An esteemed professor, once renowned for his ability to explain intricate topics like seamless switching of a plug-in hybrid vehicle between battery power and fuel, suddenly began to struggle during his lectures. Midway through his talks, his speech would falter, and over time he gradually lost his ability to command a hall with the same confidence and clarity that had once captivated large audiences. The condition responsible for this devastating decline was Amyotrophic Lateral Sclerosis (ALS), a progressive neurodegenerative disease. Another well-known exceptional person who lived with the same condition was the renowned physicist Dr. Stephen Hawking. This disease initially attacks the nerve cells in the brain and spinal cord that control voluntary muscle movements. As the disease progresses, these neurons degenerate and die, leading to increasing muscle weakness, loss of motor function, and, ultimately, paralysis. 

To help the professor, whose speech has deteriorated and to translate his thoughts into a talk for the family and clients, a neurotechnology startup Neuralink has designed their latest implant. The developed Neuralink electrodes were implanted in the speech region of his brain, and then the waves that his thoughts form were transliterated by the brain-computer interface (BCI) into speech. These brain computer interfaces are the direct communication pathways translating electrical brain activity into digital commands to control external devices without using muscles.  

Brain signals collected by sensors or electrodes are extremely noisy and full of background biological chatter. Artificial intelligence (AI) classifies these physiological signals and translates them into real-time operational commands for external hardware, screens, or robotic devices faster and more accurately than the traditional programming technologies, opening a world full of possibilities for the patients struggling with their day-to-day work 

 By merging AI's machine learning capabilities with neural engineering, the interfaces have evolved from basic research concepts into powerful tools creating real-time medical and consumer technologies. This cross-disciplinary amalgamation of computer science, neuroscience and robotics assists upgradation of next generation medical devices. Constant advancement in the machine learning field has taken increases the outreach from labs to wider audiences making them more and more inclusive and sustainable for the layman, aligning with the goal of SDG 9 community.  

 Artificial intelligence and neurotechnology have the potential to transform neurological care, but their successful adoption will ultimately depend on public trust. Building and sustaining this trust requires responsible development, transparent communication and reporting, meaningful public engagement, and robust ethical oversight. Without these foundations, even technologies with substantial potential benefits may struggle to achieve public legitimacy and widespread adoption. We at Springer Nature are constantly putting in efforts to make the research and editorial community aware of the technological advancements and how those can be fruitful for mankind. We invite researchers to submit relevant work to our open collections and contribute evidence that advances artificial intelligence and neuroscience research and align with SDG 9: industry innovation and infrastructure  

 The collections below provide dedicated publication opportunities across three complementary areas of reproductive and maternal health. 

Submit Your Research to Scientific Reports  and Discover Neuroscience open Collections 

•  Biophysics of Neuroscience  

This Collection is focused on the application of principles of physics and methods to understand the nervous system. It combines neuroscience, physics, and biology to investigate the complex interactions within and between neurons, neural networks, and the brain as a whole. This field explores the physical aspects of neural function, including electrical, mechanical, and fluidic properties, using an experimental approach. 

•  Systems Neuroengineering to understand the brain 

This Collection will bring together interdisciplinary research on neuroimaging, both structural and functional (MRI), computational neuroscience, neural signal processing, neural interfacing and decoding, and neuromodulation. Systems engineering studies in humans and animal models that advance our understanding of neural circuitry function and modulation are welcome. 

•  AI based Neurotechnologies 

This Collection comprises original research articles focusing on brain-computer interfaces and imaging, machine learning, brain mapping, EEG analysis, non-invasive brain stimulation techniques, cognitive computing, neural data science, and computational modelling.  

• Translational Multimodal Neuroimaging in Dementia: Linking Brain Phenotypes to Disease Biology 

This Collection explores how multimodal neuroimaging can improve our understanding of dementia, enhancing biological interpretability and translational relevance. Particular interest is given to AI-driven analytics, machine learning, and computational methods that integrate complex datasets, identify predictive biomarkers, and improve early detection. 

•  Artificial Intelligence and Internet of Things for Smart Healthcare and Well-Being

This collection focuses on integrating IoT technologies with Artificial Intelligence (AI) and Machine Learning (ML) to advance healthcare, remote monitoring, rehabilitation, and assistive systems. It highlights the growing role of connected devices, wearable sensors, and smart healthcare infrastructures in enabling early diagnosis, personalized treatment, and improved patient outcomes. 

 Why Submit Your Research to Open Collections?  

• Contribute evidence relevant to SDG 9, reach a global research audience, strengthen the evidence-based clinical practice and transform neurological care.  

• Researchers, clinicians, and public health experts are invited to submit relevant work to these open collections. Contributions can showcase innovative research, strengthen collaboration, and accelerate discoveries that inform clinical practice and technological development.