ABSTRACT
Contents Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288 14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288 14.2 Functional connectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
14.2.1 Why do ndings diverge? . . . . . . . . . . . . . . . . . . . . . . . 290 14.2.2 Challenge no. 1: “Resting” state . . . . . . . . . . . . . . . . . . 294 14.2.3 Challenge no. 2: Dynamic connectivity . . . . . . . . . . . . 295
14.3 Anatomical connectivity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297 14.3.1 Findings in children, adolescents, and adults . . . . . . . . 298 14.3.2 Findings in infants and toddlers . . . . . . . . . . . . . . . . . . 299 14.3.3 Challenge no. 1: Understanding microstructural
underpinnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 14.3.4 Challenge no. 2: Complex ber orientations . . . . . . . . 300 14.3.5 Challenge no. 3: Motion . . . . . . . . . . . . . . . . . . . . . . . . 301
14.4 Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 14.4.1 A developmental model of neurofunctional
organization in ASD . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 14.4.2 From genes to treatment: Can neuroimaging
bridge the gap? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307
Abstract Beyond the general consensus of ASD being a brain-based disorder, there is increasing evidence of anomalies in network organization and connectivity. However, the abundance of ndings is coupled with low replication rates. In this chapter, we review some main ndings from functional and anatomical connectivity research in ASD. Major methodological challenges in functional connectivity and diffusion weighted MRI and potential solutions are discussed. A developmental model of dual network impairment is presented that reconciles some apparent inconsistencies in ndings, followed by a discussion of conceptual challenges and the importance of data-driven approaches.
