Title A Naturalistic Assessment of the Organization of Children ' s Memories Predicts Cognitive Functioning and Reading Ability Permalink

To explore the relationship between memory and early school performance, we used graph theory to investigate memory reports from 76 children aged 6–8 years. The reports comprised autobiographical memories of events days to years past, and memories of novel images reported immediately after encoding. We also measured intelligence quotient (IQ) and theory of mind (ToM). Reading and Mathematics were assessed before classes began (December 2013), around the time of report collection (June 2014), and at the end of the academic year (December 2014). IQ and ToM correlated positively with word diversity and word-to-word connectivity, and negatively with word recurrence. Connectivity correlated positively with Reading in June 2014 as well as December 2014, even after adjusting for IQ and ToM. To our knowledge, this is the first study demonstrating a link between the structure of children’s memories and their cognitive or academic performance. 1Brain Institute, Federal University of Rio Grande do Norte (UFRN) 2Department of Modern Foreign Languages and Literature, Federal University of Rio Grande do Norte (UFRN) 3Department of Psychology, Federal University of Rio Grande do Norte (UFRN) 4Department of Pedagogy and Physiotherapy, Faculdade Maurício de Nassau 5Department of Psychology & Helen Wills Neuroscience Institute, University of California 6Department of Physics, Federal University of Pernambuco (UFPE) Address correspondence to Sidarta Ribeiro, Brain Institute, Federal University of Rio Grande do Norte (UFRN), Natal, RN, Brazil; e-mail sidartaribeiro@neuro.ufrn. br When children begin formal schooling, they are faced with the challenges of learning to read, write, and perform basic mathematical calculations, among others. To achieve these milestones, children must be able to attend to relevant information, keep it in mind, organize and flexibly update it, and recall it at a later time. These cognitive skills improve dramatically over the elementary school years, as measured by carefully controlled laboratory tests. At the same time, there are important individual differences in performance on these cognitive tests, and there is ample evidence that interindividual variability in working memory and cognitive control helps to explain differences in academic achievement among children (Alloway & Passolunghi, 2011; Titz & Karbach, 2014). In comparison with research on working memory and cognitive control, the degree to which episodic memory contributes to academic achievement is less clear (Sander, Werkle-Bergner, Gerjets, Shing, & Lindenberger, 2012). It is generally assumed that the ability to recall detailed accounts of past events is important for learning new material at school (Harel et al., 2014). However, the most common way to measure episodic memory is through the use of simple laboratory tests in which participants must learn a series of pairs of stimuli presented on the computer, and retrieve them after a brief delay (Alloway & Alloway, 2010; Alloway, Gathercole, Kirkwood & Elliott, 2009; Alloway & Passolunghi, 2011; Blakemore & Bunge, 2012; Bunge & Wright, 2007; Johnson, Miller Singley, Peckham, Johnson, & Bunge, 2014; Sander et al., 2012). While these types of © 2016 International Mind, Brain, and Education Society and Wiley Periodicals, Inc. 1 Memories Correlate With Academic Performance paradigms are tightly controlled, they are rather artificial and do not approach the complexity of memory processes in the real world. Here, we sought to probe the relationship between episodic memory and academic achievement in a more naturalistic context, asking children to report on their own memories. To this end, we sought to use new quantification methods applied to unstructured, spontaneous, freely produced speech. The way people report their memories reflects spontaneous associations, and indirectly reveals the underlying thought process. Recently, computational approaches based on graph theory have succeeded in using structural features of memory reports to quantify pathological cognitive deficits (Bertola et al., 2014; Mota, Furtado, Maia, Copelli, & Ribeiro, 2014; Mota et al., 2012). A memory report can be accurately represented by a graph in which the words are represented by nodes, and the temporal links between consecutive words are represented by edges. As described in Table 1, it is possible to calculate general attributes of graphs (such as the number of nodes and edges or links), to examine the relationship between those elements by studying recurrence measures (how repetitions of links between nodes and cycles of nodes appear on the graphs), and to study the overall connectivity between nodes (counting the number of nodes that are connected), as well as to describe the global features that characterize the structure of graphs as a whole (such as the degree of clustering and the average shortest path between nodes; Bollobas, 1998). Such speech graphs have recently been used to reveal cognitive deficits in pathological populations comprising patients suffering from psychosis (Mota et al., 2012, 2014) or dementia (Bertola et al., 2014). In particular, we have found that dream reports from psychotic patients were less connected than similar reports from controls. Furthermore, connectivity measurements were negatively correlated with cognitive and negative symptoms, denoting that the more isolated and cognitively impaired the subject is, the less connected the corresponding dream reports (Mota et al., 2014). In the case of dementia, the graph-theoretical analysis of the verbal fluency test led to good sorting between patients with Alzheimer’s disease and mild cognitive deficits (Bertola et al., 2014). Cognitive impairment was accompanied by increased graph density, decreased diameter, and smaller average shortest path. Graph measurements have yet to be employed to investigate the normal development of memory reports produced by a healthy population. As a first step in this direction, we set out to quantify the relationship between the structure of spontaneous memory reports, and measurements of general intelligence, theory of mind (ToM), and school achievement. The longitudinal design of this study allowed us to investigate whether these structural properties can predict academic performance over time. The first academic assessment was performed on December 2013, before the students were exposed to Reading and Math classes, which began on March 2014. Two subsequent measurements were performed on June 2014 and December 2014, allowing for the investigation of both cross-sectional and longitudinal relationships between graph measurements and academic achievement during the first year of alphabetization. In order to characterize the mechanism behind the possible relationship between declarative memory reports and cognitive performance, we separated the reports into those taxing short-term memory (STM), with a few seconds between the encoding and recall of novel images; and those taxing long-term memory (LTM), with days to years between the encoding and recall of autobiographical events. Based on previous studies of memory organization in adult psychotic patients (Mota et al., 2012, 2014), we hypothesized that three connectivity-related graph attributes that decrease in association with cognitive decline in these subjects (edges, LCC, and LSC; see Methods section) would increase in the case of typical developmental improvement in alphabetization. As this is a first exploratory graph-based study of memory reports in healthy children, we also tested whether other 11 graph attributes are relevant.