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

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.

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Grid cell co-activity patterns during sleep reflect spatial overlap of grid fields during active behaviors

10.1101/198671 ◽

2017 ◽

Cited By ~ 6

Author(s):

Sean G. Trettel ◽

John B. Trimper ◽

Ernie Hwaun ◽

Ila R. Fiete ◽

Laura Lee Colgin

Keyword(s):

Activity Patterns ◽

Cell Activity ◽

Grid Cell ◽

Network Models ◽

Grid Cells ◽

Tuning Curves ◽

Sensory Inputs ◽

Cell Network ◽

Spatial Tuning ◽

Cell Cell

ABSTRACTContinuous attractor network models of grid formation posit that recurrent connectivity between grid cells controls their patterns of co-activation. Grid cells from a common module exhibit stable offsets in their periodic spatial tuning curves across environments, which may reflect recurrent connectivity or correlated sensory inputs. Here we explore whether cell-cell relationships predicted by attractor models persist during sleep states in which spatially informative sensory inputs are absent. We recorded ensembles of grid cells in superficial layers of medial entorhinal cortex during active exploratory behaviors and overnight sleep. Per pair and collectively, we found preserved patterns of spike-time correlations across waking, REM, and non-REM sleep, which reflected the spatial tuning offsets between these cells during active exploration. The preservation of cell-cell relationships across states was not explained by theta oscillations or CA1 activity. These results suggest that recurrent connectivity within the grid cell network drives grid cell activity across behavioral states.

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Cerebellar nuclear cell activity during antagonist cocontraction and reciprocal inhibition of forearm muscles

Journal of Neurophysiology ◽

10.1152/jn.1985.54.2.231 ◽

1985 ◽

Vol 54 (2) ◽

pp. 231-244 ◽

Cited By ~ 78

Author(s):

R. Wetts ◽

J. F. Kalaska ◽

A. M. Smith

Keyword(s):

Activity Patterns ◽

Cell Activity ◽

Reciprocal Inhibition ◽

Discharge Frequency ◽

Wrist Flexion ◽

Wrist Movement ◽

Forearm Muscles ◽

Flexion Extension ◽

Nuclear Cell ◽

Low Order

Monkeys were trained to exert a maintained isometric pinch with the thumb and forefinger. This task reliably elicited a simultaneous cocontraction of the forearm muscles. The same monkeys were also taught to insert the open hand into a manipulandum, flex and extend the wrist 35 and 15 degrees, respectively, and maintain an isometric wrist position against a mechanical stop for 1 s. This second task comprised two conditions: a dynamic or movement phase and a static or isometric phase. Movement always involved a wrist displacement of 50 degrees. Although some forearm muscles demonstrated bidirectional activity during the wrist displacement phase, all the wrist and finger muscles were alternatively active in isometric flexion or extension. Of the neurons in the dentate and interposed nuclei that consistently changed discharge during repeated isometric prehension, over 90% (61/67) of the neurons increased activity during this cocontraction of forearm muscles. About 70% (47/67) of these same nuclear cells discharged with a reciprocal pattern of firing during alternating wrist flexion-extension movements. Forty-six neurons had sustained and reciprocal discharge during the maintained isometric wrist postures. No differences were seen between the activity patterns of dentate and interposed cells with respect to either the prehension task or the reciprocal wrist-movement task. The discharge frequency of some dentate and interpositus neurons could be correlated with prehensile force as well as velocity of wrist movement and torque developed by wrist muscles. Correlation coefficients were calculated between nuclear cell discharge and the amplitude of the surface EMGs of the flexors and extensors of the wrist and fingers during the wrist-movement task. Sixteen nuclear cells showed low-order, but reliably positive, correlations with one of the two forearm muscle groups (mean r = 0.33). In contrast, a sample of seven Purkinje cells recorded during the same task demonstrated low-order correlations that were negative in sign (mean r = -0.30) between discharge frequency and one of the two forearm EMGs.

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Author response for "Modified synaptic dynamics predict neural activity patterns in an auditory field within the frontal cortex"

10.1111/ejn.14600/v3/response1 ◽

2019 ◽

Author(s):

Luciana López‐Jury ◽

Adrian Mannel ◽

Francisco Garcia‐Rosales ◽

Julio C. Hechavarria

Keyword(s):

Frontal Cortex ◽

Neural Activity ◽

Activity Patterns ◽

Author Response ◽

Synaptic Dynamics ◽

Auditory Field

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A non-spatial account of place and grid cells based on clustering models of concept learning

10.1101/421842 ◽

2018 ◽

Author(s):

Robert M. Mok ◽

Bradley C. Love

Keyword(s):

Medial Temporal Lobe ◽

Conceptual Knowledge ◽

Learning Algorithm ◽

Grid Cell ◽

Relevant Information ◽

Neural Circuitry ◽

General Purpose ◽

Clustering Model ◽

Higher Dimensional ◽

Processing Steps

ABSTRACTOne view is that conceptual knowledge is organized using the circuitry in the medial temporal lobe (MTL) that supports spatial processing and navigation. In contrast, we find that a domain-general learning algorithm explains key findings in both spatial and conceptual domains. When the clustering model is applied to spatial navigation tasks, so called place and grid cell-like representations emerge because of the relatively uniform distribution of possible inputs in these tasks. The same mechanism applied to conceptual tasks, where the overall space can be higher-dimensional and sampling sparser, leads to representations more aligned with human conceptual knowledge. Although the types of memory supported by the MTL are superficially dissimilar, the information processing steps appear shared. Our account suggests that the MTL uses a general-purpose algorithm to learn and organize context-relevant information in a useful format, rather than relying on navigation-specific neural circuitry.

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