There are relatively few studies on ikigai that go beyond older adults in Japan, and there is a lack of research focusing on the link between ikigai and hikikomori. Thus, we aimed to examine the association between ikigai (having purpose and meaning in life) and hikikomori (experiencing extreme social withdrawal) in the German adult population. Data came from an online quota survey of the German general adult population (n = 3270 individuals; 18 to 74 years, average age 47 years). Data collection took place in January 2025. The validated German versions of the 25-item Hikikomori Questionnaire and Ikigai-9 scale were used to quantify key variables. Unadjusted and adjusted logistic regression analyses were performed among the total sample and additionally stratified by gender and age group. Higher ikigai levels were associated with significantly lower odds of being a hikikomori (e.g., in the fully adjusted model OR 0.91, 95
Objective: This study introduces and validates a digital twin brain framework designed to translate an individual’s brain connectome into predictions of multitask neurobehavioral dynamics and personalized functional modulations. Impact Statement: We introduce a novel 2-component architecture—where a hypernetwork personalizes a main network from an individual’s connectome—establishing a mechanistic platform to simulate and design personalized interventions by directly linking connectomes to behavior. Introduction: Personalized psychiatry requires digital twin models that can predict functions across multiple domains, such as affective and cognitive processing, from an individual’s unique neurobiology. However, existing models struggle to bridge the gap between brain structure and complex, multitask behavior, limiting their clinical utility. Methods: A hypernetwork uses an individual’s resting-state connectome to generate parameters for a main recurrent neural network that simulates participant-specific behavioral and blood-oxygen-level-dependent (BOLD) time series across tasks. Leveraging the model’s end-to-end architecture linking connectomes to behavior, we used gradient backpropagation to identify connectome manipulations designed to selectively modulate affective or cognitive functions. Results: Validated on 228 individuals, the model predicted behavioral choices with over 90% accuracy, reaction times (r > 0.85), and BOLD patterns (r = 0.84) with high fidelity. Crucially, in silico interventions successfully modulated targeted functions and reproduced realistic, interindividual variability in treatment effects arising from each person’s baseline connectome. Conclusion: This digital twin brain system enables high-fidelity, in silico prediction and personalized modulation of complex neurobehavioral functions, advancing the potential for individualized psychiatric care.
Delandistrogene moxeparvovec is a recombinant adeno-associated virus rhesus isolate serotype 74 vector-based gene therapy that addresses the absence of functional dystrophin in Duchenne muscular dystrophy (DMD). EMBARK is a phase 3, two-part, crossover, randomized, placebo-controlled trial assessing the safety and efficacy of delandistrogene moxeparvovec (single intravenous dose 1.33 × 1014 vector genomes/kg) in ambulatory male patients with DMD aged 4 to < 8 years; N = 125. One-year results demonstrated the manageable safety of delandistrogene moxeparvovec, consistent with previous clinical trials. The primary endpoint (change from baseline in North Star Ambulatory Assessment [NSAA] total score at 52 weeks compared with placebo) did not meet statistical significance. However, key secondary endpoints, comprising timed function tests, suggested slowing or stabilization of disease progression with delandistrogene moxeparvovec, which could become increasingly evident over longer periods of time. We report 2-year follow-up of safety and functional outcomes in patients receiving delandistrogene moxeparvovec in EMBARK part 1. As a result of the crossover study design, 2-year functional outcomes of patients receiving delandistrogene moxeparvovec in part 1 of EMBARK were compared, by pre-specified analysis, with a matched propensity score-weighted external control (EC). At 2 years, EMBARK patients showed statistically significant benefit versus the EC cohort in functional outcomes prognostic for delaying loss of ambulation (NSAA, Time to Rise, 10-m Walk/Run), demonstrating sustained stabilization or slowing of disease progression. Delandistrogene moxeparvovec micro-dystrophin expression and sarcolemmal localization were maintained over 64 weeks. No new safety signals were observed between week 52 and week 104. Between baseline and week 104, there were no treatment-related deaths, study discontinuations due to adverse events, or clinically significant complement-mediated adverse events. At 2 years, stabilization or slowing of DMD disease progression was observed in ambulatory male patients with DMD aged 4 to < 8 years receiving delandistrogene moxeparvovec versus a matched EC cohort. Safety was consistent with EMBARK 1-year data and manageable with appropriate monitoring. NCT05096221.
PurposeNeuromelanin-sensitive imaging visualizes degeneration of the substantia nigra pars compacta (SNc) and locus coeruleus (LC), characteristic features of Parkinson's disease (PD). Spectral presaturation with inversion recovery (SPIR), using fat-selective radiofrequency pulses, has been reported to provide superior delineation of the SNc and LC in healthy individuals and offers shorter acquisition times than conventional magnetization transfer (MT) imaging. This study evaluated the clinical utility of SPIR imaging for assessing PD compared with MT imaging.MethodsNeuromelanin-sensitive images were acquired from 24 patients with PD and 24 healthy controls using MT and SPIR sequences, each with an acquisition time of approximately five minutes. Signal ratios (SRs) of the SNc and LC were automatically quantified using established brain atlases. For each sequence and brain region, diagnostic performance in distinguishing PD from controls was assessed using receiver operating characteristic curve analysis. In patients with PD, associations between SRs and nigrostriatal degeneration, as measured by dopamine transporter SPECT imaging, were investigated.ResultsSPIR images yielded higher SRs in the SNc than MT images. Diagnostic accuracy for PD with SPIR imaging (87.50%) was significantly greater than that with MT imaging (77.08%). SRs of the SNc and LC on SPIR images were correlated with nigrostriatal degeneration on dopamine transporter SPECT, unlike MT images.ConclusionSPIR imaging demonstrated superior visualization of the SNc and LC, and outperformed MT imaging in the evaluation of PD. With shorter acquisition time and stronger correlation with nigrostriatal degeneration, SPIR represents a promising and practical tool for diagnosing and monitoring PD.
Value-based decision making emerges from coordinated neural dynamics across distributed brain networks. Recent studies using noninvasive whole-brain measurements in humans have highlighted the importance of neural activity in the 2–10 Hz frequency band for value-based decision making. Using magnetoencephalography and hidden Markov model (HMM) analysis, we examined whether and how whole-brain neural dynamics in this frequency band, evolving on a timescale of a few hundred milliseconds, reflect value-based decision processes. Thirty-five healthy adults (females and males) made binary choices between risky and sure options. Trial-wise subjective values were estimated using behavioral economic modeling based on prospect theory. We found that HMM-derived trial-by-trial whole-brain neural dynamics (defined by 2–10 Hz amplitude envelopes in distributed brain regions and their interregional coupling) were associated with the subjective values of choice options in a manner distinct from simple perceptual- or motor-evoked activity. Notably, these trial-by-trial whole-brain dynamics covaried with the difference in subjective values between the chosen and unchosen options when the neural data were time-locked to participants' responses, but not when time-locked to option onset. These findings revealed a crucial link between subsecond whole-brain neural dynamics and trial-by-trial decision variables, providing insights into how value-based decision processes unfold over time in the human brain.
