Memory and the developing brain: From description to explanation with innovation in methods

Abstract

Recent advances in human cognitive neuroscience show great promise in extending our understanding of the neural basis of memory development. We briefly review the current state of knowledge, highlighting that most work has focused on describing the neural correlates of memory in cross-sectional studies. We then delineate three examples of the application of innovative methods in addressing questions that go beyond description, towards a mechanistic understanding of memory development. First, structural brain imaging and the harmonization of measurements across laboratories may uncover ways in which the maturation of the brain constrains the development of specific aspects of memory. Second, longitudinal designs and sophisticated modeling of the data may identify age-driven changes and the factors that determine individual developmental trajectories. Third, recording memory-related activity directly from the developing brain presents an unprecedented opportunity to examine how distinct brain structures support memory in real time. Finally, the growing prevalence of data sharing offers additional means to tackle questions that demand large-scale datasets, ambitious designs, and access to rare samples. We propose that the use of such innovative methods will move our understanding of memory development from a focus on describing trends to explaining the causal factors that shape behavior.

Keywords: ECoG; Functional MRI; Hippocampus; Longitudinal design; Prefrontal cortex; Structural MRI.

Fig. 1

Number of publications on memory in adults and developing samples, by methodology, 1959-2017. (A) Number of publications in PubMed using the search term “memory” (excluding “working”) and either: (1) “fMRI,” “child,” “development;” (2) “fMRI” (excluding “child,” “development”); (3) “EEG” or “MEG” and “child,” “development” (excluding “iEEG,” “ECoG,” “sEEG”); or (4) “EEG” or “MEG” (excluding “child,” “development,” “iEEG,” “ECoG,” “sEEG”). The number of publications in adults is plotted as lines on the left axis and the number of publications conducted in developing samples is plotted as bars on the right axis at 1:30 scale. Note that the earliest search result was dated 1959. EEG, electroencephalogram; MEG, magnetoencephalogram. (B) Number of publications in PubMed using the search term “memory” (excluding “working”) and either: (1) “child,” “development” (excluding “fMRI,” “EEG,” “MEG,” “iEEG,” “ECoG,” “sEEG”); or (2) (excluding “fMRI,” “EEG,” “MEG,” “iEEG,” “ECoG,” “sEEG,” “child,” “development”). As in (A), the number of publications in adults is plotted as lines on the left axis and the number of publications conducted in developing samples is plotted as bars on the right axis at 1:30 scale. Note that this search returned entries in adults that date back to 1842, not shown.

Fig. 2

Using a subsequent memory paradigm and fMRI to map the neural correlates of memory development. (A) Subsequent memory paradigm. Participants studied indoor and outdoor scenes while fMRI data were collected, and then completed a self-paced recognition test after a delay. Encoding trials were labeled as Hit or Miss based on whether the scenes were later correctly recognized as “Old” (Hit) or incorrectly judged as “New” (Miss). Hit trials were further classified as Hit Sure (Hit_S) or Hit Not Sure (Hit_NS) based on the “Sure”/”Not Sure” rating given at test. Positive subsequent memory effects and negative subsequent memory effects were calculated by the Hit_S > Miss and Miss > Hit_S contrasts. (B) PFC regions showing age-related differences in subsequent memory effects. Positive subsequent memory effects in bilateral inferior frontal gyrus (IFG) increased with age, while negative effects in bilateral superior frontal gyrus (SFG) increased with age. The significance threshold for the t-maps shown on top is p < 0.05, corrected. Orange, positive effects; blue, negative effects. Adapted with permission from (Tang et al., 2018). (C) PFC regions showing age-related differences in the functional connectivity linked to memory formation. Connectivity between the IFG and parahippocampal gyrus (PHG) increased with age, while anti-correlated connectivity between the SFG and PHG increased with age. The significance threshold for the t-maps is p < 0.05, corrected. Orange, positive effects; blue, negative effects. Adapted with permission from (Tang et al., 2018). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 3

Age-related differences in hippocampal subfield volumetry. (A) Representative images from individuals sampled across the lifespan. Within each individual dataset, the three images are contiguous slices (0.4 × 0.4 in-plane resolution, 2-mm slice thickness) showing the range sampled for hippocampal subfield volumetry. Blue, CA3-DG; yellow, CA1-2; green, subiculum; red, entorhinal cortex. Adapted with permission from (Daugherty, et al., 2016). (B) Differences in select hippocampal subfield volumes from 8 to 26 years of age. Left: CA3-DG (age p = 0.02; age² p = 0.62; R² = 0.12). Right: CA1-2 (age p = 0.56; age² p = 0.01; R² = 0.12). Standardized effect coefficients are reported from the latent modeling that estimated linear and quadratic age differences in all regions simultaneously, accounting for correlations among subregions. Adapted with permission from (Daugherty et al., 2017). (C) Model testing age-related differences in hippocampal subfield volumes as predicting differences in recognition memory (indirect age effect p = 0.04; R² = 0.21). All coefficients are standardized. *, p < 0.05; dashed lines, non-significant covariate effects. Adapted with permission from (Daugherty et al., 2017) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

Fig. 4

Techniques for intracranial electrode placement. (A) Left: Reconstruction of a post-operative image from an epilepsy patient undergoing intracranial monitoring, illustrating two types of subdural ECoG (i.e., grid and strip) and penetrating sEEG (depth) placements. Right: Volumetric MRI coronal slice from the same patient showing sEEG placement to target the hippocampus. Red, grid (ECoG); blue, strip (ECoG); green, depth (sEEG); yellow, margin of craniotomy performed for placement of grid electrodes. Adapted with permission from (Chiong et al., 2017). (B) Reconstruction of ECoG placements in an 11-year-old patient (included in Johnson et al., 2018b), shown in lateral (top) and ventral (bottom) views (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).