Social and Affective Neuroscience Conference 2019 Symposium 5: Social Neuroinformatics and Big Data Michael Cole, Brain network organization as the computational architecture of cognition: Implications for emotion regulation and mental health Understanding neurocognitive computations–such as those involved in social and affective processing–will require not just localizing cognitive information distributed throughout the brain but also determining how that information got there. Brain connectivity clearly has something to do with it, and decades of “connectionist” (and recent“deep learning”) theory suggests connectivity patterns specify distributed neural computations. I will share my laboratory’s efforts to map the human brain’s large-scale functional network organization and to determine how that organization shapes distributed cognitive processes. First, we have identified a role for large-scale cognitive control networks in the regulation of mental health, especially emotion regulation in the context of depression. Second, we found that whole-brain functional network organization is only minimally altered between mentally healthy and unhealthy individuals, across those with autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. This suggests that the emotion dysregulation inherent in a variety of mental disorders may result from relatively small changes in large-scale functional brain network organization. Consistent with this, we developed an “activity flow” framework, which demonstrates that relatively small changes to the brain’s network organization can result in large alterations in task-related brain activations. These findings provide hope that small, well-targeted alterations to brain network organization may provide meaningful improvements for a variety of mental disorders.