Network instability dynamics drive a transient bursting period in the developing hippocampus in vivo

  1. Jürgen Graf
  2. Vahid Rahmati
  3. Myrtill Majoros
  4. Otto W Witte
  5. Christian Geis
  6. Stefan J Kiebel
  7. Knut Holthoff
  8. Knut Kirmse  Is a corresponding author
  1. Department of Neurology, Jena University Hospital, Germany
  2. Section Translational Neuroimmunology, Jena University Hospital, Germany
  3. Department of Psychology, Technical University Dresden, Germany
  4. Department of Neurophysiology, Institute of Physiology, University of Würzburg, Germany
9 figures, 1 table and 2 additional files

Figures

Calcium transient detection harnessing spatial similarity (CATHARSiS) enables reliable Ca2+ transient (CaT) detection in densely labeled tissue.

(A) Resting image of two partially overlapping simulated cells (left) and regions of interest (ROIs) used for analysis (right). bg – background. (B) ΔF template of cell 1. (C) Top, simulated trains …

A transient period of firing equalization during CA1 development in vivo.

(A) Sample D(t) traces (top) and raster plots showing reconstructed Ca2+ transient (CaT) onsets (bottom). Note the developmental transition from discontinuous to continuous network activity. (B) …

Figure 3 with 1 supplement
CA1 undergoes a transient enhanced bursting period while progressively transitioning from discontinuous to continuous activity.

(A) Sample traces of the fraction of active cells Φ(t). Gray and orange bars indicate discontinuous and continuous network activity, respectively. Bottom traces show time periods marked on top …

Figure 3—figure supplement 1
Developmental changes in network burst (NB) characteristics are robust to a wide range of definitions.

(A) Total time spent in NBs (left), mean NB duration (middle), and mean NB size (right) as a function of the parameter Δt. Δt was used for computing a Ca2+ transient (CaT) frequency-dependent …

Enhanced population coupling (PopC) underlies network burstiness in the second postnatal week in vivo.

(A) The mean PopC index peaked at P11. (B) Mean fraction of cells with significant PopC. (C) Mean PopC index of significantly coupled cells only. (D) Sample spike-time tiling coefficient (STTC) …

Motifs of CA1 network activity undergo distinct developmental alterations.

(A) Similarity matrices (matching index) of binary activity patterns (re-ordered for illustration of motif detection) from three individual fields of view (FOVs) at P4, P11, and P18. (B) Global …

Figure 6 with 2 supplements
Effects of nitrous oxide (N2O) on body movements, vital parameters, and network activity at P11.

(A) Sample respiration/movement signal from an individual mouse receiving either 75% N2O/25% O2 (top) or pure O2 (Unanesth., bottom). Detected movement periods are highlighted. (B) Respiration rate …

Figure 6—figure supplement 1
Detection of body movements, breathing, and heart rate.

(A and B) Sample respiration/movement signal (middle) and time-aligned spectrogram (bottom; 0.5–20 Hz, window length: 1 s, overlap: 50%) used to detect movement periods, respiration, and heart rate. …

Figure 6—figure supplement 2
Effects of nitrous oxide on CA1 network dynamics at P11.

(A) Experimental timeline. In each animal, two fields of view (FOVs) were recorded with and without N2O (paired design). (B) Rasterplots (top) and time-aligned fraction of active cells Φ(t) (bottom) …

A neural network model with inhibitory GABA identifies intrinsic instability dynamics as key to the emergence of network bursts.

(A) Schematic diagram of the short-term synaptic plasticity (STP)-recurrent neural network (RNN) model. (B) The AIN-APC-plane of the full STP-RNN’s stationary dynamics. Note the presence of two stable fixed …

Figure 8 with 1 supplement
Internal deadline of state transitions.

(A–C) Input delivered to the network before the deadline can move it to active state. (A) A successful transition. The input delivered at t = 0.8 s; ePC=0.25, eIN=0.25. (B) The AIN-APC-plane of the short-term synaptic …

Figure 8—figure supplement 1
Re-emergence of an internal deadline after a transition failure.

(A–H) Same format as in Figure 8. Following the failure of the network in transitioning to the active state due to missing the deadline (dotted black line #1, at t = 1.45 s), the subsequent input …

Figure 9 with 1 supplement
Inhibitory stabilization of a persistent active state in the bi-stable short-term synaptic plasticity (STP)-recurrent neural network (RNN) model.

(A) The inhibition-stabilized network (ISN) regime becomes accessible to the network upon the developmental emergence of synaptic inhibition. The colored regions in each AIN-APC-plane of the network model …

Figure 9—figure supplement 1
A bi-stable short-term synaptic plasticity (STP)-recurrent neural network (RNN) model with inhibitory GABA robustly explains the experimental observations.

(A) In contrast to the bi-stable STP-RNN, Mono-RNNi and Mono-RNNe networks lack a silent state (i.e. a fixed point [FP] at origin). Same format as Figure 9A, overlaid by the APC-nullcline (red), the AIN-nullcline (blue), …

Tables

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain and strain background (Mus musculus)B6.129S2-Emx1tm1(cre)Krj/J
(Emx1IREScre)
The Jackson Laboratory RRID: IMSR_JAX:005628
Strain and strain background (Mus musculus)B6;129S6-Gt(ROSA)26Sortm96(CAG-GCaMP6s)Hze/J
(Rosa26LSL-GCaMP6s)
The Jackson Laboratory RRID: IMSR_JAX:024106
Software and algorithmWolfram Mathematica 13Wolfram RRID:SCR_014448
Software and algorithmMatlab 2021bMathworks RRID:SCR_001622
Software and algorithmFijiPMID:22743772 RRID:SCR_002285
Software and algorithmCalcium transient detection harnessing spatial similarity (CATHARSiS)This paper N/Ahttps://github.com/kirmselab/CATHARSiS

Additional files

Supplementary file 1

Statistical tests used in this study.

(a) Synopsis of statistical tests related to Figure 1. Numerical data are provided in the Figure 1—source data 1. (b) Synopsis of statistical tests related to Figure 2. Numerical data are provided in the Figure 2—source data 1. (c) Synopsis of statistical tests related to Figure 3. Numerical data are provided in the Figure 3—source data 1. (d) Synopsis of statistical tests related to Figure 4. Numerical data are provided in the Figure 4—source data 1. (e) Synopsis of statistical tests related to Figure 5. Numerical data are provided in the Figure 5—source data 1. (f) Synopsis of statistical tests related to Figure 6 and Figure 6—figure supplement 2. Numerical data are provided in the Figure 6—source data 1.

https://cdn.elifesciences.org/articles/82756/elife-82756-supp1-v1.docx
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https://cdn.elifesciences.org/articles/82756/elife-82756-transrepform1-v1.pdf

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