NeuroBLOG

*Emerging trends in neuroscience* Key Points: • An explainable machine learning model using simple baseline data (personality, sleep, education) predicted who would respond to qEEG-informed neurofeedback for ADHD with about 88% accuracy. • Specific personality traits linked to emotional stability, organization, openness and interpersonal style – plus years of education – emerged as key predictors of treatment response. • This work supports a more personalized approach to ADHD neurofeedback, where clinical decision-making integrates psychological profiles, lifestyle factors and EEG-guided protocols instead of relying on “one-size-fits-all” training.

*Emerging trends in neuroscience* Key points : • An eight-week Digital Yoga Therapy program combining yoga, HRV biofeedback, and EEG-based monitoring led to robust improvements in attention, hyperactivity, and autonomic regulation in children with ADHD. • The intervention integrates Ayurvedic concepts, Vedantic awareness practices, and yogic ethics into a structured, AI-adaptive digital platform, offering a culturally grounded yet scientifically rigorous approach. • Findings highlight the potential of biofeedback-augmented contemplative practices as an adjunct to standard ADHD treatments, while raising important questions about long-term outcomes, ethics, and the role of human guidance.

*Emerging trends in neuroscience* Key Points : • The brain can evaluate what to choose and how sure we are about that choice at the same time, not in two separate steps. • Neurons in the lateral intraparietal area (LIP) track a decision variable that supports both choice and confidence, with strongly overlapping but partially separable population codes. • These findings strengthen the idea that metacognitive signals like confidence are embedded directly in sensorimotor circuits, with important implications for how we design neurofeedback and biofeedback protocols that target decision-making and self-awareness.

*Emerging trends in neuroscience* Key Points: • A new simulation framework (DecNefLab) lets researchers test decoded fMRI neurofeedback protocols in silico before running real human experiments. • The framework shows how design choices – especially the classifier’s alternative class, the learner’s starting state, and randomness in strategy – can create apparent “non-responders” or misleadingly good feedback. • By separating latent cognitive states from observable brain signals, DecNefLab challenges the assumption that good decoding equals meaningful brain change, and offers a path to more robust, interpretable neurofeedback.

*Emerging trends in neuroscience( Key Points: • Heart-rate biofeedback can be woven directly into tabletop game mechanics to shape tension, cooperation, deception, and strategy, without sacrificing the tactile, social essence of board games. • Through an 18-month Research-through-Design process, Tu and colleagues developed One Pulse: Treasure Hunter, a social deduction game where live heart-rate data drives missions, failures, and hidden information. • The design trade-offs they identify—how to display physiology, how seating and space change interaction, and how fair it is to use HR in deception—offer rich lessons for biofeedback and neurofeedback clinicians wanting more playful, engaging training environments.

*Emerging trends in neuroscience* Key Points: • Public trust in science has eroded due to limited engagement, communication gaps, and increasing politicization of scientific issues. • The authors argue that scientists must adopt a new model of open communication and advocacy to rebuild credibility and broaden understanding. • Restoring trust requires transparency, humility, and genuine dialogue across ideological, cultural, and disciplinary divides.