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Abstract While large language models learn sound statistical representations of the language and information therein, ontologies are symbolic knowledge representations that can complement the former ideally. Research at this critical intersection relies on datasets that intertwine ontologies and text corpora to enable training and comprehensive benchmarking of neurosymbolic models. We present the MaterioMiner dataset and the linked materials mechanics ontology where ontological concepts from the mechanics of materials domain are associated with textual entities within the literature corpus. Another distinctive feature of the dataset is its eminently fine-grained annotation. Specifically, 179 distinct classes are manually annotated by three raters within four publications, amounting to 2191 entities that were annotated and curated. Conceptual work is presented for the symbolic representation of causal composition-process-microstructure-property relationships. We explore the annotation consistency between the three raters and perform fine-tuning of pre-trained language models to showcase the feasibility of training named entity recognition models. Reusing the dataset can foster training and benchmarking of materials language models, automated ontology construction, and knowledge graph generation from textual data.

Surfaces with tailored wettability have attracted considerable attention because of their wide range of potential applications. Wettability can be finely designed by controlling the chemistry and/or morphology of a surface. However, the commonly adopted analytical theories of Wenzel and Cassie-Baxter cannot describe a variety of intermediate and metastable states, being a thorough understanding of the combined chemical and morphological effect on surface wettability still lacking. Hence, the design and optimization of these surfaces is generally expensive and time-consuming. In this work, we propose a numerical method based on the phase-field model to predict the wettability of micro-structured surfaces and assist their design. First, we simulated the sessile droplet experiment on flat surfaces to calibrate model parameters. Second, we modelled several surface morphologies, intrinsic contact angles and droplet impact velocities. Finally, we produced and tested 3D printed flat and micro-structured samples to validate the phase-field model, obtaining a reasonable qualitative and quantitative agreement between numerical and experimental results. The validated model proposed here can help design and prototype surfaces with tailored wettability. Furthermore, integrated with atomistic/mesoscopic simulations, it represents the last step of a predictive multi-scale model, where both chemical and morphological features of surfaces can be designed a priori.

Uniaxial fatigue testing of micro-mechanical metallic specimens can provide valuable insight into damage formation. Magnetic and piezomagnetic testing are commonly used for qualitative characterization of damage in ferromagnetic specimens. Sensitive and accurate measurements with magnetic sensors is a key part of such a characterization. This work presents an experimental setup to induce structural defects in a micro-mechanical fatigue test. Simultaneously, the resulting piezomagnetic signals are measured during the complete lifetime of the tested specimen. The key component is a highly sensitive optically pumped magnetometer (OPM) used to measure the piezomagnetic hysteresis of a small specimen whose structural defects can be analyzed on a small scale by other metallographic characterization methods as well. This setup aims to quantify the magnetic signatures of damage during the fatigue process, which could enable non-destructive mechanical testing of materials. This paper reports the initial results obtained from this novel micro-magneto-mechanical test setup for a ferritic steel specimen.

Abstract Previous research on the neural correlates of consciousness (NCC) in visual perception revealed an early event-related potential (ERP), the visual awareness negativity (VAN), to be associated with stimulus awareness. However, due to the use of brief stimulus presentations in previous studies, it remains unclear whether awareness-related negativities represent a transient onset-related response or correspond to the duration of a conscious percept. Studies are required that allow prolonged stimulus presentation under aware and unaware conditions. The present ERP study aimed to tackle this challenge by using a novel stimulation design. Male and female human participants (n = 62) performed a visual task while task-irrelevant line stimuli were presented in the background for either 500 or 1000 ms. The line stimuli sometimes contained a face, which needed so-called visual one-shot learning to be seen. Half of the participants were informed about the presence of the face, resulting in faces being perceived by the informed but not by the uninformed participants. Comparing ERPs between the informed and uninformed group revealed an enhanced negativity over occipitotemporal electrodes that persisted for the entire duration of stimulus presentation. Our results suggest that sustained visual awareness negativities (SVAN) are associated with the duration of stimulus presentation.

Faces can acquire emotional meaning by learning to associate individuals with specific behaviors. Here, we investigated emotional evaluation and brain activations toward faces of persons who had given negative or positive evaluations to others. Furthermore, we investigated how emotional evaluations and brain activation generalize to perceptually similar faces. Valence ratings indicated learning and generalization effects for both positive and negative faces. Brain activation, measured with functional magnetic resonance imaging (fMRI), showed significantly increased activation in the fusiform gyrus (FG) to negatively associated faces but not positively associated ones. Remarkably, brain activation in FG to faces to which emotional meaning (negative and positive) was successfully generalized was decreased compared to neutral faces. This suggests that the emotional relevance of faces is not simply associated with increased brain activation in visual areas. While, at least for negative conditions, faces paired with negative feedback behavior are related to potentiated brain responses, the opposite is seen for perceptually very similar faces despite generalized emotional responses.

Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders of a given treatment) when using clinical routine data such as demographic and questionnaire data, while neuroimaging data achieved superior prediction accuracy. However, these studies may be considerably biased due to very limited sample sizes and bias-prone methodology. Adequately powered and cross-validated samples are a prerequisite to evaluate predictive performance and to identify the most promising predictors. We therefore analyzed resting state functional magnet resonance imaging (rs-fMRI) data from two large clinical trials to test whether functional neuroimaging data continues to provide good prediction accuracy in much larger samples. Data came from two distinct German multicenter studies on exposure-based CBT for anxiety disorders, the Protect-AD and SpiderVR studies. We separately and independently preprocessed baseline rs-fMRI data from n = 220 patients (Protect-AD) and n = 190 patients (SpiderVR) and extracted a variety of features, including ROI-to-ROI and edge-functional connectivity, sliding-windows, and graph measures. Including these features in sophisticated machine learning pipelines, we found that predictions of individual outcomes never significantly differed from chance level, even when conducting a range of exploratory post-hoc analyses. Moreover, resting state data never provided prediction accuracy beyond the sociodemographic and clinical data. The analyses were independent of each other in terms of selecting methods to process resting state data for prediction input as well as in the used parameters of the machine learning pipelines, corroborating the external validity of the results. These similar findings in two independent studies, analyzed separately, urge caution regarding the interpretation of promising prediction results based on neuroimaging data from small samples and emphasizes that some of the prediction accuracies from previous studies may result from overestimation due to homogeneous data and weak cross-validation schemes. The promise of resting-state neuroimaging data to play an important role in the prediction of CBT treatment outcomes in patients with anxiety disorders remains yet to be delivered.

Abstract Although highly effective on average, exposure-based treatments do not work equally well for all patients with anxiety disorders. The identification of pre-treatment response-predicting patient characteristics may enable patient stratification. Preliminary research highlights the relevance of inhibitory fronto-limbic networks as such. We aimed to identify pre-treatment neural signatures differing between exposure treatment responders and non-responders in spider phobia and to validate results through rigorous replication. Data of a bi-centric intervention study comprised clinical phenotyping and pre-treatment resting-state functional connectivity (rsFC) data of n = 79 patients with spider phobia (discovery sample) and n = 69 patients (replication sample). RsFC data analyses were accomplished using the Matlab-based CONN-toolbox with harmonized analyses protocols at both sites. Treatment response was defined by a reduction of >30% symptom severity from pre- to post-treatment (Spider Phobia Questionnaire Score, primary outcome). Secondary outcome was defined by a reduction of >50% in a Behavioral Avoidance Test (BAT). Mean within-session fear reduction functioned as a process measure for exposure. Compared to non-responders and pre-treatment, results in the discovery sample seemed to indicate that responders exhibited stronger negative connectivity between frontal and limbic structures and were characterized by heightened connectivity between the amygdala and ventral visual pathway regions. Patients exhibiting high within-session fear reduction showed stronger excitatory connectivity within the prefrontal cortex than patients with low within-session fear reduction. Whereas these results could be replicated by another team using the same data (cross-team replication), cross-site replication of the discovery sample findings in the independent replication sample was unsuccessful. Results seem to support negative fronto-limbic connectivity as promising ingredient to enhance response rates in specific phobia but lack sufficient replication. Further research is needed to obtain a valid basis for clinical decision-making and the development of individually tailored treatment options. Notably, future studies should regularly include replication approaches in their protocols.

Abstract While inattentional blindness and deafness studies have revealed neural correlates of consciousness (NCC) without the confound of task relevance in the visual and auditory modality, comparable studies for the somatosensory modality are lacking. Here, we investigated NCC using functional magnetic resonance imaging (fMRI) in an inattentional numbness paradigm. Participants (N = 44) received weak electrical stimulation on the left hand while solving a demanding visual task. Half of the participants were informed that task-irrelevant weak tactile stimuli above the detection threshold would be applied during the experiment, while the other half expected stimuli below the detection threshold. Unexpected awareness assessments after the experiment revealed that altogether 10 participants did not consciously perceive the somatosensory stimuli during the visual task. Awareness was not significantly modulated by prior information. The fMRI data show that awareness of stimuli led to increased activation in the contralateral secondary somatosensory cortex. We found no significant effects of stimulus awareness in the primary somatosensory cortex or frontoparietal areas. Thus, our results support the hypothesis that somatosensory stimulus awareness is mainly based on activation in higher areas of the somatosensory cortex and does not require strong activation in extended anterior or posterior networks, which is usually seen when perceived stimuli are task-relevant.

Abstract Negative emotional content is prioritized across different stages of information processing as reflected by different components of the event-related potential (ERP). In this preregistered study (N = 40), we investigated how varying the attentional focus allows us to dissociate the involvement of specific ERP components in the processing of negative and neutral words. Participants had to discriminate the orientation of lines overlaid onto the words, the word type (adjective/noun), or the emotional content (negative/neutral). Thus, attention was either not focused on words (distraction task), non-emotional aspects, or the emotional relevance of words. Regardless of the task, there were no significant differences between negative and neutral words for the P1, N1, or P2 components. In contrast, interactions between emotion and task were observed for the early posterior negativity (EPN) and late positive potential (LPP). EPN differences were absent during the distraction task but were present in the other two tasks. LPP emotion differences were found only when attention was directed to the emotional content of words. Our study adds to the evidence that early ERP components do not reliably separate negative and neutral words. However, results show that mid-latency and late stages of emotion processing are separable by different attention tasks. The EPN represents a stage of attentional enhancement of negative words given sufficient attentional resources. Differential activations during the LPP stage are associated with more elaborative processing of the emotional meaning of words.

This article details a correction to: Röseler, L., Weber, L., Helgerth, K., Stich, E., Günther, M., Tegethoff, P., … Schütz, A. (2022). The Open Anchoring Quest Dataset: Anchored Estimates from 96 Studies on Anchoring Effects. Journal of Open Psychology Data, 10(1), 16. DOI: https://doi.org/10.5334/jopd.67

Abstract Load theory assumes that neural activation to distractors in early sensory cortices is modulated by the perceptual load of a main task, regardless of whether task and distractor share the same sensory modality or not. While several studies have investigated the question of load effects on distractor processing in early sensory areas, there is no functional magnetic resonance imaging (fMRI) study regarding load effects on somatosensory stimuli. Here, we used fMRI to investigate effects of visual perceptual load on neural responses to somatosensory stimuli applied to the wrist in a study with 44 participants. Perceptual load was manipulated by an established sustained visual detection task, which avoided simultaneous target and distractor presentations. Load was operationalized by detection difficulty of subtle or clear color changes of one of 12 rotating dots. While all somatosensory stimuli led to activation in somatosensory areas SI and SII, we found no statistically significant difference in brain activation to these stimuli under high compared to low sustained visual load. Moreover, exploratory Bayesian analyses supported the absence of differences. Thus, our findings suggest a resistance of somatosensory processing to at least some forms of visual perceptual load, possibly due to behavioural relevance of discrete somatosensory stimuli and separable attentional resources for the somatosensory and visual modality.

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Abstract While perceptual load has been proposed to reduce the processing of task-unrelated stimuli, theoretical arguments and empirical findings for other forms of task load are inconclusive. Here, we systematically investigated the detection and neural processing of auditory stimuli varying in stimulus intensity during a stimuli-unrelated visual working memory task alternating between low and high load. We found, depending on stimulus strength, decreased stimulus detection and reduced P3, but unaffected N1 amplitudes of the event-related potential to auditory stimuli under high as compared to low load. In contrast, load independent awareness effects were observed during both early (N1) and late (P3) time windows. Findings suggest a late neural effect of visual working memory load on auditory stimuli leading to lower probability of reported awareness of these stimuli.

Abstract Prioritized processing of fearful compared to neutral faces is reflected in increased amplitudes of components of the event-related potential (ERP). It is unknown whether specific face parts drive these modulations. Here, we investigated the contributions of face parts on ERPs to task-irrelevant fearful and neutral faces using an ERP-dependent facial decoding technique and a large sample of participants (N = 83). Classical ERP analyses showed typical and robust increases of N170 and EPN amplitudes by fearful relative to neutral faces. Facial decoding further showed that the absolute amplitude of these components, as well as the P1, was driven by the low-frequency contrast of specific face parts. However, the difference between fearful and neutral faces was not driven by any specific face part, as supported by Bayesian statistics. Furthermore, there were no correlations between trait anxiety and main effects or interactions. These results suggest that increased N170 and EPN amplitudes to task-irrelevant fearful compared to neutral faces are not driven by specific facial regions but represent a holistic face processing effect.

Load Theory states that perceptual load prevents, or at least reduces, the processing of task-unrelated stimuli. This study systematically examined the detection and neural processing of auditory stimuli unrelated to a visual foreground task. The visual task was designed to create continuous perceptual load, alternated between low and high load, and contained performance feedback to motivate participants to focus on the visual task instead of the auditory stimuli presented in the background. The auditory stimuli varied in intensity, and participants signaled their subjective perception of these stimuli without receiving feedback. Depending on stimulus intensity, we observed load effects on detection performance and P3 amplitudes of the event-related potential (ERP). N1 amplitudes were unaffected by perceptual load, as tested by Bayesian statistics. Findings suggest that visual perceptual load affects the processing of auditory stimuli in a late time window, which is associated with a lower probability of reported awareness of these stimuli.

Thin, flat textile roofing offers negligible heat insulation. In warm areas, such roofing membranes are therefore equipped with metallized surfaces to reflect solar heat radiation, thus reducing the warming inside a textile building. Heat reflection effects achieved by metallic coatings are always accompanied by shading effects as the metals are non-transparent for visible light (VIS). Transparent conductive oxides (TCOs) are transparent for VIS and are able to reflect heat radiation in the infrared. TCOs are, e.g., widely used in the display industry. To achieve the perfect coatings needed for electronic devices, these are commonly applied using costly vacuum processes at high temperatures. Vacuum processes, on account of the high costs involved and high processing temperatures, are obstructive for an application involving textiles. Accepting that heat-reflecting textile membranes demand less perfect coatings, a wet chemical approach has been followed here when producing transparent heat-reflecting coatings. Commercially available TCOs were employed as colloidal dispersions or nanopowders to prepare sol–gel-based coating systems. Such coatings were applied to textile membranes as used for architectural textiles using simple coating techniques and at moderate curing temperatures not exceeding 130 °C. The coatings achieved about 90% transmission in the VIS spectrum and reduced near-infrared transmission (at about 2.5 µm) to nearly zero while reflecting up to 25% of that radiation. Up to 35% reflection has been realized in the far infrared, and emissivity values down to ε = 0.5777 have been measured.

Background: Fear generalization is pivotal for the survival-promoting avoidance of potential danger, but, if too pronounced, it promotes pathological anxiety. Similar to adult patients with anxiety disorders, healthy children tend to show overgeneralized fear responses. Objective: This study aims to investigate neuro-developmental aspects of fear generalization in adolescence – a critical age for the development of anxiety disorders. Methods: We compared healthy adolescents (14–17 years) with healthy adults (19–34 years) regarding their fear responses towards tilted Gabor gratings (conditioned stimuli, CS; and slightly differently titled generalization stimuli, GS). In the conditioning phase, CS were paired (CS+) or remained unpaired (CS-) with an aversive stimulus (unconditioned stimuli, US). In the test phase, behavioral, peripheral and neural responses to CS and GS were captured by fear- and UCS expectancy ratings, a perceptual discrimination task, pupil dilation and source estimations of event-related magnetic fields. Results: Closely resembling adults, adolescents showed robust generalization gradients of fear ratings, pupil dilation, and estimated neural source activity. However, in the UCS expectancy ratings, adolescents revealed shallower generalization gradients indicating overgeneralization. Moreover, adolescents showed stronger visual cortical activity after as compared to before conditioning to all stimuli. Conclusion: Various aspects of fear learning and generalization appear to be mature in healthy adolescents. Yet, cognitive aspects might show a slower course of development.

Several event-related potentials (ERPs) have been proposed as neural correlates of consciousness (NCC), most prominently the early visual awareness negativity (VAN) and the late P3b component. Highly influential support for the P3b comes from studies utilizing the attentional blink (AB), where conscious perception of a first visual target (T1) impairs reporting a second target (T2) presented shortly afterwards. Recent no-report studies using other paradigms suggest that the P3b component may reflect post-perceptual processes associated with decision-making rather than awareness. However, no-report studies are limited in their awareness assessment, and their conclusions have not been tested in an AB paradigm. The present study (N = 38) addressed these issues using a novel AB paradigm, which reduced decision-making processes by omitting a discrimination task on T2 stimuli and rendering their relevance uncertain. Nevertheless, awareness was assessed trial by trial. Comparing ERPs in response to seen versus unseen T2 stimuli revealed a VAN but no enhanced P3b regardless of whether they were marked as distinct from distractor stimuli or not. Our results corroborate the VAN and challenge the P3b as NCC despite rigorous trial-by-trial assessment of conscious perception. Thus, they support the idea that awareness emerges during early sensory processing.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

Detection of regularities and their violations in sensory input is key to perception. Violations are indexed by an early EEG component called the mismatch negativity (MMN) – even if participants are distracted or unaware of the stimuli. On a mechanistic level, two dominant models have been suggested to contribute to the MMN: adaptation and prediction. Whether and how context conditions, such as awareness and task relevance, modulate the mechanisms of MMN generation is unknown. We conducted an EEG study disentangling influences of task relevance and awareness on the visual MMN. Then, we estimated different computational models for the generation of single-trial amplitudes in the MMN time window. Amplitudes were best explained by a prediction error model when stimuli were task-relevant but by an adaptation model when task-irrelevant and unaware. Thus, mismatch generation does not rely on one predominant mechanism but mechanisms vary with task relevance of stimuli.

There is an ongoing debate on the neural correlates of consciousness (NCC) in the attentional blink (AB). Theoretical accounts propose that NCC during the attentional blink occur late in the processing hierarchy and that this quality is specific to the AB. We investigated this question by recording event-related potentials during an AB experiment with faces as T2. We analyzed ERPs to T2 stimuli inside (short lag) and outside (long lag) the AB window after carefully calibrating T2 stimuli to ensure equal visibility ratings across lags. We found that the N170, the visual awareness negativity (VAN), and the P3b showed an increased amplitude for seen compared to unseen face stimuli regardless of stimulus lag and that all these components scale linearly with subjective visibility. These findings suggest similar early and late mechanisms of graded perceptual awareness within and outside the AB across perceptual (N170, VAN) and post-perceptual (P3b) processing stages.

Neural mismatch responses have been proposed to rely on different mechanisms, including prediction error-related activity and adaptation to frequent stimuli. However, the hierarchical cortical structure of these mechanisms is unknown. To investigate this question, we recorded hemodynamic responses while participants (N = 54) listened to an auditory oddball sequence as well as a suited control condition. In addition to effects in sensory processing areas (Heschl's gyrus, superior temporal gyrus (STG)), we found several distinct clusters that indexed deviance processing in frontal and parietal regions (anterior cingulate cortex/supplementary motor area (ACC/SMA), inferior parietal lobule (IPL), anterior insula (AI), inferior frontal junction (IFJ)). Comparing responses to the control stimulus with the deviant and standard enabled us to delineate the contributions of prediction error- or adaptation-related brain activation, respectively. We observed significant effects of adaptation in Heschl's gyrus, STG and ACC/SMA, while prediction error-related activity was observed in STG, IPL, AI and IFJ. Additional dynamic causal modeling confirmed the superiority of a hierarchical processing structure compared to a flat structure. Thus, we found that while prediction-error related processes increased with the hierarchical level of the brain area, adaptation declined. This suggests that the relative contribution of different mechanisms in deviance processing varies across the cortical hierarchy.

Abstract Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA‐PGC PTSD sites underwent T1‐weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel‐wise (brainageR) and region‐of‐interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three‐way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age‐related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan.