10 research outputs found

    Network supporting contextual fear learning after dorsal hippocampal damage has increased dependence on retrosplenial cortex

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    <div><p>Hippocampal damage results in profound retrograde, but no anterograde amnesia in contextual fear conditioning (CFC). Although the content learned in the latter have been discussed, alternative regions supporting CFC learning were seldom proposed and never empirically addressed. Here, we employed network analysis of pCREB expression quantified from brain slices of rats with dorsal hippocampal lesion (dHPC) after undergoing CFC session. Using inter-regional correlations of pCREB-positive nuclei between brain regions, we modelled functional networks using different thresholds. The dHPC network showed small-world topology, equivalent to SHAM (control) network. However, diverging hubs were identified in each network. In a direct comparison, hubs in both networks showed consistently higher centrality values compared to the other network. Further, the distribution of correlation coefficients was different between the groups, with most significantly stronger correlation coefficients belonging to the SHAM network. These results suggest that dHPC network engaged in CFC learning is partially different, and engage alternative hubs. We next tested if pre-training lesions of dHPC and one of the new dHPC network hubs (perirhinal, Per; or disgranular retrosplenial, RSC, cortices) would impair CFC. Only dHPC-RSC, but not dHPC-Per, impaired CFC. Interestingly, only RSC showed a consistently higher centrality in the dHPC network, suggesting that the increased centrality reflects an increased functional dependence on RSC. Our results provide evidence that, without hippocampus, the RSC, an anatomically central region in the medial temporal lobe memory system might support CFC learning and memory.</p></div

    Hub identification of the networks.

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    <p>(A) The rankings of each centrality are shown for the dHPC network under the 0.05 threshold. The colored nodes are the upper 25% most central in each metric. (B) The intersections of the upper 25% most central regions of each metric are shown for the dHPC network under the 0.05 threshold. Any region within the overlapping area of at least three metrics was considered a network hub (inside the red perimeter). The hubs were identified in the networks with 0.025 and 0.01 thresholds as well (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006207#pcbi.1006207.s002" target="_blank">S2</a>ā€“<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006207#pcbi.1006207.s004" target="_blank">S4</a> Figs), and the hubs of each threshold were intersected (C) to identify stable hubs across the thresholds in each network. Nodes are colored according to the code in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006207#pcbi.1006207.g002" target="_blank">Fig 2</a>.</p

    Connectivity change in dHPC network.

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    <p>(A) Cumulative distributions of the Fisherā€™s Z transformed correlation coefficients from the SHAM-nH and dHPC matrices. The ā€œ#ā€ indicates that these distributions are significantly different (Kolgomorov-Smirnov test, p<0.05). (B) Cumulative distribution showing the z-score of the correlation coefficient differences between the groups. The dashed line shows the absolute Z-score of 2, revealing the values considered significant (beyond it) at the level of Ī± = 0.05. (C) The significantly different coefficients were plotted in each network, showing the network and nodes to which it belonged. The same procedure was performed in the 0.025 and 0.01 threshold networks and showed similar results <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006207#pcbi.1006207.s006" target="_blank">S6 Fig</a>.</p

    Centrality comparison between SHAM-nH and dHPC networks.

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    <p>The comparison was done for each region, centrality metric and threshold. Values in each cell show ranks of the amount of significant differences (p < 0.05 in the permutation test) across the thresholds in each region and metric, ranging from 0 to 3. The hub score column shows the amount of thresholds in which a region was considered a hub. Significantly higher centrality values and hub scores in the dHPC and SHAM networks are shown in shades of blue and green, respectively. If a region was hub in both networks, a stripped blue-green cell is shown with their respective gradient. It is possible to observe which hub scores are associated with significant differences in the centrality comparisons. The thresholds in which each difference and hub occurred is shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006207#pcbi.1006207.s005" target="_blank">S5 Fig</a>. Wdg: Weighted Degree; Evc: Eigenvector; Clo: Closeness; Bet: Betweenness.</p

    dHPC lesion does not impair CFC learning and memory.

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    <p>(A) Schematic diagram showing the distribution of the lesions in the dHPC group. (B) Mean (black line) and bootstrapped 95% CI of the Total Freezing Time during the five min context fear memory test of dHPC (N = 12), SHAM (N = 12) and Imm (N = 8) groups. The open circles show data distribution in each group. (C) Cumulative distribution of the sample as a function of Freezing Time showing the sample distributions. The ā€œ*ā€ shows a significant difference from Imm at level of p<0.05. (D) Mean (black line) and Bootstrapped 95% CI of the mean (boxplots) of the pCREB-positive nuclei density in each region and each group. The black dots show the data point distributions.</p

    Per and dHPC-Per lesions on CFC learning.

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    <p>(A) Histological diagrams showing the distribution of areas damaged in dHPC, Per and dHPC-Per groups. The more overlapped the damaged areas across subjects, the darker the area. (B) Mean and bootstrapped 95% IC of the total freezing time in SHAM, dHPC, Per and dHPC-Per groups during 5 min of CFC memory test. Dots show the sample distribution of each group. (C) Cumulative distribution of the total freezing time in each group in the same CFC memory test. The bottom table shows all the statistical tests performed and the corrected p-value for each comparison.</p

    Regions included in Experiment 1.

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    <p>The columns show the name of each region, the abbreviations, the source of the anatomical definition adopted, and the color code used in the following figures for each group of regions. Color codeā€”Red: basolateral complex of the amygdala; Dark Red: central amygdala nuclei; Blue: dorsal hippocampus; Light Blue: ventral hippocampus; Green: parahippocampal regions; Purple: prefrontal cortices; Magenta: retrosplenial cortices. A) 3D diagram of a rat brain showing anatomical localization of the included regions. Representative photomicrograph of a pCREB immunolabelled brain slice before (B) and after (C) nuclei quantification and region parcellation by Cellprofiler. The scale bars indicate 200 Ī¼m.</p

    dHPC damage does not alter the CFC learning network small-worldness.

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    <p>Boxplots showing mean, lower and upper quartiles, and 95% CIs of the Empirical/Random ratio of Geff and mean Leff for the SHAM (left), SHAM-nH (center) and dHPC (right) networks and on the 0.05 (bottom), 0.025 (center) and 0.01 (top) thresholds. Small-world networks are expected to have Geff ratios around 1 (empirical and randomized networks have roughly the same values) and higher mean Leff ratios (higher empirical values than those of the randomized networks).</p

    Generation of connectivity networks in each group.

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    <p>After computing the inter-regional correlations (left), three thresholds were applied (p < 0.05, 0.025 and 0.01) and the most robust correlation coefficients (center) composed the networks (right). Networks were generated for SHAM (top), SHAM-nH (middle) and dHPC (bottom) matrices. In the matrices, colors reflect correlation strength (scale, right). In the network, the colors of the nodes are coded according to the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006207#pcbi.1006207.g002" target="_blank">Fig 2</a>, and the sizes of the nodes represent their degree (number of connections).</p

    RSC and dHPC-RSC lesions on CFC learning.

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    <p>(A) Histological diagrams showing the distribution of areas damaged in dHPC, RSC and dHPC-RSC groups. The more overlapped the damaged areas across subjects, the darker the area. (B) Mean and bootstrapped 95% IC of the total freezing time in SHAM, dHPC, RSC and dHPC-RSC groups during 5 min of CFC memory test. Dots show the sample distribution of each group. (C) Cumulative distribution of the total freezing time in each group in the same CFC memory test. The bottom table shows all the statistical tests performed and the corrected p-value for each comparison. ā€œ*ā€ shows significant differences relative to SHAM group (corrected-p <0.05).</p
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