scholarly journals The retrosplenial cortex combines internal and external cues to encode head velocity during navigation

2021 ◽  
Author(s):  
Sepiedeh Keshavarzi ◽  
Edward F. Bracey ◽  
Richard A. Faville ◽  
Dario Campagner ◽  
Adam L. Tyson ◽  
...  

The extent to which we successfully navigate the environment depends on our ability to continuously track our heading direction. Neurons that encode the speed and the direction of head turns during navigation, known as angular head velocity (AHV) cells, are fundamental to this process, but the sensory computations underlying their activity remain unknown. By performing chronic single-unit recordings in the retrosplenial cortex (RSP) of the mouse and tracking the activity of individual AHV neurons between freely moving and head-restrained conditions, we find that vestibular inputs dominate AHV signalling. In addition, we discover that self-generated optic flow input onto these neurons increases the gain and signal-to-noise ratio of angular velocity coding during navigation. Psychophysical experiments and neural decoding further reveal that vestibular-visual integration increases the perceptual accuracy of egocentric angular velocity and the fidelity of its representation by RSP ensembles. We propose that while AHV coding is dependent on vestibular cues, it also utilises vision to maximise navigation accuracy in nocturnal and diurnal environments.

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Thomas Zhihao Luo ◽  
Adrian Gopnik Bondy ◽  
Diksha Gupta ◽  
Verity Alexander Elliott ◽  
Charles D Kopec ◽  
...  

The use of Neuropixels probes for chronic neural recordings is in its infancy and initial studies leave questions about long-term stability and probe reusability unaddressed. Here, we demonstrate a new approach for chronic Neuropixels recordings over a period of months in freely moving rats. Our approach allows multiple probes per rat and multiple cycles of probe reuse. We found that hundreds of units could be recorded for multiple months, but that yields depended systematically on anatomical position. Explanted probes displayed a small increase in noise compared to unimplanted probes, but this was insufficient to impair future single-unit recordings. We conclude that cost-effective, multi-region, and multi-probe Neuropixels recordings can be carried out with high yields over multiple months in rats or other similarly sized animals. Our methods and observations may facilitate the standardization of chronic recording from Neuropixels probes in freely moving animals.


eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Maciej M Jankowski ◽  
Md Nurul Islam ◽  
Nicholas F Wright ◽  
Seralynne D Vann ◽  
Jonathan T Erichsen ◽  
...  

Discrete populations of brain cells signal heading direction, rather like a compass. These ‘head direction’ cells are largely confined to a closely-connected network of sites. We describe, for the first time, a population of head direction cells in nucleus reuniens of the thalamus in the freely-moving rat. This novel subcortical head direction signal potentially modulates the hippocampal CA fields directly and, thus, informs spatial processing and memory.


2018 ◽  
Author(s):  
Ardi Tampuu ◽  
Tambet Matiisen ◽  
H. Freyja Ólafsdóttir ◽  
Caswell Barry ◽  
Raul Vicente

AbstractPlace cells in the mammalian hippocampus signal self-location with sparse spatially stable firing fields. Based on observation of place cell activity it is possible to accurately decode an animal’s location. The precision of this decoding sets a lower bound for the amount of information that the hippocampal population conveys about the location of the animal. In this work we use a novel recurrent neural network (RNN) decoder to infer the location of freely moving rats from single unit hippocampal recordings. RNNs are biologically plausible models of neural circuits that learn to incorporate relevant temporal context without the need to make complicated assumptions about the use of prior information to predict the current state. When decoding animal position from spike counts in 1D and 2D-environments, we show that the RNN consistently outperforms a standard Bayesian model with flat priors. In addition, we also conducted a set of sensitivity analysis on the RNN decoder to determine which neurons and sections of firing fields were the most influential. We found that the application of RNNs to neural data allowed flexible integration of temporal context, yielding improved accuracy relative to a commonly used Bayesian approach and opens new avenues for exploration of the neural code.Author summaryBeing able to accurately self-localize is critical for most motile organisms. In mammals, place cells in the hippocampus appear to be a central component of the brain network responsible for this ability. In this work we recorded the activity of a population of hippocampal neurons from freely moving rodents and carried out neural decoding to determine the animals’ locations. We found that a machine learning approach using recurrent neural networks (RNNs) allowed us to predict the rodents’ true positions more accurately than a standard Bayesian method with flat priors. The RNNs are able to take into account past neural activity without making assumptions about the statistics of neuronal firing. Further, by analyzing the representations learned by the network we were able to determine which neurons, and which aspects of their activity, contributed most strongly to the accurate decoding.


2021 ◽  
Author(s):  
Sepiedeh Keshavarzi ◽  
Edward Bracey ◽  
Richard Faville ◽  
Dario Campagner ◽  
Adam Tyson ◽  
...  

Author(s):  
Barry J. Gallacher ◽  
Zhongxu Hu ◽  
Kiran Mysore Harish ◽  
Stephen Bowles ◽  
Harry Grigg

Parametric excitation, via electrostatic stiffness modulation, can be exploited in resonant MEMS gyroscopes. In the case of the Rate gyroscope, which is by far the most common type of MEMS gyro, parametric excitation may be used to amplify either the primary mode of the gyro or the response to the angular rate. Both approaches will be discussed. In the more complex mode of operation, known as “Rate Integrating” the output of the gyro is angle directly as opposed to angular velocity in the case of Rate gyro. In this rate integrating mode of operation parametric excitation does offer an effective energy control used to initiate, sustain the vibration and minimise damping perturbations. Parametric amplification of the primary mode of the rate gyroscope is presented and supported with experimental results. In this implementation parametric excitation is combined with external harmonic forcing of the primary mode in order to reduce electrical feedthrough of the driving signal to the sense electrodes. A practical parametric excitation scheme implemented using Digital Signal Processing has been developed to enable either amplification of the primary mode of the gyroscope or amplification of the response to the applied angular velocity. Parametric amplification of the primary mode of the gyroscope is achieved by frequency tracking and regulation of the amplitudes of the harmonic forcing and parametric excitation to maintain a desired parametric gain by closed loop PID control. Stable parametric amplification of the primary mode by a factor of 20 is demonstrated experimentally. This has important benefits regarding the minimisation of electrical feedthrough of the drive signal to the sense electrodes of the secondary mode. By taking advantage of the phase dependence of parametric amplification and the orthogonality of the Coriolis force and quadrature forcing, the response to the applied angular velocity may be parametrically amplified by applying excitation of a particular phase directly to the sensing mode. The major advantage of parametric amplification applied to MEMs gyroscopes is that it can mechanically amplify the Coriolis response before being picked off electrically. This is particularly advantageous for sensors where electronic noise is the major noise contributor. In this case parametric amplification can significantly improve the signal to noise ratio of the secondary mode by an amount approximately equal to the parametric amplification. Preliminary rate table tests performed in open loop demonstrate a magnification of the signal to noise ratio of the secondary mode by a factor of 9.5.


eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Wen-Hao Zhang ◽  
He Wang ◽  
Aihua Chen ◽  
Yong Gu ◽  
Tai Sing Lee ◽  
...  

Our brain perceives the world by exploiting multisensory cues to extract information about various aspects of external stimuli. The sensory cues from the same stimulus should be integrated to improve perception, and otherwise segregated to distinguish different stimuli. In reality, however, the brain faces the challenge of recognizing stimuli without knowing in advance the sources of sensory cues. To address this challenge, we propose that the brain conducts integration and segregation concurrently with complementary neurons. Studying the inference of heading-direction via visual and vestibular cues, we develop a network model with two reciprocally connected modules modeling interacting visual-vestibular areas. In each module, there are two groups of neurons whose tunings under each sensory cue are either congruent or opposite. We show that congruent neurons implement integration, while opposite neurons compute cue disparity information for segregation, and the interplay between two groups of neurons achieves efficient multisensory information processing.


2020 ◽  
Vol 20 (2) ◽  
pp. 99-107
Author(s):  
M Phomsoupha ◽  
J Jeuvrey ◽  
G Laffaye

Aim. Forearm extension and radio-ulnar pronation are two common components of the final movement during each badminton smash stroke. By coordinating the forearm to produce both extension and pronation at the same time, racket head velocity can be increased. Thus, this study examined maximal velocity and racket deflection during both movements in regard with skill level. Materials and methods. Twenty-two players (8 experts and 14 novices) participated in this study. Wrist, handle and racket head velocity were recorded using high speed cameras (Vicon V8i at a frequency of 250 Hz). Results. The racket head velocity with radio-ulnar pronation was 16 % higher than with forearm extension. This higher velocity resulted from an 8 % higher acceleration and a 70 % higher maximal angular velocity of the end points of the forearm segments during radio-ulnar pronation. In each movement, experts’ maximal velocity was higher than that of novices (p < .001).The maximal velocity of the racket for novices was obtained with elbow extension (20.9 ± 4.8 m/s), with a gain of 47 %, whereas for experts, it was obtained with radio-ulnar pronation (33.9 ± 5.8 m/s), with a gain of 53 %. Conclusion. The difference between the best velocities in both samples is 39 %, obtained respectively by radio-ulnar pronation for experts and an elbow extension for novices. Forearm extension and radio-ulnar pronation acceleration on the handle led to an increase in racket head velocity.


2018 ◽  
Author(s):  
Wen-Hao Zhang ◽  
He Wang ◽  
Aihua Chen ◽  
Yong Gu ◽  
Tai Sing Lee ◽  
...  

Abstract Our brain perceives the world by exploiting multiple sensory modalities to extract information about various aspects of external stimuli. If these sensory cues are from the same stimulus of interest, they should be integrated to improve perception; otherwise, they should be segregated to distinguish different stimuli. In reality, however, the brain faces the challenge of recognizing stimuli without knowing in advance whether sensory cues come from the same or different stimuli. To address this challenge and to recognize stimuli rapidly, we argue that the brain should carry out multisensory integration and segregation concurrently with complementary neuron groups. Studying an example of inferring heading-direction via visual and vestibular cues, we develop a concurrent multisensory processing neural model which consists of two reciprocally connected modules, the dorsal medial superior temporal area (MSTd) and the ventral intraparietal area (VIP), and that at each module, there exists two distinguishing groups of neurons, congruent and opposite neurons. Specifically, congruent neurons implement cue integration, while opposite neurons compute the cue disparity, both optimally as described by Bayesian inference. The two groups of neurons provide complementary information which enables the neural system to assess the validity of cue integration and, if necessary, to recover the lost information associated with individual cues without re-gathering new inputs. Through this process, the brain achieves rapid stimulus perception if the cues come from the same stimulus of interest, and differentiates and recognizes stimuli based on individual cues with little time delay if the cues come from different stimuli of interest. Our study unveils the indispensable role of opposite neurons in multisensory processing and sheds light on our understanding of how the brain achieves multisensory processing efficiently and rapidly.Significance StatementOur brain perceives the world by exploiting multiple sensory cues. These cues need to be integrated to improve perception if they come from the same stimulus and otherwise be segregated. To address the challenge of recognizing whether sensory cues come from the same or different stimuli that are unknown in advance, we propose that the brain should carry out multisensory integration and segregation concurrently with two different neuron groups. Specifically, congruent neurons implement cue integration, while opposite neurons compute the cue disparity, and the interplay between them achieves rapid stimulus recognition without information loss. We apply our model to the example of inferring heading-direction based on visual and vestibular cues and reproduce the experimental data successfully.


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