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Decades of research identify the hippocampal formation as central to memory storage and recall. Events are stored via distributed population codes, the parameters of which (e.g., sparsity and overlap) determine both storage capacity and fidelity. However, it remains unclear whether the parameters governing information storage are similar between species. Because episodic memories are rooted in the space in which they are experienced, the hippocampal response to navigation is often used as a proxy to study memory. Critically, recent studies in rodents that mimic the conditions typical of navigation studies in humans and nonhuman primates (i.e., virtual reality) show that reduced sensory input alters hippocampal representations of space. The goal of this study was to quantify this effect and determine whether there are commonalities in information storage across species. Using functional molecular imaging, we observe that navigation in virtual environments elicits activity in fewer CA1 neurons relative to real-world conditions. Conversely, comparable neuronal activity is observed in hippocampus region CA3 and the dentate gyrus under both conditions. Surprisingly, we also find evidence that the absolute number of neurons used to represent an experience is relatively stable between nonhuman primates and rodents. We propose that this convergence reflects an optimal ensemble size for episodic memories.SIGNIFICANCE STATEMENT One primary factor constraining memory capacity is the sparsity of the engram, the proportion of neurons that encode a single experience. Investigating sparsity in humans is hampered by the lack of single-cell resolution and differences in behavioral protocols. Sparsity can be quantified in freely moving rodents, but extrapolating these data to humans assumes that information storage is comparable across species and is robust to restraint-induced reduction in sensory input. Here, we test these assumptions and show that species differences in brain size build memory capacity without altering the structure of the data being stored. Furthermore, sparsity in most of the hippocampus is resilient to reduced sensory information. This information is vital to integrating animal data with human imaging navigation studies.

Although the circuit mediating contextual fear conditioning has been extensively described, the precise contribution that specific anatomical nodes make to behavior has not been fully elucidated. To clarify the roles of the dorsal hippocampus (DH), basolateral amygdala (BLA), and medial prefrontal cortex (mPFC) in contextual fear conditioning, activity within these regions was mapped using cellular compartment analysis of temporal activity using fluorescence in situ hybridization (catFISH) for Arc mRNA. Rats were delay-fear conditioned or immediately shocked (controls) and thereafter reexposed to the shocked context to test for fear memory recall. Subsequent catFISH analyses revealed that in the DH, cells were preferentially reactivated during the context test, regardless of whether animals had been fear conditioned or immediately shocked, suggesting that the DH encodes spatial information specifically, rather then the emotional valence of an environment. In direct contrast, neuronal ensembles in the BLA were only reactivated at test if animals had been fear conditioned, suggesting that the amygdala specifically tracks the emotional properties of a context. Interestingly, Arc expression in the mPFC was consistent with both amygdala- and hippocampus-like patterns, supporting a role for the mPFC in both fear and contextual processing. Collectively, these data provide crucial insight into the region-specific behavior of neuronal ensembles during contextual fear conditioning and demonstrate a dissociable role for the hippocampus and amygdala in processing the contextual and emotional properties of a fear memory.

The article argues that U.S. President Donald Trump's immigration laws and policies violated the equal protection rights of Latino men under the Fourteenth Amendment. It criticizes the laws for having a discriminatory motive because they unfairly target Latino males. The U.S. Immigration and Customs Enforcement (ICE) revealed the increasing numbers of Latino men who were detained and deported. Also discussed is the utilization of the traditional equal protection analysis and case law by courts.

After spatial exploration in rats, Arc mRNA is expressed in --2% of dentate gyrus (DG) granule cells, and this proportion of Arc-positive neurons remains stable for ~8 h. This long-term presence of Arc mRNA following behavior is not observed in hippocampal CAI pyramidal cells. We report here that in rats --50% of granule cells with cytoplasmic Arc mRNA, induced some hours previously during exploration, also show Arc expression in the nucleus. This suggests that recent transcription can occur long after the exploration behavior that elicited it. To confirm that the delayed nuclear Arc expression was indeed recent transcription, Actinomycin D was administered immediately after exploration. This treatment resulted in inhibition of recent Arc expression both when evaluated shortly after explor-atory behavior as well as after longer time intervals. Together, these data demonstrate a unique kinetic profile for Arc transcription in hippocampal granule neurons following behavior that is not observed in other cell types. Among a number of possibilities, this sustained transcription may provide a mechanism that ensures that the synaptic connection weights in the sparse population of granule cells recruited during a given behavioral event are able to be modified. [ABSTRACT FROM AUTHOR]

Background: Automated segmentation of fluorescently labeled cell nuclei in three-dimensional confocal images is essential for numerous studies, e.g., spatiotemporal fluorescence in situ hybridization quantification of immediate early gene transcription. High accuracy and automation levels are required in high-throughput and large-scale studies. Common sources of segmentation error include tight clustering and fragmentation of nuclei. Previous region-based methods are limited because they perform merging of two nuclear fragments at a time. To achieve higher accuracy without sacrificing scale, more sophisticated yet computationally efficient algorithms are needed., Methods: A recursive tree-based algorithm that can consider multiple object fragments simultaneously is described. Starting with oversegmented data, it searches efficiently for the optimal merging pattern guided by a quantitative scoring criterion based on object modeling. Computation is bounded by limiting the depth of the merging tree., Results: The proposed method was found to perform consistently better, achieving merging accuracy in the range of 92% to 100% compared with our previous algorithm, which varied in the range of 75% to 97%, even with a modest merging tree depth of 3. The overall average accuracy improved from 90% to 96%, with roughly the same computational cost for a set of representative images drawn from the CA1, CA3, and parietal cortex regions of the rat hippocampus., Conclusion: Hierarchical tree model-based algorithms significantly improve the accuracy of automated nuclear segmentation without sacrificing speed.