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The human medial temporal lobe (MTL) plays a crucial role in recognizing visual objects, a key cognitive function that relies on the formation of semantic representations. Nonetheless, it remains unknown how visual information of general objects is translated into semantic representations in the MTL. Furthermore, the debate about whether the human MTL is involved in perception has endured for a long time. To address these questions, we investigated three distinct models of neural object coding—semantic coding, axis-based feature coding, and region-based feature coding—in each subregion of the MTL, using high-resolution fMRI in two male and six female participants. Our findings revealed the presence of semantic coding throughout the MTL, with a higher prevalence observed in the parahippocampal cortex (PHC) and perirhinal cortex (PRC), while axis coding and region coding were primarily observed in the earlier regions of the MTL. Moreover, we demonstrated that voxels exhibiting axis coding supported the transition to region coding and contained information relevant to semantic coding. Together, by providing a detailed characterization of neural object coding schemes and offering a comprehensive summary of visual coding information for each MTL subregion, our results not only emphasize a clear role of the MTL in perceptual processing but also shed light on the translation of perception-driven representations of visual features into memory-driven representations of semantics along the MTL processing pathway. Significance StatementIn this study, we delved into the mechanisms underlying visual object recognition within the human medial temporal lobe (MTL), a pivotal region known for its role in the formation of semantic representations crucial for memory. In particular, the translation of visual information into semantic representations within the MTL has remained unclear, and the enduring debate regarding the involvement of the human MTL in perception has persisted. To address these questions, we comprehensively examined distinct neural object coding models across each subregion of the MTL, leveraging high-resolution fMRI. We also showed transition of information between object coding models and across MTL subregions. Our findings significantly contributes to advancing our understanding of the intricate pathway involved in visual object coding.
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Using multi‐task experiments to test principles of hippocampal function
Abstract Investigations of hippocampal functions have revealed a dizzying array of findings, from lesion‐based behavioral deficits, to a diverse range of characterized neural activations, to computational models of putative functionality. Across these findings, there remains an ongoing debate about the core function of the hippocampus and the generality of its representation. Researchers have debated whether the hippocampus's primary role relates to the representation of space, the neural basis of (episodic) memory, or some more general computation that generalizes across various cognitive domains. Within these different perspectives, there is much debate about the nature of feature encodings. Here, we suggest that in order to evaluate hippocampal responses—investigating, for example, whether neuronal representations are narrowly targeted to particular tasks or if they subserve domain‐general purposes—a promising research strategy may be the use of multi‐task experiments, or more generally switching between multiple task contexts while recording from the same neurons in a given session. We argue that this strategy—when combined with explicitly defined theoretical motivations that guide experiment design—could be a fruitful approach to better understand how hippocampal representations support different behaviors. In doing so, we briefly review key open questions in the field, as exemplified by articles in this special issue, as well as previous work using multi‐task experiments, and extrapolate to consider how this strategy could be further applied to probe fundamental questions about hippocampal function.
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- Award ID(s):
- 1945230
- PAR ID:
- 10485149
- Publisher / Repository:
- John Wiley & Sons
- Date Published:
- Journal Name:
- Hippocampus
- Volume:
- 33
- Issue:
- 5
- ISSN:
- 1050-9631
- Page Range / eLocation ID:
- 646 to 657
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The hippocampus is thought to enable the encoding and retrieval of ongoing experience, the organization of that experience into structured representations like contexts, maps, and schemas, and the use of these structures to plan for the future. A central goal is to understand what the core computations supporting these functions are, and how these computations are realized in the collective action of single neurons. A potential access point into this issue is provided by ‘splitter cells’, hippocampal neurons that fire differentially on the overlapping segment of trajectories that differ in their past and/or future. However, the literature on splitter cells has been fragmented and confusing, owing to differences in terminology, behavioral tasks, and analysis methods across studies. In this review, we synthesize consistent findings from this literature, establish a common set of terms, and translate between single-cell and ensemble perspectives. Most importantly, we examine the combined findings through the lens of two major theoretical ideas about hippocampal function: representation of temporal context and latent state inference. We find that unique signature properties of each of these models are necessary to account for the data, but neither theory, by itself, explains all of its features. Specifically, the temporal gradedness of the splitter signal is strong support for temporal context, but is hard to explain using state models, while its flexibility and task-dependence is naturally accounted for using state inference, but poses a challenge otherwise. These theories suggest a number of avenues for future work, and we believe their application to splitter cells is a timely and informative domain for testing and refining theoretical ideas about hippocampal function.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1002/hipo.23540
