scholarly journals Adaptation to conflicting visual and physical self-motion information during walking

2010 ◽  
Vol 8 (6) ◽  
pp. 1155-1155
Author(s):  
J. Saunders ◽  
F. Durgin
2017 ◽  
Vol 17 (10) ◽  
pp. 211
Author(s):  
Jonathan Matthis ◽  
Karl Muller ◽  
Kathryn Bonnen ◽  
Mary Hayhoe

2018 ◽  
Vol 115 (7) ◽  
pp. E1637-E1646 ◽  
Author(s):  
Tale L. Bjerknes ◽  
Nenitha C. Dagslott ◽  
Edvard I. Moser ◽  
May-Britt Moser

Place cells in the hippocampus and grid cells in the medial entorhinal cortex rely on self-motion information and path integration for spatially confined firing. Place cells can be observed in young rats as soon as they leave their nest at around 2.5 wk of postnatal life. In contrast, the regularly spaced firing of grid cells develops only after weaning, during the fourth week. In the present study, we sought to determine whether place cells are able to integrate self-motion information before maturation of the grid-cell system. Place cells were recorded on a 200-cm linear track while preweaning, postweaning, and adult rats ran on successive trials from a start wall to a box at the end of a linear track. The position of the start wall was altered in the middle of the trial sequence. When recordings were made in complete darkness, place cells maintained fields at a fixed distance from the start wall regardless of the age of the animal. When lights were on, place fields were determined primarily by external landmarks, except at the very beginning of the track. This shift was observed in both young and adult animals. The results suggest that preweaning rats are able to calculate distances based on information from self-motion before the grid-cell system has matured to its full extent.


1983 ◽  
Vol 27 (12) ◽  
pp. 996-1000
Author(s):  
Dean H. Owen ◽  
Lawrence J. Hettinger ◽  
Shirley B. Tobias ◽  
Lawrence Wolpert ◽  
Rik Warren

Several methods are presented for breaking linkages among global optical flow and texture variables in order to assess their usefulness in experiments requiring observers to distinguish change in speed or heading of simulated self motion from events representing constant speed or level flight. Results of a series of studies testing for sensitivity to flow acceleration or deceleration, flow-pattern expansion variables, and the distribution of optical texture density are presented. Theoretical implications for determining the metrics of visual self-motion information, and practical relevance for pilot and flight simulator evaluation and for low-level, high-speed flight are discussed.


2011 ◽  
Vol 11 (11) ◽  
pp. 898-898
Author(s):  
M. Parade ◽  
J. S. Matthis ◽  
B. R. Fajen

2021 ◽  
Author(s):  
Yue Zhang ◽  
Ruoyu Huang ◽  
Wiebke Nörenberg ◽  
Aristides Arrenberg

The perception of optic flow is essential for any visually guided behavior of a moving animal. To mechanistically predict behavior and understand the emergence of self-motion perception in vertebrate brains, it is essential to systematically characterize the motion receptive fields (RFs) of optic flow processing neurons. Here, we present the fine-scale RFs of thousands of motion-sensitive neurons studied in the diencephalon and the midbrain of zebrafish. We found neurons that serve as linear filters and robustly encode directional and speed information of translation-induced optic flow. These neurons are topographically arranged in pretectum according to translation direction. The unambiguous encoding of translation enables the decomposition of translational and rotational self-motion information from mixed optic flow. In behavioral experiments, we successfully demonstrated the predicted decomposition in the optokinetic and optomotor responses. Together, our study reveals the algorithm and the neural implementation for self-motion estimation in a vertebrate visual system.


2019 ◽  
Author(s):  
Dmitri Laptev ◽  
Neil Burgess

AbstractPlace cells and grid cells in the hippocampal formation are thought to integrate sensory and self-motion information into a representation of estimated spatial location, but the precise mechanism is unknown. We simulated a parallel attractor system in which place cells form an attractor network driven by environmental inputs and grid cells form an attractor network performing path integration driven by self-motion, with inter-connections between them allowing both types of input to influence firing in both ensembles. We show that such a system is needed to explain the spatial patterns and temporal dynamics of place cell firing when rats run on a linear track in which the familiar correspondence between environmental and self-motion inputs is changed (Gothard et al., 1996b; Redish et al., 2000). In contrast, the alternative architecture of a single recurrent network of place cells (performing path integration and receiving environmental inputs) cannot reproduce the place cell firing dynamics. These results support the hypothesis that grid and place cells provide two different but complementary attractor representations (based on self-motion and environmental sensory inputs respectively). Our results also indicate the specific neural mechanism and main predictors of hippocampal map realignment and make predictions for future studies.


2010 ◽  
Vol 50 (9) ◽  
pp. 914-923 ◽  
Author(s):  
Aurore Capelli ◽  
Alain Berthoz ◽  
Manuel Vidal

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 49717-49729
Author(s):  
Kun Han ◽  
Dewei Wu ◽  
Lei Lai ◽  
Jing He

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