Velocity-Tuned Oscillators for NeuroSLAM and Spatial Navigation

Nasrallah, Alia; Chen, Zhaoqi; Alemohammad, Milad; Balaji, A.; Cellon, Adam B.; Furuta, Mamoru; Etienne‐Cummings, Ralph

doi:10.1109/iscas45731.2020.9180441

Cited by 3 publications

(4 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When experimenting with the model, we adopt square-wave oscillation and quantized phases to demonstrate the model's suitability for hardware implementation. Our team built a mixed-mode theta chip [32] to imitate the behavior of theta cells described in equation ( 1), which has substantial variations across all theta cells, as figure 12 shows. With the proposed model, variations might be a beneficial feature for construction of place cells.…”

Section: Discussionmentioning

confidence: 99%

Neuromorphic model of hippocampus place cells using an oscillatory interference technique for hardware implementation

Chen

Nasrallah

Alemohammad

et al. 2022

Neuromorph. Comput. Eng.

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a simplified and robust model for Place cell generation based on the Oscillatory Interference (OI) model concept. Aiming toward hardware implementation in bio-inspired Simultaneous Localization and Mapping (SLAM) systems for mobile robotics, we base our model on logic operations that reduce its computational complexity. The model compensates for parameter variations in the behaviors of the population of constituent Theta cells, and allows the Theta cells to have square-wave oscillation profiles. The robustness of the model, with respect to mismatch in the Theta cell’s base oscillation frequency and gain—as a function of modulatory inputs—is demonstrated. Place cell composed of 48 Theta cells with base frequency variations with a 25% standard deviation from the mean and a gain error with 20% standard deviation from the mean only result in a 20% deformations within the place field and 0.24% outer side lobes, and an overall pattern with 0.0015 mean squared error on average. We also present how the model can be used to achieve the localization and path-tracking functionalities of SLAM. Hence, we propose a model for spatial cell formation using Theta cells with behaviors that are biologically plausible and hardware implementable for real world application in neurally-inspired SLAM.

show abstract

Section: Discussionmentioning

confidence: 99%

Neuromorphic model of hippocampus place cells using an oscillatory interference technique for hardware implementation

Chen

Nasrallah

Alemohammad

et al. 2022

Neuromorph. Comput. Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…When experimenting with the model, we adopt squarewave oscillation and quantized phases to demonstrate the model's suitability for hardware implementation. Our team built a mixed-mode theta chip [32] to imitate the behavior of Theta cells described in equation ( 1), which has substantial variations across all Theta cells, as figure 11 shows. With the proposed model, variations might be a beneficial feature for construction of Place cells.…”

Section: Discussionmentioning

confidence: 99%

Neuromorphic Model of Hippocampus Place cells using an Oscillatory Interference Technique for Hardware Implementation

Chen

Nasrallah

Alemohammad

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a simplified and robust model for Place cell generation based on the Oscillatory Interference (OI) model concept. Aiming toward hardware implementation in bio-inspired Simultaneous Localization and Mapping (SLAM) systems for mobile robotics, we base our model on logic operations that reduce its computational complexity. The model compensates for parameter variations in the behaviors of the population of constituent Theta cells, and allows the Theta cells to have square-wave oscillation profiles. The robustness of the model, with respect to mismatch in the Theta cell's base oscillation frequency and gain as a function of modulatory inputs is demonstrated. Place cell composed of 48 Theta cells with base frequency variations with a 25% standard deviation from the mean and a gain error with 20% standard deviation from the mean only result in a 20% deformations within the place field and 0.24% outer side lobes, and an overall pattern with 0.0015 mean squared error on average. We also present how the model can be used to achieve the localization and path-tracking functionalities of SLAM.

show abstract

“…We also choose digital output for the theta unit oscillations for easier handling by external components. We briefly describe the final design of the chip below; a detailed description of an early design of the included circuits is discussed previously in [21].…”

Section: Design Of the Theta Chipmentioning

confidence: 99%

“…To amend this problem, we designed a theta chip that employs the principle of abstract neuromorphism to implement the theta cells' behavior model by exploiting the simplicity of analog computation circuitries. We published an early design for the chip in [21] and then taped out the chip in the TSMC 65 nm process. In this paper, we will briefly introduce the final design of the theta chip in section 3, and its performance and proposed application in implementing place cells in section 6.…”

Section: Introductionmentioning

confidence: 99%

Neuromorphic place cells

Chen,

Nasrallah,

Etienne-Cummings

2024

Neuromorph. Comput. Eng.

Self Cite

View full text Add to dashboard Cite

A neuromorphic SLAM system shows potential for more efficient implementation than its traditional counterpart. At the mean time a neuromorphic model of spatial encoding neurons in silicon could provide insights on the functionality and dynamic between each group of cells. Especially when realistic factors including variations and imperfections on the neural movement encoding are presented to challenge the existing hypothetical models for localization. We demonstrate a mixed-mode implementation for spatial encoding neurons including theta cells, egocentric place cells, and the typical allocentric place cells. Together, they form a biologically plausible network that could reproduce the localization functionality of place cells observed in rodents. The system consists of a theta chip with 128 theta cell units and an FPGA implementing 4 networks for egocentric place cells formation that provides the capability for tracking on a 11 by 11 place cell grid. Experimental results validate the robustness of our model when suffering from as much as 18% deviation, induced by parameter variations in analog circuits, from the mathematical model of theta cells. We provide a model for implementing dynamic neuromorphic SLAM systems for dynamic-scale mapping of cluttered environments, even when subject to significant errors in sensory measurements and real-time analog computation. We also suggest a robust approach for the network topology of spatial cells that can mitigate neural non-uniformity and provides a hypothesis for the function of grid cells and the existence of egocentric place cells.

show abstract

Velocity-Tuned Oscillators for NeuroSLAM and Spatial Navigation

Cited by 3 publications

References 16 publications

Neuromorphic model of hippocampus place cells using an oscillatory interference technique for hardware implementation

Neuromorphic model of hippocampus place cells using an oscillatory interference technique for hardware implementation

Neuromorphic Model of Hippocampus Place cells using an Oscillatory Interference Technique for Hardware Implementation

Neuromorphic place cells

Contact Info

Product

Resources

About