The Picower Institute Spring 2023 Symposium "Environmental and Social Determinants of Child Mental Health
Studies show that abuse, neglect or trauma during childhood can lead to lifelong struggles including with mental health. Fortunately research also indicates that solutions and interventions at various stages of life can be developed to help. But even among people who remain resilient or do not experience acute stresses, a lack of opportunity early in life due to poverty or systemic racism can still constrain their ability to realize their full potential. In what ways are health and other outcomes affected by early life difficulty? What can individuals and institutions do to enhance opportunity?" "This daylong event will feature talks by neuroscientists, policy experts, physicians, educators and activists as they discuss how our experiences and biology work together to affect how our minds develop and what can be accomplished in helping people overcome early disadvantages.
The Picower Institute Spring 2021 Symposium: Early Life Stress & Mental Health
Though studies show that abuse, neglect or trauma during childhood can lead to lifelong lifelong struggles including in mental health, research also indicates that solutions and interventions at various stages of life can be developed to help. And while many people manage to remain resilient, a lack of opportunity early in life, including because of poverty and systemic racism, can constrain their ability to realize their full potential. In what ways are health and other outcomes affected? How can systems instead restore opportunity? "The Picower Institute for Learning and Memory's biennial spring symposium, 'Early Life Stress & Mental Health,' will examine these issues. The daylong event will feature talks by neuroscientists, policy experts, physicians, educators and activists as they discuss how our experiences and biology work together to affect how our minds develop and what can be accomplished in helping people overcome early disadvantages.
Portable neuroscience: using devices and apps for diagnosis and treatment of neurological disease
Scientists work in laboratories; comfortable spaces which we equip and configure to be ideal for our needs. The scientific paradigm has been adopted by clinicians, who run diagnostic tests and treatments in fully equipped hospital facilities. Yet advances in technology mean that that increasingly many functions of a laboratory can be compressed into miniature devices, or even into a smartphone app. This has the potential to be transformative for healthcare in developing nations, allowing complex tests and interventions to be made available in every village. In this talk, I will give two examples of this approach from my recent work. In the field of stroke rehabilitation, I will present basic research which we have conducted in animals over the last decade. This reveals new ways to intervene and strengthen surviving pathways, which can be deployed in cheap electronic devices to enhance functional recovery. In degenerative disease, we have used Bayesian statistical methods to improve an algorithm to measure how rapidly a subject can stop an action. We then implemented this on a portable device and on a smartphone app. The measurement obtained can act as a useful screen for Parkinson’s Disease. I conclude with an outlook for the future of this approach, and an invitation to those who would be interesting in collaborating in rolling it out to in African settings.
Multilevel Causal Modeling
Complex systems can be modeled at various levels of granularity, e.g., we can model a person at the cognitive level, on the neuronal level, or down to the biochemical level. When multiple models represent the same system at different scales, we would like to be able to reason about the causal effects of interventions on each level in such a way that the models remain consistent across levels. In the first part of this talk, I consider which conditions must be fulfilled for two structural equation models (SEMs) to stand in such a causally consistent relation. In the second part of the talk, I present recent work on learning causally consistent SEMs across multiple levels, distinguishing between bottom-up (micro- to macro-level) and top-down (macro- to micro-level) approaches.