| dc.description.abstract | “Statistical learning” refers to the learning effects exhibited by organisms through adaptation to regularities embedded in their environment under natural settings. While it encompasses a broad range of learning phenomena, researchers have proposed that they can generally be categorized as the extraction and integration of information, with memory processes serving as foundational building blocks for their emergence. Accumulating evidence from behavioral and functional neuroimaging studies suggests that SL is not supported by a single mechanism, but involves nearly all neural networks engaged in the processing of task-related information. The hippocampus, by virtue of its hierarchical position as well as its neural characteristics and architecture, plays a unique and significant role in the dynamic processes of learning and memory. Current researchers generally agree that the hippocampus facilitates the acquisition of associations by developing shared memory engram cells, with its pattern completion function having a synergistic effect. Conversely, its pattern separation function is considered to serve a complementary purpose, primarily responsible for maintaining the precision and distinctiveness of information. However, we speculated that pattern separation may also contribute to the acquisition of associations. To explore this possibility, the current study employed two experimental approaches: First, examining individual differences to investigate correlations between SL and other individual abilities, particularly the pattern separation function of the hippocampus. Second, exploring changes in brain activity associated with SL processes, focusing on the hippocampus (which supports pattern separation) and visual cortices (which are essential for visual processing).
Our first experiment sought to determine whether variation in SL performance across individuals can be associated with the efficacy of their hippocampal pattern separation function. We adopted an individual differences approach to examine whether a significant mechanistic link exists between these two cognitive processes, by analyzing the relationships between participants’ performances across a series of tasks. Experiment 1 comprised two parts, 1a and 1b, involving 105 young adults and 47 older adults, respectively, to further understand the potential the impact of aging on SL mechanisms. Participants performed tasks including two conventional SL tasks in visual or auditory modalities, one motor sequence learning task, a memory test sensitive to pattern separation, three traditional long-term memory tests, two working memory tests, and two fluid intelligence tests.
Results from Experiment 1a demonstrated an interconnection between SL abilities across sensory modalities, with performances on both SL tasks correlated with lure discrimination performance, which is closely related to the competence of hippocampal pattern separation function. This suggests that the superiority of the hippocampus to encode distinct experiences uniquely may influence the efficiency in SL. Experiment 1b further revealed that, among older adults, while the performance in visual SL remained correlated with the ability to discriminate lures in memory, those of auditory SL didn’t and, instead, showed an increased connection with the ability to explicitly learn (auditorily presented) paired associations. Furthermore, with aging, SL abilities across sensory modalities become less predictive of each other. These results indicate that, in elderlies, the capability to perceive and process auditory information may become a dominant factor influencing the variability of SL performance. Consequently, the impact of hippocampal pattern separation appears reduced, leading to a lack of observed modality-general SL mechanisms.
Our second, fMRI experiment had a dual purpose: Firstly, we aimed to identify a signature indicating that hippocampal pattern separation takes a part in SL processes. Secondly, we sought to explore the temporal dynamics across different brain regions during SL. To these ends, we recruited 37 participants, presented them with a series of geometrical shapes that were implicitly structured as triplets (i.e., three items with a fixed temporal order). On one hand, we examined whether representational patterns of shape stimuli sitting astride triplet boundaries would undergo differentiation after being familiarized with such regularity structure, implying pattern separation aids in reducing confusion caused by accidentally experienced associations. On the other hand, we explored whether and how regions at different levels of the visual information processing hierarchy, including the hippocampus, three MTL cortices, and four visual cortices (combined V1 and V2, remaining lateral occipital cortex, fusiform gyrus, inferior temporal gyrus), would exhibit different patterns of activity changes throughout the familiarization phase, possibly contingent upon the predictiveness (the first and the second items within a triplet can predict upcoming stimuli) and predictability (the second and the third items within a triplet can be predicted) of stimuli.
The results of Experiment 2 did not detect any significant changes in representational similarity across brain regions after learning. Notably, despite behavioral evidence of learning triplet structure (or sequential associations among stimuli), we were unable to reproduce previous results showing increased representational similarity for associated stimuli (i.e., items belonging to the same triplet) within the hippocampal system. Considering the use of simpler and more memorable visual stimuli compared to previous studies, we speculate that the plasticity of internal representations may vary depending on the properties of the stimulus materials. Regarding the second purpose, we found that activity dynamics during the learning phase vary across brain regions. Visual cortices were consistently engaged throughout the SL process, with its higher-level parts (excluding combined V1 and V2) showing a decline in activity over time, regardless of whether the stimuli is predictable. The hippocampus showed no consistent participation for most of the time, but increased its activity for predictive stimuli in the middle stages of the learning phase, possibly engaged in predictive coding process, facilitating perceptual processing by generating prediction signals through pattern completion. The MTL cortices exhibited complex activity patterns, roughly resembling those of the hippocampus, but also increased activity for predictable stimuli during the middle phase and decreased its response intensity over time, suggesting their involvement in multiple mechanisms that require further investigation.
In conclusion, the results of this study, both from behavioral and neuroimaging evidence, indicate that the hippocampus plays a role in SL processes. Furthermore, our results suggest that both the “pattern separation” and “pattern completion” functions of the hippocampus contribute to the better grasping of regularities in the environment. While current researchers predominantly associate the hippocampus’s involvement in SL with its pattern completion function, future studies should consider exploring the potential for the hippocampus to serve various functions at different stages of the SL process. | en_US |