Brain Inspired Navigation Blog

Category: Spatial Cognition

How does the brain achieve variable neuronal activity?

Johnston, W. Jeffrey, Stephanie E. Palmer, and David J. Freedman. “Nonlinear mixed selectivity supports reliable neural computation.” bioRxiv (2019): 577288.

Summary
Neuronal activity in the brain is variable, yet both perception and behavior are generally reliable. How does the brain …

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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 …

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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 …

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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 …

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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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How grid cells could possibly organize?

Anselmi, Fabio, Benedetta Franceschiello, Micah M. Murray, and Lorenzo Rosasco. “A computational model for grid maps in neural populations.” arXiv preprint arXiv:1902.06553 (2019).

The following content is extracted from Anselmi 2019.

Anselmi, Fabio, Benedetta Franceschiello, Micah M. Murray, …

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How the brain implements recognition of familiar faces, objects, and scenes at the neural level?

Bicanski and Burgess 2019 propose that grid cells support visual recognition memory, by encoding translation vectors between salient stimulus features. They provide an explicit neural mechanism for the role of directed saccades in hypothesis-driven, constructive perception and recognition, and …

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Insect Navigation: From Ants to Robots and Back Again

The latest RIN Navigation News focus on  Insect Navigation: From Ants to Robots and Back Again.

For further info, please visit the RIN website. …

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A gravity-based three-dimensional compass in the mouse brain

Head direction cells in the mammalian limbic system are thought to function as an allocentric neuronal compass. Although traditional views hold that the compass of ground-dwelling species is planar, Angelaki et al. 2019 show that head-direction cells in the rodent …

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NeuroSLAM : Neural Simultaneous Localization and Mapping Workshop 13-14 Mar 2019 Paris (France)

NeuroSLAM: Neural Simultaneous Localization and Mapping Workshop

 

Simultaneous Localization and Mapping (or SLAM) refers to the problem of constructing a map of an unknown environment as it is actively being explored. SLAM has been treated extensively in mobile robotics, providing …

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How the brain represent 3D head direction in 3D space?

The note is an excerpt from the Shinder et al. 2019. We just describe some key conception and results in this study as a significant note. Please read the original paper if you are interested in the study on https://www.physiology.org/doi/full/10.1152/jn.00880.2017…

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Robots are learning how to walk like we do

Robots have walked on legs for decades. Today’s most advanced humanoid robots can tramp along flat and inclined surfaces, climb up and down stairs, and slog through rough terrain. Some can even jump.

A report about legged robots on the …

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Brain Inspired Navigation Blog

New discovery worth spreading on brain-inspired navigation in neurorobotics and neuroscience

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