1
|
Wang Y, Cao R, Wang S. Encoding of Visual Objects in the Human Medial Temporal Lobe. J Neurosci 2024; 44:e2135232024. [PMID: 38429107 PMCID: PMC11026346 DOI: 10.1523/jneurosci.2135-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/10/2024] [Accepted: 02/25/2024] [Indexed: 03/03/2024] Open
Abstract
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 human 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.
Collapse
Affiliation(s)
- Yue Wang
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110
| | - Runnan Cao
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110
| | - Shuo Wang
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110
| |
Collapse
|
2
|
Wang J, Cao R, Chakravarthula PN, Li X, Wang S. A critical period for developing face recognition. PATTERNS (NEW YORK, N.Y.) 2024; 5:100895. [PMID: 38370121 PMCID: PMC10873156 DOI: 10.1016/j.patter.2023.100895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/09/2023] [Accepted: 11/14/2023] [Indexed: 02/20/2024]
Abstract
Face learning has important critical periods during development. However, the computational mechanisms of critical periods remain unknown. Here, we conducted a series of in silico experiments and showed that, similar to humans, deep artificial neural networks exhibited critical periods during which a stimulus deficit could impair the development of face learning. Face learning could only be restored when providing information within the critical period, whereas, outside of the critical period, the model could not incorporate new information anymore. We further provided a full computational account by learning rate and demonstrated an alternative approach by knowledge distillation and attention transfer to partially recover the model outside of the critical period. We finally showed that model performance and recovery were associated with identity-selective units and the correspondence with the primate visual systems. Our present study not only reveals computational mechanisms underlying face learning but also points to strategies to restore impaired face learning.
Collapse
Affiliation(s)
- Jinge Wang
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
| | - Runnan Cao
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | | | - Xin Li
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
- Department of Computer Science, University at Albany, Albany, NY 12222, USA
| | - Shuo Wang
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| |
Collapse
|
3
|
Cao R, Wang J, Brunner P, Willie JT, Li X, Rutishauser U, Brandmeir NJ, Wang S. Neural mechanisms of face familiarity and learning in the human amygdala and hippocampus. Cell Rep 2024; 43:113520. [PMID: 38151023 PMCID: PMC10834150 DOI: 10.1016/j.celrep.2023.113520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 09/12/2023] [Accepted: 11/14/2023] [Indexed: 12/29/2023] Open
Abstract
Recognizing familiar faces and learning new faces play an important role in social cognition. However, the underlying neural computational mechanisms remain unclear. Here, we record from single neurons in the human amygdala and hippocampus and find a greater neuronal representational distance between pairs of familiar faces than unfamiliar faces, suggesting that neural representations for familiar faces are more distinct. Representational distance increases with exposures to the same identity, suggesting that neural face representations are sharpened with learning and familiarization. Furthermore, representational distance is positively correlated with visual dissimilarity between faces, and exposure to visually similar faces increases representational distance, thus sharpening neural representations. Finally, we construct a computational model that demonstrates an increase in the representational distance of artificial units with training. Together, our results suggest that the neuronal population geometry, quantified by the representational distance, encodes face familiarity, similarity, and learning, forming the basis of face recognition and memory.
Collapse
Affiliation(s)
- Runnan Cao
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA; Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA.
| | - Jinge Wang
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
| | - Peter Brunner
- Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jon T Willie
- Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Xin Li
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
| | - Ueli Rutishauser
- Departments of Neurosurgery and Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | | | - Shuo Wang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA; Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA; Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO 63110, USA.
| |
Collapse
|
4
|
Zhao F, Behnisch T. The Enigmatic CA2: Exploring the Understudied Region of the Hippocampus and Its Involvement in Parkinson's Disease. Biomedicines 2023; 11:1996. [PMID: 37509636 PMCID: PMC10377725 DOI: 10.3390/biomedicines11071996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disease that affects both motor and non-motor functions. Although motor impairment is a prominent clinical sign of PD, additional neurological symptoms may also occur, particularly in the preclinical and prodromal stages. Among these symptoms, social cognitive impairment is common and detrimental. This article aims to review non-motor symptoms in PD patients, focusing on social cognitive deficits. It also examines the specific characteristics of the CA2 region and its involvement in social behavior, highlighting recent advances and perspectives. Additionally, this review provides critical insights into and analysis of research conducted in rodents and humans, which may help improve the understanding of the current status of putative therapeutic strategies for social cognitive dysfunction in PD and potential avenues related to the function of the hippocampal CA2 region.
Collapse
Affiliation(s)
- Fang Zhao
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai 200032, China
| | - Thomas Behnisch
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai 200032, China
| |
Collapse
|
5
|
Donoghue T, Cao R, Han CZ, Holman CM, Brandmeir NJ, Wang S, Jacobs J. Single neurons in the human medial temporal lobe flexibly shift representations across spatial and memory tasks. Hippocampus 2023; 33:600-615. [PMID: 37060325 PMCID: PMC10231142 DOI: 10.1002/hipo.23539] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 03/17/2023] [Accepted: 03/21/2023] [Indexed: 04/16/2023]
Abstract
Investigations into how individual neurons encode behavioral variables of interest have revealed specific representations in single neurons, such as place and object cells, as well as a wide range of cells with conjunctive encodings or mixed selectivity. However, as most experiments examine neural activity within individual tasks, it is currently unclear if and how neural representations change across different task contexts. Within this discussion, the medial temporal lobe is particularly salient, as it is known to be important for multiple behaviors including spatial navigation and memory, however the relationship between these functions is currently unclear. Here, to investigate how representations in single neurons vary across different task contexts in the medial temporal lobe, we collected and analyzed single-neuron activity from human participants as they completed a paired-task session consisting of a passive-viewing visual working memory and a spatial navigation and memory task. Five patients contributed 22 paired-task sessions, which were spike sorted together to allow for the same putative single neurons to be compared between the different tasks. Within each task, we replicated concept-related activations in the working memory task, as well as target-location and serial-position responsive cells in the navigation task. When comparing neuronal activity between tasks, we first established that a significant number of neurons maintained the same kind of representation, responding to stimuli presentations across tasks. Further, we found cells that changed the nature of their representation across tasks, including a significant number of cells that were stimulus responsive in the working memory task that responded to serial position in the spatial task. Overall, our results support a flexible encoding of multiple, distinct aspects of different tasks by single neurons in the human medial temporal lobe, whereby some individual neurons change the nature of their feature coding between task contexts.
Collapse
Affiliation(s)
| | - Runnan Cao
- Lane Department of Computer Science and Electrical Engineering, West Virginia University
| | - Claire Z. Han
- Department of Biomedical Engineering, Columbia University
| | | | | | - Shuo Wang
- Department of Radiology, Washington University in St. Louis
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University
- Department of Neurological Surgery, Columbia University
| |
Collapse
|
6
|
Donoghue T, Cao R, Han CZ, Holman CM, Brandmeir NJ, Wang S, Jacobs J. Single neurons in the human medial temporal lobe flexibly shift representations across spatial and memory tasks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.22.529437. [PMID: 36865334 PMCID: PMC9980106 DOI: 10.1101/2023.02.22.529437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Investigations into how individual neurons encode behavioral variables of interest have revealed specific representations in single neurons, such as place and object cells, as well as a wide range of cells with conjunctive encodings or mixed selectivity. However, as most experiments examine neural activity within individual tasks, it is currently unclear if and how neural representations change across different task contexts. Within this discussion, the medial temporal lobe is particularly salient, as it is known to be important for multiple behaviors including spatial navigation and memory, however the relationship between these functions is currently unclear. Here, to investigate how representations in single neurons vary across different task contexts in the MTL, we collected and analyzed single-neuron activity from human participants as they completed a paired-task session consisting of a passive-viewing visual working memory and a spatial navigation and memory task. Five patients contributed 22 paired-task sessions, which were spike sorted together to allow for the same putative single neurons to be compared between the different tasks. Within each task, we replicated concept-related activations in the working memory task, as well as target-location and serial-position responsive cells in the navigation task. When comparing neuronal activity between tasks, we first established that a significant number of neurons maintained the same kind of representation, responding to stimuli presentations across tasks. Further, we found cells that changed the nature of their representation across tasks, including a significant number of cells that were stimulus responsive in the working memory task that responded to serial position in the spatial task. Overall, our results support a flexible encoding of multiple, distinct aspects of different tasks by single neurons in the human MTL, whereby some individual neurons change the nature of their feature coding between task contexts.
Collapse
Affiliation(s)
| | - Runnan Cao
- Lane Department of Computer Science and Electrical Engineering, West Virginia University
| | - Claire Z Han
- Department of Biomedical Engineering, Columbia University
| | | | | | - Shuo Wang
- Department of Radiology, Washington University in St. Louis
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University
- Department of Neurological Surgery, Columbia University
| |
Collapse
|