Everyday life unfolds continuously, yet we tend to remember past experiences as discrete event sequences or episodes. Although this phenomenon has been well documented, the neuromechanisms that support the transformation of continuous experience into distinct and memorable episodes remain unknown. Here, we show that changes in context, or event boundaries, elicit a burst of autonomic arousal, as indexed by pupil dilation. Event boundaries also lead to the segmentation of adjacent episodes in later memory, evidenced by changes in memory for the temporal duration, order, and perceptual details of recent event sequences. These subjective and objective changes in temporal memory are also related to distinct temporal features of pupil dilations to boundaries as well as to the temporal stability of more prolonged pupil-linked arousal states. Collectively, our findings suggest that pupil measures reflect both stability and change in ongoing mental context representations, which in turn shape the temporal structure of memory.

Episodic memory is critical to human functioning. In adults, episodic memory involves a distributed neural circuit in which the hippocampus plays a central role. As episodic memory abilities continue to develop across childhood and into adolescence, studying episodic memory maturation can provide insight into the development and construction of these hippocampal networks, and ultimately clues to their function in adulthood. While past developmental studies have shown that the hippocampus helps to support memory in middle childhood and adolescence, the extent to which ongoing maturation within the hippocampus contributes to developmental change in episodic memory abilities remains unclear. In contrast, slower maturing regions, such as the PFC, have been suggested to be the neurobiological locus of memory improvements into adolescence. However, it is also possible that the methods used to detect hippocampal development during middle childhood and adolescence are not sensitive enough. Here, we examine how temporal covariance (or differentiation) in voxel representations within anterior and posterior hippocampus change with age to support the development of detailed recollection in male and female developing humans. We find age-related increases in the distinctiveness of temporal activation profiles in the posterior, but not anterior, hippocampus. Second, we show that this measure of granularity, when present during postencoding rest periods, correlates with the recall of detailed memories of preceding stimuli several weeks postencoding, suggesting that granularity may promote memory stabilization.

A particularly elusive puzzle concerning the hippocampus is how the structural differences along its long anteroposterior axis might beget meaningful functional differences, particularly in terms of the granularity of information processing. One measure posits to quantify this granularity by calculating the average statistical independence of the BOLD signal across neighboring voxels, or intervoxel similarity (IVS), and has shown the anterior hippocampus to process coarser-grained information than the posterior hippocampus. This measure, however, has yielded opposing results in studies of developmental and healthy aging samples, which also varied in fMRI acquisition parameters and hippocampal parcellation methods. To reconcile these findings, we measured IVS across two separate resting-state fMRI acquisitions and compared the results across many of the most widely used parcellation methods in a large youngadult sample of male and female humans (Acquisition 1, N = 233; Acquisition 2, N = 176). Finding conflicting results across acquisitions and parcellations, we reasoned that a data-driven approach to hippocampal parcellation is necessary. To this end, we implemented a group masked independent components analysis to identify functional subunits of the hippocampus, most notably separating the anterior hippocampus into separate anterior-medial, anterior-lateral, and posteroanterior-lateral components. Measuring IVS across these components revealed a decrease in IVS along the medial-lateral axis of the anterior hippocampus but an increase from anterior to posterior. We conclude that intervoxel similarity is deeply affected by parcellation and that grounding one's parcellation in a functionally informed approach might allow for a more complex and reliable characterization of the hippocampus.

Everyday life unfolds continuously, yet we tend to remember past experiences as discrete event sequences or episodes. Although this phenomenon has been well documented, the brain mechanisms that support the transformation of continuous experience into memorable episodes remain unknown. Here we show that a sudden change in context, or 'event boundary', elicits a burst of autonomic arousal, as indexed by pupil dilation. These boundaries during dynamic experience also led to the segmentation of adjacent episodes in later memory, evidenced by changes in memory for the timing, order, and perceptual details of recent event sequences.Critically, we find that distinct cognitive components of this pupil response were associated with both subjective (temporal distance judgements) and objective (temporal order discrimination) measures of episodic memory, suggesting that multiple arousal-mediated cognitive processes help construct meaningful mnemonic events. Together, these findings reveal that arousal processes may play a fundamental role in everyday memory organization. RUNNING HEAD: AROUSAL AND EVENT BOUNDARIES

Knowledge tracing is a popular and successful approach to modeling student learning. In this paper, we investigate whether the addition of neuroimaging observations to a knowledge tracing model enables accurate prediction of memory performance in held-out data. We propose a Hidden Markov Model of memory acquisition related to Bayesian Knowledge Tracing and show how continuous functional magnetic resonance imaging (fMRI) signals can be incorporated as observations related to latent knowledge states. We then show, using data collected from a simple second-language learning experiment, that fMRI data acquired during a learning session can be used to improve predictions about student memory at test. The fitted models can also potentially give new insight into the neural mechanisms that contribute to learning and memory.