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Zhang Z, Tang F, Li Y, Feng X. A spatial transformation-based CAN model for information integration within grid cell modules. Cogn Neurodyn 2024; 18:1861-1876. [PMID: 39104694 PMCID: PMC11297887 DOI: 10.1007/s11571-023-10047-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 10/13/2023] [Accepted: 11/26/2023] [Indexed: 08/07/2024] Open
Abstract
The hippocampal-entorhinal circuit is considered to play an important role in the spatial cognition of animals. However, the mechanism of the information flow within the circuit and its contribution to the function of the grid-cell module are still topics of discussion. Prevailing theories suggest that grid cells are primarily influenced by self-motion inputs from the Medial Entorhinal Cortex, with place cells serving a secondary role by contributing to the visual calibration of grid cells. However, recent evidence suggests that both self-motion inputs and visual cues may collaboratively contribute to the formation of grid-like patterns. In this paper, we introduce a novel Continuous Attractor Network model based on a spatial transformation mechanism. This mechanism enables the integration of self-motion inputs and visual cues within grid-cell modules, synergistically driving the formation of grid-like patterns. From the perspective of individual neurons within the network, our model successfully replicates grid firing patterns. From the view of neural population activity within the network, the network can form and drive the activated bump, which describes the characteristic feature of grid-cell modules, namely, path integration. Through further exploration and experimentation, our model can exhibit significant performance in path integration. This study provides a new insight into understanding the mechanism of how the self-motion and visual inputs contribute to the neural activity within grid-cell modules. Furthermore, it provides theoretical support for achieving accurate path integration, which holds substantial implications for various applications requiring spatial navigation and mapping.
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Affiliation(s)
- Zhihui Zhang
- The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No.114, Nanta Street Heping District, Shenyang, 110016 Liaoning China
- University of Science and Technology of China, No.96, JinZhai Road Baohe District, Hefei, 230026 Anhui China
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, No.135, Chuangxin Road Hunnan District, Shenyang, 110169 Liaoning China
| | - Fengzhen Tang
- The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No.114, Nanta Street Heping District, Shenyang, 110016 Liaoning China
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, No.135, Chuangxin Road Hunnan District, Shenyang, 110169 Liaoning China
| | - Yiping Li
- The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No.114, Nanta Street Heping District, Shenyang, 110016 Liaoning China
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, No.135, Chuangxin Road Hunnan District, Shenyang, 110169 Liaoning China
| | - Xisheng Feng
- The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No.114, Nanta Street Heping District, Shenyang, 110016 Liaoning China
- University of Science and Technology of China, No.96, JinZhai Road Baohe District, Hefei, 230026 Anhui China
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, No.135, Chuangxin Road Hunnan District, Shenyang, 110169 Liaoning China
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Nguyen D, Wang G, Gu Y. The medial entorhinal cortex encodes multisensory spatial information. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.09.574924. [PMID: 38313299 PMCID: PMC10836072 DOI: 10.1101/2024.01.09.574924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Animals employ spatial information in multisensory modalities to navigate their natural environments. However, it is unclear whether the brain encodes such information in separate cognitive maps or integrates all into a single, universal map. We addressed this question in the microcircuit of the medial entorhinal cortex (MEC), a cognitive map of space. Using cellular-resolution calcium imaging, we examined the MEC of mice navigating virtual reality tracks, where visual and auditory cues provided comparable spatial information. We uncovered two cell types: "unimodality cells" and "multimodality cells". The unimodality cells specifically represent either auditory or visual spatial information. They are anatomically intermingled and maintain sensory preferences across multiple tracks and behavioral states. The multimodality cells respond to both sensory modalities with their responses shaped differentially by auditory and visual information. Thus, the MEC enables accurate spatial encoding during multisensory navigation by computing spatial information in different sensory modalities and generating distinct maps.
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Affiliation(s)
- Duc Nguyen
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Current address: Center of Neural Science, New York University, New York, NY, USA
| | - Garret Wang
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yi Gu
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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Purohit P, Dutta P, Roy PK. Empirically validated theoretical analysis of visual-spatial perception under change of nervous system arousal. Front Comput Neurosci 2023; 17:1136985. [PMID: 37251600 PMCID: PMC10213702 DOI: 10.3389/fncom.2023.1136985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 04/03/2023] [Indexed: 05/31/2023] Open
Abstract
Introduction Visual-spatial perception is a process for extracting the spatial relationship between objects in the environment. The changes in visual-spatial perception due to factors such as the activity of the sympathetic nervous system (hyperactivation) or parasympathetic nervous system (hypoactivation) can affect the internal representation of the external visual-spatial world. We formulated a quantitative model of the modulation of visual-perceptual space under action by hyperactivation or hypoactivation-inducing neuromodulating agents. We showed a Hill equation based relationship between neuromodulator agent concentration and alteration of visual-spatial perception utilizing the metric tensor to quantify the visual space. Methods We computed the dynamics of the psilocybin (hyperactivation-inducing agent) and chlorpromazine (hypoactivation-inducing agent) in brain tissue. Then, we validated our quantitative model by analyzing the findings of different independent behavioral studies where subjects were assessed for alterations in visual-spatial perception under the action of psilocybin and under chlorpromazine. To validate the neuronal correlates, we simulated the effect of the neuromodulating agent on the computational model of the grid-cell network, and also performed diffusion MRI-based tractography to find the neural tracts between the cortical areas involved: V2 and the entorhinal cortex. Results We applied our computational model to an experiment (where perceptual alterations were measured under psilocybin) and found that for n (Hill-coefficient) = 14.8 and k = 1.39, the theoretical prediction followed experimental observations very well (χ2 test robustly satisfied, p > 0.99). We predicted the outcome of another psilocybin-based experiment using these values (n = 14.8 and k = 1.39), whereby our prediction and experimental outcomes were well corroborated. Furthermore, we found that also under hypoactivation (chlorpromazine), the modulation of the visual-spatial perception follows our model. Moreover, we found neural tracts between the area V2 and entorhinal cortex, thus providing a possible brain network responsible for encoding visual-spatial perception. Thence, we simulated the altered grid-cell network activity, which was also found to follow the Hill equation. Conclusion We developed a computational model of visuospatial perceptual alterations under altered neural sympathetic/parasympathetic tone. We validated our model using analysis of behavioral studies, neuroimaging assessment, and neurocomputational evaluation. Our quantitative approach may be probed as a potential behavioral screening and monitoring methodology in neuropsychology to analyze perceptual misjudgment and mishaps by highly stressed workers.
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Affiliation(s)
- Pratik Purohit
- School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, India
| | - Prasun Dutta
- Department of Physics, Indian Institute of Technology (BHU), Varanasi, India
| | - Prasun K. Roy
- School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, India
- Department of Life Sciences, Shiv Nadar University (SNU), Greater Noida, India
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Dumont NSY, Stöckel A, Furlong PM, Bartlett M, Eliasmith C, Stewart TC. Biologically-Based Computation: How Neural Details and Dynamics Are Suited for Implementing a Variety of Algorithms. Brain Sci 2023; 13:brainsci13020245. [PMID: 36831788 PMCID: PMC9954128 DOI: 10.3390/brainsci13020245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/28/2023] [Accepted: 01/28/2023] [Indexed: 02/04/2023] Open
Abstract
The Neural Engineering Framework (Eliasmith & Anderson, 2003) is a long-standing method for implementing high-level algorithms constrained by low-level neurobiological details. In recent years, this method has been expanded to incorporate more biological details and applied to new tasks. This paper brings together these ongoing research strands, presenting them in a common framework. We expand on the NEF's core principles of (a) specifying the desired tuning curves of neurons in different parts of the model, (b) defining the computational relationships between the values represented by the neurons in different parts of the model, and (c) finding the synaptic connection weights that will cause those computations and tuning curves. In particular, we show how to extend this to include complex spatiotemporal tuning curves, and then apply this approach to produce functional computational models of grid cells, time cells, path integration, sparse representations, probabilistic representations, and symbolic representations in the brain.
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Affiliation(s)
- Nicole Sandra-Yaffa Dumont
- Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON N2L 3G1, Canada
- Correspondence:
| | | | - P. Michael Furlong
- Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Madeleine Bartlett
- Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Chris Eliasmith
- Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON N2L 3G1, Canada
- Applied Brain Research Inc., Waterloo, ON N2T 1G9, Canada
| | - Terrence C. Stewart
- National Research Council, University of Waterloo Collaboration Centre, Waterloo, ON N2L 3G1, Canada
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Chen ZS, Zhang X, Long X, Zhang SJ. Are Grid-Like Representations a Component of All Perception and Cognition? Front Neural Circuits 2022; 16:924016. [PMID: 35911570 PMCID: PMC9329517 DOI: 10.3389/fncir.2022.924016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/14/2022] [Indexed: 11/24/2022] Open
Abstract
Grid cells or grid-like responses have been reported in the rodent, bat and human brains during various spatial and non-spatial tasks. However, the functions of grid-like representations beyond the classical hippocampal formation remain elusive. Based on accumulating evidence from recent rodent recordings and human fMRI data, we make speculative accounts regarding the mechanisms and functional significance of the sensory cortical grid cells and further make theory-driven predictions. We argue and reason the rationale why grid responses may be universal in the brain for a wide range of perceptual and cognitive tasks that involve locomotion and mental navigation. Computational modeling may provide an alternative and complementary means to investigate the grid code or grid-like map. We hope that the new discussion will lead to experimentally testable hypotheses and drive future experimental data collection.
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Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, Neuroscience Institute, New York University School of Medicine, New York, NY, United States
| | - Xiaohan Zhang
- Department of Psychiatry, Department of Neuroscience and Physiology, Neuroscience Institute, New York University School of Medicine, New York, NY, United States
| | - Xiaoyang Long
- Department of Neurosurgery, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Sheng-Jia Zhang
- Department of Neurosurgery, Xinqiao Hospital, Army Medical University, Chongqing, China
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Harrison SJ, Reynolds N, Bishoff B, Stergiou N, White E. Homing tasks and distance matching tasks reveal different types of perceptual variables associated with perceiving self-motion during over-ground locomotion. Exp Brain Res 2022; 240:1257-1266. [PMID: 35199188 DOI: 10.1007/s00221-022-06337-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 02/15/2022] [Indexed: 11/28/2022]
Abstract
Self-motion perception refers to the ability to perceive how the body is moving through the environment. Perception of self-motion has been shown to depend upon the locomotor action patterns used to move the body through the environment. Two separate lines of enquiry have led to the establishment of two distinct theories regarding this effect. One theory has proposed that distances travelled during locomotion are perceived via higher order perceptual variables detected by the haptic perceptual system. This theory proposes that two higher order haptic perceptual variables exist, and that the implication of one of these variables depends upon the type of gait pattern that is used. A second theory proposes that self-motion is perceived via a higher order perceptual variable termed multimodally specified energy expenditure (MSEE). This theory proposes that the effect of locomotor actions patterns upon self-motion perception is related to changes in the metabolic cost of locomotion per unit of perceptually specified traversed distance. Here, we test the hypothesis that the development of these distinct theories is the result of different choices in methodology. The theory of gait type has been developed based largely on the results of homing tasks, whereas the effect of MSEE has been developed based on the results of distance matching tasks. Here we test the hypothesis that the seemly innocuous change in experimental design from using a homing task to using a distance matching task changes the type of perceptual variables implicated in self-motion perception. To test this hypothesis, we closely replicated a recent study of the effect of gait type in all details bar one-we investigated a distance matching task rather than a homing task. As hypothesized, this change yielded results consistent with the predictions of MSEE, and distinct from gait type. We further show that, unlike the effect of gait type, the effect of MSEE is unaffected by the availability of vision. In sum, our findings support the existence of two distinct types of higher order perceptual variables in self-motion perception. We discuss the roles of these two types of perceptual variables in supporting effective human wayfinding.
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Affiliation(s)
- Steven J Harrison
- Department of Kinesiology, University of Connecticut, Storrs, CT, 06269, USA. .,Center for Ecological Study of Perception and Action, University of Connecticut, Storrs, USA. .,Department of Biomechanics, University of Nebraska at Omaha, Omaha, USA.
| | - Nicholas Reynolds
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, USA
| | - Brandon Bishoff
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, USA
| | - Nicholas Stergiou
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, USA
| | - Eliah White
- Department of Psychological Science, Northern Kentucky University, Highland Heights, USA
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Houser TM. Spatialization of Time in the Entorhinal-Hippocampal System. Front Behav Neurosci 2022; 15:807197. [PMID: 35069143 PMCID: PMC8770534 DOI: 10.3389/fnbeh.2021.807197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 12/06/2021] [Indexed: 11/19/2022] Open
Abstract
The functional role of the entorhinal-hippocampal system has been a long withstanding mystery. One key theory that has become most popular is that the entorhinal-hippocampal system represents space to facilitate navigation in one's surroundings. In this Perspective article, I introduce a novel idea that undermines the inherent uniqueness of spatial information in favor of time driving entorhinal-hippocampal activity. Specifically, by spatializing events that occur in succession (i.e., across time), the entorhinal-hippocampal system is critical for all types of cognitive representations. I back up this argument with empirical evidence that hints at a role for the entorhinal-hippocampal system in non-spatial representation, and computational models of the logarithmic compression of time in the brain.
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Affiliation(s)
- Troy M. Houser
- Department of Psychology, University of Oregon, Eugene, OR, United States
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