The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis.

The large number of different analytical choices used by researchers is partly responsible for the challenge of replication in neuroimaging studies. For an exhaustive robustness analysis, knowledge of the full space of analytical options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable parameter choices. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the parameter settings within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) parameter tuning within steps, and 3) distinct sequencing of steps. We have developed a decision support application with high educational value called METEOR to facilitate access to the data in order to design well-informed robustness (multiverse) analysis.

Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment.

BACKGROUND: Mobile health (mHealth) solutions can improve the quality, accessibility, and equity of health services, fostering early rehabilitation. For individuals with hearing loss, mHealth apps might be designed to support the decision-making processes in auditory diagnostics and provide treatment recommendations to the user (eg, hearing aid need). For some individuals, such an mHealth app might be the first contact with a hearing diagnostic service and should motivate users with hearing loss to seek professional help in a targeted manner. However, personalizing treatment recommendations is only possible by knowing the individual's profile regarding the outcome of interest. OBJECTIVE: This study aims to characterize individuals who are more or less prone to seeking professional help after the repeated use of an app-based hearing test. The goal was to derive relevant hearing-related traits and personality characteristics for personalized treatment recommendations for users of mHealth hearing solutions. METHODS: In total, 185 (n=106, 57.3% female) nonaided older individuals (mean age 63.8, SD 6.6 y) with subjective hearing loss participated in a mobile study. We collected cross-sectional and longitudinal data on a comprehensive set of 83 hearing-related and psychological measures among those previously found to predict hearing help seeking. Readiness to seek help was assessed as the outcome variable at study end and after 2 months. Participants were classified into help seekers and nonseekers using several supervised machine learning algorithms (random forest, naïve Bayes, and support vector machine). The most relevant features for prediction were identified using feature importance analysis. RESULTS: The algorithms correctly predicted action to seek help at study end in 65.9% (122/185) to 70.3% (130/185) of cases, reaching 74.8% (98/131) classification accuracy at follow-up. Among the most important features for classification beyond hearing performance were the perceived consequences of hearing loss in daily life, attitude toward hearing aids, motivation to seek help, physical health, sensory sensitivity personality trait, neuroticism, and income. CONCLUSIONS: This study contributes to the identification of individual characteristics that predict help seeking in older individuals with self-reported hearing loss. Suggestions are made for their implementation in an individual-profiling algorithm and for deriving targeted recommendations in mHealth hearing apps.

The association of dispositional anxiety with the NoGo N2 under relaxation instruction vs. speed/accuracy instruction.

Prior research suggests that cognitive control, indicated by NoGo N2 amplitudes in Go/NoGo tasks, is associated with dispositional anxiety. This negative association tends to be reduced in anxiety-enhancing experimental conditions. However, anxiety-reducing conditions have not yet been investigated systematically. Thus, the present study compares the effect of a relaxation instruction with the conventional speed/accuracy instruction in a Go/NoGo task on the correlation of the NoGo N2 with two subconstructs of dispositional anxiety, namely anxious apprehension and anxious arousal. As the test of differences between correlations needs considerable statistical power, the present study was included into the multi-lab CoScience Project. The hypotheses, manipulation checks, and the main path of pre-processing and statistical analysis were preregistered. Complete data sets of 777 participants were available for data analysis. Preregistered general linear models revealed that the different instructions of the task (speed/accuracy vs. relaxation) had no effect on the association between dispositional anxiety and the NoGo N2 amplitude in general. This result was supported by Cooperative-Forking-Path analysis. In contrast, a preregistered latent growth model with categorical variables revealed that anxious arousal was a negative predictor of the NoGo N2 intercept and a positive predictor of the NoGo N2 slope. Non-preregistered growth models, allowing for correlations of anxious apprehension with anxious arousal, revealed that higher anxious apprehension scores were associated with more negative NoGo N2 amplitudes with increased relaxation. Results are discussed in the context of the compensatory error monitoring hypothesis and the revised Reinforcement Sensitivity Theory.

What to think or how to think - is symptom reduction in posttraumatic symptomatology associated with change in posttraumatic cognitions or perseverative thinking? A latent change score model approach.

OBJECTIVE: Patients with posttraumatic stress disorder (PTSD) report changes in what they think of the world and themselves, referred to as posttraumatic cognitions, and changes in how they think, reflected in increased perseverative thinking. We investigated whether pre-post therapy changes in the two aspects of thinking were associated with pre-post therapy changes in posttraumatic symptom severity. METHOD: 219 d clinic patients with posttraumatic stress symptoms received trauma-focused psychotherapy with cognitive behavioral and metacognitive elements. The posttraumatic cognitions inventory (PTCI), the perseverative thinking questionnaire (PTQ), and the Davidson trauma scale (DTS) were applied at two occasions, pre- and post-therapy. Using latent change score models, we investigated whether change in PTCI and change in PTQ were associated with change in DTS and its subscales. We then compared the predictive value of PTQ and PTCI in joint models. RESULTS: When jointly modeled, change in overall DTS score was associated with change in both PTCI and PTQ. Concerning DTS subscales, reexperiencing and avoidance were significantly associated with change in PTCI, but not in PTQ. CONCLUSION: Results indicate that both aspects of cognition may be valuable targets of psychotherapy. A focus on posttraumatic cognitions might be called for in patients with severe reexperiencing and avoidance.

To see or not to see: the parallel processing of self-relevance and facial expressions.

The self, like the concept of central "gravity", facilitates the processing of information that is directly relevant to the self. This phenomenon is known as the self-prioritization effect. However, it remains unclear whether the self-prioritization effect extends to the processing of emotional facial expressions. To fill this gap, we used a self-association paradigm to investigate the impact of self-relevance on the recognition of emotional facial expressions while controlling for confounding factors such as familiarity and overlearning. Using a large and diverse sample, we replicated the effect of self-relevance on face processing but found no evidence for a modulation of self-relevance on facial emotion recognition. We propose two potential theoretical explanations to account for these findings and emphasize that further research with different experimental designs and a multitasks measurement approach is needed to understand this mechanism fully. Overall, our study contributes to the literature on the parallel cognitive processing of self-relevance and facial emotion recognition, with implications for both social and cognitive psychology.

Are there good days and bad days for hearing? Quantifying day-to-day intraindividual speech perception variability in older and younger adults.

Moment-to-moment variations in hearing and speech perception have long been observed. Depending on the researcher's theoretical position, the observed fluctuations have been attributed to measurement error or to internal, nonsensory factors such as fluctuations in attention. While cognitive performance has been shown to fluctuate from day to day over longer time, such fluctuations have not been quantified for speech perception, despite being well-recognized by clinical audiologists and hearing-impaired patients. In three studies, we aimed to explore and quantify the magnitude of daily variability in speech perception and to investigate whether such variability goes beyond test unreliability. We also asked whether intraindividual variability depends on overall speech perception performance as observed in different groups of individuals. Older adults with objective hearing impairment and mostly hearing aids (N1 = 45), with subjective hearing problems but no hearing aids (N2 = 113), and younger adults without hearing problems (N3 = 20) participated in three ecological momentary assessment studies. They performed a digit-in-noise test two to three times a day for several weeks. Variance heterogeneous linear mixed-effects models indicated reliable intraindividual variability in speech perception and substantial individual differences in daily variability. A protective factor against daily fluctuations is a higher average speech perception. These studies show that day-to-day variations in speech perception cannot simply be attributed to test unreliability and pave the way for investigating how psychological states that do not vary from moment-to-moment, but rather from day to day, predict variations in speech perception. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Explicit face memory abilities are positively related to the non-intentional encoding of faces: Behavioral and ERP evidence.

Individual differences in face memory abilities have been shown to be related to individual differences in brain activity. The present study investigated brain-behavior relationships for the N250 component in event-related brain potentials, which is taken as a neural sign of face familiarity. We used a task in which a designated, typical target face and several (high- and low-distinctive) nontarget faces had to be distinguished during multiple presentations across a session. Separately, face memory/recognition abilities were measured with easy versus difficult tasks. We replicated an increase of the N250 amplitude to the target face across the session and observed a similar increase for the non-target faces, indicating the build-up of memory representations also for these faces. On the interindividual level, larger across-session N250 amplitude increases to low-distinctive non-target faces were related to faster face recognition as measured in an easy task. These findings indicate that non-intentional encoding of non-target faces into memory is associated with the swift recognition of explicitly learned faces; that is, there is shared variance of incidental and intentional face memory.

Comparing two relaxation procedures to ease fatigue in multiple sclerosis: a single-blind randomized controlled trial.

BACKGROUND: Various relaxation procedures have been proposed to reduce fatigue in multiple sclerosis (MS). However, it is unknown, which type of relaxation has the largest effect on fatigue reduction and on autonomic nervous system (ANS) activity. OBJECTIVE: We aimed to compare two biofeedback-supported relaxation exercises: a deep breathing (DB) exercise and progressive muscle relaxation (PMR), which may ameliorate MS fatigue and alter ANS activity. METHODS: We performed a single-blind randomized clinical trial, introducing MS patients (n = 34) to the DB or PMR exercise. We first tested cardiovagal integrity, reflected by changes in heart rate variability (HRV) in response to DB. Participants then performed a fatigue-inducing vigilance task, followed by the DB or PMR. State fatigue was recorded consecutively at baseline, after the vigilance task, and after the relaxation exercise, along with HRV reflecting ANS activity. RESULTS: Only patients assigned to the PMR group experienced a significant drop in fatigue, whereas both relaxation exercises changed ANS activity. MS patients showed the expected autonomic response during the cardiovagal reflex test. The vigilance task elevated short-term feelings of fatigue and significantly reduced HRV parameters of parasympathetic activity. Trait fatigue was negatively correlated with HRV during the second half of the vigilance task. CONCLUSION: PMR alleviates short-term feelings of fatigue in persons with MS. The vigilance task in combination with HRV measurements may be helpful for evaluating relaxation procedures as a treatment of fatigue. Hereby, future studies should ensure longer and more frequent relaxation exercises and focus on patients with weak to moderate fatigue. TRIAL REGISTRATION: Trial Registry: DRKS00024358.

Cognitive abilities are associated with specific conjunctions of structural and functional neural subnetworks.

Cognitive neuroscience assumes that different mental abilities correspond to at least partly separable brain subnetworks and strives to understand their relationships. However, single-task approaches typically revealed multiple brain subnetworks to be involved in performance. Here, we chose a bottom-up approach of investigating the association between structural and functional brain subnetworks, on the one hand, and domain-specific cognitive abilities, on the other. Structural network was identified using machine-learning graph neural network by clustering anatomical brain properties measured in 838 individuals enroled in the WU-Minn Young Adult Human Connectome Project. Functional network was adapted from seven Resting State Networks (7-RSN). We then analyzed the results of 15 cognitive tasks and estimated five latent abilities: fluid reasoning (Gf), crystallized intelligence (Gc), memory (Mem), executive functions (EF), and processing speed (Gs). In a final step we determined linear associations between these independently identified ability and brain entities. We found no one-to-one mapping between latent abilities and brain subnetworks. Analyses revealed that abilities are associated with properties of particular combinations of brain subnetworks. While some abilities are more strongly associated to within-subnetwork connections, others are related with connections between multiple subnetworks. Importantly, domain-specific abilities commonly rely on node(s) as hub(s) to connect with other subnetworks. To test the robustness of our findings, we ran the analyses through several defensible analytical decisions. Together, the present findings allow a novel perspective on the distinct nature of domain-specific cognitive abilities building upon unique combinations of associated brain subnetworks.

Evaluation of adjustment behaviour in a semi-supervised self-adjustment fine-tuning procedure for hearing aids.

OBJECTIVE: This study investigated the adjustment behaviour of hearing aid (HA) users participating in a semi-supervised self-adjustment fine-tuning procedure for HAs. The aim was to link behaviour with the reproducibility and duration of the adjustments. DESIGN: Participants used a two-dimensional user interface to identify their HA gain preferences while listening to realistic sound scenes presented in a laboratory environment. The interface allowed participants to adjust amplitude (vertical axis) and spectral slope (horizontal axis) simultaneously. Participants were clustered according to their interaction with the user interface, and their search directions were analysed. STUDY SAMPLE: Twenty older experienced HA users were invited to participate in this study. RESULTS: We identified four different archetypes of adjustment behaviour (curious, cautious, semi-browsing, and full-on browsing) by analysing the trace points of all measurements for each participant. Furthermore, participants used predominantly horizontal or vertical paths when searching for their preference. Neither the archetype, nor the search directions, nor the participants' technology commitment was predictive of the reproducibility or the adjustment duration. CONCLUSIONS: The findings suggest that enforcement of a specific adjustment behaviour or search direction is not necessary to obtain fast, reliable self-adjustments. Furthermore, no strict requirements with respect to technology commitment are necessary.

Preterm birth and neonatal white matter microstructure in in-vivo reconstructed fiber tracts among audiovisual integration brain regions.

Individuals born preterm are at risk of developing a variety of sequelae. Audiovisual integration (AVI) has received little attention despite its facilitating role in the development of socio-cognitive abilities. The present study assessed the association between prematurity and in-vivo reconstructed fiber bundles among brain regions relevant for AVI. We retrieved data from 63 preterm neonates enrolled in the Developing Human Connectome Project (http://www.developingconnectome.org/) and matched them with 63 term-born neonates from the same study by means of propensity score matching. We performed probabilistic tractography, DTI and NODDI analysis on the traced fibers. We found that specific DTI and NODDI metrics are significantly associated with prematurity in neonates matched for postmenstrual age at scan. We investigated the spatial overlap and developmental order of the reconstructed tractograms between preterm and full-term neonates. Permutation-based analysis revealed significant differences in dice similarity coefficients and developmental order between preterm and full term neonates at the group level. Contrarily, no group differences in the amount of interindividual variability of DTI and NODDI metrics were observed. We conclude that microstructural detriment in the reconstructed fiber bundles along with developmental and morphological differences are likely to contribute to disadvantages in AVI in preterm individuals.

Resting-state brain signal complexity discriminates young healthy APOE e4 carriers from non-e4 carriers.

It is well established that the e4 allele of the APOE gene is associated with impaired brain functionality and cognitive decline in humans at elder age. However, it is controversial whether and how the APOE e4 allele is associated with superior brain function among young healthy individuals, thus indicates a case of antagonistic pleiotropy of APOE e4 allele. Signal complexity is a critical aspect of brain activity that has been associated with brain function. In this study, the multiscale entropy (MSE) of resting-state EEG signals among a sample of young healthy adults (N = 260) as an indicator of brain signal complexity was investigated. It was of interest whether MSE differs across APOE genotype groups while age and education level were controlled for and whether the APOE genotype effect on MSE interacts with MSE time scale, as well as EEG recording condition. Results of linear mixed models indicate overall larger MSE in APOE e4 carriers. This genotype-dependent difference is larger at high as compared with low time scales. The interaction effect between APOE genotype and recording condition indicates increased between-state MSE change in young healthy APOE e4 carriers as compared with non-carriers. Because higher complexity is commonly taken to be associated with better cognitive functioning, the present results complement previous findings and therefore point to a pleiotropic spectrum of the APOE gene polymorphism.

The Open Virtual Mirror Framework for enfacement illusions : Enhancing the sense of agency with avatars that imitate facial expressions.

Enfacement illusions are traditionally elicited by visuo-tactile stimulation, but more active paradigms become possible through the usage of virtual reality techniques. For instance, virtual mirrors have been recently proposed to induce enfacement by visuo-motor stimulation. In a virtual mirror experiment, participants interact with an avatar that imitates their facial movements. The active control over the avatar greatly enhances the sense of agency, which is an important ingredient for successful enfacement illusion induction. Due to technological challenges, most virtual mirrors so far were limited to the imitation of the participant's head pose, i.e., its location and rotation. However, stronger experiences of agency can be expected by an increase in the avatar's mimicking abilities. We here present a new open-source framework for virtual mirror experiments, which we call the Open Virtual Mirror Framework (OVMF). The OVMF can track and imitate a large range of facial movements, including pose and expressions. It has been designed to run on standard computer hardware and easily interfaces with existing toolboxes for psychological experimentation, while satisfying the requirement of a tightly controlled experimental setup. Further, it is designed to enable convenient extension of its core functionality such that it can be flexibly adjusted to many different experimental paradigms. We demonstrate the usage of the OVMF and experimentally validate its ability to elicit experiences of agency over an avatar, concluding that the OVMF can serve as a reference for future experiments and that it provides high potential to stimulate new directions in enfacement research and beyond.

Evaluation of a semi-supervised self-adjustment fine-tuning procedure for hearing aids.

OBJECTIVE: This study investigated the effects of different adjustment criteria and sound scenes on self-adjusted hearing-aid gain settings. Self-adjusted settings were evaluated for speech recognition in noise, perceived listening effort, and preference. DESIGN: This study evaluated a semi-supervised self-adjustment fine-tuning procedure that presents realistic everyday sound scenes in a laboratory environment, using a two-dimensional user interface, and enabling simultaneous changes in amplitude and spectral slope. While exploring the two-dimensional space of parameter settings, the hearing-aid users were instructed to optimise either listening comfort or speech understanding. STUDY SAMPLE: Twenty experienced hearing aid users (median age 69.5 years) were invited to participate in this study. RESULTS: Adjustment criterion and sound scenes had a significant effect on preferred gain settings. No differences in signal-to-noise ratios required for 50% speech intelligibility or in the perceived listening effort were observed between the adjusted settings of the two adjustment criteria. There was a preference for the self-adjusted settings over the prescriptive first fit. CONCLUSIONS: Listeners could reliably select their preferred gains to the two adjustment criteria and for different speech stimuli.

A Lower-Class Advantage in Face Memory.

People remember what they deem important. In line with research suggesting that lower-class (vs. higher class) individuals spontaneously appraise other people as more relevant, we show that social class is associated with the habitual use of face memory. We find that lower-class (vs. higher class) participants exhibit better incidental memory for faces (i.e., spontaneous memory for faces they had not been instructed to memorize; Studies 1 and 2). No social-class differences emerge for faces participants are instructed to learn (Study 2), suggesting that this pattern reflects class-based relevance appraisals rather than memory ability. Study 3 extends our findings to eyewitness identification. Lower-class (vs. higher-class) participants' eyewitness accuracy is less impacted by the explicit relevance of a target (clearly relevant thief vs. incidental bystander). Integrative data analysis shows a robust negative association between social class and spontaneous face memory. Preregistration (Studies 1 and 3) and cross-cultural replication (Study 2) further strengthen the results.

Expert validation of prediction models for a clinical decision-support system in audiology.

For supporting clinical decision-making in audiology, Common Audiological Functional Parameters (CAFPAs) were suggested as an interpretable intermediate representation of audiological information taken from various diagnostic sources within a clinical decision-support system (CDSS). Ten different CAFPAs were proposed to represent specific functional aspects of the human auditory system, namely hearing threshold, supra-threshold deficits, binaural hearing, neural processing, cognitive abilities, and a socio-economic component. CAFPAs were established as a viable basis for deriving audiological findings and treatment recommendations, and it has been demonstrated that model-predicted CAFPAs, with machine learning models trained on expert-labeled patient cases, are sufficiently accurate to be included in a CDSS, but it requires further validation by experts. The present study aimed to validate model-predicted CAFPAs based on previously unlabeled cases from the same data set. Here, we ask to which extent domain experts agree with the model-predicted CAFPAs and whether potential disagreement can be understood in terms of patient characteristics. To these aims, an expert survey was designed and applied to two highly-experienced audiology specialists. They were asked to evaluate model-predicted CAFPAs and estimate audiological findings of the given audiological information about the patients that they were presented with simultaneously. The results revealed strong relative agreement between the two experts and importantly between experts and the prediction for all CAFPAs, except for the neural processing and binaural hearing-related ones. It turned out, however, that experts tend to score CAFPAs in a larger value range, but, on average, across patients with smaller scores as compared with the machine learning models. For the hearing threshold-associated CAFPA in frequencies smaller than 0.75 kHz and the cognitive CAFPA, not only the relative agreement but also the absolute agreement between machine and experts was very high. For those CAFPAs with an average difference between the model- and expert-estimated values, patient characteristics were predictive of the disagreement. The findings are discussed in terms of how they can help toward further improvement of model-predicted CAFPAs to be incorporated in a CDSS for audiology.

Assessing individual differences in face recognition: No impact of task design features on the structure of this ability.

The ability to remember faces is essential for everyday life, with deficits indicative of some neurological conditions. Face recognition ability tasks vary considerably in their design (i.e., use of the same or a different picture for learning and recall and inclusion or exclusion of nonface characteristics), which is known to impact performance levels. However, it is unknown whether these design features cause additional cognitive abilities to be assessed. We preregistered three hypotheses, namely performance on face recognition tasks can best be explained by: (Hypothesis 1) a single general face recognition ability; (Hypothesis 2) a general face recognition ability and an unrelated ability representing one's capacity to ignore external information when recognizing faces; and (Hypothesis 3) a general face recognition ability, a separable unrelated ability to ignore external information, and a third unrelated ability representing one's capacity to recognize faces specifically when different photographs of the same individual are used. During a controlled laboratory session, N = 176 adults (Mage = 25.52 years) completed 16 face recognition tasks that comprised different versions of the aforementioned task designs. With confirmatory factor analysis, we found support for Hypothesis 1, indicating that the rank order of participants regarding their face recognition ability does not meaningfully differ due to the different task designs, indicating additional abilities are not needed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Individual differences in white matter microstructure of the face processing brain network are more differentiated from global fibers with increasing ability.

Face processing-a crucial social ability-is known to be carried out in multiple dedicated brain regions which form a distinguishable network. Previous studies on face processing mainly targeted the functionality of face-selective grey matter regions. Thus, it is still partly unknown how white matter structures within the face network underpins abilities in this domain. Furthermore, how relevant abilities modulate the relationship between face-selective and global fibers remains to be discovered. Here, we aimed to fill these gaps by exploring linear and non-linear associations between microstructural properties of brain fibers (namely fractional anisotropy, mean diffusivity, axial and radial diffusivity) and face processing ability. Using structural equation modeling, we found significant linear associations between specific properties of fibers in the face network and face processing ability in a young adult sample (N = 1025) of the Human Connectome Project. Furthermore, individual differences in the microstructural properties of the face processing brain system tended toward stronger differentiation from global brain fibers with increasing ability. This is especially the case in the low or high ability range. Overall, our study provides novel evidence for ability-dependent specialization of brain structure in the face network, which promotes a comprehensive understanding of face selectivity.

What do neuroanatomical networks reveal about the ontology of human cognitive abilities?

Over the last decades, cognitive psychology has come to a fair consensus about the human intelligence ontological structure. However, it remains an open question whether anatomical properties of the brain support the same ontology. The present study explored the ontological structure derived from neuroanatomical networks associated with performance on 15 cognitive tasks indicating various abilities. Results suggest that the brain-derived (neurometric) ontology partly agrees with the cognitive performance-derived (psychometric) ontology complemented with interpretable differences. Moreover, the cortical areas associated with different inferred abilities are segregated, with little or no overlap. Nevertheless, these spatially segregated cortical areas are integrated via denser white matter structural connections as compared with the general brain connectome. The integration of ability-related cortical networks constitutes a neural counterpart to the psychometric construct of general intelligence, while the consistency and difference between psychometric and neurometric ontologies represent crucial pieces of knowledge for theory building, clinical diagnostics, and treatment.

Fiber tracing and microstructural characterization among audiovisual integration brain regions in neonates compared with young adults.

Audiovisual integration has been related with cognitive-processing and behavioral advantages, as well as with various socio-cognitive disorders. While some studies have identified brain regions instantiating this ability shortly after birth, little is known about the structural pathways connecting them. The goal of the present study was to reconstruct fiber tracts linking AVI regions in the newborn in-vivo brain and assess their adult-likeness by comparing them with analogous fiber tracts of young adults. We performed probabilistic tractography and compared connective probabilities between a sample of term-born neonates (N = 311; the Developing Human Connectome Project (dHCP, http://www.developingconnectome.org) and young adults (N = 311 The Human Connectome Project; https://www.humanconnectome.org/) by means of a classification algorithm. Furthermore, we computed Dice coefficients to assess between-group spatial similarity of the reconstructed fibers and used diffusion metrics to characterize neonates' AVI brain network in terms of microstructural properties, interhemispheric differences and the association with perinatal covariates and biological sex. Overall, our results indicate that the AVI fiber bundles were successfully reconstructed in a vast majority of neonates, similarly to adults. Connective probability distributional similarities and spatial overlaps of AVI fibers between the two groups differed across the reconstructed fibers. There was a rank-order correspondence of the fibers' connective strengths across the groups. Additionally, the study revealed patterns of diffusion metrics in line with early white matter developmental trajectories and a developmental advantage for females. Altogether, these findings deliver evidence of meaningful structural connections among AVI regions in the newborn in-vivo brain.