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The BACON computational model of hippocampal function reproduces the behavioral effects of a variety of DG manipulations. The BACON computational model.

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Presentation on theme: "The BACON computational model of hippocampal function reproduces the behavioral effects of a variety of DG manipulations. The BACON computational model."— Presentation transcript:

1 The BACON computational model of hippocampal function reproduces the behavioral effects of a variety of DG manipulations. The BACON computational model of hippocampal function reproduces the behavioral effects of a variety of DG manipulations. A, The BACON cortex–hippocampus–amygdala circuit includes 1000 entorhinal cortex neurons (ECin) projecting to 10,000 DG granule cells. The 3000 CA3 neurons are innervated by ECin, DG, and recurrent collaterals from other CA3 pyramidal cells. CA1 is omitted from the model. ECout and amygdala are innervated directly by CA3 pyramidal neurons. The CA3–amygdala projection allows fear to become conditioned directly to hippocampal context representations. Context fear memory acquisition depends on plasticity at ECin–DG, ECin–CA3, CA3–CA3, and CA3–amygdala synapses, which are highlighted in green. The DG–CA3 projection operates during both memory acquisition and retrieval. A complete description is available in Krasne et al. (2015). B, Experimental data (left) from the current study (rows 1–3) and two previously published studies (Nakashiba et al., 2012; Denny et al., 2014; rows 4–5) compared with predictions from BACON simulations. The middle column shows the results of simulations in which BACON used DG during recall. The right column represents simulations in which BACON was prevented from using DG during recall. The labels at left denote the degree of DG suppression during conditioning and test sessions. Bars represent freezing during the test session as a percentage of freezing in control conditions. BACON recapitulates the seemingly contradictory behavioral results only when it is allowed to use DG during recall. Brian E. Bernier et al. J. Neurosci. 2017;37: ©2017 by Society for Neuroscience


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