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Bioelectrical coordination of cell activity toward anatomical target states
Published in David M. Gardiner, Regenerative Engineering and Developmental Biology, 2017
Celia Herrera-Rincon, Justin Guay, Michael Levin
Importantly, computational neuroscience increasingly reveals the mechanisms by which cellular networks achieve this capability. One of the most remarkable examples comes from the place cells in rodents (Kubie et al. 1990) and the way by which discharge patterns of single cells (hippocampal neurons) and their collective activity encode dynamical spatial patterns (Kubie et al. 1990, Leutgeb et al. 2005, Colgin et al. 2008). Place cells are neurons that are activated selectively when an animal occupies a particular location in its environment (the place field of the neuron; Kubie et al. 1990, Muller et al. 1996, Ferbinteanu and Shapiro 2003, Ainge et al. 2007, 2012). The hippocampal networks are also thought to retain sequential information. Past, present, and future events (or sequences) could be separated spatially by cell assemblies and temporally by network theta oscillations (Buzsaki 2002; reviewed in Leutgeb et al. 2005). The encoding of the spatial and temporal patterns allows animals to navigate from their current position to a goal position (Barca and Pezzulo 2015). The study of this example, in which electrical activity of cell networks implements spatial memory, could lead to new models with which to understand the guidance of trajectory of cell behavior toward specific spatial patterns in regeneration.
Comprehensive Approach to Pilot Disorientation Countermeasures
Published in Michael A. Vidulich, Pamela S. Tsang, Improving Aviation Performance through Applying Engineering Psychology, 2019
Recent neuroscience research suggested that the human brain is not truly organized in terms of systems that process a single sensory modality, such as vision, balance, touch or hearing, but rather processes information about spatial relationships, movements, and shapes (Pascal-Leone & Hamilton, 2001). For example, young children with retinoblastoma (causing vision loss from an early age) exhibit a larger volume of auditory cortex (Hoover, Harris & Steeves, 2012; Nys, Aerts, Ytebrouck, Vreysen, Laeremans, & Arckens et al., 2014), which demonstrates an adaptive reorganization of neurons to integrate the function of two or more sensory systems (cross modal plasticity). Furthermore, specific neurons involved in navigation have been found. For example, “Head Direction Cells” in the rat’s anterior thalamic region (Taube, Muller & Ranck, 1990; Taube 1998) and “Path Cells” in the entorhinal cortex of neurosurgical patients (Jacobs, Kahana, Ekstrom, Mollison & Fried, 2010) fire only when subjects orient their head in selective directions, turning either clockwise or counterclockwise. The behavior of these cells was also found to be influenced by landmarks as well as motor and vestibular information concerning how the head moves through space. The “Grid Cells” in the entorhinal cortex of the rats act as the brain’s Global Positioning System (GPS) indicating where they are relative to where they started (Hafting, Fyhn, Molden, Moser, & Moser, 2005; Moser, Kropff & Moser, 2008; Sargolini, Fyhn, Hafting, McNaughton, Witter, Moser, & Moser et al. 2006). Finally, the “Place Cells” in the hippocampus of humans activates when we move into a specific location, so that such groups of Place Cells form a map of the environment (O’Keefe & Burgess, 2005). How neuroplasticity and specific orientation neurons influence the mechanisms of pilot orientation in flight remains to be investigated.
Subjective disorientation as a metacognitive feeling
Published in Spatial Cognition & Computation, 2020
Pablo Fernández Velasco, Roberto Casati
The notion of a cognitive map gained neuroscientific support with the discovery of place cells, a set of cells in the rat’s hippocampus that fire as a function of their spatial location (O’Keefe & Dostrovsky, 1971). Later, the discovery of grid cells. head direction cells and boundary vector cells further supported the existence of cognitive maps, as these mechanisms are best interpreted as feeding map-like representations of space. Grid cells fire in a hexagonal grid that corresponds with the environment floor (Hafting et al., 2005). Head direction cells fire according to head orientation (Ranck, 1985; Taube et al., 1990). Boundary vector cells fire when the rat gets to a specific distance from an environmental boundary (Barry et al, 2006). In hindsight, the behavior of specialized cells can be interpreted as constraining the solution to the space representation problem: place, grid, head orientation and boundary cells provide individual, metric, angle and topological constraints respectively (Fernandez Velasco & Casati 2019). Dudchenko argues that, if the idea of a cognitive map can be extrapolated to humans (see Epstein et al., 2017 for a review of empirical literature supporting this extrapolation), it seems that visual landmarks play an important role in anchoring these cognitive maps (see Yoder, Clark, & Taube, 2011). This is because “the head direction, grid, and place cell systems can be re-set by salient landmarks” (p.252, Dudchenko, 2010). In other words, the head direction system tracks visual landmarks in order to update the subject’s location within a cognitive map.
A boundary vector cell model of place field repetition
Published in Spatial Cognition & Computation, 2018
Roddy M Grieves, Éléonore Duvelle, Paul A Dudchenko
Place cells are neurons in the hippocampus that increase their firing rate when an animal visits specific regions of its environment (O’Keefe, 1979; O’Keefe & Conway, 1978; O’Keefe & Nadel, 1978). Different place cells have “place fields” in different areas of an environment, so that together the entire surface of an environment is represented (O’Keefe, 1976; Wilson & McNaughton, 1993). The main argument of the current work is that place fields are driven by local geometric features, for example the walls of a maze. To test this, we used a computational model based on inputs to place cells from cells that encode the distance and direction of local boundaries.