ORIGINAL RESEARCH published: 10 February 2022 doi: 10.3389/fpsyg.2022.813444 Local Prefrontal Cortex TMS-Induced Reactivity Is Related to Working Memory and Reasoning in Middle-Aged Adults María Redondo-Camós 1,2,3 , Gabriele Cattaneo 1,2,3 , Ruben Perellón-Alfonso 4,5 , Vanessa Alviarez-Schulze 1,2,3,6 , Timothy P. Morris 7 , Javier Solana-Sanchez 1,2,3 , Goretti España-Irla 1,2,3 , Selma Delgado-Gallén 1,2,3 , Catherine Pachón-García 1,2,3 , Edited by: Valerio Santangelo, Sergiu Albu 1,2,3 , Henrik Zetterberg 8,9,10,11,12 , Josep M. Tormos 1,2,3 , University of Perugia, Italy Alvaro Pascual-Leone 1,13,14*† and David Bartres-Faz 1,4,5*† Reviewed by: 1 Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la Universitat Autónoma de Barcelona, Barcelona, Sanjeev Kumar, Spain, 2 Departament de Medicina, Facultat de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain, 3 Fundació University of Toronto, Canada Institut d’Investigació en Ciències de la Salut Germans Trias i Pujol, Barcelona, Spain, 4 Institut d’Investigacions Biomèdiques Robert Blumenfeld, August Pi i Sunyer (IDIBAPS), Barcelona, Spain, 5 Departament de Medicina, Facultat de Medicina i Ciències de la Salut, i California State Polytechnic University, Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain, 6 Departamento de Ciencias del Comportamiento, Pomona, United States Escuela de Psicología, Universidad Metropolitana, Caracas, Venezuela, 7 Center for Cognitive and Brain Health, Department Aron T. Hill, of Psychology, Northeastern University, Boston, MA, United States, 8 Department of Psychiatry and Neurochemistry, Institute Deakin University, Australia of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden, 9 Clinical *Correspondence: Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden, 10 Department of Neurodegenerative Disease, David Bartres-Faz University College London Institute of Neurology, London, United Kingdom, 11 UK Dementia Research Institute, University dbartres@ub.edu College London, London, United Kingdom, 12 Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China, 13 Alvaro Pascual-Leone Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew apleone@hsl.harvard.edu SeniorLife, Boston, MA, United States, 14 Department of Neurology, Harvard Medical School, Boston, MA, United States † These authors have contributed equally to this work Introduction: The prefrontal cortex (PFC) plays a crucial role in cognition, particularly in executive functions. Cortical reactivity measured with Transcranial Magnetic Stimulation Specialty section: combined with Electroencephalography (TMS-EEG) is altered in pathological conditions, This article was submitted to Cognition, and it may also be a marker of cognitive status in middle-aged adults. In this a section of the journal study, we investigated the associations between cognitive measures and TMS evoked Frontiers in Psychology EEG reactivity and explored whether the effects of this relationship were related to Received: 11 November 2021 neurofilament light chain levels (NfL), a marker of neuroaxonal damage. Accepted: 18 January 2022 Published: 10 February 2022 Methods: Fifty two healthy middle-aged adults (41–65 years) from the Barcelona Citation: Brain Health Initiative cohort underwent TMS-EEG, a comprehensive neuropsychological Redondo-Camós M, Cattaneo G, Perellón-Alfonso R, Alviarez-Schulze V, assessment, and a blood test for NfL levels. Global and Local Mean-Field Power Morris TP, Solana-Sanchez J, (GMFP/LMFP), two measures of cortical reactivity, were quantified after left prefrontal España-Irla G, Delgado-Gallén S, cortex (L-PFC) stimulation, and cognition was set as the outcome of the regression Pachón-García C, Albu S, Zetterberg H, Tormos JM, analysis. The left inferior parietal lobe (L-IPL) was used as a control stimulation condition. Pascual-Leone A and Bartres-Faz D (2022) Local Prefrontal Cortex Results: Local reactivity was significantly associated with working memory TMS-Induced Reactivity Is Related to and reasoning only after L-PFC stimulation. No associations were found Working Memory and Reasoning in between NfL and cognition. These specific associations were independent Middle-Aged Adults. Front. Psychol. 13:813444. of the status of neuroaxonal damage indexed by the NfL biomarker doi: 10.3389/fpsyg.2022.813444 and remained after adjusting for age, biological sex, and education. Frontiers in Psychology | www.frontiersin.org 1 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition Conclusion: Our results demonstrate that TMS evoked EEG reactivity at the L-PFC, but not the L-IPL, is related to the cognitive status of middle-aged individuals and independent of NfL levels, and may become a valuable biomarker of frontal lobe- associated cognitive function. Keywords: transcranial magnetic stimulation (TMS), Electroencephalography, TMS-EEG, cortical reactivity, prefrontal cortex (PFC), cognition INTRODUCTION changes in brain function can occur decades prior to the onset of clinically measurable symptoms (Beason-Held et al., Cognitive functioning refers to a set of multiple mental abilities 2013). that involve the overall dynamics of information processing Transcranial Magnetic Stimulation combined with of stimuli (acquisition, coding, storage, retrieval, thinking, Electroencephalography (TMS-EEG) is a non-invasive approach and decision making) to generate an adequate response that allows the study of cortical reactivity via the perturbation of (motor or verbal) to the environment (Lezak et al., 2004). The a cortical site and registration of the activity spread throughout characterization of cognitive performance and cognitive profiles the brain (Ilmoniemi and Kičić, 2010; Hallett et al., 2017). is typically carried out through specific domains referring The spatiotemporal analysis of this reactivity and propagation to different processes and abilities within the global term allowed previous studies to explore functional network integrity “cognition” (Harvey, 2019), such as attention, episodic memory, in healthy and clinical populations (Pascual-Leone et al., 2011; working memory, reasoning, fluid intelligence, language, Tremblay et al., 2019; Ozdemir et al., 2020). cognitive flexibility, visuospatial skills, and processing speed. Cortical reactivity has been defined as the relationship These cognitive domains have been related to specific between the strength of the stimulus and the subsequent anatomic areas and brain networks (Wu et al., 2020), and response (Komssi and Kähkönen, 2006). It is relevant because amongst them, the prefrontal cortex (PFC) plays a central role. optimal excitatory and inhibitory cortical balance is needed The PFC is connected to almost all sensory, motor, neocortical for the correct functioning of the brain, connectivity between and subcortical structures and is often implicated in “top- cortical regions, and cognitive functioning (Dehghani et al., down” modulation of cognitive functions (Miller, 2000). In a 2016). Local and Global Mean-Field Power (GMFP/LMFP) hierarchical model of the neurophysiology of the cortex, the reflect TMS-evoked brain reactivity on a specific subgroup of PFC constitutes the highest area of cortical representations electrodes or throughout the entire brain, respectively (Lehmann (as opposed to lower cortical structures such as sensory and and Skrandies, 1980; Komssi and Kähkönen, 2006; Romero motor areas) dedicated to the integration and execution of Lauro et al., 2014). Both measures can reflect the electrical higher-order executive functions (Fuster, 2001; Breukelaar et al., field distribution on the scalp (Skrandies, 1990). They could 2018). As these functions are significantly affected during aging, be valuable for measuring local reactivity directly on the the role of the PFC has been extensively studied, and it has stimulated region and reflecting its distribution to other brain been shown that greater PFC activity is associated with better areas (Lehmann and Skrandies, 1980). The neurophysiological cognition (Eyler et al., 2011; Fernandez-Ruiz et al., 2018) and effect of non-invasive protocols (repetitive TMS or Transcranial that preservation of PFC activity contributes to the maintenance Direct Current Stimulation) has been studied through these of cognitive abilities (Morcom and Henson, 2018; Vidal-Piñeiro measures in healthy adults (Casarotto et al., 2010; Romero et al., 2019). Lauro et al., 2014; Pisoni et al., 2018; Ozdemir et al., 2021) Beyond correlational evidence from brain-behavior and earlier research showed how these measures were directly investigations, direct experimental data using repetitive related to pathological conditions, like depression (Voineskos transcranial magnetic stimulation (rTMS) to modulate older et al., 2019). However, the relation between GMFP/LMFP and adults’ PFC function demonstrated that high-frequency cognition in a healthy middle-aged population has not been rTMS delivered over the bilateral PFC can enhance cognitive studied before. functioning (e.g. Solé-Padullés et al., 2006; Cui et al., 2020). If The goal of this study was to explore the relationship interpreted in the framework of theoretical models of cognitive between cognition and local and global cortical reactivity aging, this enhancement may be due to the promotion of after PFC stimulation using TMS-EEG in healthy middle- compensatory mechanisms by rTMS (Cabeza et al., 2018). aged adults. Moreover, we investigated whether the effects are Given the role of the PFC in cognition and its relevance in independent of a general measure of neuroaxonal damage and healthy aging, the characterization of its neurophysiological neurodegeneration as derived from plasma neurofilament light activity in middle-aged adults, often understudied as compared chain (NfL; Gisslén et al., 2016), a biomarker that has been with other age brackets (Willis et al., 2010; Lachman, 2015), associated with cognitive decline amongst elderly adults in the could represent a valuable biomarker predictive of cognitive preclinical phase of Alzheimer’s disease (AD) (Hu et al., 2019) decline in older adults (McGinnis et al., 2011). Furthermore, and potentially in healthy middle-aged adults (Beydoun et al., research in middle-aged populations is relevant because 2021). Frontiers in Psychology | www.frontiersin.org 2 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition MATERIALS AND METHODS in the relaxed first dorsal interosseous muscle (FDI) in five out of 10 trials. MEPs were measured using surface electromyography Subjects and Study Design (EMG) with electrodes placed in a belly-tendon montage and the Fifty two middle-aged adults (36 male) between 41 and 65 years ground electrode on the ulnar styloid process and connected to (M = 54, SD = 6.85) were recruited as part of the Barcelona Brain a Biopac EMG100C amplifier (BIOPAC Systems Inc., California, Health Initiative (Cattaneo et al., 2018). They underwent a TMS- USA). Handedness was assessed by the Edinburgh handedness EEG session, neuropsychological testing, a medical assessment questionnaire (Oldfield, 1971; Veale, 2014). with blood sample collection, and structural Magnetic Resonance TMS was applied using a Medtronic Magpro X100 stimulator Imaging (MRI). Participants were excluded during the medical through a Cool-B65 figure-of-eight coil. One hundred and visit if they had any neurological or neuropsychiatric disorders or twenty biphasic single pulses were applied at 120% of RMT used medications that could affect brain excitability or cognitive at random intervals between 3 and 6 s. Also, stimulation was functions. Further exclusion criteria included contraindications applied over two target locations: the left prefrontal cortex (L- for TMS (Rossini et al., 2015; Rossi et al., 2021) or MRI. PFC) and a control target, the Inferior Parietal Lobule (L-IPL). All participants gave written informed consent, and the local The cohort had two different target procedures, based on the ethics committee (Comité d’Ètica i Investigació Clínica de la anatomy of each subject or using a cortical functional parcellation Unió Catalana d’Hospitals) approved the study protocol, which (Yeo et al., 2011) (See Supplementary Material for details on conformed to the Declaration of Helsinki for research involving targeting procedure). human subjects. Due to time constraints during the experimental sessions, 77% of the individuals completed L-PFC stimulation (a total of 40 Neuropsychological Assessment participants) and 67% L-IPL (35 participants), with 44% of them The neuropsychological assessment consisted of paper and pencil completing both conditions (23 participants). The complete TMS tests administered by two licensed neuropsychologists (VA, CP). procedure lasted 2 h. The testing session lasted ∼90 min and included 14 validated gold-standard instruments (see Cattaneo et al., 2018): Rey EEG Recordings Auditory Verbal Learning Test (RAVLT) (Schmidt, 1996), Digit- The EEG equipment used to record EEG responses to TMS Span Forward and Backward, Corsi block tapping test, Letter- was made up of a TMS-compatible EEG amplifier (ActiChamp Number Sequencing test (Peña-Casanova et al., 2012), Trail system, Brain Products, GmbH, Munich, Germany) attached Making Test A and B (TMT) (Reitan and Wolfson, 1985; Peña- to 64 active electrodes (ActiCAP slim, Brain Products, GmbH, Casanova et al., 2012), Matrix Reasoning and Block design, the Munich, Germany), following the 10–20 international system for Digit symbol task, and the Cancellation test (Wechsler, 2012). electrode montage. The ground was placed at the Fpz electrode Raw scores of each test were transformed into z-scores site, and the signal was referenced to the AFz electrode. Electrode and, similar to our previous reports (Vidal-Piñeiro et al., impedances were kept below 5 kΩ during the recording, 2014; España-Irla et al., 2021), were grouped into five and a continuous signal was collected, filtered DC to 500 Hz, cognitive domains: episodic memory (RAVLT immediate recall, and digitized at a sampling rate of 1,000 Hz. Besides wearing delayed recall, and recognition; Digit-span forward; Corsi block earplugs to protect from the “click” of the TMS pulse, subjects tapping), working memory (Digit-span backward; Letter-number listened to white noise during stimulation to dampen the sequencing), reasoning (Matrix and Block design WAIS-IV), auditory evoked potential. The volume of the white noise was flexibility (TMT B and B-A), and processing speed (TMT A; Digit individually adjusted to each subjects’ tolerance, and it was played symbol test; Cancellation test). through an active noise-canceling inserted earphone (Beoplay E4, Bang&Olufsen, Denmark). TMS Protocol Participants were asked to sit in a comfortable armchair, look at EEG Preprocessing a fixation cross placed at a 1.5 m distance, stay still, and keep The EEG signal was first preprocessed offline with custom their eyes open. The coil was placed tangentially over the scalp MATLAB scripts (R2020b, The MathWorks Inc., Natick, roughly at a 45-degree angle (relative to the mid-sagittal plane), Massachusetts) that incorporate function from the EEGLAB resulting in a posterior-to-anterior current flow. A frameless toolbox (Delorme and Makeig, 2004) and TESA plugin (Rogasch stereotactic neuronavigation system (Brainsight, Rogue Research et al., 2017). The EEG signal was epoched around the TMS Inc., Montreal, QC Canada) was used with the subject’s T1 pulse (−1,000 to +2,000 ms) and baseline corrected (−900 to weighted structural MRI (obtained from a 3T Siemens Magnetom −100 ms). Excessively noisy channels were removed, but no Prisma) to ensure accurate targeting of the stimulation sites more than three channels had to be discarded for any subject. throughout the session. Data was zero-padded between −2 and +14 ms around the Participant’s Resting Motor Threshold (RMT) was assessed at TMS pulse to remove the early TMS pulse artifact. Epochs were the motor hotspot (M1) of the dominant hemisphere following inspected visually, and excessively noisy epochs were removed the recommendations from the International Federation for (M = 19, SD = 7). A two-step fast Independent Component Clinical Neurophysiology (Rossini et al., 2015; Rossi et al., 2021). Analysis (fICA) was conducted. The first fICA, was performed Briefly, RMT was defined as the lowest stimulation intensity with Principal Component Analysis dimension reduced to 40 to required to produce motor-evoked potentials (MEPs) of ≥ 50 µV minimize overfitting and was used to remove the decay artifact, Frontiers in Psychology | www.frontiersin.org 3 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition typically 2 components were removed for each subject. Before TABLE 1 | Demographic Variables, RMT and NfL plasma values (n = 52). the second round of fICA, the zero-padded TMS pulse was Min Max Mean SD linearly interpolated, Butterworth band-pass (1 and 100 Hz) and notch (48 and 52 Hz) filters were applied, and data were re- Age 41 65 53.96 6.85 referenced to the average reference. The second round of fICA Years of Education 8 28 18.40 3.83 was used to remove any remaining artifacts, including eye blinks, RMT 43 82 59.77 8.76 lateral eye movement, muscle, TMS-evoked muscle, electrode NfL levels (pg/mL) 4.09 29.8 12.22 5.35 noise, and auditory evoked potentials (M = 28, SD = 3; a range of 21–31 out of 38). Finally, initially discarded channels were spline interpolated. the Clinical Neurochemistry Laboratory at the University of Cortical Reactivity TMS-EEG Measures Gothenburg by board-certified laboratory technicians who were Global Mean-Field Power (GMFP) and Local Mean-Field Power blinded to clinical data. (LMFP) were used to quantify overall and local brain reactivity measures, respectively. Statistical Analysis Mean Field-Power (MFP) was calculated for both measures All statistical analyses were performed in SPSS version 22.0 using the following formula: (Statistical Package for Social Sciences, Chicago, IL, USA). s First, to explore changes between local and global reactivity [ Pk (V i (t) − Vmean (t))2 ] before and after stimulation, we ran a repeated-measures i MFP (t) = ANOVA using the variable “Time” (Baseline and Post- K stimulation) and “Mean-Field Type” (LMFP and GMFP) as where “t” is time, “V” is the voltage in the channel “I,” “K” is the within-subject factors. number of channels, and “Vmean” the mean of the voltage across Then, to investigate the relation between TMS reactivity, electrodes (Lehmann and Skrandies, 1980; Esser et al., 2006). at local and global levels, and cognition, we ran multivariate All EEG electrodes were used to compute GMFP, whereas, for multiple regressions for each stimulation site (PFC, IPL). L-IPL LMFP, a subset of electrodes was chosen for L-PFC (FC1, FC3, was used as a control condition to validate if our associations with FC5, F1, F3, F5) and L-IPL (CP1, CP3, CP5, P1, P3, P5) (Ozdemir cognition in L-PFC results were specific to this target. Models et al., 2020). LMFP was used to calculate the local reactivity of the were run using cognitive composite scores as dependent variables stimulation target region. (episodic memory, working memory, reasoning, flexibility, and For GMFP and LMFP, the area under the curve was calculated processing speed) and Mean-Field Type, targeting method, NfL using trapezoidal integration within two-time windows, before levels, age, biological sex, and years of education as predictors. and after the pulse (Baseline and Post-stimulation). Baseline Also, we run the same models without using covariates (targeting refers to the activity before each pulse (−500 to −3 ms), while method, NfL levels, age, biological sex, and years of education). Post-stimulation activity includes data between 15 and 400 ms Finally, to specifically explore the associations between NfL after the TMS pulse. This time window has been selected to level and cognition, we first performed a bivariate correlation, minimize the TMS artifact’s impact and capture the entirety of and then to see the effect of age, we ran a partial correlation the TMS evoked brain response (Fuggetta et al., 2005; Van Der controlled by this variable. Werf et al., 2006). This time window has been used in recent and similar research (Ozdemir et al., 2020; Rocchi et al., 2020; RESULTS Vallesi et al., 2021). Furthermore, baseline data was used to normalize the activity post-stimulation, subtracting it from the All subjects were right-handed and tolerated well the activity post-TMS. experimental procedures, and no adverse events were reported. Descriptive statistics of age, educational level, RMT, and plasma NfL Measurement NfL levels are presented in Table 1, while cognitive scores are in We collected blood samples using EDTA tubes during the the Supplementary Material (Supplementary Table 1). medical assessment, and plasma was aliquoted and stored in a refrigerator at −80◦ C in a biobank facility following standard TMS Cortical Reactivity Changes procedures usually employed for clinical purposes. Plasma NfL L-PFC concentration was measured using the Single-molecule array Repeated measures ANOVA showed a main effect of Time [F (1,39) (Simoa) NF-light Advantage Kit on an HD-X instrument as = 54.05, p < 0.001], indicating difference between pre and post described by the kit manufacturer (Quanterix, Billerica, MA). stimulation, and a main effect of the Mean-Field Type [F (1,39) = The limit of quantification was 2.7 pg/mL, and the limit of 69.02, p < 0.001], indicating that local reactivity was greater (M = detection was 0.3 pg/mL. For the quality control (QC) sample 262.32; SD = 13.90) than global cortical reactivity (M = 206.91; with an 11.2 pg/mL concentration, repeatability was 3.6%, and SD = 9.54). The significant interaction between Time and Mean- intermediate precision was 5.0%. For a QC sample with a 115 Field Type [F (1,39) = 145.97, p < 0.001] indicated a difference in pg/mL concentration, repeatability was 5.3%, and intermediate the effects of stimulation between “local” and “global” conditions. precision was 6.8%. The measurements were performed at While LMFP showed significant differences between baseline and Frontiers in Psychology | www.frontiersin.org 4 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition FIGURE 1 | L-PFC. Graphical representation of local (LMFP) and global FIGURE 2 | L-IPL. Graphical representation of LFMP and GFMP at baseline (GMFP) reactivity, at baseline and after stimulation. and after stimulation. model. Full model results including covariates can be found in post-TMS [t (39) = 13.56, p < 0.001, d = 2.14] GMFP did not [t (39) Supplementary Table 3. = 1.16, p = 0.253, d = 0.18; see Figure 1]. Conversely, no significant results were seen between cognition and cortical reactivity in models without covariates (see L-IPL Supplementary Tables 4, 5). Repeated measures ANOVA also showed a main effect of Time [F (1,34) = 20.01, p < 0.001], indicating difference between pre L-IPL and post stimulation, and a main effect of the Mean-Field Type For stimulation to left IPL, no statistically significant relations [F (1,34) = 89.38, p < 0.001] showing that local reactivity was were found between any of the cognitive functions and either greater (M = 260.10; SD = 15.78) than global cortical reactivity global or local TMS-EEG induced reactivity measures at baseline (M = 200.63; SD = 12.02). The significant interaction between or post-stimulation. Model results including covariates are Time and Mean-Field Type [F (1,34) =143.96, p < 0.001] suggested presented in Supplementary Tables 6, 7. Also, no significant difference in the effects of stimulation between “local” and results were seen between cognition and cortical reactivity in “global” conditions. Similarly to the L-PFC analysis, while LMFP models without covariates (see Supplementary Tables 8, 9). showed significative differences between baseline and post-TMS [t (34) = 8.55, p < 0.001, d = 1.44] GMFP did not [t(34) = 0.311, p NfL Levels and Cognitive Functions = 0.758, d = 0.05; see Figure 2]. Also, an example of TMS-EEG We first ran a bivariate correlation between NfL levels and responses after a PFC and IPL pulse is presented in Figure 3. cognitive variables and found that it was significantly and inversely correlated to participants’ cognitive performance in reasoning (r = −0.373, p = 0.006), processing speed (r = Cortical Reactivity and Cognitive Functions −0.338, p = 0.014), and cognitive flexibility (r = −0.293, p = Associations 0.035; see Supplementary Table 10). However, when controlled L-PFC for age, such associations disappeared, indicating that the Age and local reactivity resulted in statistically significant age of participants largely drove the correlations. In addition, results for the multivariate regression analysis [respectively and as revealed by the multivariate regression analyses, NfL F (5,28) = 3.28, p < 0.019, Wilks’ 3 = 0.631, partial η2 concentration was not significantly associated with cognitive = 0.369; F (5,28) = 2.91, p = 0.031, Wilks’ 3 = 0.658, status (see Supplementary Tables 3, 7). partial η2 = 0.342; see Supplementary Table 2]. The analysis revealed a significant positive association between working DISCUSSION memory and local reactivity to stimulation of the L-PFC [F (1,32) = 5.01, p = 0.032, partial η2 = 0.135], as well as an In the present study, we explored the relationship between association between reasoning and both age [F (1,32) = 6.76, EEG reactivity to TMS of the PFC and IPL and cognition p = 0.014, partial η2= 0.174] and local reactivity to L-PFC in healthy middle-aged adults, and the possible role of stimulation [F (1,32) = 4.70, p = 0.038, partial η2= 0.128] (see neuroaxonal damage measured by plasma NfL. Results indicate Figure 4). Episodic memory, processing speed, and flexibility that local TMS-EEG reactivity after PFC stimulation is were unrelated to the independent variables introduced in the positively associated with executive functions, specifically Frontiers in Psychology | www.frontiersin.org 5 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition FIGURE 3 | Butterfly plots of a subject’s TMS-EEG responses after PFC (A) and IPL (B) stimulation. Each figure time-series are plotted −100 to +400 ms around the TMS pulse. FIGURE 4 | Multiple regression scatterplots between local cortical reactivity after PFC stimulation and working memory (A) and reasoning (B) after controlling for targeting method, NfL levels, age, biological sex, and years of education. Z-scores were used on the Y-axis and unstandardized Predicted Values on the X-axis (µV). Frontiers in Psychology | www.frontiersin.org 6 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition working memory and reasoning. However, after IPL stimulation, Furthermore, NfL was shown to be negatively related to cortical reactivity was not related to cognitive function. Finally, cognition, but this effect disappeared if controlled by the it was shown that neuroaxonal damage measured by NfL did individual’s age, and NfL level didn’t have a significant influence not play a role in these associations. Despite that, a significant on the identified relation between cortical reactivity and cognitive effect was seen when we correlated directly NfL level and functions. NfL level is a marker of neuro-axonal damage cognitive functions, which disappeared when we controlled in diseases such as Alzheimer’s disease, Parkinson’s disease, by age. multiple sclerosis, or amyotrophic lateral sclerosis, where high The fact that the relation between TMS-EEG reactivity and concentrations of NfL have been reported (Gaetani et al., cognitive were limited to the local response following PFC 2019; Dhiman et al., 2020). Recent studies (Khalil et al., 2020; stimulation, and not globally or when stimulating the L-IPL, is Beydoun et al., 2021; Rübsamen et al., 2021) have explored consistent with the specific PFC role in the top-down regulation in healthy individuals the relation between NfL levels, brain of higher-order cognitive control (Miller, 2000). These results structures, and cognitive scores, suggesting that higher NfL levels indicate that individual differences in local cortical reactivity to could be associated with brain atrophy, and in consequence TMS of the PFC could be a practical, specific, sensitive, and worse cognition. Our study sample was limited to middle- simple biomarker to assess cognitive functioning, independently aged, cognitively-unimpaired adults, and the fact that the of the global brain and axonal degeneration. level of NfL didn’t influence the reactivity/cognition prediction Cortical reactivity has been previously related to factors could be because of collinearity between age and NfL level, such as alcohol or medication intake (Kähkönen et al., 2003; or that most past results have focused on older adults or Khedr et al., 2020) and various TMS parameters (Casula various patient populations. More studies in healthy middle- et al., 2018). A rich literature has demonstrated that activity aged adults are needed to determine the significance and and connectivity between PFC and IPL are associated with potential clinical utility of NfL plasma levels (Beydoun et al., cognition (Lückmann et al., 2014; Friedman and Robbins, 2021). 2021). In particular, whereas PFC has been more related To conclude, our results indicate that cortical reactivity of to executive function and cognitive control (Friedman and L-PFC as characterized by TMS-EEG is related to cognition in Robbins, 2021), IPL has been associated with language and middle-aged adults regardless of neuroaxonal damage (indicated social cognition (Numssen et al., 2021). In line with our by NfL), age, biological sex, and education. This TMS-EEG results, Ngetich et al. (2020) showed that after a continuous metric may represent a valuable and independent biomarker theta burst stimulation over L-PFC, there was a change in for cognition. executive functions like working memory and decision making As with all studies, the design of the current study is subject (Ngetich et al., 2020). Similarly, it has been shown that abnormal to limitations. First, we acknowledge that our sample size higher cortical excitability in the PFC in patients with AD was small, but still, it was in line with other studies whose than healthy controls was inversely associated with global objective was to associate TMS measures with cognition. Second, cognition/executive functions (Joseph et al., 2021), confirming our sample was characterized by highly educated individuals, the relation between cognitive functions performance and PFC and there was a high prevalence of men. Furthermore, our evoked activity. statistical analysis was done for each stimulation site separately The role of PFC in working memory has been extensively because of missing data. Given the small sample sizes, multiple studied in the past decade with animals and humans, suggesting comparisons corrections were not applied to maintain statistical that PFC is strongly related to the cognitive process of power and avoid strongly increasing the probability of type maintaining available and select information for delayed II errors. Hence, further studies are needed, including more responses (see Curtis and D’Esposito, 2003 for a review). It has participants with both PFC and IPL stimulation data to confirm been proposed that while the PFC is crucial to manipulate and these results. Finally, a layer of foam between the coil and select relevant information, a more posterior part of PFC (e.g., the electrodes was not used in this research, and despite this Brodmann area 8) is involved in mechanisms of maintenance preventive measure could add some distance, increasing the (Rowe et al., 2000; Glahn et al., 2002). Also, complex reasoning resting motor threshold and the effect varies between subjects tasks have been consistently associated with PFC activity and (ter Braack et al., 2015), it could have been beneficial for the integrity. It has been proposed that PFC is strongly involved reduction of auditory evoked potentials in the EEG analysis. in logic processing (Santarnecchi et al., 2013), and specifically, Future investigations with larger and more heterogeneous its rostrolateral part is essential for relational integration and samples are necessary to validate the conclusions of our study, associations (Christoff et al., 2001; Krawczyk et al., 2011). and it would be valuable to explore if changes in cortical The association between cognition and PFC activity and reactivity, measured longitudinally, may be predictive of age- connectivity is especially important in studying the maintenance related changes in cognition. of cognitive functioning in aging. Indeed it has been proposed that PFC activity could be related to the recruitment of compensatory mechanisms (Solé-Padullés et al., 2006; Höller- DATA AVAILABILITY STATEMENT Wallscheid et al., 2017; Abellaneda-Pérez et al., 2019) that allow individuals to maintain cognition in the face of age-related The raw data supporting the conclusions of this article will be brain changes. made available by the authors, without undue reservation. Frontiers in Psychology | www.frontiersin.org 7 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition ETHICS STATEMENT by the National Institutes of Health (R24AG06142, and P01 AG031720), the National Science Foundation, DARPA, and the The studies involving human participants were reviewed and Barcelona Brain Health Initiative funded primarily by La Caixa approved by Comité d’Ètica i Investigació Clínica de la Unió (LCF/PR/PR16/11110004), and HZ is a Wallenberg Scholar Catalana d’Hospitals. The patients/participants provided their supported by grants from the Swedish Research Council (#2018- written informed consent to participate in this study. 02532), the European Research Council (#681712), Swedish State Support for Clinical Research (#ALFGBG-720931), AUTHOR CONTRIBUTIONS the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer’s AP-L, DB-F, and JT-M participated in the initial conception of Association (#ADSF-21-831376-C, #ADSF-21-831381-C the design of the BBHI project. MR-C, DB-F, AP-L, GC, and RP- and #ADSF-21-831377-C), the Olav Thon Foundation, the A contributed to conception and design of the present study. Erling-Persson Family Foundation, Stiftelsen för Gamla MR-C, SD-G, GE-I, VA-S, CP-G, SA, JS-S, and TM contributed to Tjänarinnor, Hjärnfonden, Sweden (#FO2019-0228), the the acquisition of data. MR-C, GC, TM, HZ, and RP-A analyzed European Union’s Horizon 2020 Research and Innovation the data. MR-C, GC, and DB-F contributed to the draft of the Programme under the Marie Skłodowska-Curie grant agreement manuscript. All authors contributed to manuscript revision, read, No 860197 (MIRIADE), and the UK Dementia Research Institute and approved the submitted version. at UCL. FUNDING ACKNOWLEDGMENTS DB-F and RP-A were funded by a Spanish Ministry of A special thanks is extended to all BBHI participants, the Science, Innovation and Universities (MICIU/FEDER; project team and research assistants, and other partners (Ad- RTI2018-095181-B-C21) and an ICREA Academia 2019 Salutem Institute, Sodexo, I.C.A. Informàtica y Comunicaciones Research Grants, and also supported by an ICREA Academia Avanzadas, Neuroelectrics, Corporació Catalana de Mitjans 2019 Grand Award, RP-A was supported by a fellowship Audiovisuals, Club Metropolitan, Casa Ametller, and Agència from la Caixa Foundation (ID 100010434, Fellowship code: de Qualitat i Avaluació Sanitàries de Catalunya-AQuAS) for LCF/BQ/DI19/11730050), JT-M was partly supported Fundació their collaboration. Joan Ribas (Araquistain_FJRA), AGAUR, Agència de Gestió d’Ajuts Universitaris i de Recerca. Convocatòria 2018 d’Indústria del Coneixement (modalitat PRODUCTE) and FEDER, Fons SUPPLEMENTARY MATERIAL Europeu de Desenvolupament Regional (2018 PROD 00172), Fundació La Marató De TV3 (201735.10), and European The Supplementary Material for this article can be found Commission - H2020/Call H2020-SC1-2016-2017 (RIA) online at: https://www.frontiersin.org/articles/10.3389/fpsyg. (Grant Agreement No. 777107), AP-L was partly supported 2022.813444/full#supplementary-material REFERENCES perturbation parameters and repeatable over time. PLoS One 5, e10281. doi: 10.1371/journal.pone.0010281 Abellaneda-Pérez, K., Vaqué-Alcázar, L., Solé-Padullés, C., and Bartrés-Faz, D. Casula, E. P., Rocchi, L., Hannah, R., and Rothwell, J. C. (2018). Effects of (2019). Combining non-invasive brain stimulation with functional magnetic pulse width, waveform and current direction in the cortex: A combined resonance imaging to investigate the neural substrates of cognitive aging. J. cTMS-EEG study. Brain Stimul. 11, 1063–1070. doi: 10.1016/j.brs.2018. Neurosci. Res. doi: 10.1002/jnr.24514. [Epub ahead of print]. 04.015 Beason-Held, L. L., Goh, J. O., An, Y., Kraut, M. A., O’Brien, R. J., Cattaneo, G., Bartrés-Faz, D., Morris, T. P., Sánchez, J. S., Macià, D., Tarrero, C., Ferrucci, L., et al. (2013). Changes in brain function occur years et al. (2018). The Barcelona brain health initiative: a cohort study to define before the onset of cognitive impairment. J. Neurosci. 33, 18008–18014. and promote determinants of brain health. Front. Aging Neurosci. 10, 32‘. doi: 10.1523/JNEUROSCI.1402-13.2013 doi: 10.3389/fnagi.2018.00321 Beydoun, M. A., Noren Hooten, N., Beydoun, H. A., Maldonado, A. I., Weiss, J., Christoff, K., Prabhakaran, V., Dorfman, J., Zhao, Z., Kroger, J. K., Holyoak, Evans, M. K., et al. (2021). Plasma neurofilament light as a potential biomarker K. J., et al. (2001). Rostrolateral prefrontal cortex involvement in for cognitive decline in a longitudinal study of middle-aged urban adults. relational integration during reasoning. Neuroimage 14, 1136–1149. Transl. Psychiatry 11, 1–12. doi: 10.1038/s41398-021-01563-9 doi: 10.1006/nimg.2001.0922 Breukelaar, I. A., Williams, L. M., Antees, C., Grieve, S. M., Foster, S. L., Gomes, Cui, X., Ren, W., Zheng, Z., and Li, J. (2020). Repetitive transcranial magnetic L., et al. (2018). Cognitive ability is associated with changes in the functional stimulation improved source memory and modulated recollection- organization of the cognitive control brain network. Hum. Brain Mapp. 39, based retrieval in healthy older adults. Front. Psychol. 11, 1137. 5028–5038. doi: 10.1002/hbm.24342 doi: 10.3389/fpsyg.2020.01137 Cabeza, R., Albert, M., Belleville, S., Craik, F. I. M., Duarte, A., Grady, C. Curtis, C. E., and D’Esposito, M. (2003). Persistent activity in the L., et al. (2018). Maintenance, reserve and compensation: the cognitive prefrontal cortex during working memory. Trends Cogn. Sci. 7, 415–423. neuroscience of healthy ageing. Nat. Rev. Neurosci. 19, 701–710. doi: 10.1016/S1364-6613(03)00197-9 doi: 10.1038/s41583-018-0068-2 Dehghani, N., Peyrache, A., Telenczuk, B., Le Van Quyen, M., Halgren, E., Cash, Casarotto, S., Lauro, L. J. R., Bellina, V., Casali, A. G., Rosanova, M., Pigorini, S. S., et al. (2016). Dynamic balance of excitation and inhibition in human and A., et al. (2010). EEG responses to TMS are sensitive to changes in the monkey neocortex. Sci. Rep. 6, 23176. doi: 10.1038/srep23176 Frontiers in Psychology | www.frontiersin.org 8 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition Delorme, A., and Makeig, S. (2004). EEGLAB: an open source toolbox for their association with morphologic brain changes. Nat. Commun. 11:812. analysis of single-trial EEG dynamics. J. Neurosci. Methods 134, 9–21. doi: 10.1038/s41467-020-14612-6 doi: 10.1016/j.jneumeth.2003.10.009 Khedr, E. M., Tony, A. A., Abdelwarith, A., and Safwat, M. (2020). Dhiman, K., Gupta, V. B., Villemagne, V. L., Eratne, D., Graham, P. L., Fowler, Effect of chronic nicotine consumption on motor cortical excitability: a C., et al. (2020). Cerebrospinal fluid neurofilament light concentration predicts transcranial magnetic stimulation study. Neurophysiol. Clin. 50, 33–39. brain atrophy and cognition in Alzheimer’s disease. Alzheimer’s Dement. 12, doi: 10.1016/j.neucli.2019.11.003 e12005. doi: 10.1002/dad2.12005 Komssi, S., and Kähkönen, S. (2006). The novelty value of the España-Irla, G., Gomes-Osman, J., Cattaneo, G., Albu, S., Cabello-Toscano, M., combined use of electroencephalography and transcranial magnetic Solana-Sanchéz, J., et al. (2021). Associations between cardiorespiratory fitness, stimulation for neuroscience research. Brain Res. Rev. 52, 183–192. cardiovascular risk, and cognition are mediated by structural brain health in doi: 10.1016/j.brainresrev.2006.01.008 midlife. J. Am. Heart Assoc. 10, e020688. doi: 10.1161/JAHA.120.020688 Krawczyk, D. C., Michelle McClelland, M., and Donovan, C. M. (2011). A Esser, S. K., Huber, R., Massimini, M., Peterson, M. J., Ferrarelli, F., hierarchy for relational reasoning in the prefrontal cortex. Cortex 47, 588–597. and Tononi, G. (2006). A direct demonstration of cortical LTP in doi: 10.1016/j.cortex.2010.04.008 humans: A combined TMS/EEG study. Brain Res. Bull. 69, 86–94. Lachman, M. E. (2015). Mind the gap in the middle: a call to study midlife. Res. doi: 10.1016/j.brainresbull.2005.11.003 Hum. Dev. 12, 327–334. doi: 10.1080/15427609.2015.1068048 Eyler, L. T., Sherzai, A., Kaup, A. R., and Jeste, D. V. (2011). A review of functional Lehmann, D., and Skrandies, W. (1980). Reference-free identification brain imaging correlates of successful cognitive aging. Biol. Psychiatry 70, of components of checkerboard-evoked multichannel potential 115–122. doi: 10.1016/j.biopsych.2010.12.032 fields. Electroencephalogr. Clin. Neurophysiol. 48, 609–621. Fernandez-Ruiz, J., Peltsch, A., Alahyane, N., Brien, D. C., Coe, B. C., doi: 10.1016/0013-4694(80)90419-8 Garcia, A., et al. (2018). Age related prefrontal compensatory mechanisms Lezak, M., Howieson, D., and Loring, D. (2004). Neuropsychological Assessment, for inhibitory control in the antisaccade task. Neuroimage 165, 92–101. 4th Edn. New York, NY: Oxford University Press. doi: 10.1016/j.neuroimage.2017.10.001 Lückmann, H. C., Jacobs, H. I. L., and Sack, A. T. (2014). The cross-functional Friedman, N. P., and Robbins, T. W. (2021). The role of prefrontal cortex in role of frontoparietal regions in cognition: internal attention as the overarching cognitive control and executive function. Neuropsychopharmacology, 47, 72–89. mechanism. Prog. Neurobiol. 116, 66–86. doi: 10.1016/j.pneurobio.2014.02.002 doi: 10.1038/s41386-021-01132-0 McGinnis, S. M., Brickhouse, M., Pascual, B., and Dickerson, B. C. (2011). Age- Fuggetta, G., Fiaschi, A., and Manganotti, P. (2005). Modulation of cortical related changes in the thickness of cortical zones in humans. Brain Topogr. 24, oscillatory activities induced by varying single-pulse transcranial magnetic 279–291. doi: 10.1007/s10548-011-0198-6 stimulation intensity over the left primary motor area: a combined EEG and Miller, E. K. (2000). The prefontral cortex and cognitive control. Nat. Rev. Neurosci. TMS study. Neuroimage 27, 896–908. doi: 10.1016/j.neuroimage.2005.05.013 1, 59–65. doi: 10.1038/35036228 Fuster, J. M. (2001). The prefrontal cortex - an update: time is of the essence. Morcom, A. M., and Henson, R. N. A. (2018). Increased prefrontal activity Neuron 30, 319–333. doi: 10.1016/S0896-6273(01)00285-9 with aging reflects nonspecific neural responses rather than compensation. J. Gaetani, L., Blennow, K., Calabresi, P., Di Filippo, M., Parnetti, L., and Zetterberg, Neurosci. 38, 7303–7313. doi: 10.1523/JNEUROSCI.1701-17.2018 H. (2019). Neurofilament light chain as a biomarker in neurological disorders. Ngetich, R., Zhou, J., Zhang, J., Jin, Z., and Li, L. (2020). Assessing the effects J. Neurol. Neurosurg. Psychiatry 870–881. doi: 10.1136/jnnp-2018-320106 of continuous theta burst stimulation over the dorsolateral prefrontal cortex Gisslén, M., Price, R. W., Andreasson, U., Norgren, N., Nilsson, S., Hagberg, on human cognition: a systematic review. Front. Integr. Neurosci. 14, 35. L., et al. (2016). Plasma concentration of the Neurofilament Light Protein doi: 10.3389/fnint.2020.00035 (NFL) is a biomarker of CNS Injury in HIV Infection: a cross-sectional study. Numssen, O., Bzdok, D., and Hartwigsen, G. (2021). Functional specialization EBioMedicine 3, 135–140. doi: 10.1016/j.ebiom.2015.11.036 within the inferior parietal lobes across cognitive domains. Elife 10. Glahn, D. C., Kim, J., Cohen, M. S., Poutanen, V. P., Therman, S., doi: 10.7554/eLife.63591.sa2 Bava, S., et al. (2002). Maintenance and manipulation in spatial working Oldfield, R. C. (1971). The assessment and analysis of handedness. memory: dissociations in the prefrontal cortex. Neuroimage 17, 201–213. Neuropsychologia 9, 97–113. doi: 10.1016/0028-3932(71)90067-4 doi: 10.1006/nimg.2002.1161 Ozdemir, R. A., Boucher, P., Fried, P. J., Momi, D., Jannati, A., Pascual- Hallett, M., Di Iorio, R., Rossini, P. M., Park, J. E., Chen, R., Celnik, P., Leone, A., et al. (2021). Reproducibility of cortical response modulation et al. (2017). Contribution of transcranial magnetic stimulation to assessment induced by intermittent and continuous theta-burst stimulation of the of brain connectivity and networks. Clin. Neurophysiol. 128, 2125–2139. human motor cortex. Brain Stimul. 14, 949–964. doi: 10.1016/j.brs.2021. doi: 10.1016/j.clinph.2017.08.007 05.013 Harvey, P. D. (2019). Domains of cognition and their assessment. Dialogues Clin. Ozdemir, R. A., Tadayon, E., Boucher, P., Momi, D., Karakhanyan, K. A., Fox, M. Neurosci. 21, 227–237. doi: 10.31887/DCNS.2019.21.3/pharvey D., et al. (2020). Individualized perturbation of the human connectome reveals Höller-Wallscheid, M. S., Thier, P., Pomper, J. K., and Lindner, A. (2017). Bilateral reproducible biomarkers of network dynamics relevant to cognition. Proc. Natl. recruitment of prefrontal cortex in working memory is associated with task Acad. Sci. U. S. A. 117, 8115–8125. doi: 10.1073/pnas.1911240117 demand but not with age. Proc. Natl. Acad. Sci. U. S. A. 114, E830–E839. Pascual-Leone, A., Freitas, C., Oberman, L., Horvath, J. C., Halko, M., Edaief, M., doi: 10.1073/pnas.1601983114 et al. (2011). Characterizing brain cortical plasticity and network dynamics Hu, H., Chen, K. L., Ou, Y. N., Cao, X. P., Chen, S. D., Cui, M., et al. (2019). across the age-span in health and disease with TMS-EEG and TMS-fMRI. Brain Neurofilament light chain plasma concentration predicts neurodegeneration Topogr. 23, 302–315. doi: 10.1007/s10548-011-0196-8 and clinical progression in nondemented elderly adults. Aging (Albany. NY). Peña-Casanova, J., Casals-Coll, M., Quintana, M., Sánchez-Benavides, G., 11, 6904–6914. doi: 10.18632/aging.102220 Rognoni, T., Calvo, L., et al. (2012). Estudios normativos españoles Ilmoniemi, R. J., and Kičić, D. (2010). Methodology for combined TMS and EEG. en población adulta joven (Proyecto NEURONORMA jóvenes): Brain Topogr. 22, 233–248. doi: 10.1007/s10548-009-0123-4 métodos y características de la muestra. Neurologia 27, 253–260. Joseph, S., Patterson, R., Wang, W., Blumberger, D. M., Rajji, T., and Kumar, S. doi: 10.1016/j.nrl.2011.12.019 (2021). Quantitative assessment of cortical excitability in alzheimer’s dementia Pisoni, A., Mattavelli, G., Papagno, C., Rosanova, M., Casali, A. G., and and its association with clinical symptoms: a systematic review and meta- Lauro, L. J. R. (2018). Cognitive enhancement induced by Anodal tDCS analyses. J. Alzheimer’s Dis. doi: 10.3233/JAD-210311. [Epub ahead of print]. drives circuit-specific cortical plasticity. Cereb. Cortex 28, 1132–1140. Kähkönen, S., Wilenius, J., Nikulin, V. V., Ollikainen, M., and Ilmoniemi, doi: 10.1093/cercor/bhx021 R. J. (2003). Alcohol reduces prefrontal cortical excitability in humans: Reitan, R. M., and Wolfson, D. (1985). The Halstead-Reitan Neuropsychological A combined TMS and EEG study. Neuropsychopharmacology 28, 747–754. Test Battery: Theory and Interpretattion. Tucson, AZ: Neuropsychology Press. doi: 10.1038/sj.npp.1300099 Rocchi, L., Di Santo, A., Brown, K., Ibáñez, J., Casula, E., Rawji, V., et al. (2020). Khalil, M., Pirpamer, L., Hofer, E., Voortman, M. M., Barro, C., Leppert, Disentangling EEG responses to TMS due to cortical and peripheral activations. D., et al. (2020). Serum neurofilament light levels in normal aging and Brain Stimul. 14, 4–18. doi: 10.1016/j.brs.2020.10.011 Frontiers in Psychology | www.frontiersin.org 9 February 2022 | Volume 13 | Article 813444 Redondo-Camós et al. Prefrontal Cortical Reactivity and Cognition Rogasch, N. C., Sullivan, C., Thomson, R. H., Rose, N. S., Bailey, N. high memory function over 8 years in aging. Cereb. Cortex 29, 3111–3123. W., Fitzgerald, P. B., et al. (2017). Analysing concurrent transcranial doi: 10.1093/cercor/bhy177 magnetic stimulation and electroencephalographic data: a review and Vidal-Piñeiro, D., Valls-Pedret, C., Fernández-Cabello, S., Arenaza-Urquijo, E. introduction to the open-source TESA software. Neuroimage 147, 934–951. M., Sala-Llonch, R., Solana, E., et al. (2014). Decreased default mode network doi: 10.1016/j.neuroimage.2016.10.031 connectivity correlates with age-associated structural and cognitive changes. Romero Lauro, L. J., Rosanova, M., Mattavelli, G., Convento, S., Pisoni, A., Front. Aging Neurosci. 6, 256. doi: 10.3389/fnagi.2014.00256 Opitz, A., et al. (2014). Anodal transcranial direct current stimulation (tDCS) Voineskos, D., Blumberger, D. M., Zomorrodi, R., Rogasch, N. C., Farzan, increases cortical excitability: direct evidence from TMS-EEG. Cortex 58, F., Foussias, G., et al. (2019). Altered transcranial magnetic stimulation– 99–111. doi: 10.1016/j.cortex.2014.05.003 electroencephalographic markers of inhibition and excitation in the Rossi, S., Antal, A., Bestmann, S., Bikson, M., Brewer, C., Brockmöller, dorsolateral prefrontal cortex in major depressive disorder. Biol. Psychiatry 85, J., et al. (2021). Safety and recommendations for TMS use in healthy 477–486. doi: 10.1016/j.biopsych.2018.09.032 subjects and patient populations, with updates on training, ethical and Wechsler, D. (2012). WAIS-IV. Escala de inteligencia de Wechsler para adultos-IV. regulatory issues: expert Guidelines. Clin. Neurophysiol. 132, 269–306. Manual De Aplicación Y Corrección. Madrid: NCS Pearson, Inc. doi: 10.1016/j.clinph.2020.10.003 Willis, S. L., Martin, M., and Rocke, C. (2010). Longitudinal perspectives Rossini, P. M., Burke, D., Chen, R., Cohen, L. G., Daskalakis, Z., Di on midlife development: Stability and change. Eur. J. Ageing 7, 131–134. Iorio, R., et al. (2015). Non-invasive electrical and magnetic stimulation doi: 10.1007/s10433-010-0162-4 of the brain, spinal cord, roots and peripheral nerves: basic principles Wu, T., Chen, C., Spagna, A., Wu, X., Mackie, M. A., Russell-Giller, S., and procedures for routine clinical and research application: an updated et al. (2020). The functional anatomy of cognitive control: a domain-general report from an I.F.C.N. Committee. Clin. Neurophysiol. 126, 1071–1107. brain network for uncertainty processing. J. Comp. Neurol. 528, 1265–1292. doi: 10.1016/j.clinph.2015.02.001 doi: 10.1002/cne.24804 Rowe, J. B., Toni, I., Josephs, O., Frackowiak, R. S. J., and Passingham, R. E. (2000). Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., The prefrontal cortex: response selection or maintenance within working Hollinshead, M., et al. (2011). The organization of the human cerebral cortex memory? Science (80-.) 288, 1656–1660. doi: 10.1126/science.288.5471.1656 estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165. Rübsamen, N., Maceski, A., Leppert, D., Benkert, P., Kuhle, J., Wiendl, H., et al. doi: 10.1152/jn.00338.2011 (2021). Serum neurofilament light and tau as prognostic markers for all-cause mortality in the elderly general population—an analysis from the MEMO study. Conflict of Interest: AP-L is a co-founder of Linus Health and TI Solutions AG; BMC Med. 19, 1–10. doi: 10.1186/s12916-021-01915-8 serves on the scientific advisory boards for Starlab Neuroscience, Magstim Inc., Santarnecchi, E., Polizzotto, N. R., Godone, M., Giovannelli, F., Feurra, Radiant Hearts, and MedRhythms; is listed as an inventor on several issued and M., Matzen, L., et al. (2013). Frequency-dependent enhancement of fluid pending patents on the real-time integration of non-invasive brain stimulation intelligence induced by transcranial oscillatory potentials. Curr. Biol. 23, with electroencephalography and magnetic resonance imaging and is an Associate 1449–1453. doi: 10.1016/j.cub.2013.06.022 Editor for Annals of Neurology. HZ has served at scientific advisory boards and/or Schmidt, M. (1996). Rey Auditory and Verbal Learning Test: A Handbook. Los as a consultant for Abbvie, Alector, Annexon, Artery Therapeutics, AZTherapies, Ángeles: Western Psychological Services. CogRx, Denali, Eisai, Nervgen, Pinteon Therapeutics, Red Abbey Labs, Passage Skrandies, W. (1990). Global field power and topographic similarity. Brain Topogr. Bio, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, 3, 137–141. doi: 10.1007/BF01128870 has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure Solé-Padullés, C., Bartrés-Faz, D., Junqué, C., Clemente, I. C., Molinuevo, J. and Biogen, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB L., Bargalló, N., et al. (2006). Repetitive transcranial magnetic stimulation (BBS), which is a part of the GU Ventures Incubator Program (outside submitted effects on brain function and cognition among elders with memory work). dysfunction. A randomized sham-controlled study. Cereb. Cortex 16, 1487–1493. doi: 10.1093/cercor/bhj083 The remaining authors declare that the research was conducted in the absence of ter Braack, E. M., de Vos, C. C., and van Putten, M. J. A. M. (2015). Masking any commercial or financial relationships that could be construed as a potential the auditory evoked potential in TMS–EEG: a comparison of various methods. conflict of interest. Brain Topogr. 28, 520–528. doi: 10.1007/s10548-013-0312-z Tremblay, S., Rogasch, N. C., Premoli, I., Blumberger, D. M., Casarotto, S., Publisher’s Note: All claims expressed in this article are solely those of the authors Chen, R., et al. (2019). Clinical utility and prospective of TMS–EEG. Clin. and do not necessarily represent those of their affiliated organizations, or those of Neurophysiol. 130, 802–844. doi: 10.1016/j.clinph.2019.01.001 the publisher, the editors and the reviewers. Any product that may be evaluated in Vallesi, A., Del Felice, A., Capizzi, M., Tafuro, A., Formaggio, E., Bisiacchi, P., this article, or claim that may be made by its manufacturer, is not guaranteed or et al. (2021). Natural oscillation frequencies in the two lateral prefrontal cortices induced by transcranial magnetic stimulation: prefrontal natural frequencies. endorsed by the publisher. Neuroimage 227, 117655. doi: 10.1016/j.neuroimage.2020.117655 Van Der Werf, Y. D., Sadikot, A. F., Strafella, A. P., and Paus, T. (2006). Copyright © 2022 Redondo-Camós, Cattaneo, Perellón-Alfonso, Alviarez-Schulze, The neural response to transcranial magnetic stimulation of the human Morris, Solana-Sanchez, España-Irla, Delgado-Gallén, Pachón-García, Albu, motor cortex. II. Thalamocortical contributions. Exp. Brain Res. 175, 246–255. Zetterberg, Tormos, Pascual-Leone and Bartres-Faz. This is an open-access article doi: 10.1007/s00221-006-0548-x distributed under the terms of the Creative Commons Attribution License (CC BY). Veale, J. F. (2014). Edinburgh Handedness Inventory - Short Form: A revised The use, distribution or reproduction in other forums is permitted, provided the version based on confirmatory factor analysis. Laterality 19, 164–177. original author(s) and the copyright owner(s) are credited and that the original doi: 10.1080/1357650X.2013.783045 publication in this journal is cited, in accordance with accepted academic practice. Vidal-Piñeiro, D., Sneve, M. H., Nyberg, L. H., Mowinckel, A. M., Sederevicius, No use, distribution or reproduction is permitted which does not comply with these D., Walhovd, K. B., et al. (2019). Maintained frontal activity underlies terms. Frontiers in Psychology | www.frontiersin.org 10 February 2022 | Volume 13 | Article 813444