The influence of prior knowledge on memory: A developmental cognitive neuroscience perspective

Across ontogenetic development, individuals gather manifold experiences during which they detect regularities in their environment and thereby accumulate knowledge. This knowledge is used to guide behavior, make predictions, and acquire further new knowledge. In this review, we discuss the influence of prior knowledge on memory from both the psychology and the emerging cognitive neuroscience literature and provide a developmental perspective on this topic. Recent neuroscience findings point to a prominent role of the medial prefrontal cortex (mPFC) and of the hippocampus (HC) in the emergence of prior knowledge and in its application during the processes of successful memory encoding, consolidation, and retrieval. We take the lateral PFC into consideration as well and discuss changes in both medial and lateral PFC and HC across development and postulate how these may be related to the development of the use of prior knowledge for remembering. For future direction, we argue that, to measure age differential effects of prior knowledge on memory, it is necessary to distinguish the availability of prior knowledge from its accessibility and use

Single-trial characterization of neural rhythms: Potential and challenges

The average power of rhythmic neural responses as captured by MEG/EEG/LFP recordings is a prevalent index of human brain function. Increasing evidence questions the utility of trial-/group averaged power estimates however, as seemingly sustained activity patterns may be brought about by time-varying transient signals in each single trial. Hence, it is crucial to accurately describe the duration and power of rhythmic and arrhythmic neural responses on the single trial-level. However, it is less clear how well this can be achieved in empirical MEG/EEG/LFP recordings. Here, we extend an existing rhythm detection algorithm (extended Better OSCillation detection: “eBOSC”; cf. Whitten et al., 2011) to systematically investigate boundary conditions for estimating neural rhythms at the single-trial level. Using simulations as well as resting and task-based EEG recordings from a micro-longitudinal assessment, we show that alpha rhythms can be successfully captured in single trials with high specificity, but that the quality of single-trial estimates varies greatly between subjects. Despite those signal-to-noise-based limitations, we highlight the utility and potential of rhythm detection with multiple proof-of-concept examples, and discuss implications for single-trial analyses of neural rhythms in electrophysiological recordings. Using an applied example of working memory retention, rhythm detection indicated load-related increases in the duration of frontal theta and posterior alpha rhythms, in addition to a frequency decrease of frontal theta rhythms that was observed exclusively through amplification of rhythmic amplitudes.Peer Reviewe

On the estimation of brain signal entropy from sparse neuroimaging data

Multi-scale entropy (MSE) has been recently established as a promising tool for the analysis of the moment-to-moment variability of neural signals. Appealingly, MSE provides a measure of the predictability of neural operations across the multiple time scales on which the brain operates. An important limitation in the application of the MSE to some classes of neural signals is MSE’s apparent reliance on long time series. However, this sparse-data limitation in MSE computation could potentially be overcome via MSE estimation across shorter time series that are not necessarily acquired continuously (e.g., in fMRI block-designs). In the present study, using simulated, EEG, and fMRI data, we examined the dependence of the accuracy and precision of MSE estimates on the number of data points per segment and the total number of data segments. As hypothesized, MSE estimation across discontinuous segments was comparably accurate and precise, despite segment length. A key advance of our approach is that it allows the calculation of MSE scales not previously accessible from the native segment lengths. Consequently, our results may permit a far broader range of applications of MSE when gauging moment-to- moment dynamics in sparse and/or discontinuous neurophysiological data typical of many modern cognitive neuroscience study designs

The two-component model of memory development, and its potential implications for educational settings

We recently introduced a two-component model of the mechanisms underlying age differences in memory functioning across the lifespan. According to this model, memory performance is based on associative and strategic components. The associative component is relatively mature by middle childhood, whereas the strategic component shows a maturational lag and continues to develop until young adulthood. Focusing on work from our own lab, we review studies from the domains of episodic and working memory informed by this model, and discuss their potential implications for educational settings. The episodic memory studies uncover the latent potential of the associative component in childhood by documenting children's ability to greatly improve their memory performance following mnemonic instruction and training. The studies on working memory also point to an immature strategic component in children whose operation is enhanced under supportive conditions. Educational settings may aim at fostering the interplay between associative and strategic components. We explore possible routes towards this goal by linking our findings to recent trends in research on instructional design

Hippocampal maturity promotes memory distinctiveness in childhood and adolescence

Adaptive learning systems need to meet two complementary and partially conflicting goals: detecting regularities in the world versus remembering specific events. The hippocampus (HC) keeps a fine balance between computations that extract commonalities of incoming information (i.e., pattern completion) and computations that enable encoding of highly similar events into unique representations (i.e., pattern separation). Histological evidence from young rhesus monkeys suggests that HC development is characterized by the differential development of intrahippocampal subfields and associated networks. However, due to challenges in the in vivo investigation of such developmental organization, the ontogenetic timing of HC subfield maturation remains controversial. Delineating its course is important, as it directly influences the fine balance between pattern separation and pattern completion operations and, thus, developmental changes in learning and memory. Here, we relate in vivo, high-resolution structural magnetic resonance imaging data of HC subfields to behavioral memory performance in children aged 6–14 y and in young adults. We identify a multivariate profile of age-related differences in intrahippocampal structures and show that HC maturity as captured by this pattern is associated with age differences in the differential encoding of unique memory representations

Episodic memory across the lifespan: The contributions of associative and strategic components

The structural and functional brain circuitries supporting episodic memory undergo profound reorganization in childhood and old age. We propose a two-component framework that combines and integrates evidence from child development and aging. It posits that episodic memory builds on two interacting components: (a) the strategic component, which refers to memory control operations, and (b) the associative component, which refers to mechanisms that bind different features of a memory episode into a compound representation. We hypothesize that: (a) children's difficulties in episodic memory primarily originate from low levels of strategic operations, and reflect the protracted development of the prefrontal cortex (PFC); (b) deficits in episodic memory performance among older adults originate from impairments in both strategic and associative components, reflecting senescent changes in the PFC and the medio-temporal lobes (MTL). Initial behavioral and neural evidence is consistent with both hypotheses. The two-component framework highlights the specificities of episodic memory in different age periods, helps to identify and dissociate its components, and contributes to understanding the interplay among maturation, learning, and senescence

Neural pattern similarity differentially affects memory performance of younger and older adults: age differences in neural similarity and memory

Age-related memory decline is associated with changes in neural functioning but little is known about how aging affects the quality of information representation in the brain. Whereas a long-standing hypothesis of the aging literature links cognitive impairments to less distinct neural representations in old age, memory studies have shown that high similarity between activity patterns benefits memory performance for the respective stimuli. Here, we addressed this apparent conflict by investigating between-item representational similarity in 50 younger (19–27 years old) and 63 older (63–75 years old) human adults (male and female) who studied scene-word associations using a mnemonic imagery strategy while electroencephalography was recorded. We compared the similarity of spatiotemporal frequency patterns elicited during encoding of items with different subsequent memory fate. Compared to younger adults, older adults’ memory representations were more similar to each other but items that elicited the most similar activity patterns early in the encoding trial were those that were best remembered by older adults. In contrast, young adults’ memory performance benefited from decreased similarity between earlier and later periods in the encoding trials, which might reflect their better success in forming unique memorable mental images of the joint picture–word pair. Our results advance the understanding of the representational properties that give rise to memory quality as well as how these properties change in the course of aging

Coordinated within-Trial Dynamics of Low-Frequency Neural Rhythms Controls Evidence Accumulation

Higher cognitive functions, such as human perceptual decision making, require information processing and transmission across widespread cortical networks. Temporally synchronized neural firing patterns are advantageous for efficiently representing and transmitting information within and between assemblies. Computational, empirical, and conceptual considerations all lead to the expectation that the informational redundancy of neural firing rates is positively related to their synchronization. Recent theorizing and initial evidence also suggest that the coding of stimulus characteristics and their integration with behavioral goal states require neural interactions across a hierarchy of timescales. However, most studies thus have focused on neural activity in a single frequency range or on a restricted set of brain regions. Here we provide evidence for cooperative spatiotemporal dynamics of slow and fast EEGsignals during perceptual decision making at the single-trial level. Participants performed three masked two-choice decision tasks, one each with numerical, verbal, or figural content. Decrements in posterior power (8 -14 Hz) were paralleled by increments in high-frequency (>30 Hz) signal entropy in trials demanding active sensory processing. Simultaneously, frontocentral power (4 -7 Hz) increased, indicating evidence integration. The coordinated a/0 dynamics were tightly linked to decision speed and remarkably similar across tasks, suggesting a domain-general mechanism. In sum, we demonstrate an inverse association between decision-related changes in widespread low-frequency power and local high-frequency entropy. The cooperation among mechanisms captured by these changes enhances the informational density of neural response patterns and qualifies as a neural coding system in the service of perceptual decision making

Hippocampal Subfield Volumes: Age, Vascular Risk, and Correlation with Associative Memory

Aging and age-related diseases have negative impact on the hippocampus (HC), which is crucial for such age-sensitive functions as memory formation, maintenance, and retrieval. We examined age differences in hippocampal subfield volumes in 10 younger and 19 older adults, and association of those volumes with memory performance in the older participants. We manually measured volumes of HC regions CA1 and CA2 (CA1–2), sectors CA3 and CA4 plus dentate gyrus (CA3–4/DG), subiculum, and the entorhinal cortex using a contrast-optimized high-resolution PD-weighted MRI sequence. Although, as in previous reports, the volume of one region (CA1–2) was larger in the young, the difference was due to the presence of hypertensive subjects among the older adults. Among older participants, increased false alarm rate in an associative recognition memory task was linked to reduced CA3–4/DG volume. We discuss the role of the DG in pattern separation and the formation of discrete memory representations