scholarly journals Individual differences in functional brain connectivity predict temporal discounting preference in the transition to adolescence

2018 ◽  
Vol 34 ◽  
pp. 101-113 ◽  
Author(s):  
Jeya Anandakumar ◽  
Kathryn L. Mills ◽  
Eric A. Earl ◽  
Lourdes Irwin ◽  
Oscar Miranda-Dominguez ◽  
...  
2018 ◽  
Vol 40 (6) ◽  
pp. 1887-1897 ◽  
Author(s):  
Tanveer Talukdar ◽  
Marta K. Zamroziewicz ◽  
Christopher E. Zwilling ◽  
Aron K. Barbey

2016 ◽  
Vol 12 (11) ◽  
pp. e1005178 ◽  
Author(s):  
Elizabeth N. Davison ◽  
Benjamin O. Turner ◽  
Kimberly J. Schlesinger ◽  
Michael B. Miller ◽  
Scott T. Grafton ◽  
...  

Author(s):  
Olaf Sporns

The connectome refers to a comprehensive network map of the connectivity of the nervous system. Such network maps are composed of sets of neural elements, which may correspond to individual neurons or brain areas, and their interconnections, which may correspond to synaptic links or inter-areal pathways. Connectome maps, at a given level of scale, provide a complete and systematic account of brain connectivity that portrays a complete set of anatomical or physiological relationships. This chapter provides an overview of the origins and definitions of the concept and its application to structural and functional brain connectivity, brief surveys of the major findings on the topology of the human connectome and how its connectivity structure shapes dynamic brain activity, and a selection of current themes in the study of individual differences in development and clinical populations.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Carsten Gießing ◽  
Mohsen Alavash ◽  
Christoph S. Herrmann ◽  
Claus C. Hilgetag ◽  
Christiane M. Thiel

2018 ◽  
Author(s):  
Jeya Anandakumar ◽  
Kathryn L. Mills ◽  
Eric Earl ◽  
Lourdes Irwin ◽  
Oscar Miranda-Dominguez ◽  
...  

AbstractThe transition from childhood to adolescence is marked by distinct changes in behavior, including how one values waiting for a large reward compared to receiving an immediate, yet smaller, reward. While previous research has emphasized the relationship between this preference and age, it is also proposed that this behavior is related to circuitry between valuation and cognitive control systems. In this study, we examined how age and intrinsic functional connectivity strength within and between these neural systems relate to changes in discounting behavior across the transition into adolescence. We used mixed-effects modeling and linear regression to assess the contributions of age and connectivity strength in predicting discounting behavior. First, we identified relevant connections in a longitudinal sample of 64 individuals who completed MRI scans and behavioral assessments 2-3 times across ages 7-15 years (137 scans). We then repeated the analysis in a separate, cross-sectional, sample of 84 individuals (7-13 years). Both samples showed an age-related increase in preference for waiting for larger rewards. Connectivity strength within and between valuation and cognitive control systems accounted for further variance not explained by age. These results suggest that individual differences in functional neural organization can account for behavioral changes typically associated with age.


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