Hippocampal replays have been demonstrated to play a crucial role in memory. Chains of ripples (ripple bursts) in CA1 have been reported to co-occur with long-range place cell sequence replays during the quiet awake state, but roles of neural inputs to CA1 in ripple bursts and replays are unknown. Here we show that ripple bursts in CA1 and medial entorhinal cortex (MEC) are temporally associated. An inhibition of MECIII input to CA1 during quiet awake reduced ripple bursts in CA1 and restricted the spatial coverage of replays to a shorter distance corresponding to single ripple events. The reduction did not occur with MECIII input inhibition during slow-wave sleep. Inhibition of CA3 activity suppressed ripples and replays in CA1 regardless of behavioral state. Thus, MECIII input to CA1 is crucial for ripple bursts and long-range replays specifically in quiet awake, whereas CA3 input is essential for both, regardless of behavioral state.
Pubmed ID: 28957670 RIS Download
Mesh terms: Animals | CA1 Region, Hippocampal | CA3 Region, Hippocampal | Entorhinal Cortex | Male | Maze Learning | Mice | Mice, Transgenic | Neural Inhibition | Neural Pathways | Place Cells | Sleep | Wakefulness
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Open-source software package for the analysis of neural data. Chronux routines may be employed in the analysis of both point process and continuous data, ranging from preprocessing, exploratory and confirmatory analysis. The current release is implemented as a MATLAB library. Chronux offers several routines for computing spectra and coherences for both point and continuous processes. In addition, it also offers several general purpose routines that were found useful such as a routine for extracting specified segments from data, or binning spike time data with bins of a specified size. Since the data can be continuous valued, point process times, or point processes that are binned, methods that apply to all these data types are given in routines whose names end with ''''c'''' for continuous, ''''pb'''' for binned point processes, and ''''pt'''' for point process times. Thus, mtspectrumc computes the spectrum of continuous data, mtspectrumpb computes a spectrum for binned point processes, and mtspectrumpt compute spectra for data consisting of point process times. Hybrid routines are also available and similarly named - for instance coherencycpb computes the coherency between continuous and binned point process data.
toolView all literature mentions
A multi-paradigm numerical computing environment and fourth-generation programming language. It allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. (Adapted from Wikipedia) The high-level language and interactive environment lets you explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.
toolView all literature mentions