES was applied inside an MRI scanner. 2018; Lang et al., 2019). All stimulation parameters adhered to Here, an rs-fMRI sequence (∼8 min) was acquired before safety criteria guidelines (Zaghi et al., 2010b; Fertonani et al., subjects underwent two sequential task-based fMRI (tb-fMRI) 2015; Bikson et al., 2016; Woods et al., 2016; Matsumoto and acquisitions while performing two identical verbal n-back tasks Ugawa, 2017; see SM for more details). (∼11 min each one; Sala-Llonch et al., 2012). The rs-fMRI and the first tb-fMRI datasets were acquired during stimulation (i.e., online fMRI n-back task) and the second tb-fMRI sequence N-Back Task after stimulation delivery was turned off (i.e., post-stimulation Subjects performed a verbal n-back task, a commonly used fMRI n-back task). A high-resolution three-dimensional (hr-3D) paradigm to investigate WM in fMRI (Owen et al., 2005). The structural image (∼8 min) was acquired at the end of the n-back task had different levels of memory load (from 1 to MRI session for co-registration purposes. A questionnaire 3 letters to be retained) and a basic level of target stimulus of tES-related adverse events was administered at the end of identification that were randomly presented during the two FIGURE 1 | Study protocol. (A) Assignment of participants to one of the experimental groups. (B) Stimulation montage for all groups, with the first electrode (anode for tDCS) centered over the F3 (in red) and the second electrode (cathode for tDCS) placed over the FP2 (in blue) in a 10–10 system map. (C) Timeline of the procedures accomplished before, during and after the tES-MRI protocol. tDCS, transcranial direct current stimulation; tACS, transcranial alternating current stimulation; tES, transcranial electrical stimulation; MRI, magnetic resonance imaging; rs-fMRI, resting-state functional MRI; hr-3D, high-resolution three-dimensional. Frontiers in Neuroscience | www.frontiersin.org 3 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI consecutive tasks achieved inside the MRI scan (Sala-Llonch et al., 2012; see SM for more information). MRI Acquisition All participants were scanned with a Siemens Magnetom Trio Tim Syngo 3 Tesla system using an 8-channel head coil at the Magnetic Resonance Image Core Facility (IDIBAPS) at the Hospital Clínic de Barcelona, Barcelona, Spain. The imaging sequences were acquired with the following parameters. First, a rs-fMRI dataset (T2∗ -weighted GE-EPI sequence; interleaved acquisition; repetition time [TR] = 2,700 ms; echo time [TE] = 30 ms; 40 slices per volume; slice thickness = 3.0 mm; interslice gap = 15%; voxel size = 3.0 mm × 3.0 mm × 3.0 mm; field of view [FOV] = 216 mm; 178 volumes) was acquired. Later, two identical fMRI n-back task datasets (T2∗ weighted EPI scans; interleaved acquisition; TR = 2,000 ms; TE = 28 ms; 34 slices per volume; slice thickness = 3.5 mm; interslice gap = 15%; voxel size = 3.5 mm × 3.5 mm × 3.5 mm; FOV = 238 mm; 336 volumes) were acquired, one during stimulation and another one after stimulation cessation. Lastly, a hr-3D structural dataset (T1-weighted magnetization-prepared rapid gradient-echo [T1-weighted MPRAGE]; sagittal plane acquisition; TR = 2,300 ms; TE = 2.98 ms; inversion time [IT] = 900 ms; slice thickness = 1.0 mm; voxel size = 1.0 mm × 1.0 mm × 1.0 mm; FOV = 256 mm; 240 FIGURE 2 | Selected networks and their respective ROIs location. slices) was acquired. (A) Cognitive networks with their corresponding ROIs in red for the DMN, in light blue for the lFPN, in dark blue for the rFPN, and in green for the ECN. (B) Control networks with their corresponding ROIs in purple for the SMN and Image Analyses in orange for the VMN. DMN, default-mode network; lFPN, left fronto-parietal The FMRIB Software Library (FSL; version 6.001 ) and the network; rFPN, right fronto-parietal network; ECN, executive-control network; Analysis of Functional NeuroImages (AFNI2 ) were used for SMN, sensorimotor network; VMN, visual-medial network. For ROI abbreviations see Table 1. preprocessing and analyzing neuroimaging data. Rs- and tb-fMRI preprocessing pipelines and head movement considerations are described in SM. 2009). Moreover, two components that do not include the Functional Connectivity Analyses l-dlPFC and are not related to cognitive processing were Resting-state functional connectivity (rs-FC) analyses were used as control networks, namely the sensorimotor and performed using a seed-to-seed approach, following previous visual-medial networks (SMN and VMN, respectively), as has procedures in our group (i.e., Abellaneda-Pérez et al., 2019). been done in previous work of our group (i.e., Peña-Gómez Firstly, the concatenated fMRI dataset containing all rs- et al., 2012). All components were identified using spatial fMRI acquisitions from the entire sample was decomposed correlations against previously defined maps (Smith et al., through independent component analysis (ICA) into 15 2009). Secondly, the main regions of interest (ROIs) were components using the Multivariate Exploratory Linear selected based on the peak voxels of each network (Figure 2 Optimized Decomposition into Independent Components and Table 1). Next, spherical seeds with a 6-mm radius were (MELODIC; version 3.15) algorithm, part of the FSL (Smith placed over the identified regions, and ROI-specific time-series et al., 2004; Beckmann et al., 2005; Jenkinson et al., 2012). from the preprocessed and regressed data were extracted. The components related to the archetypical resting-state Finally, to obtain an rs-FC measure for each seed-to-seed network, namely the DMN (Fox et al., 2005; Buckner et al., coupling in each subject, obtained ROI time-series were 2008; Raichle, 2015), along with the WM-related systems, correlated with each other within every network using Pearson’s the left and right fronto-parietal networks (lFPN and rFPN, correlation coefficients. respectively), were selected in a similar manner as described in previous reports from our group (i.e., Sala-Llonch et al., N-Back fMRI Data 2012). Furthermore, the executive-control network (ECN) Tb-fMRI data were analyzed with the FEAT-FSL software (Smith was additionally considered due to its prefrontal nodes and et al., 2004). At the first-level analysis, data were fit into a its known relevance in cognitive functions (Smith et al., general linear model (GLM) containing the task time-series with a gamma convolution of the hemodynamic response function 1 http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/ (Woolrich et al., 2001). In this GLM, four regressors and their 2 https://afni.nimh.nih.gov/ first temporal derivatives were modeled: 0-back, 1-back, 2-back, Frontiers in Neuroscience | www.frontiersin.org 4 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI TABLE 1 | Selected networks and their respective ROIs with associated and 3-back. We defined three contrasts of interest combining coordinates in the Montreal Neurological Institute (MNI) system. the distinct loads, as the difference of brain activity between 1- RSNs MNI coordinates ROI ROI back, 2-back, and 3-back and the lowest load (0-back), namely: abbreviated (1) lowest WM load: 1 > 0-back; (2) intermediate WM load: 2 > 0-back; and (3) highest WM load: 3 > 0-back. The results of X Y Z the first-level analysis were further fit into higher-level or group- DMN 0 51 −15 Medial prefrontal cortex mPFC level statistics, performed using the FMRIB’s Local Analysis of 6 −54 21 Precuneus cortex PCU Mixed Effects (FLAME; Woolrich et al., 2004). We conducted −48 −66 30 Left inferior parietal lobule lIPL GLM matrices modeling the different tES time-points (online 54 −60 27 Right inferior parietal lobule rIPL and post-stimulation) and experimental groups (sham, tDCS, −63 −9 −21 Left middle temporal gyrus lMTGa and tACS). Using this second-level GLM and the appropriate (anterior division) contrasts, we evaluated: (1) the group-mean activity maps of 60 −3 −24 Right middle temporal gyrus rMTGa the three selected contrasts of interest in the first-level analysis (anterior division) (1 > 0-back, 2 > 0-back, and 3 > 0-back), in order to explore −12 15 3 Left caudate lCa the WM-related neural patterns for each one in every tES 15 15 6 Right caudate rCa time-point; (2) the interactions between tES time-point as a −27 −36 −18 Left hippocampal formation lHF within-subject factor and group as a between-subject factor; 27 −33 −15 Right hippocampal rHF (3) the patterns of time-related change within each group, as formation pairwise paired-samples t-tests; and (4) the group differences in −45 −69 −42 Left cerebellum lCer each tES time-point separately, exploring neural changes in the 45 −69 −42 Right cerebellum rCer∗ following contrasts: tDCS vs. sham, tACS vs. sham and tDCS lFPN −51 21 21 Left inferior frontal gyrus lIFG vs. tACS, as pairwise independent-samples t-tests. These analyses −39 −60 42 Left inferior parietal lobule lIPL were performed voxel-wise and the statistical significance of −63 −39 −9 Left middle temporal gyrus lMTGp the resulting maps was set at p ≤ 0.05 and z ≥ 2.3 (cluster- (posterior division) wise corrected). −6 −39 33 Cingulate gyrus (posterior pCG division) 12 −78 −30 Right cerebellum rCer Statistical Analyses rFPN 48 33 27 Right inferior frontal gyrus rIFG Non-imaging data analyses were performed using IBM SPSS 48 −51 48 Right inferior parietal lobule rIPL (IBM, Corp., Released 2016. IBM SPSS Statistics for Windows, 63 −30 −15 Right middle temporal gyrus rMTGp (posterior division) Version 24.0. Armonk, NY, United States: IBM, Corp.) and 6 −39 36 Cingulate gyrus (posterior pCG MATLAB (Version R2019a, The MathWorks, Inc., Natick, division) MA, United States). To evaluate differences between groups −39 −69 −48 Left cerebellum lCer (sham, tDCS, and tACS) in seed-to-seed rs-FC connections, ECN 6 27 24 Cingulate gyrus (anterior aCG a one-factorial analysis of variance (ANOVA) was conducted, division) and all post hoc pairwise comparisons were subjected to −30 51 18 Left frontal pole lFP Bonferroni correction. This statistical procedure was also used 27 57 18 Right frontal pole rFP when considering tES-related adverse events. To evaluate −39 12 −6 Left insular cortex lIC differences in cognitive performance, a univariate ANOVA was 45 15 −6 Right insular cortex rIC conducted with tES time-point (online and post-stimulation) −57 −48 30 Left supramarginal gyrus lSG as a within-subject factor and group (sham, tDCS, and 63 −39 33 Right supramarginal gyrus rSG tACS) as a between-subject factor. Following this ANOVA, SMN 0 −9 51 Juxtapositional lobule cortex JLC if there were significant interactions, two pairwise analyses −18 −30 63 Left precentral gyrus lPG were conducted. First, paired-samples t-tests were conducted 21 −30 60 Right precentral gyrus rPG to assess differences in performance over time in each VMN 0 −78 18 Supracalcarine cortex SC group. Second, independent-samples t-tests were conducted −21 −87 27 Left lateral occipital cortex lLOC∗ to compare performance between groups for each tES time- 21 −87 27 Right lateral occipital cortex rLOC point separately. Further, to obtain summary statistics, we −9 −72 0 Left lingual gyrus lLG extracted the mean values of the blood oxygen level dependent 9 −72 0 Right lingual gyrus rLG∗ (BOLD) signal from the fMRI clusters derived from the significant neuroimaging results. These data were used to The asterisk (∗ ) represents those ROIs that were not identified based on the functional peak voxels but selected for anatomo-functional reasons regarding the plot the fMRI findings and to corroborate the obtained coordinates of the homologous region in the other hemisphere, being the two ROIs results. Moreover, these data were used to associate the fMRI inside the network in the most anatomically plausible position. RSNs, resting-state BOLD signal with cognitive performance estimates and rs-FC networks; DMN, default-mode network; lFPN, left fronto-parietal network; rFPN, right fronto-parietal network; ECN, executive-control network; SMN, sensorimotor data using Pearson’s correlations. All non-imaging statistical network; VMN, visual-medial network; MNI, Montreal Neurological Institute; ROI, analyses were two-tailed and α was set at 0.05 (see SM for region of interest. further details). Frontiers in Neuroscience | www.frontiersin.org 5 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI TABLE 2 | Demographics and neuropsychological data. Total Sham tDCS tACS (N = 44) (N = 15) (N = 15) (N = 14) Age 25.25 ± 4.22 25.40 ± 3.16 24.33 ± 4.12 26.07 ± 5.31 Gender 20/24 8/7 7/8 5/9 (female/male) Years of education 21.11 ± 3.40 21.00 ± 1.73 20.87 ± 4.50 21.50 ± 3.61 Laterality (right-/ 36/8 13/2 11/4 12/2 left-handed) Vocabulary 44.16 ± 4.40 43.60 ± 2.80 42.93 ± 5.86 46.07 ± 3.54 WAIS-IV Data are presented as mean ± SD for the whole sample and considering the three experimental groups. WAIS-IV, Wechsler Adult Intelligence Scale-IV; tDCS, transcranial direct current stimulation; tACS, transcranial alternating current stimulation. RESULTS FIGURE 3 | Seed-to-seed statistically significant results within the DMN (in red) and the ECN (in green) for: (A) interaction between groups, (B) Demographics and N-Back Task tDCS > sham, (C) tACS < sham, and (D) tDCS > tACS. tDCS, transcranial direct current stimulation; tACS, transcranial alternating current stimulation. Performance For ROI abbreviations see Table 1. No differences in age, gender, years of education, laterality and premorbid intelligence were found between groups (all p values > 0.05; see Table 2). Behaviorally, we did Differential Effects Across tES Time-Points not observe any significant difference in n-back task The active stimulation groups showed differential changes in performance between tES time-points and experimental brain activity between both tES time-points. No time-related groups (Supplementary Figure S1). fMRI variances were found in sham participants. Specifically, neural modulations in the tDCS group were driven by clear Effects of tDCS and tACS on rs-FC decreases in brain activity post-stimulation as compared to Rs-FC was differentially modulated with respect to the online. These modulations were noticeable in view of the slight specific tES protocol. An interaction between groups neural differences across time in the sham group within the revealed different connectivity of distinct couplings within observed significant areas. Anatomically, these changes were the DMN and the ECN. Comparing the real tES groups found in posterior midline structures during the lowest WM load with sham we observed higher rs-FC in the tDCS group and within medial frontal areas during the highest WM load and lower connectivity in the tACS group. Contrasting (Figure 4A). Conversely, tACS effects appeared to be directed by across the two real tES groups, we observed higher rs- manifest neural increases and robust lower deactivations online FC in the tDCS group as compared to the tACS group as compared to post-stimulation, in view of the minor brain (Figure 3 and Table 3). No differences between groups activity changes in the sham group across time in the detected were found for left and right FPNs. Control networks also significant regions. At the anatomical level, increased neural remained unmodified. activity was mainly evident during the intermediate WM load in the PCU, frontal and temporal regions, and the occipital lobe. Reduced deactivations were detected in the highest WM Effects of tDCS and tACS on load in the medial frontal, posterior midline structures, and the WM-Related Neural Activity left inferior parietal lobe (lIPL; Figure 4B). It is worth noticing An interaction between tES time-points and experimental groups that numerous of the detected fMRI clusters correspond to the was found in the precuneus (PCU) cortex and the posterior main nodes of the DMN (i.e., those areas entailing typical task- cingulate gyrus in the 2 > 0-back contrast (Supplementary deactivation processes). Figure S2A). Further, another interaction was observed in the lateral occipital and the angular gyrus in the 3 > 0-back contrast Differential Online Effects (Supplementary Figure S2B). The group-mean activity maps During the online fMRI n-back task performance, participants obtained from each contrast (1 > 0-back, 2 > 0-back, and 3 > 0- who received tACS exhibited larger brain activity compared to back) in the sham group (considered as the ‘reference’ WM those who received sham in the three contrasts of interest. At brain patterns) are additionally displayed in SM (Supplementary the lowest and intermediate WM loads, more brain activity Figure S3). These maps show the characteristic fronto-parietal was found bilaterally in frontal regions, within the PCU, and WM patterns and the expected task-deactivations, mainly placed in numerous widespread cortical (i.e., occipital) and subcortical within DMN-related areas, like the medial prefrontal cortex (i.e., parahippocampal) regions. For the highest WM load, greater (mPFC) and the PCU. brain activity was only found bilaterally within the frontal pole Frontiers in Neuroscience | www.frontiersin.org 6 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI TABLE 3 | Seed-to-seed connections with statistically significant interactions and subsequent significant pairwise post hoc analyses within the DMN and the ECN. RSNs Seed-to-seed coupling Interaction between groups tDCS > sham tACS < sham tDCS > tACS DMN mPFC-lIPL F = 4.510, p = 0.017 p = 0.021 − − mPFC-lCer F = 5.089, p = 0.011 − − p = 0.009 lIPL-lMTGa H = 10.960, p = 0.004 − − p = 0.003 lIPL-rMTGa F = 5.569, p = 0.007 − − p = 0.008 lIPL-lCer F = 3.525, p = 0.039 p = 0.037 − − rIPL-lMTGa H = 6.904, p = 0.032 − − p = 0.033 rIPL-rCer F = 3.352, p = 0.045 − − p = 0.043 rMTGa-rCer F = 4.495, p = 0.017 − − p = 0.020 lCa-rCer H = 13.020, p = 0.001 − p = 0.001 − lHF-rHF F = 3.371, p = 0.044 − − p = 0.046 ECN lIC-rIC H = 8.502, p = 0.014 − − p = 0.013 lIC-rSG H = 7.875, p = 0.020 − p = 0.016 – RSNs, resting-state networks; DMN, default-mode network; ECN, executive-control network; tDCS, transcranial direct current stimulation; tACS, transcranial alternating current stimulation. For ROI abbreviations see Table 1. FIGURE 4 | Comparison between the online and post-stimulation fMRI n-back tasks in each group. (A) Online vs. post-stimulation results in the tDCS group. (B) Online vs. post-stimulation results in the tACS group. Top: statistically significant fMRI activity maps on the standard MNI for each contrast of interest. Results are shown in red-yellow for higher activations (or lower deactivations) online as compared to post-stimulation. Down: plots of mean BOLD signal values at the fMRI clusters considering sham, tDCS and tACS where significant differences between both fMRI n-back tasks were found. Data are presented as mean with standard error of the mean (SEM). tDCS, transcranial direct current stimulation; tACS, transcranial alternating current stimulation; BOLD, blood oxygen level dependent. (Figure 5A). Furthermore, the tACS group exhibited larger brain in distinct cortical (i.e., frontal and parietal) and subcortical (i.e., activity in frontal areas, the PCU, and within the lIPL, when thalamic) areas. At the highest WM load, subjects who received compared to the tDCS group, in the intermediate and highest tDCS showed lower activity as compared to tACS in right frontal WM loads (Figure 5B). No significant differences were found areas only (Figure 6B). No significant differences were found when comparing tDCS with sham at this tES time-point. when comparing tACS with sham at this tES time-point. Differential Post-stimulation Effects Associations Between WM-Related During the post-stimulation fMRI n-back task performance, Neural Activity and Performance differences in brain activity between tDCS and sham were At the highest WM load, those tDCS subjects with a greater detected. Specifically, in the intermediate WM load, the reduction in brain activity post-stimulation compared to online subcallosal cortex was found to be significantly more active in the within the fMRI cluster where tDCS showed less activity than tDCS than in the sham group. For the highest WM load, more sham post-stimulation (Figure 6A, blue-light blue fMRI cluster) fMRI signal was detected in a minor area of the right post-central showed faster reaction time (RT) post-stimulation as compared gyrus in the tDCS group as compared to sham. Additionally, to online performance (r = 0.540, p = 0.038; Figure 7). for the same WM load condition, the tDCS group showed Faster responses were not associated with lower accuracy significant lower brain activity within medial frontal structures (i.e., d0 ; p > 0.05). No significant associations were detected when compared to sham (Figure 6A). When comparing tDCS vs. between brain activity and performance in the tACS group (all tACS, less brain activity was found in tDCS at the lowest WM load p values > 0.05). Frontiers in Neuroscience | www.frontiersin.org 7 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI FIGURE 5 | Online fMRI n-back task results. (A) tACS vs. sham results are shown in red-yellow. (B) tDCS vs. tACS results are shown in green. Left: statistically significant fMRI activity maps on the standard MNI for each contrast of interest and group comparison. Right: plots of mean BOLD signal values at the fMRI clusters considering sham, tDCS and tACS where significant differences between groups were found. Data are presented as mean with SEM. tACS, transcranial alternating current stimulation; tDCS, transcranial direct current stimulation; BOLD, blood oxygen level dependent. FIGURE 6 | Post-stimulation fMRI n-back task results. (A) tDCS vs. sham results are shown in red-yellow for higher activations and blue-light blue for lower activations. (B) tDCS vs. tACS results are shown in green. Left and up: statistically significant fMRI activity maps on the standard MNI for each contrast of interest and group comparison. Right and below: plots of mean BOLD signal values at the fMRI clusters considering sham, tDCS and tACS where significant differences between groups were found. Data are presented as mean with SEM. tDCS, transcranial direct current stimulation; tACS, transcranial alternating current stimulation; BOLD, blood oxygen level dependent. Frontiers in Neuroscience | www.frontiersin.org 8 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI 2015; Röhner et al., 2018). However, these studies did not explore the distinct impact of those protocols on fMRI network dynamics. Our main results showed that using our tES montage: (1) prefrontal tDCS is capable of increasing rs-FC, mainly within the DMN, while prefrontal theta tACS appears to disrupt rs- fMRI systems. (2) Comparing both fMRI WM tasks, tDCS seem to exert its neural effects through a reduction on neural activity after stimulation, whilst tACS increase neural activity during stimulation, occurring both modulations mainly within DMN areas. (3) In the online fMRI WM task, tACS induced distributed neural activity which was not accommodated within the WMN, but overlapping certain posterior DMN areas. (4) In the post-stimulation fMRI WM task, tDCS strengthened FIGURE 7 | Scatter plot showing the relationship at the highest WM load expected medial prefrontal DMN deactivations, which correlated between tDCS-induced changes in BOLD signal post-stimulation when with faster responses. (5) Lastly, we observed that tDCS showed compared to online within the fMRI cluster where tDCS showed less activity certain consistency on their neural effects across rs- and tb-fMRI, than sham after stimulation (Figure 6A, blue-light blue fMRI cluster) and RT post-stimulation as compared to online. Data are presented with z scores. which was not the case for tACS. tDCS, transcranial direct current stimulation; BOLD, blood oxygen level dependent; Diff, difference; RT, reaction time. Effects of tDCS and tACS on rs-FC We observed higher connectivity within the DMN in the tDCS group. This is in line with a previous investigation reporting tES-Related Individual Variability rs-FC increases in this system after prefrontal tDCS (Keeser Significant associations between rs-FC and brain activity were et al., 2011). This connectivity increase has been proposed to detected in the tDCS group. More precisely, those subjects of reflect augmented resources and higher readiness to facilitate the tDCS group who exhibited higher mPFC-lIPL connectivity cognition (Keeser et al., 2011). On the contrary, tACS appeared to within the DMN also showed less BOLD signal at the highest reduce DMN and ECN rs-FC. Although relevant data about the WM load in the mPFC post-stimulation (Figure 6A; blue-light tACS effects on rs-fMRI dynamics have recently been reported blue fMRI cluster; r = −0.664, p = 0.007; Figure 8A). Similarly, using distinct tES montages (i.e., Cabral-Calderin et al., 2016; those subjects in the tDCS group displaying greater lIPL-left Vosskuhl et al., 2016; Bächinger et al., 2017; Weinrich et al., cerebellum connectivity within the DMN also showed a higher 2017), prefrontal theta tACS impact on resting-state connectivity reduction in brain activity within the PCU at the lowest WM load remains largely uninvestigated. The observed reduction in rs- post-stimulation as compared to online (Figure 4A; red-yellow FC for the tACS group could be explained as a disruption fMRI cluster; r = −0.643, p = 0.010; Figure 8B). No significant of the endogenous theta rhythm of the stimulated area. The relationships were observed between rs-FC and brain activity in theta frequency band mediates long-range connections in the the tACS group (all p values > 0.05). brain through phase synchrony and cross-frequency coupling (for a review see Lisman and Jensen, 2013). Therefore, it is tES-Related Adverse Events plausible that tACS at 6 Hz introduced an exogenous rhythm An interaction between experimental groups was found as that disrupted phase synchrony on the DMN and ECN and regards tingling (H = 6.982, p = 0.030). Pairwise post hoc thus decreased rs-FC. analyses revealed more tingling estimates in the tACS group as compared to sham (p = 0.025). Another interaction was found Effects of tDCS and tACS on regarding phosphenes occurrence (χ2 = 11.360, p = 0.003). WM-Related Neural Activity Pairwise comparisons revealed a higher phosphenes occurrence Differential Effects Across tES Time-Points in the tACS group in comparison to the tDCS group (p = 0.002, Fisher’s exact test; see Supplementary Table S1). In the present investigation, tDCS effects were primarily driven by reductions in neural activity after stimulation (Figure 4A). This is in line with the notion that some of the tDCS effects might DISCUSSION take place after the cessation of stimulation rather than during stimulation, as observed in the motor cortex (Santarnecchi et al., Our study employed fMRI connectivity and activity analyses 2014). On the contrary, tACS effects appeared to be particularly to investigate, in an exploratory manner, the effects of two driven by changes during stimulation (Figure 4B). This is commonly used tES protocols over the WMN and its major coherent with the outcome obtained using a similar protocol to anticorrelated circuit, the DMN. Albeit the usage of the same ours, where a significant tACS effect on WM accuracy was only neurophysiological readout (i.e., fMRI) is a critical condition to observed online, but not post-stimulation (Meiron and Lavidor, be able to directly compare the effects of distinct stimulation 2014). At the neuroanatomical level, the effects of both tES modalities, this approach has seldom been used. To the best of protocols on fMRI brain activity were mainly observed within our knowledge, there have only been two studies that compared relevant DMN areas, such as the mPFC and the PCU, the main the effects of tDCS and tACS on WM performance (Hoy et al., hubs of this network (Buckner et al., 2008). Frontiers in Neuroscience | www.frontiersin.org 9 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI FIGURE 8 | Scatter plots showing the relationships in the tDCS group between (A) mPFC-lIPL rs-FC and post-stimulation 3 > 0-back BOLD signal (in the tDCS < sham fMRI cluster) and (B) lIPL-lCer rs-FC and 1 > 0-back difference in BOLD signal (in the post-stimulation – online fMRI cluster). Data are presented with z scores. tDCS, transcranial direct current stimulation; BOLD, blood oxygen level dependent; Diff, difference; mPFC, medial prefrontal cortex; lIPL, left inferior parietal lobule; rs-FC, resting-state functional connectivity; lCer, left cerebellum. Differential Online Effects et al., 2012). In this case, neural efficiency may be operated via In line with the abovementioned results, when exploring the the inhibition of areas that need to be suppressed instead of neural modulations for each tES time-point, tACS effects were an activity decrease in hyperactivated areas, as seen in normal revealed to be different as compared to sham only in the online and pathological aging (Meinzer et al., 2013, 2015). Thus, tDCS WM task (Figure 5A). Furthermore, neural activity changes were might be reinforcing the activation/deactivation WMN-DMN found in a cognitive load-dependent manner, were tACS engaged shift during the accomplishment of cognitive tasks, which is then distributed neural resources in low load conditions, while at the associated with better performance. highest demanding load, activity increases were only evident bifrontally. Notwithstanding, while the spatial distribution of Cognitive Performance the neuroimaging results did not completely overlap with the Despite the brain-behavioral associations previously mentioned WM-dependent neural activity pattern, it plainly did meet some (see section “Differential Post-stimulation Effects”), we were areas belonging to the DMN, such as the PCU. These tACS not able to detect any cognitive effects between tES time- effects over the DMN were even more evident compared to tDCS points and experimental groups. In this sense, although (Figure 5B), where activity modulations in other DMN core areas some studies with the same tDCS montage have reported also emerged, such as the lIPL. Altogether, prefrontal theta tACS significant improvements on WM performance both online and during stimulation seemed to disrupt the characteristic WMN- post-stimulation (Fregni et al., 2005; Ohn et al., 2008), more DMN shift during externally oriented tasks (i.e., via a poorer recent investigations have revealed that a single session of DMN suppression, particularly within its posterior nodes). prefrontal tDCS does not (or at best, modestly) induce cognitive However, since no major significant behavioral differences were improvements in WM performance in healthy subjects (Brunoni found between groups, this brain perturbation-like process (Paus, and Vanderhasselt, 2014; Nilsson et al., 2015; Mancuso et al., 2005) could have triggered compensatory overactivations in 2016; Hill et al., 2017; Medina and Cason, 2017; Imburgio widespread regions regardless the WM-related areas, probably to and Orr, 2018). This may be due to ceiling effects in healthy allow a suitable response to the cognitive load required, and thus populations (Hsu et al., 2015). Regarding the effects of our maintain cognition at an adequate level (i.e., such as the other tACS montage on cognitive performance, certain improvements experimental groups; see Supplementary Figure S1). in fluid intelligence have been previously observed (Pahor and Jaušovec, 2014), but not on WM (Jaušovec and Jaušovec, 2014). Differential Post-stimulation Effects However, using slightly different tACS montages, either targeting On the post-stimulation task, when compared to sham, we only prefrontal regions (Meiron and Lavidor, 2014; Alekseichuk detected brain activity changes in the tDCS group (Figure 6A). et al., 2016) or the fronto-parietal circuit (Polanía et al., 2012; The most noteworthy outcome was a tDCS-induced activity Violante et al., 2017), WM improvements have been reported. reduction in a typically deactivated area corresponding to the Yet, data in these regards is likewise inconsistent to date anterior DMN node, namely the mPFC, in the highest WM load. (Pahor and Jaušovec, 2018). It is worth noting that activity decreases are proportional to task difficulty (McKiernan et al., 2003). However, tDCS appeared tES-Related Individual Variability to strengthen this characteristic medial prefrontal deactivation Notable inter- and intra-individual variability has been seen in pattern. More interestingly, greater decreases in brain activity in response to distinct non-invasive brain stimulation protocols this area were correlated with shorter response times (Figure 7). (i.e., Hamada et al., 2013; López-Alonso et al., 2014; Martin- These results might be in line with the notion that tDCS increases Trias et al., 2018). More specifically, López-Alonso et al. (2014) neural efficiency on brain dynamics (Holland et al., 2011; Meinzer observed that only 45% of subjects responded as expected when Frontiers in Neuroscience | www.frontiersin.org 10 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI the motor cortex was targeted with anodal tDCS. However, DATA AVAILABILITY STATEMENT whether individual responses to different stimulation techniques are consistent across distinct fMRI modalities has not yet been The data that support the findings of this study are available from explored. Our study is the first to investigate this issue. Our the corresponding author upon reasonable request. results indicate that in the tDCS group, those subjects displaying higher rs-FC in specific couplings also exhibited greater tb-fMRI modulations (Figure 8). Therefore, subjects that received tDCS ETHICS STATEMENT seem to display consistency on their neural effects across different fMRI modalities, which seems not to be the case for tACS. The studies involving human participants were reviewed and approved by University of Barcelona’s Bioethics Commission (IRB 00003099). The patients/participants provided their written Limitations informed consent to participate in this study. This investigation presents a number of limitations. First, although comparable to previous studies employing similar designs, the sample size was relatively modest. Second, an fMRI AUTHOR CONTRIBUTIONS scan and a WM assessment at baseline (or using a cross-over design) could have permitted a more powerful analysis of the KA-P, LV-A, and DB-F designed the research and wrote neural and cognitive effects of stimulation. Notwithstanding, the manuscript. KA-P and LV-A analyzed the data. KA- to avoid practice effects, which previous WM studies have P, LV-A, RP-A, NB, M-FK, AP-L, MN, and DB-F edited suffered (i.e., Röhner et al., 2018), a between-subjects design the manuscript. was selected. Further, in our study, methodological issues related to electrodes size or location might have underlie the absence of cognitive effects (for tDCS, see Imburgio and Orr, 2018; for FUNDING tACS, see Mehta et al., 2015). Moreover, it is also worth noting that using individualized theta frequencies could have boosted This work was supported by grants from the Spanish Ministry cognitive performance in our experimental setting, although of Economy and Competitiveness (MINECO/FEDER; PSI2015- it does not guarantee any behavioral improvement by itself 64227-R) and the Spanish Ministry of Science, Innovation (Jaušovec and Jaušovec, 2014). Altogether, present data might and Universities (MICIU/FEDER; RTI2018-095181-B-C21) to provide a novel proof of concept of NIBS-fMRI effects for future DB-F, which was also supported by an ICREA Academia 2019 research in the field. However, it is relevant to consider that our grant award. KA-P was supported by a fellowship from the results should be interpreted in a cautious manner due to the Spanish Ministry of Education, Culture and Sport (MECD; stated limitations, which makes them exploratory and warranting reference number, FPU14/02728). LV-A was supported by further confirmation in larger studies. a fellowship associated with the MINECO/FEDER PSI2015- 64227-R grant (reference number, BES-2016-077620). AP-L was supported by the Sidney R. Baer Jr. Foundation, the National Institutes of Health (NIH R01 MH100186, R01 NS073601, R01 CONCLUSION HD069776, R21 MH099196, R21 NS082870, R21 NS085491, and R21 HD07616), Harvard Catalyst | The Harvard Clinical In sum, in the present investigation we have shown that and Translational Science Center (NCRR and the NCATS NIH, prefrontal tDCS and tACS appear to display different effects on UL1 RR025758), DARPA (via HR001117S0030), and the Football rs- and tb-fMRI neural dynamics. However, both particularly Players Health Study at Harvard University. The project that gave would affect DMN functioning at rest as well as during rise to these results also received the support of a fellowship WM performance. In fact, the DMN is known to be highly from “la Caixa” Foundation (ID 100010434). The fellowship susceptible to alterations by means of transcranial stimulation code is LCF/BQ/DI19/11730050. This research was furthermore (i.e., Antonenko et al., 2018). This is crucial given that this supported by the Government of Catalonia (2017SGR748). network supports basic cognitive processes (Buckner et al., 2008). In addition, it is negatively affected both by advancing age (Andrews-Hanna et al., 2007; Chen et al., 2016; Schultz et al., ACKNOWLEDGMENTS 2017; Staffaroni et al., 2018) and in distinct neuropsychiatric conditions (Beucke et al., 2014; Hu et al., 2017; Wise et al., We are indebted to the Magnetic Resonance Imaging Core 2017; Yan et al., 2019). Indeed, its capability to being deactivated Facility of the IDIBAPS for the technical help. during externally oriented tasks is a process strongly affected both in aging (Miller et al., 2008) and disease (Fryer et al., 2013). In this vein, present results, along with those of other SUPPLEMENTARY MATERIAL investigations allowing a better understanding of how the distinct DMN mechanisms -and its relationships with other systems- can The Supplementary Material for this article can be found online be extrinsically modulated might provide valuable knowledge for at: https://www.frontiersin.org/articles/10.3389/fnins.2019. future applications in both basic research and clinical care. 01440/full#supplementary-material Frontiers in Neuroscience | www.frontiersin.org 11 January 2020 | Volume 13 | Article 1440 Abellaneda-Pérez et al. tDCS vs. tACS Effects on fMRI REFERENCES Cabral-Calderin, Y., Williams, K. A., Opitz, A., Dechent, P., and Wilke, M. (2016). Transcranial alternating current stimulation modulates spontaneous Abellaneda-Pérez, K., Vaqué-Alcázar, L., Vidal-Piñeiro, D., Jannati, A., Solana, low frequency fluctuations as measured with fMRI. Neuroimage 141, 88–107. E., Bargalló, N., et al. (2019). 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No A., et al. (2017). Externally induced frontoparietal synchronization modulates use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Neuroscience | www.frontiersin.org 14 January 2020 | Volume 13 | Article 1440