NOÏSIS startup

At NOïSIS, our mission is to significantly improve the development of treatments for patients with brain disorders by making useful and informative analytical services to monitor the brain state in longitudinal studies.  We founded our startup company NOïSIS as part of our vision.  We are truly focused on exploring the measurement of brain states to provide a quantitative approach for evaluating the effectiveness of novel drugs and therapies.

background – the mind

Cognition :  An Ancient Greek term, noïsis or νόησις stands for idea, reasoning or mind, or more precisely, human cognition.  Preserving cognitive capacity is the ultimate objective in medicine.  Mental well-being is the outcome measure which matters the most to patients and their loved ones.  The burden of mental illness to society is paramount.  In fact, disorders of the central nervous system costs our society more than all other medical disorders combined, worldwide.

The Brain, a ‘black box’ :  The brain translates a gamete of electric activity across the scalp surface, though its intrinsic pro­cesses remain largely hidden in what we casually call a black box.  However, advances in neuroscience and com­pu­ta­tional mathematics imply that offspring tech­niques can foster fundamentally new and useful insights into neural processes and hence lead up to a diagnostic modelling of brain states

our vision – brain state imaging

Monitoring the Mind : Developing novel therapeutic agents requires monitoring the safety and efficacy of treatments through quantitative outcome measures.   A myriad of unidentified factors influence an individual’s cognitive performance, be that neurological, metabolic or toxic in origin, disease, or other variables such as medical interventions, like chemotherapy.

Brain State Imaging : At Harvard University, our founders had developed BSI, a hypothesis-free data-driven approach (pdf) using traditional technology to account for such unknowns in time and space of functional MRI data in the course of studying learning disabilities.

Deep learning : As emerging innovations in the field of artificial intelligence (AI) and deep learning mature, we will enhance our former approach for extracting clinically-relevant markers from complex brain signals, such as electro-encephalograms (EEG) recorded from common electrodes.   We expect that by harnessing AI, we can unmask healthful from harmful effects upon cognition that are inherent to treatment.  We believe that AI can empower the medical com­munity to monitor cognitive integrity on neurobiological grounds.

relevant publications

Below a list of relevant scientific publications about Brain State Imaging (see BSI and pdf ) :

  • Morocz IA et al.  Time-resolved and spatio-temporal analysis of complex cognitive processes and their role in disorders like developmental dyscalculia.  Int J Imaging Syst Technol.  22(1):81-96, 2010.
  • Janoos F et al.  Spatio-temporal models of mental processes from fMRI.  Neuroimage.  57(2):362-377, 2011.
  • Janoos F et al.  State-space analysis of working memory in schizophrenia – an fBIRN study.  Psychometrica.  78(2):279-307, 2013.
  • Janoos F et al.  State-space models of mental processes from fMRI.  Inf Process Med Imaging.  22:588-599, 2011.
  • Firdaus F et al.  Idenitification of recurrent patterns in the activation of brain networks.  NIPS.  25:683-691, 2012.