Category: Neural Basis of Navigation
Whether the established neural signature of spatial memory and navigation – MTL theta oscillations – are also present during the retrieval of relational verbal memory
Solomon, Ethan A., Bradley C. Lega, Michael R. Sperling, and Michael J. Kahana. “Hippocampal theta codes for distances in semantic and temporal spaces.” bioRxiv (2019): 611681.
ABSTRACT
The medial temporal lobe (MTL) is known to support episodic memory …
Two Compasses in the Central Complex of the Locust Brain
Pegel, Uta, Keram Pfeiffer, Frederick Zittrell, Christine Scholtyssek, and Uwe Homberg. “Two compasses in the central complex of the locust brain.” Journal of Neuroscience 39, no. 16 (2019): 3070-3080.
In the brain of the desert locust, neurons sensitive …
Learning to navigate – how desert ants calibrate their compass systems?
Robin Grob, Pauline N. Fleischmann and Wolfgang Rössler*. Learning to navigate – how desert ants calibrate their compass systems. Neuroforum 2019. https://doi.org/10.1515/nf-2018-0011
Navigating through the environment is a challenging task that animals cope with on a daily basis. Many …
How insects could store and recall path integration vectors to follow food-ward paths, take shortcuts, search at the feeder and re-calibrate their vector-memories with experience?
Le Moël, Florent, Thomas Jonathan Stone, Mathieu Lihoreau, Antoine Wystrach, and Barbara Webb. “The central complex as a potential substrate for vector based navigation.” Frontiers in Psychology 10 (2019): 690.
Fig from Le Moël et al. 2019.
The …
How to build goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network？
Edvardsen, Vegard. “Goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network.” Natural Computing 18, no. 1 (2019): 13-27.
The following content is extracted from Edvardsen 2019.
Edvardsen, Vegard. “Goal-directed navigation based …
How to implement long-range navigation by path integration and decoding of grid cells in a neural network?
Edvardsen, Vegard. “Long-range navigation by path integration and decoding of grid cells in a neural network.” In 2017 International Joint Conference on Neural Networks (IJCNN), pp. 4348-4355. IEEE, 2017.
The following content is extracted from Edvardsen 2017.
Neural …
How grid cells generate unambiguous and high-capacity representations of variables in much higher-dimensional space?
Klukas, Mirko, Marcus Lewis, and Ila Fiete. “Flexible representation and memory of higher-dimensional cognitive variables with grid cells.” bioRxiv (2019): 578641.
The following content is from Klukas 2019.
Grid cell representations are simultaneously flexible and powerful yet rigid …
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CogNav Blog
New discovery worth spreading on cognitive navigation in neurorobotics and neuroscience
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- How to build a bio-inspired hardware implementation of an analog spike-based hippocampus memory model?
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