We’re excited to welcome you to an extraordinary event dedicated to the latest advancements, pioneering research, and forward-thinking innovations in neuroscience, was slated on October 09-10, 2025 in Tokyo, Japan. Whether you're a seasoned researcher, a practicing clinician, or simply passionate about the brain, this conference offers a unique platform to connect with leading experts, share knowledge, and explore the complexities of the nervous system.
Throughout this conference, you'll have the opportunity to immerse yourself in keynote presentations, interactive workshops, and engaging discussions spanning topics from neurotechnology and brain mapping to cognitive neuroscience and neurological disorders.
Thank you for joining us on this remarkable exploration of neuroscience’s cutting-edge. We anticipate an inspiring, insightful, and intellectually stimulating event!
The Neuroscience 2025 Conference is a pivotal gathering of the brightest minds exploring the intricate workings of the human brain. With the rapid advancement of technologies like neuroimaging, AI, and computational neuroscience, this event offers a platform where innovation meets the frontier of human understanding.
The conference also offered numerous workshops, allowing participants to engage in hands-on activities and discussions. Provide an ideal platform to meet and interact with fellow researchers, professionals, and industry leaders in the neuroscience field. Building these connections can lead to collaborations, job opportunities, and mentorship.
By attending a neuroscience conference, individuals from these diverse backgrounds can enhance their knowledge, contribute to discussions, and build relationships that advance their careers and the field of neuroscience as a whole.
Industry Professionals
Business Leaders and Executives
Academics and Researchers
Entrepreneurs and Start-ups
Vendors and Sponsors
Policy Makers and Government Officials
Students and Early Career Professionals
General Enthusiasts
Attending a conference is an investment in yourself and your career, offering a mix of education, networking, and inspiration.
Attending a conference offers a wide range of benefits, including:
Access to Resources
Motivation and Inspiration
Registering for a conference is essential to gain access to the unique opportunities and secure a chance to grow, connect and gain insights that can drive your personal and professional success.
The global neuroscience market, valued at $42.5 billion in 2022, is expected to grow at a 5.56% CAGR, reaching $65.2 billion by 2030. This growth is driven by the rising prevalence of neurological disorders like Alzheimer's, which affects over 6 million Americans. Advances in neuroimaging and the integration of digital health solutions, including brain-computer interfaces, are enhancing diagnostics and treatments. North America leads the market due to its established healthcare infrastructure, while the Asia Pacific region is also experiencing rapid growth. Technological innovations and increased healthcare investments are key factors driving market expansion.
A recent study explores the relationship between brain connectivity and intelligence, highlighting the value of interpretability in predictive modeling for deeper insights into human cognition.
Machine learning in neuroscience
Neuroscientific research on human cognition has evolved from focusing on single-variable explanatory studies to employing machine learning-based predictive modeling. This shift enables the analysis of relationships between behavior and multiple neurobiological variables to forecast behavior across diverse samples.
Intelligence, a key predictor of life outcomes such as health and academic achievement, has been extensively studied, with theories dividing it into fluid and crystallized components. Recent machine learning approaches have enhanced intelligence prediction using brain connectivity data. However, limited conceptual insights, reliance on specific intelligence measures, and methodological constraints highlight the need for further research to systematically explore predictive brain features.
The present study adhered to a rigorous methodology, with all analyses, sample sizes, and variables preregistered on the Open Science Framework. The primary analyses followed preregistered protocols, with additional post hoc analyses conducted to further explore brain connections most relevant for intelligence prediction.
Study participants were drawn from the Human Connectome Project (HCP) Young Adult Sample S1200, consisting of 1,200 individuals between 22 and 37 years of age. Informed consent was obtained in accordance with the Declaration of Helsinki and all procedures were approved by the Washington University Institutional Review Board.
After exclusions for missing data, cognitive impairment based on Mini-Mental State Examination (MMSE) scores of 26 and less, or excessive head motion, the final sample included 806 participants, 418 of whom were female and 733 right-handed. Measures of intelligence including general intelligence (gg), crystallized intelligence (gCgC), and fluid intelligence (gFgF) were estimated using bi-factor and exploratory factor analyses from cognitive test scores.
Functional magnetic resonance imaging (fMRI) data were collected during resting state and seven cognitive tasks to construct subject-specific functional connectivity (FC) matrices. Minimally pre-processed fMRI data underwent additional preprocessing steps, including nuisance regression, global signal correction, and removal of task-evoked activation, to improve connectivity estimates. Predictive modeling utilized feedforward neural networks, which incorporated five-fold cross-validation, hyperparameter optimization, and an out-of-sample deconfounding approach to control for covariates such as age, sex, and head motion.
Model interpretability was enhanced using layer-wise relevance propagation (LRP) to identify functional brain connections most critical for predictions. External replication was performed using two independent d