Encoding and retrieval of associative recognition memory engage different sub-networks within a hippocampal-thalamo-cortical memory circuit

Recognition of previously encountered stimuli and their associated spatial and temporal information depends on neural activity within a brain-wide network in which the CA1 region of the hippocampus, nucleus reuniens of the thalamus (NRe) and medial prefrontal cortex (mPFC) are key nodes. However, the pathways crucial for coordinating activity during memory encoding and/or retrieval phases have been little explored. Here we opto- or chemo associative recognition memory. We discovered that encoding, but not retrieval depended on the CA1 to mPFC and NRe to mPFC projections. In contrast, retrieval depended on the mPFC to NRe projection. Interestingly the NRe to CA1 pathway was required for both memory phases. Our findings therefore reveal that encoding and retrieval engage dissociable sub-networks within a hippocampal-thalamo-cortical recognition memory circuit in order to enable binding of recent and related information, whilst ensuring a separation of processing.

Developmental change in prefrontal cortex recruitment supports the emergence of value-guided memory

Prioritizing memory for valuable information can promote adaptive behavior across the lifespan, but it is unclear how the neurocognitive mechanisms that enable the selective acquisition of useful knowledge develop. Here, using a novel task coupled with functional magnetic resonance imaging, we examined how children, adolescents, and adults (N = 90) learn from experience what information is likely to be rewarding, and modulate encoding and retrieval processes accordingly. We found that the ability to use learned value signals to selectively enhance memory for useful information strengthened throughout childhood and into adolescence. Encoding and retrieval of high- vs. low-value information was associated with increased activation in striatal and prefrontal regions implicated in value processing and cognitive control. Age-related increases in value-based lateral prefrontal cortex modulation mediated the relation between age and memory selectivity. Our findings demonstrate that developmental increases in the strategic engagement of the prefrontal cortex support the emergence of adaptive memory.

The Retrieval-related Anterior shift is Moderated by Age and Correlates with Memory Performance

Recent research suggests that episodic memory is associated with systematic differences in the localization of neural activity observed during memory encoding and retrieval. The retrieval-related anterior shift is a phenomenon whereby the retrieval of a stimulus event (e.g., a scene image) is associated with a peak neural response which is localized more anteriorly than the response elicited when the stimulus is experienced directly. Here, we examine whether the magnitude of the anterior shift, i.e., the distance between encoding- and retrieval-related response peaks, is moderated by age, and also whether the shift is associated with memory performance. Younger and older human subjects of both sexes underwent fMRI as they completed encoding and retrieval tasks on word-face and word-scene pairs. We localized peak scene- and face-selectivity for each individual participant within the face-selective precuneus (PCU) and in three scene-selective (parahippocampal place area [PPA], medial place area [MPA], occipital place area [OPA]) regions of interest (ROIs). In line with recent findings, we identified an anterior shift in PPA and OPA in both age groups and, in older adults only, in MPA and PCU also. Of importance, the magnitude of the anterior shift was larger in older than in younger adults. The shift within the PPA exhibited an age-invariant across-participant negative correlation with source memory performance, such that a smaller displacement between encoding- and retrieval-related neural activity was associated with better performance. These findings provide novel insights into the functional significance of the anterior shift, especially in relation to memory decline in older age.

Episodic Memory Encoding and Retrieval in Face-Name Paired Paradigm: An fNIRS Study

Background: Episodic memory (EM) is particularly sensitive to pathological conditions and aging. In a neurocognitive context, the paired-associate learning (PAL) paradigm, which requires participants to learn and recall associations between stimuli, has been used to measure EM. The present study aimed to explore whether functional near-infrared spectroscopy (fNIRS) can be employed to determine cortical activity underlying encoding and retrieval. Moreover, we examined whether and how different aspects of task (i.e., novelty, difficulty) affects those cortical activities. Methods: Twenty-two male college students (age: M = 20.55, SD = 1.62) underwent a face-name PAL paradigm under 40-channel fNIRS covering fronto-parietal and middle occipital regions. Results: A decreased activity during encoding in a broad network encompassing the bilateral frontal cortex (Brodmann areas 9, 11, 45, and 46) was observed during the encoding, while an increased activity in the left orbitofrontal cortex (Brodmann area 11) was observed during the retrieval. Increased HbO concentration in the superior parietal cortices and decreased HbO concentration in the inferior parietal cortices were observed during encoding while dominant activation of left PFC was found during retrieval only. Higher task difficulty was associated with greater neural activity in the bilateral prefrontal cortex and higher task novelty was associated with greater activation in occipital regions. Conclusion: Combining the PAL paradigm with fNIRS provided the means to differentiate neural activity characterising encoding and retrieval. Therefore, the fNIRS may have the potential to complete EM assessments in clinical settings.

Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics

The nature of firefighters` duties requires them to work for long periods under unfavorable conditions. To perform their jobs effectively, they are required to endure long hours of extensive, stressful training. Creating such training environments is very expensive and it is difficult to guarantee trainees’ safety. In this study, firefighters are trained in a virtual environment that includes virtual perturbations such as fires, alarms, and smoke. The objective of this paper is to use machine learning methods to discern encoding and retrieval states in firefighters during a visuospatial episodic memory task and explore which regions of the brain provide suitable signals to solve this classification problem. Our results show that the Random Forest algorithm could be used to distinguish between information encoding and retrieval using features extracted from fNIRS data. Our algorithm achieved an F-1 score of 0.844 and an accuracy of 79.10% if the training and testing data are obtained at similar environmental conditions. However, the algorithm’s performance dropped to an F-1 score of 0.723 and accuracy of 60.61% when evaluated on data collected under different environmental conditions than the training data. We also found that if the training and evaluation data were recorded under the same environmental conditions, the RPM, LDLPFC, RDLPFC were the most relevant brain regions under non-stressful, stressful, and a mix of stressful and non-stressful conditions, respectively.