Research
At Bitsphi we conduct research in the fields of neuroscience, psychology, information theory and artificial intelligence to derive novel paradigms in the assessment of cognitive function in general, and the diagnose of ADHD in particular.
Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental condition characterised by high levels of inattention, hyperactivity or impulsivity that usually manifest since childhood. Global estimations of the prevalence of ADHD are higher than 5% in children and teenagers and 2.5% in adults.
However, despite the high prevalence, the gold-standard diagnosis of ADHD depends on subjective clinical interviews and therefore, the expertise of the clinician, which sometimes leads to erroneous diagnosis and the wrong treatment.
Prevalence is according to the World Health Organization (WHO).
For this reason, Bitsphi has developed a novel cognitive model based on Shannon’s Information Theory that, in combination with a Go/No-Go cognitive task that includes contextual and episodic top-down violations, allow us to discern healthy individuals from ADHD patients based on their brain connectivity patterns.
The mathematical model has been validated using Magnetoencephalography (MEG) recordings at the Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CBT) (Madrid, Spain). We are currently working on validating the same results using Electroencephalography (EEG).
Based on the results obtained, we believe that Bitsphi has discovered a useful biomarker that will help healthcare professionals to make informed diagnoses, and thus opens the way for the use of Electroencephalography (EEG) to support the effective, fast and precise diagnosis of ADHD.
Bitsphi Diagnosis was founded with a strong research focus, recognized by the Innovative SME seal awarded by the Ministry of Science, Innovation, and Universities. This commitment was further strengthened in 2024 with the support of a Torres Quevedo Grant.
Torres Quevedo Program Grant PTQ2023-013279, contract funded by MCIU/AEI/10.13039/501100011033.
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Funded by the European Union NextGenerationEU
This company is capitalized by Innvierte, an investment program of CDTI.