Experience transforms crossmodal object representations in the anterior temporal lobes
- University of Toronto, Canada
- University of Calgary, Canada
- Florida State University, United States
Abstract
Combining information from multiple senses is essential to object recognition, core to the ability to learn concepts, make new inferences, and generalize across distinct entities. Yet how the mind combines sensory input into coherent crossmodal representations - the crossmodal binding problem - remains poorly understood. Here, we applied multi-echo fMRI across a four-day paradigm, in which participants learned 3-dimensional crossmodal representations created from well-characterized unimodal visual shape and sound features. Our novel paradigm decoupled the learned crossmodal object representations from their baseline unimodal shapes and sounds, thus allowing us to track the emergence of crossmodal object representations as they were learned by healthy adults. Critically, we found that two anterior temporal lobe structures - temporal pole and perirhinal cortex - differentiated learned from non-learned crossmodal objects, even when controlling for the unimodal features that composed those objects. These results provide evidence for integrated crossmodal object representations in the anterior temporal lobes that were different from the representations for the unimodal features. Furthermore, we found that perirhinal cortex representations were by default biased towards visual shape, but this initial visual bias was attenuated by crossmodal learning. Thus, crossmodal learning transformed perirhinal representations such that they were no longer predominantly grounded in the visual modality, which may be a mechanism by which object concepts gain their abstraction.
Data availability
Anonymized data are available on the Open Science Framework: https://osf.io/vq4wj/.Univariate maps are available on NeuroVault: https://neurovault.org/collections/LFDCGMAY/
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Crossmodal Object Representations Rely on Integrative CodingOpen Science Framework, https://doi.org/10.17605/OSF.IO/VQ4WJ.
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https://neurovault.org/collections/LFDCGMAY/NeuroVault, https://identifiers.org/neurovault.collection:12807.
Article and author information
Author details
Natalia Ladyka-Wojcik
Dirk Bernhardt-Walther
Funding
Natural Sciences and Engineering Research Council of Canada (Alexander Graham Bell Canada Graduate Scholarship-Doctoral)
- Aedan Yue Li
Natural Sciences and Engineering Research Council of Canada (Discovery Grant (RGPIN-2020-05747))
- Morgan Barense
James S. McDonnell Foundation (Scholar Award)
- Morgan Barense
Canada Research Chairs
- Morgan Barense
Ontario Ministry of Research and Innovation (Early Researcher Award)
- Morgan Barense
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All experiments described in this study were approved by the University of Toronto Ethics Review Board: 37590. Informed consent was obtained for all participants in the study.
Copyright
© 2024, Li et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Experience transforms crossmodal object representations in the anterior temporal lobes
eLife 13:e83382.
https://doi.org/10.7554/eLife.83382
Further reading
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When holding visual information temporarily in working memory (WM), the neural representation of the memorandum is distributed across various cortical regions, including visual and frontal cortices. However, the role of stimulus representation in visual and frontal cortices during WM has been controversial. Here, we tested the hypothesis that stimulus representation persists in the frontal cortex to facilitate flexible control demands in WM. During functional MRI, participants flexibly switched between simple WM maintenance of visual stimulus or more complex rule-based categorization of maintained stimulus on a trial-by-trial basis. Our results demonstrated enhanced stimulus representation in the frontal cortex that tracked demands for active WM control and enhanced stimulus representation in the visual cortex that tracked demands for precise WM maintenance. This differential frontal stimulus representation traded off with the newly-generated category representation with varying control demands. Simulation using multi-module recurrent neural networks replicated human neural patterns when stimulus information was preserved for network readout. Altogether, these findings help reconcile the long-standing debate in WM research, and provide empirical and computational evidence that flexible stimulus representation in the frontal cortex during WM serves as a potential neural coding scheme to accommodate the ever-changing environment.
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Human-specific cognitive abilities depend on information processing in the cerebral cortex, where the neurons are significantly larger and their processes longer and sparser compared to rodents. We found that, in synaptically connected layer 2/3 pyramidal cells (L2/3 PCs), the delay in signal propagation from soma to soma is similar in humans and rodents. To compensate for the longer processes of neurons, membrane potential changes in human axons and/or dendrites must propagate faster. Axonal and dendritic recordings show that the propagation speed of action potentials (APs) is similar in human and rat axons, but the forward propagation of excitatory postsynaptic potentials (EPSPs) and the backward propagation of APs are 26 and 47% faster in human dendrites, respectively. Experimentally-based detailed biophysical models have shown that the key factor responsible for the accelerated EPSP propagation in human cortical dendrites is the large conductance load imposed at the soma by the large basal dendritic tree. Additionally, larger dendritic diameters and differences in cable and ion channel properties in humans contribute to enhanced signal propagation. Our integrative experimental and modeling study provides new insights into the scaling rules that help maintain information processing speed albeit the large and sparse neurons in the human cortex.
