Nano Neuro ( when risk taking becomes Suicidal Behavior )
Advancing wellbeing using new ways to communicate, understand, and respond to emotion.
The Affective Computing group aims to bridge the gap between human emotions and computational technology. Current research addresses machine recognition and modeling of human emotional expression, including the invention of new software and hardware tools to help people gather, communicate, and express emotional information, together with tools to help people better manage and understand the ways emotion impacts health, social interaction, learning, memory, and behavior. Our projects are diverse: from inventing ways to help people who face communication and emotion regulation challenges; to enabling customers to give rich emotional feedback; to quantifying patterns of autonomic activity (core emotional physiology) during seizures, stress-related disorders, and sleep.
"Kind and Grateful": Promoting Kindness and Gratitude with Pervasive Technology
Asma Ghandeharioun, Asaph Azaria, and Rosalind W. Picard
We have designed a novel system to promote kindness and gratitude. We leverage pervasive technologies to naturally embed gratitude inspiration in everyday life. Mobile sensor data is utilized to infer optimal moments for stimulating contextually relevant thankfulness and appreciation. We analyze the interplay between mood, contextual cues, and gratitude expressions.
Affective Response to Haptic signals
Grace Leslie, Rosalind Picard, Simon Lui, Suranga Nanayakkara
This study attempts to examine humans' affective responses to superimposed sinusoidal signals. These signals can be perceived either through sound, in the case of electronically synthesized musical notes, or through vibro-tactile stimulation, in the case of vibrations produced by vibrotactile actuators. This study is concerned with the perception of superimposed vibrations, whereby two or more sinusoisal signals are perceived simultaneously, producing a perceptual impression that is substantially different than of each signal alone, owing to the interactions between perceived sinusoidal vibrations that give rise to a unified percept of a sinusoidal chord. The theory of interval affect was derived from systematic analyses of Indian, Chinese, Greek, and Arabic music theory and tradition, and proposes a universal organization of affective response to intervals organized using a multidimensional system. We hypothesize that this interval affect system is multi-modal and will transfer to the vibrotactile domain.
Nanotechnologies for the study of the central nervous system
Description of novel nanotechnologies to deliver a translational bridge between basic and clinical neuroscience research.
Evaluation of novel in vitro and in vivo nanodiagnostic tools for neuroimaging and the study of structural/functional plasticity.
Novel approaches to modelling central nervous system development through recent advances in nano-modified array technologies to study functional circuit physiology.
The impact of central nervous system (CNS) disorders on the human population is significant, contributing almost €800 billion in annual European healthcare costs. These disorders not only have a disabling social impact but also a crippling economic drain on resources. Developing novel therapeutic strategies for these disorders requires a better understanding of events that underlie mechanisms of neural circuit physiology. Studying the relationship between genetic expression, synapse development and circuit physiology in CNS function is a challenging task, involving simultaneous analysis of multiple parameters and the convergence of several disciplines and technological approaches. However, current gold-standard techniques used to study the CNS have limitations that pose unique challenges to furthering our understanding of functional CNS development.
The recent advancement in nanotechnologies for biomedical applications has seen the emergence of nanoscience as a key enabling technology for delivering a translational bridge between basic and clinical research. In particular, the development of neuroimaging and electrophysiology tools to identify the aetiology and progression of CNS disorders have led to new insights in our understanding of CNS physiology and the development of novel diagnostic modalities for therapeutic intervention. This review focuses on the latest applications of these nanotechnologies for investigating CNS function and the improved diagnosis of CNS disorders.