Nathan Spreng, PhD
Nathan Spreng is studying how brain networks underlie various cognitive processes, such as the ability to store and retrieve information and how we use that knowledge to make decisions. His laboratory explores the dynamics of large neural networks and their role in cognition. Current studies focus on attention, memory, cognitive control and social cognition, as well as the interacting networks of the brain that support them. We are actively involved in the development and application of multi-variable, network-based statistical approaches to assess brain structure, connectivity and brain activity.
Schmitz, TW & Spreng, RN (2016). Basal forebrain degeneration precedes the cortical spread of Alzheimer's pathology. Nature Communications, 7, 13249.
Turner, GR & Spreng, RN (2015). Prefrontal commitment and reduced default network suppression co-occur and are dynamically coupled in older adults. Journal of Cognitive Neuroscience, 27, 2462-2476.
Spreng, RN, DuPre, E., Selarka, D., Garcia, J., Gojkovic, S., Mildner, J., Luh, W.-M. & Turner, GR (2014). Goal-congruent default network activity facilitates cognitive control. Journal of Neuroscience, 34, 14108-14111.
Andrews-Hanna, JR, Smallwood, J & Spreng, RN (2014). The default network and self-generated thought: Component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences, 1316, 29-52.
Spreng, RN, Sepulcher, J., Turner, GR, Stevens, WD & Schacter, DL (2013). Intrinsic architecture underlying the relationships among the default, dorsal attention, and frontoparietal control networks of the human brain. Journal of Cognitive Neuroscience, 25, 74-86.
Spreng, RN, Stevens, WD, Chamberlain, J., Gilmore, AW & Schacter, DL (2010). Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition.NeuroImage, 53, 303-317.
Spreng, RN, Mar, RA & Kim, ASN (2009). The common neural basis of autobiographical memory, prospecting, navigation, theory of mind and the default mode: A quantitative meta-analysis. Journal of Cognitive Neuroscience, 21, 489-510.
