Cellule de grille | EPFL Graph Search

thumb|right|198px|Trajectoire d'un rat dans un environnement carré (représenté en noir). Les points rouges indiquent les emplacements où une cellule de grille entorhinal s'est activée. Une cellule de grille est un type de neurone présent dans le cerveau de nombreuses espèces qui leur permet de connaître leur position dans l'espace. right|thumb|150x150px|Les cellules de grille tirent leur nom du fait qu'en reliant les centres de leurs champs d'activation, on obtient une grille triangulaire. Les cellules de grille ont été découvertes en 2005 par Edvard Moser, May-Britt Moser et leurs élèves Torkel Hafting, Marianne Fyhn et Sturla Molden du Centre de biologie de la Mémoire (CBM) en Norvège. Ils ont reçu le Prix Nobel 2014 de physiologie ou médecine avec John O'Keefe pour la découverte de cellules constituant un système de positionnement dans le cerveau. L'agencement des champs d'activation spatiale des cellules de grille montre une égale distance entre chaque cellule voisine. Cette obser

Bodily self and human grid cell-like activity: probing spatial representation with immersive virtual reality

Hyukjun Moon

Grid cells are place-modulated neurons that encode the location of an agent in space, relying on the integration of various sensorimotor signals from the body. Of note, the integration of those signals is also fundamental for the agent's conscious experience of selfhood, referred to as bodily self-consciousness (BSC). Although both grid cells and BSC systems are related to the brain mechanisms of self-location and are based on multimodal signal integration, their interplay has never been investigated. My thesis aimed at revealing their links in humans by assessing the impact of BSC modulations on grid cell-like representation (GCLR): an fMRI proxy of grid cell activity in entorhinal cortex (EC). In Study 1, I assessed whether manipulation on BSC, specifically enhancing self-identification, affects GCLR during spatial navigation in a virtual reality (VR) environment. I implemented a novel fMRI paradigm integrating a spatial navigation task with online BSC manipulation through a motion-mimicking avatar. The data showed a significant reduction of GCLR as well as improved spatial navigation performance in the condition with the self-identified avatar, linking entorhinal grid cell activity and BSC through bodily self-motion cues provided online during spatial navigation. These behavioral and neural changes were further associated with increased activity in posterior parietal and retrosplenial cortex, collectively suggesting the impact of BSC on a distributed spatial navigation networks in the human brain. Consistent with the previous BSC research, in Study1, I observed illusory drifts in experienced self-location toward the self-identified avatar. In Study2, I further investigated whether illusory self-location changes would be sufficient to elicit GCLR in the absence of active spatial navigation. Adopting the Full-body illusion (FBI) paradigm to the MRI scanner, my data extend changes in self-location related to multisensory stimulation and demonstrated that these indeed evoke GCLR. Although the amplitude of GCLR during the FBI was smaller than the one during virtual navigation, their grid orientations were similar. These data suggest that the brain mechanisms underlying the BSC-induced illusory self-location are similar and comparable, albeit weaker, to the ones during virtual navigation.Temporal Interference (TI) stimulation is a novel method that can excite or inhibit neurons in the deep brain by combining high-frequency electrical fields. Building on the previous studies, in study3, I probed the causal link between GCLR and spatial navigation by applying TI stimulation to EC of participants while they were performing a VR navigation task in the scanner. The preliminary results showed that their spatial navigation was improved by excitatory stimuli compared to the control, while it deteriorated during the inhibition. Besides, I found that modulated GCLR was also associated with improved performance in the excitatory condition. Together, these data provide the first causal link between GCLR and spatial navigation, showing potential future avenues for navigation enhancement in humans. To summarize, I investigated BSC and grid cell systems jointly in humans and, for the first time, uncovered their links through robust evidence based on both behavioral and neuroimaging data. My thesis shed new light on the research of both systems which are closely intermingled but have hitherto been considered separately.

EPFL2021

Sense of self impacts spatial navigation and hexadirectional coding in human entorhinal cortex

Olaf Blanke, Nathan Quentin Faivre, Baptiste Gauthier, Hyukjun Moon, Hyeongdong Park

Grid cells in entorhinal cortex (EC) encode an individual’s location in space and rely on environmental cues and self-motion cues derived from the individual’s body. Body-derived signals are also primary signals for the sense of self and based on integrated sensorimotor signals (proprioceptive, tactile, visual, motor) that have been shown to enhance self-centered processing. However, it is currently unknown whether such sensorimotor signals that modulate self-centered processing impact grid cells and spatial navigation. Integrating the online manipulation of bodily signals, to modulate self-centered processing, with a spatial navigation task and an fMRI measure to detect grid cell-like representation (GCLR) in humans, we report improved performance in spatial navigation and decreased GCLR in EC. This decrease in entorhinal GCLR was associated with an increase in retrosplenial cortex activity, which was correlated with participants’ navigation performance. These data link self-centered processes during spatial navigation to entorhinal and retrosplenial activity and highlight the role of different bodily factors at play when navigating in VR.

2022

Probable nature of higher-dimensional symmetries underlying mammalian grid-cell activity patterns

Alexander Mathis

Lattices abound in nature—from the crystal structure of minerals to the honey-comb organization of ommatidia in the compound eye of insects. These arrangements provide solutions for optimal packings, efficient resource distribution, and cryptographic protocols. Do lattices also play a role in how the brain represents information? We focus on higher-dimensional stimulus domains, with particular emphasis on neural representations of physical space, and derive which neuronal lattice codes maximize spatial resolution. For mammals navigating on a surface, we show that the hexagonal activity patterns of grid cells are optimal. For species that move freely in three dimensions, a face-centered cubic lattice is best. This prediction could be tested experimentally in flying bats, arboreal monkeys, or marine mammals. More generally, our theory suggests that the brain encodes higher-dimensional sensory or cognitive variables with populations of grid-cell-like neurons whose activity patterns exhibit lattice structures at multiple, nested scales. The brain of a mammal has to store vast amounts of information. The ability of animals to navigate through their environment, for example, depends on a map of the space around them being encoded in the electrical activity of a finite number of neurons. In 2014 the Nobel Prize in Physiology or Medicine was awarded to neuroscientists who had provided insights into this process. Two of the winners had shown that, in experiments on rats, the neurons in a specific region of the brain ‘fired’ whenever the rat was at any one of a number of points in space. When these points were plotted in two dimensions, they made a grid of interlocking hexagons, thereby providing the rat with a map of its environment. However, many animals, such as bats and monkeys, navigate in three dimensions rather than two, and it is not clear whether these same hexagonal patterns are also used to represent three-dimensional space. Mathis et al. have now used mathematical analysis to search for the most efficient way for the brain to represent a three-dimensional region of space. This work suggests that the neurons need to fire at points that roughly correspond to the positions that individual oranges take up when they are stacked as tight as possible in a pile. Physicists call this arrangement a face-centered cubic lattice. At least one group of experimental neuroscientists is currently making measurements on the firing of neurons in freely flying bats, so it should soon be possible to compare the predictions of Mathis et al. with data from experiments.