4.8 Article

Neuronal sequences during theta rely on behavior-dependent spatial maps

期刊

ELIFE
卷 10, 期 -, 页码 -

出版社

eLIFE SCIENCES PUBL LTD
DOI: 10.7554/eLife.70296

关键词

hippocampus; place cell; theta oscillation; phase precession; theta sequence; neural coding; Rat

类别

资金

  1. German Research Foundation [419037518 -FOR 2812]
  2. National Institute of Mental Health [NIMH R01MH109170]
  3. Federal Ministry of Education and Research [01GQ1506]

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The study examines the relationships between theta phase, represented position, and true location in navigation through space in mammalian brains. Existing concepts of 'spatial' or 'temporal' theta sweeps are found to be inadequate in explaining how relevant variables change with running speed. A new concept of 'behavior-dependent' sweeps is introduced, where theta sweep length and place field properties vary based on running speed characteristics at different locations in the environment, providing essential structured heterogeneity for understanding the hippocampal code.
Navigation through space involves learning and representing relationships between past, current, and future locations. In mammals, this might rely on the hippocampal theta phase code, where in each cycle of the theta oscillation, spatial representations provided by neuronal sequences start behind the animal's true location and then sweep forward. However, the exact relationship between theta phase, represented position and true location remains unclear and even paradoxical. Here, we formalize previous notions of 'spatial' or 'temporal' theta sweeps that have appeared in the literature. We analyze single-cell and population variables in unit recordings from rat CA1 place cells and compare them to model simulations based on each of these schemes. We show that neither spatial nor temporal sweeps quantitatively accounts for how all relevant variables change with running speed. To reconcile these schemes with our observations, we introduce 'behavior-dependent' sweeps, in which theta sweep length and place field properties, such as size and phase precession, vary across the environment depending on the running speed characteristic of each location. These behavior-dependent spatial maps provide a structured heterogeneity that is essential for understanding the hippocampal code.

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