Researchers at Weill Cornell Medicine have utilised advanced machine learning techniques to identify three distinct subtypes of Parkinson’s disease, potentially paving the way for more personalised treatment approaches.
A groundbreaking neuroimaging study has identified distinct patterns of brain activation associated with various forms of love, offering new insights into the neural underpinnings of this complex emotion.
Researchers at the RIKEN Center for Brain Science in Japan have identified a new type of grid cell in the brain that predicts an animal’s future position, shedding light on how we navigate a spatial environment.
Groundbreaking research led by Karolinska Institutet reveals significantly elevated risks of mortality and morbidity for pregnant women with epilepsy and their babies, emphasising the need for specialised care throughout pregnancy and beyond.
A groundbreaking study from Princeton University has uncovered new insights into how our brains synchronise during verbal communication, demonstrating that specific words activate mirror patterns of brain activity in both speakers and listeners.
A groundbreaking study from Finnish researchers uncovers alarming trends in early-onset dementia among working-age adults, with Alzheimer’s disease cases nearly doubling over the past decade.
A groundbreaking MIT study published in Nature offers new insights into the cellular mechanisms underlying Alzheimer’s disease, revealing potential targets for interventions to maintain cognitive function.
Neurotechnology firm Synchron has announced the incorporation of OpenAI’s generative artificial intelligence (AI) into its brain-computer interface (BCI) platform, introducing a novel chat feature. This integration aims to enhance the capabilities of Synchron’s BCI technology, enabling individuals with severe paralysis and loss of upper limb mobility to interact with digital interfaces through thought alone.
A groundbreaking study led by Stanford Medicine researchers has unveiled six distinct biological subtypes of depression using brain imaging and machine learning techniques. This discovery could change the approach to diagnosing and treating depression, potentially leading to more effective, personalised interventions.
April 2024
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Pärttyli Rinne et al 2024, Aalto University
Tsai Lab/ MIT Picower Institute