Mouse entorhinal cortex encodes a diverse repertoire of self-motion signals

Mallory, Caitlin S.; Hardcastle, Kiah; Campbell, Malcolm; Attinger, Alexander; Low, Isabel I. C.; Raymond, Jennifer L.; Giocomo, Lisa M.

doi:10.1038/s41467-021-20936-8

Cited by 27 publications

(28 citation statements)

References 59 publications

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“…The robust representation of vestibular stimuli observed here complements and extends recent work on vestibular-evoked responses in the rodent cortical network (44,62,67). AHV neurons in the RSP may belong to the same population of cells that were previously shown to provide head motion information to the primary visual cortex (44), and may also be the source of head motion signals in other cortical areas that are directly connected to the RSP, such as postsubiculum ( 68) and the entorhinal cortex (69). The pathways that provide AHV information to the RSP are yet to be described but one possible route could involve the ascending thalamocortical head direction network.…”

Section: Discussionsupporting

confidence: 79%

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

Keshavarzi

Bracey

et al. 2021

Preprint

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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.

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Section: Discussionsupporting

confidence: 79%

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

Keshavarzi

Bracey

et al. 2021

Preprint

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“…Cortical AHV neurons that track the activity of the vestibular organs were first reported in head-fixed monkeys and cats decades ago (Büttner and Buettner, 1978;Vanni-Mercier and Magnin, 1982). Later, AHV neurons were also found in the rodent cortex, specifically in pre-and postsubiculum (Preston-Ferrer et al, 2016;Sharp, 1996), entorhinal cortex (Mallory et al, 2021), posterior parietal cortex (Wilber et al, 2014), anterior cingulate cortex (Mehlman et al, 2019) and RSC (Cho and Sharp, 2001). However, the underlying modalities that drive tuning have remained unknown.…”

Section: Discussionmentioning

confidence: 99%

“…To reduce the influence of conjunctive head direction tuning, we limited the range of directions that the mouse could face by rotating the stage back and forth between two target positions located 180°apart (Figure 3A, 4928 cells, 10 mice). To determine the distribution of behaviourally relevant AHV, we analysed published data of freely moving mice (Laurens et al, 2019) and found that about 90 % of all head rotations are slower than 180°/s (see Methods, n = 25 mice, see also Mallory et al (2021)). Therefore, we rotated the mice at speeds between -180 to +180°/s in steps of 45°/s (Figure 3A).…”

Section: A Large Fraction Of Turn-selective Neurons Encode Ahvmentioning

confidence: 99%

Mapping vestibular and visual contributions to angular head velocity tuning in the cortex

Hennestad

Witoelar

Chambers

et al. 2021

Preprint

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Neurons that signal the direction and angular velocity of head movements (AHV cells) are critically important to process visual and spatial information. However, it has been challenging to isolate the sensory modality that drives them and to compre hensively map their cortical distribution. To address this, we developed a method that enables rotating awake, head-fixed mice under a two-photon microscope in a visual environment. Starting in layer 2/3 of the retrosplenial cortex, a key area for vision and navigation, we found that a significant fraction of rotation sensitive neurons report AHV. These tuning properties depend on vestibular input because they persist in darkness and are reduced when replaying visual flow to stationary animals. When mapping the spatial extent, we found AHV cells in all cortical areas that we explored, including motor, somatosensory, visual and posterior parietal cortex. Notably, the vestibular and visual contributions to AHV are area dependent. Thus, many cortical circuits have access to AHV, enabling a diverse integration with sensorimotor and cognitive information.

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“…The location information is transmitted to the main computer on a dedicated link. Additional sensors include the nose-poke detectors at each feeding port that report their state in real time; the status of the food and water ports; and analog sensors carried by the animals such as a microphone, accelerometers, and gyroscopes 33 .…”

Section: The Setupmentioning

confidence: 99%

The RIFF: an automated environment for studying the neural basis of auditory-guided complex behavior

Jankowski

Polterovich

Kazakov

et al. 2021

Preprint

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Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. However, while brain activity varies at fast, sub-seconds time scales, behavioral measures tend to be temporally coarse, often limited just to the success or failure in a trial. The large gap between the temporal resolutions at which brain and behavior are observed likely impedes our understanding of the neural mechanisms underlying behavior. To overcome this problem, we developed the RIFF: an interactive arena for rats that has multiple feeding areas, multiple sound sources, and high-resolution tracking of behavior, with concomitant wireless electrophysiological recordings. The RIFF can be flexibly programmed to create arbitrarily complex tasks that the rats have to solve. It records unrestrained rat behavior together with neuronal data from chronically implanted electrodes. We present here a detailed description of the RIFF. We illustrate its power with results from two exemplary tasks. Rats learned within two days a complex task that required timed movement, and developed anticipatory behavior. Rats found solution strategies that differed between animals but were stable within each animal. We report auditory responses in and around primary auditory cortex as well as in the posterior insular cortex, but show that often the same neurons were also sensitive to non-auditory parameters such as rat location and body orientation. These parameters are crucial for state assessment and the selection of future actions. Our findings show that the complex, unrestrained behavior of rats can be studied in a controlled environment, enabling novel insights into the cognitive capabilities and learning mechanisms of rats. This combination of electrophysiology and detailed behavioral observation opens the way to a better understanding of how the brain controls behavior.

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Mouse entorhinal cortex encodes a diverse repertoire of self-motion signals

Cited by 27 publications

References 59 publications

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

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

Mapping vestibular and visual contributions to angular head velocity tuning in the cortex

The RIFF: an automated environment for studying the neural basis of auditory-guided complex behavior

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