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      Corrigendum to “Behavioral and cognitive correlates of the aperiodic (1/f-like) exponent of the EEG power spectrum in adolescents with and without ADHD” [Dev. Cogn. Neurosci. 48C (2021) 100931]

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          Abstract

          The authors regret an error in a data processing script used for the manuscript titled, “Behavioral and cognitive correlates of the aperiodic (1/f-like) exponent of the EEG power spectrum in adolescents with and without ADHD,”. The authors discovered a typo that binded aperiodic exponent values to the main data frame without accounting for the 7 participants who did not provide EEG data. Reanalysis of corrected data did not substantively affect the primary findings, but does lead to adolescent age being significantly associated with aperiodic exponents. All other changes were minor and did not affect interpretations or conclusions of our results. Corrections to values reported in the main text are as follows: 1. In Section 3.2, the correlation between the eyes-open and eyes-closed conditions should be: r = 0.79. The association between aperiodic exponents and adolescent sex should be: t(175) = 1.62, p = .11. 2. In Table 1, the aperiodic exponent values should be M = 1.71 (SD = 0.30) for children with ADHD and M = 1.80 (SD = 0.27) for children in the non-ADHD control group (p = .04, 95 % CI [0.003, 0.173]). 3. In Table 2, aperiodic exponents are associated with other variables as follows: age (r = − 0.29, p < .001); mean RT (r = − 0.01, p = .94); log-transformed reaction time variability (r = 0.15, p = .05); drift rate (r = − 0.13, p = .08); boundary separation (r = 0.05, p = .56); and non-decision time (r < 0.01, p = .97). 4. Age and aperiodic exponents are positively correlated (r = − 0.29, p < .001), such that older adolescents had smaller exponents (flatter PSDs). This association is stronger for adolescents in the non-ADHD control group (r = − 0.39, p < .001) than for adolescents with ADHD (r = − 0.21, p = .06). Below, we present a plot of the association between aperiodic exponents and age by ADHD status. fx1 5. Section 3.3 should read: “Adolescents with ADHD had smaller exponents relative to the control group (β = − .15, t(175) = − 2.04, p = .04), indicative of a flattened PSD (Fig. 1F). Power spectral densities for each condition by ADHD status (in log-log and semi-log) are presented in Fig. 1G–H. Exponents did not differ by stimulant medication history, t(172) = 0.18, p = .86. Regression analyses showed that, controlling for ADHD status, exponents were positively associated with SDRT (β = 0.20, p < .01), indicating that less intraindividual variability was related to a flattened PSD. Exponents were also associated with drift rate (β = − 0.19, p < .01); faster drift rate was related to a flattened PSD. These effects are plotted by ADHD status in Fig. 2. Exponents did not predict mean RT (β = − 0.02, p = .83), boundary separation (β = 0.04, p = .65), or non-decision time (β = − 0.03, p = .72). There was no significant interaction between ADHD status and aperiodic exponents on any of the reaction time or drift diffusion parameters (ps > 0.26). Results remained the same when adolescent sex was included in the model. Finally, results were similar when accounting for missingness via MICE (van Buuren and Groothuis-Oudshoorn, 2011). Adolescents with ADHD had smaller exponents relative to the control group, t(172.57) = − 1.99, p = .05). Controlling for ADHD status, exponents were significantly associated with SDRT (p < .01) and drift rate (p < .01). Exponents and did not predict mean RT (p = .98), boundary separation (p = .71), or non-decision time (p = .84). Posthoc analyses showed that results were similar when the 17 adolescents in the ADHD group at Year 1 who transitioned to the control group were excluded from the primary analyses.” 6. In the main text, Fig. 1 should appear as follows: Fig. 1 Distribution and group comparison of mean reaction time ( A ), reaction time variability ( B ), drift rate ( C ), boundary separation ( D ), non-decision time ( E ), and aperiodic exponents ( F ). Power spectral densities in semi-log and log-log space for both eyes-closed (solid lines) and eyes-open (dotted lines) averaged across adolescents in the ADHD (orange) and control (blue) groups are presented in subplots G and H , respectively. FOOOF (Donoghue et al., 2020a) removes periodic activity (putative oscillations) that rise above the aperiodic component of the neural signal, disentangling power spectral features that are thought to have distinct physiological mechanisms. We did not expect a knee in the PSD across the examined frequency range, nor did we observe one when visually inspecting each PSD after spectral parameterization via FOOOF. On average, we did observe an alpha ”bump” around ∼ 10 Hz as well as a smaller beta “bump” around ∼ 20 Hz, each of which is more prominent in the eyes closed relative to eyes open conditions, as would be expected. Fig. 1 7. In the main text, Fig. 1 should appear as follows: fx2 We have rechecked our analyses in detail to ensure there are no other errors. The authors would like to apologize for any confusion or inconvenience this error may have caused readers, other researchers, and the editors.

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          Author and article information

          Contributors
          Journal
          Dev Cogn Neurosci
          Dev Cogn Neurosci
          Developmental Cognitive Neuroscience
          Elsevier
          1878-9293
          1878-9307
          26 July 2023
          December 2023
          26 July 2023
          : 64
          : 101273
          Affiliations
          [a ]Department of Psychology, The Pennsylvania State University, United States
          [b ]Department of Psychology, University of Richmond, United States
          [c ]Department of Psychology, University of Utah, United States
          [d ]Department of Psychological Sciences, Purdue University, United States
          Author notes
          [* ]Corresponding author. bdo12@ 123456psu.edu
          Article
          S1878-9293(23)00078-6 101273
          10.1016/j.dcn.2023.101273
          10757306
          37500418
          c015feba-1dce-4923-8a16-75a0e83ff6aa
          © 2023 The Authors

          This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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          Neurosciences

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