Tonya White

Artificial intelligence (AI) is increasingly being explored and adopted across the research lifecycle, from idea generation and literature discovery to data analysis, manuscript preparation, and editorial and peer-review processes. This perspective provides an overview of AI’s role across the stages of scientific research. We describe emerging tools and workflows, illustrating how AI can assist researchers by aggregating and synthesizing a large body of work across various domains, supporting methodological implementation, and facilitating communication and publication. We also discuss their shortcomings, including surface-level reasoning, the fabrication of plausible but incorrect outputs, and the challenges posed by the fact that researchers new to a field may not know which questions to ask or which nuances to interrogate. In addition, we discuss recent advances toward more agentic and end-to-end AI systems, highlighting both their technical feasibility and the challenges they pose for validation, oversight, and responsible use. For each stage of the research lifecycle, we outline key limitations of current AI systems and propose practical considerations, what researchers should and should not do to support rigorous and ethical integration of AI into scientific workflows. This integration requires coordinated frameworks across the ecosystem. Journals, funding agencies, universities, and policymakers play essential roles in defining standards for transparency and accountability, while individual researchers remain responsible for methodological rigor and validity of reported results.

Both brain and behavior undergo considerable changes during adolescence, a time synonymous with the emergence several psychiatric disorders, including mood and psychotic disorders. Multiple studies have explored the interaction between brain and behavior during childhood and adolescence, with both mixed and convergent findings between the studies. One challenge is that different longitudinal models can be applied to both the same or similar dataset and yet yield different results. Without knowing the ground truth, the best modeling approach to understanding the brain/behavior interplay during development remains unclear. Within this context, simulated datasets can provide a mechanism to test many different neurodevelopmental features, not only regarding the interplay between brain and behavior, but also how specific epidemiologic factors can influence study findings. Simulated datasets have the ‘ground truth’ relationships embedded within the models used to create these datasets. Thus, the goal of this study was to assess the epidemiologic and clinical characteristics of 15 large simulated longitudinal neuroimaging datasets, independently created from five research groups from three different continents. We found that while most of the neuroimaging and behavioral trajectories in the simulated datasets reflected growth patterns identified in the literature, there was also considerable variability between how the groups modeled the epidemiologic, clinical, and neurodevelopmental growth patterns. The conclusion is that while simulation studies are an underused strategy to test assumptions related to neurodevelopmental disorders, simulation studies require iterative approaches, testing simulated against real-world data and challenging the different assumptions associated with the neurodevelopmental models, until there is convergence between actual and simulated datasets.

Adults with sickle cell disease (SCD) are at risk of decline in brain health and cognition, even without clinical stroke. SCD-related changes on MRI include brain atrophy and T2 fluid attenuated inversion recovery (FLAIR) white matter hyperintensity (WMH) growth. Hematopoietic stem cell transplant (HSCT) can be curative, but conditioning regimens risk new complications, particularly for adults with accumulated organ damage. We tested whether successful HSCT for adults with SCD was associated with reduced brain atrophy or WMH growth. In this cohort study, adults with severe SCD underwent HSCT as part of 5 research protocols at the National Institutes of Health Clinical Center, including autologous gene therapy, HLA-matched donor HSCs, and haploidentical HSCs. Serial brain MRI scans acquired before and after transplant for up to 12 years included 3D T1-weighted and axial FLAIR sequences. Longitudinal brain volumes, segmented using FreeSurfer and corrected for total intracranial volume (TICV), were used to measure brain parenchymal fraction (BPF). A deep learning algorithm segmented WMH volumes from FLAIR sequences. Volumes were log₂-transformed as a percentage of TICV. We tested whether HSCT success (persistent engraftment vs graft failure) or change in hemoglobin (Hb) (post-pre-HSCT) was associated with the rate of brain atrophy or WMH growth using mixed-effects linear regression. Random effects included scanner, participant intercept, and slope, while fixed effects included age and sex. Seventy-seven participants (mean age 32 ± 9 years, 43% female) who underwent HSCT were followed for a median 5.3 years (interquartile range [IQR] = 4.6). For 65 participants with successful HSCT, BPF declined nonsignificantly (-0.055%/year; 95% CI -0.12, 0.006; p = 0.08). Twelve participants with graft failure had a 7-fold greater BPF decline (-0.42%/year; 95% CI -0.57, -0.26; p < 0.001; group difference p < 0.001). A smaller change in Hb after HSCT was associated with steeper BPF decline (0.035%/year per unit Hb; 95% CI 0.017, 0.053; interaction p < 0.001). WMH growth was similar in both groups (0.038% vs 0.030% per year; interaction p = 0.50) and was associated with older age and baseline WMHs, but not treatment success. Successful HSCT was associated with preserved brain volume, but not WMH growth, another brain health biomarker. Whether these HSCT-related brain structural changes translate to cognitive preservation remains to be determined. ClinicalTrials.gov NCT02140554 registered 2014-05-14, first enrollment February 2015; ClinicalTrials.gov NCT00061568; registered 2004-07-16, first enrollment July 2004; ClinicalTrials.gov NCT02105766; registered 2014-04-01, first enrollment April 2014; ClinicalTrials.gov NCT03077542; registered 2017-03-10, first enrollment April 2017; ClinicalTrials.gov NCT00977691; registered 2009-12-14, first enrollment December 2009. This study provides Class III evidence that in adults with sickle cell disease, successful hematopoietic stem cell transplant is associated with slower declines in BPFs over a median period of 5 years, compared with patients with transplant failure.

Introduction: Anorexia nervosa (AN) and autism are distinct conditions, yet individuals with AN often exhibit elevated autistic traits. These traits are linked to complex clinical presentations, but their impact on AN remains unclear. This longitudinal study investigates associations between autistic traits, AN symptoms, and weight recovery in adolescents with first‐onset AN. Methods: The study compared 66 females with first‐onset AN and 64 typically developing (TD) controls. Autistic traits, AN symptoms, and weight recovery were assessed using the Social Responsiveness Scale (SRS), Eating Disorder Examination (EDE),and standardized deviation score for weight‐for‐height (SDS weight‐for‐height). Measurements at baseline and 1 year later were analyzed using linear regression models. Results: Adolescents with AN exhibited higher baseline autistic traits than TD controls. Over 1 year, AN symptoms and SDS weight‐for‐height improved significantly in the AN group, while autistic traits remained stable. No significant associations were found between baseline autistic traits and clinical outcomes or between changes in autistic traits, AN symptoms, and SDS weight‐for‐height. Discussion: The stability of autistic traits despite improvements in AN symptoms and weight suggests these traits may not influence the initial trajectory of first‐onset AN in adolescence. Further longitudinal research is needed to explore their long‐term impact on AN progression.

Introduction: While global brain volume differences between males and females have been shown to manifest during prenatal life, it is unclear whether global differences remain stable or show variability over the lifespan. Therefore, our goal was to use the existing literature coupled with large-population-based studies to assess age-related differences in effect size estimates of brain size between males and females over the life-span. Methods: We quantified effect size measures (Cohen’s d) of sex differences in terms of head circumference using data drawn from the literature of prenatal (14 weeks to birth) ultrasounds of n = 36,487 uncomplicated healthy births and direct postnatal (0–7 years) head circumference measurements from 85,598 children. The effect size of sex differences of cortical surface area, cortical thickness, and cortical volume were also computed from structural magnetic resonance imaging data from 25,846 healthy individuals aged 5–89 years. Results: Head circumference was consistently larger in males from fetal life through early childhood, with effect sizes typically ranging from ∼0.3 to 0.5 across studies and developmental stages. Males exhibited greater surface area and cortical volume across development, with effect sizes increasing from ∼0.4 at age 5 to ∼1.4 by age 24, after which they remained relatively stable. Cortical thickness showed a female advantage during childhood that diminished by mid-adolescence. Conclusion: The effect size of sex differences in global brain metrics does not remain constant across the lifespan. The underlying mechanisms are likely to involve endocrine and other neurodevelopmental processes. Future studies, especially preclinical and longitudinal studies beginning in the prenatal period may offer insight into the underlying mechanisms and the potential for translation of these findings, assessing the curves in patients with neurodevelopmental disorders.

Recent evidence suggests the brain’s major excitatory neurotransmitter, glutamate, plays a key role in attention-deficit/hyperactivity disorder (ADHD). Here we ask if glutamate also plays a role in the variable clinical courses of ADHD. While some children ‘grow out’ of ADHD by adolescence, others experience persistent symptoms into adulthood. Prior work implicates structural and functional differences in medial prefrontal cortex as pivotal in these different ADHD symptom courses, and we now ask if glutamate developmental change also contributes. Given the role of glutamate in neurotransmission, we also investigate potential impacts on the brain’s intrinsic connectivity. Using a glutamate-specific magnetic resonance spectroscopy sequence at 3 T, we analyzed 241 spectra on 161 participants, including 69 with persistent ADHD, 20 with remitting ADHD, and 72 never affected controls. Intrinsic functional connectivity was also assessed in a subset of 104 participants with 141 functional MRI scans. Using linear mixed models, we found an age-related increase in medial prefrontal glutamate in the persistent ADHD group which differed significantly from an age-related decrease among those who remitted and the never affected controls. Furthermore, altered prefrontal glutamate concentrations were associated with changes in intrinsic connectivity between the default mode network (which includes medial frontal cortex) and subcortical regions. These findings may indicate altered maturation of glutamate in the medial prefrontal cortex in youth with persistent ADHD.

The OHBM Brainhack 2023 integrated educational innovation, creative expression, and scientific exploration to cultivate a dynamic and inclusive environment for learning and collaboration. The event featured two main components: the Train-Track, which provided structured and flexible hands-on training in a study group setting, and the Hack-Track, where participants engaged in open-source project development. To enhance engagement, the Buddy System facilitated peer support, ensuring newcomers felt welcomed within the Brainhack community. A novel addition to this year’s event was the Rhyming Battle, which encouraged participants to creatively express their experiences through scientific humor and artistic wordplay. Additionally, the introduction of the Mini-Grant Initiative aimed to recognize projects that prioritized open science, diversity, and interdisciplinary collaboration. While this initiative received mixed feedback due to its competitive nature, it provided valuable insights for future iterations. Here we reflect on the successes and lessons learned from Brainhack 2023, underscoring the collective impact of these initiatives.