Abstract
Place recognition is naturally informed by the mosaic of sensations we remember from previously visiting a location and general knowledge of our location in the world. Neurons in the mammalian brain (specifically in the hippocampus formation) named “place cells” are thought to reflect this recognition of place and are involved in implementing a spatial map that can be used for path planning and memory recall. In this research, we use bat-inspired sonar to mimic how bats might sense objects in the environment and recognize the views associated with different places. These “echo view cells” may contribute (along with odometry) to the creation of place cell representations observed in bats. Although detailed sensory template matching is straightforward, it is quite unlikely that a flying animal or robot will return to the exact 3-D position and pose where the original memory was captured. Instead, we strive to recognize views over extended regions that are many body lengths in size, reducing the number of places to be remembered for a map. We have successfully demonstrated some of this spatial invariance by training feed-forward neural networks (traditional neural networks and spiking neural networks) to recognize 66 distinct places in a laboratory environment over a limited range of translations and rotations. We further show how the echo view cells respond between known views and how their outputs can be combined over time for continuity.
Highlights
The hippocampal formation in the mammalian brain is well-known for its population of “place cells,” a type of neuron that responds when an animal is in a particular place in its environment
In the Synaptic Kernel Inverse Method (SKIM) network trained with OPIUM, we achieved up to 93.5% accuracy on our dataset
Supplementary videos show the activations of the original network, the widened network, and the leaky integration applied to the widened network similar to Figure 13, but over the entire path
Summary
The hippocampal formation in the mammalian brain is well-known for its population of “place cells,” a type of neuron that responds when an animal is in a particular place in its environment. Studies in the rat suggest that these cells use internal odometry signals (allowing the system to operate in darkness) as well as external sensory cues (allowing the system to recognize places and correct the odometry system) (O’Keefe, 1976; Jung et al, 1994). In the flying, echolocating bat, neurons with very similar properties have been found (Ulanovsky and Moss, 2007; Yartsev et al, 2011; Yartsev and Ulanovsky, 2013; Geva-Sagiv et al, 2015). The signal processing and neural mechanisms with which bats recognize places is still largely unknown, modeling this capability with biologically-plausible sensors and robotics can give us insights into problems that bats encounter and motivate future behavioral and neurophysiological experiments with bats.
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