Abstract:8The regular firing pattern exhibited by medial entorhinal (mEC) grid cells of locomoting rodents is 9hypothesized to provide spatial metric information relevant for navigation. The development of virtual reality 10 (VR) for head-fixed mice confers a number of experimental advantages and has become increasingly popular 11 as a method for investigating spatially-selective cells. Recent experiments using 1D VR linear tracks have 12 shown that some mEC cells have multiple fields in virtual space, analogous to gri… Show more
“…Figure 1) are consistent with strong visual control of the activity of retrohippocampal neurons (e.g. (Casali et al, 2018;Chen et al, 2016;Kinkhabwala et al, 2020;Pérez-Escobar et al, 2016) ). Thus, it is likely that visual signals are critical for registering ramp-like activity to the track.…”
Section: Mechanisms For Ramp-like Positional Representationsupporting
confidence: 78%
“…A further possibility is that ramp-like activity is generated by integration of inputs from other retrohippocampal neurons that encode location through discrete firing fields (Burak and Fiete, 2009; Bush et al, 2015; Stachenfeld et al, 2017; Stemmler et al, 2015). Such representations are abundant locally within the MEC and parasubiculum, and include the activity of grid cells, which may mediate path integration (Gil et al, 2017; McNaughton et al, 2006; Tennant et al, 2018), and neurons with activity driven by visual inputs (Casali et al, 2018; Kinkhabwala et al, 2020; Pérez-Escobar et al, 2016).…”
When solving navigational problems, remembering that a critical location is approaching can enable appropriate behavioural choices without waiting for sensory signals. Whereas multiple types of neuron in the hippocampus and retrohippocampal cortex represent locations using codes based on discrete spatial firing fields, analogue neural representations may be advantageous for efficiently recalling proximity to locations of behavioral importance. Here, we identify retrohippocampal neurons that use analogue ramp-like changes in firing rate to represent location as mice navigate a virtual environment in which they have learned the location of a reward. Ramp-like firing patterns had positive or negative slopes and could switch polarity or reset their rate at the reward location. These transitions were maintained when location cues were removed, indicating that path integration is sufficient to drive recall of the track structure expressed through ramp-like codes. We suggest that analogue ramp-like representations encode learned models for goal-directed navigation.
“…Figure 1) are consistent with strong visual control of the activity of retrohippocampal neurons (e.g. (Casali et al, 2018;Chen et al, 2016;Kinkhabwala et al, 2020;Pérez-Escobar et al, 2016) ). Thus, it is likely that visual signals are critical for registering ramp-like activity to the track.…”
Section: Mechanisms For Ramp-like Positional Representationsupporting
confidence: 78%
“…A further possibility is that ramp-like activity is generated by integration of inputs from other retrohippocampal neurons that encode location through discrete firing fields (Burak and Fiete, 2009; Bush et al, 2015; Stachenfeld et al, 2017; Stemmler et al, 2015). Such representations are abundant locally within the MEC and parasubiculum, and include the activity of grid cells, which may mediate path integration (Gil et al, 2017; McNaughton et al, 2006; Tennant et al, 2018), and neurons with activity driven by visual inputs (Casali et al, 2018; Kinkhabwala et al, 2020; Pérez-Escobar et al, 2016).…”
When solving navigational problems, remembering that a critical location is approaching can enable appropriate behavioural choices without waiting for sensory signals. Whereas multiple types of neuron in the hippocampus and retrohippocampal cortex represent locations using codes based on discrete spatial firing fields, analogue neural representations may be advantageous for efficiently recalling proximity to locations of behavioral importance. Here, we identify retrohippocampal neurons that use analogue ramp-like changes in firing rate to represent location as mice navigate a virtual environment in which they have learned the location of a reward. Ramp-like firing patterns had positive or negative slopes and could switch polarity or reset their rate at the reward location. These transitions were maintained when location cues were removed, indicating that path integration is sufficient to drive recall of the track structure expressed through ramp-like codes. We suggest that analogue ramp-like representations encode learned models for goal-directed navigation.
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