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.
A Learned Map for Places and Concepts in the Human Medial Temporal Lobe
Distinct lines of research in both humans and animals point to a specific role of the hippocampus in both spatial and episodic memory function. The discovery of concept cells in the hippocampus and surrounding medial temporal lobe (MTL) regions suggests that the MTL maps physical and semantic spaces with a similar neural architecture. Here, we studied the emergence of such maps using MTL microwire recordings from 20 patients (9 female, 11 male) navigating a virtual environment featuring salient landmarks with established semantic meaning. We present several key findings. The array of local field potentials in the MTL contains sufficient information for above-chance decoding of subjects' instantaneous location in the environment. Closer examination revealed that as subjects gain experience with the environment the field potentials come to represent both the subjects' locations in virtual space and in high-dimensional semantic space. Similarly, we observe a learning effect on temporal sequence coding. Over time, field potentials come to represent future locations, even after controlling for spatial proximity. This predictive coding of future states, more so than the strength of spatial representations per se, is linked to variability in subjects' navigation performance. Our results thus support the conceptualization of the MTL as a memory space, representing both spatial- and nonspatial information to plan future actions and predict their outcomes.
- NSF-PAR ID:
- 10412636
- Publisher / Repository:
- DOI PREFIX: 10.1523
- Date Published:
- Journal Name:
- The Journal of Neuroscience
- Volume:
- 43
- Issue:
- 19
- ISSN:
- 0270-6474
- Page Range / eLocation ID:
- p. 3538-3547
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Significance Statement In 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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