Identification of common human and mouse behavioral states

Anxiety disorders are the most common psychiatric illnesses of childhood and often have lifelong negative consequences. Current diagnostic methods rely on the presence of clinical symptoms, delaying implementation of interventions that may prevent anxiety onset or mitigate symptom intensity and resistance to treatment.

We are collaborating with clinicians at Boston Children’s Hospital to apply novel computational methods for identifying brain activity patterns in young children and in mice that can prospectively identify individuals at elevated risk for anxiety disorders. Detecting brain activity patterns that prospectively identify at-risk individuals will allow for early intervention to prevent the emergence of anxiety. In addition, determining patterns common to humans and animal models will enable basic research to elucidate causes of and treatments for anxiety in children.

We anticipate that this research will lead to routine screening that will enable at-risk children to be identified well in advance of becoming symptomatic and to be treated with therapies that target their specific pathology as determined via animal research.