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    • Similarly in human participants there is evidence of hippoca

    2018-11-07

    Similarly, in human participants, there is evidence of hippocampal activation as measured by magnetoencephalography (MEG) during performance of transverse patterning (Hanlon et al., 2003; Moses et al., 2009). Interestingly, hippocampal activity decreased and MTL cortical activity increased when semantic meaningfulness of the cues increased. Furthermore, and pertinent to the present findings, MEG showed that patterns of stronger right hippocampal lateralization, which was the mature pattern of activity, correlated highly with accurate performance on transverse patterning, particularly in younger subjects (11–14 years old) as compared to older teens (15–18) or adults (Hopf et al., 2013). Given the established role for the hippocampus in the spatial domain, the fact that both spatial and nonspatial relational memory abilities are both impacted by hippocampal damage and yet mature somewhat later than other spatial memory processes suggests a possible role for other later developing structures in the relational memory network. For example, the prefrontal cortex, which is late developing in monkeys and humans (e.g. Fuster, 2002; Goldman-Rakic, 1987; Malkova et al., 2014; Nejime et al., 2015; Tsujimoto, 2008) may contribute to relational memory in the spatial or nonspatial domain. Indeed, electrophysiological studies in macaques showed task specific firing of prefrontal order GS-9620 in the dorsolateral and medial prefrontal regions during performance of a transverse patterning task (Nejime et al., 2015), and human subjects showed increases in prefrontal activity with increased ‘meaningfulness’ of stimuli (Moses et al., 2009).
    Conflict of interest
    Acknowledgements Funding: This project was funded in part by the Intramural Research Program of the National Institute of Mental Health/National Institutes of Health/Department of Health and Human Services; and by NIMH grantMH58846 and NICHD grant HD35471 to JB. Writing of this manuscript was supported in part by ORIP/OD P51OD011132 (formerly NCRR P51RR000165).
    Introduction Selective attention refers to the ability to prioritize relevant stimuli in the presence of irrelevant, competing distractors (Desimone and Duncan, 1995; Hillyard et al., 1973; Serences and Kastner, 2014). This ability is proposed to be fundamental for the foundations of language, memory, literacy, and mathematics (Astheimer and Sanders, 2012; Casco et al., 1998; Commodari and Di Blasi, 2014; Markant and Amso, 2014; Stevens and Bavelier, 2012). In addition, the neural mechanisms of selective attention have been associated with key cognitive skills, such as visual working memory and nonverbal intelligence, both in adults and children (Gazzaley, 2011; Giuliano et al., 2014; Isbell et al., 2016). An extensive body of research has examined how early experiences relate to and modify the development of the neural mechanisms underlying selective attention. This research reveals the contributions of a wide range of experiential factors, including early sensory deprivation (Bavelier et al., 2000; Neville and Lawson, 1987), socioeconomic status (D\'Angiulli et al., 2008; Stevens et al., 2014), music training (Strait et al., 2015), and targeted prevention and intervention programs (Neville et al., 2013; Stevens et al., 2008, 2013). In comparison, relatively little is known about how genetic factors associate with the development of neural mechanisms of selective attention, especially in early childhood. Yet it has been argued that combining neuroscience methods with the study of alleles of specific candidate genes carries the potential to improve our understanding of how individual differences in cognitive abilities emerge and develop (Posner et al., 2007), as well as how both experiential and genetic factors contribute to the development of neural systems (Rueda et al., 2005). Further, it can allow for the investigation of gene-by-environment interactions, common in studies of social and emotional development and psychopathology (Belsky et al., 2009; Ellis et al., 2011; Manuck and McCaffery, 2014; Pluess and Belsky, 2013), and also emerging in the field of intervention research (Bakermans-Kranenburg and van IJzendoorn, 2015; Belsky and van Ijzendoorn, 2015).