 Autism and autism spectrum disorders refers to complex disorders of brain development characterized by difficulties in social communication and interaction, and in some individuals by intellectual disability, problems with sleep and gastrointestinal disturbances. Autism has widespread impact globally. The US Centers for Disease Control reported recently that 1 in 68 US children fall on the autism spectrum. A roughly 10-fold increase in prevalence over the last 40 years. Other countries report similar incidents, about 1% of the population in China and slightly more than that in South Korea. Recent estimates indicate that the lifetime cost of caring for a child with autism is roughly $3.5 to $5 million, and the US faces roughly $90 billion in annual costs for the education and treatment of individuals with autism. Although we do not know what causes autism, it's likely that a combination of autism risk genes and environmental factors such as parental age, maternal illness, and environmental toxins combine to alter early development. The most obvious signs of autism emerge at about two to three years of age, at which point the diagnosis is made. It is crucial, however, that we begin to identify early markers of autism. For earlier intervention, to maximally improve positive outcomes in the long run. Many neuroimaging studies have sought autism biomarkers, for example, by analyzing structures such as the amygdala, the cerebellum, the corpus callosum, amongst many others. These studies typically have about 20 to 30 individuals in each of the groups, and surprisingly, there have not been consistent results, and there is very little agreement on an autism marker from such studies. Recently, there's been a concerted effort to develop international collaborations for aggregating massive data sets for the analysis of autism brain scans. In the Abide Database, for example, 20 sites have archived more than thousands of brain scans from individuals with autism age six to 35 years old, and technology has made it possible to archive these massive data sets and to access them for careful analysis. There are also now automated data pipelines that allow us to rapidly evaluate in a fine-grained fashion the nature of these scans. In one recent study, for example, we took hundreds of measurements from each of thousands of brains from individuals with autism and matched control individuals, and measured, for example, volume differences in the amount of gray matter, white matter, cerebrospinal fluid, in the overall morphometry of the brain, in the cortical thickness. Surprisingly, in this massive analysis of the data, we did not find any robust distinct difference between the autism and the control brains, and this indicated to us that the key distinction may be in the way the brain functions rather than in the structure, per se. And so we have turned our efforts to examine the nature of the neural computation in the autism brain, the nature of the functional activation. And in particular, we've targeted those areas of the brain responsible for coding visual input, auditory input, and tactile input. This is particularly irrelevant because individuals with autism often report sensory changes with lights being too bright, sounds being too loud, and touch being too intense or painful. Examining sensory differences then may provide us with a useful biomarker to differentiate autism from typical controls. In one recent study, we had participants lie in a 3D Tesla brain magnet, and we showed them visual stimuli over and over again, and then extracted the cortical activation signal, say, from early visual cortex. As you see in the middle panel, there were no changes in the overall strength or magnitude of the signal. The big difference came in the noise or the fluctuations, the variability that was evident in the brains of the individuals with autism. This neural inconsistency or brain noise may serve as a signature biomarker to differentiate adults with autism from the population at large, and potentially even, it might be a useful biomarker to apply to babies with autism. My question today then, and the key challenge to the global community, is A, how can we urgently and rapidly uncover a robust, distinct signature of autism? And ultimately, how can we implement this in large-scale brain screening, perhaps even in newborn infants? The early diagnosis of autism is crucial and can potentially transform the lives of those individuals, their families and communities.