Molecular Characterization of Superficial Layers of the Presubiculum During Development

The presubiculum, a subarea of the parahippocampal region, plays a critical role in spatial navigation and spatial representation. An outstanding aspect of presubicular spatial codes is head-direction selectivity of the firing of excitatory neurons, called head-direction cells. Head-direction selectivity emerges before eye-opening in rodents and is maintained in adulthood through neurophysiological interactions between excitatory and inhibitory neurons. Although the presubiculum has been physiologically profiled in terms of spatial representation during development, the histological characteristics of the developing presubiculum are poorly understood. We found that the expression of vesicular glutamate transporter 2 (VGluT2) could be used to delimit the superficial layers of the presubiculum, which was identified using an anterograde tracer injected into the anterior thalamic nucleus (ATN). Thus, we immunostained slices from mice ranging in age from neonates to adults using an antibody against VGluT2 to evaluate the VGluT2-positive area, which was identified as the superficial layers of the presubiculum, during development. We also immunostained the slices using antibodies against parvalbumin (PV) and somatostatin (SOM) and found that in the presubicular superficial layers, PV-positive neurons progressively increased in number during development, whereas SOM-positive neurons exhibited no increasing trend. In addition, we observed repeating patch structures in presubicular layer III from postnatal days 12. The abundant expression of VGluT2 suggests that the presubicular superficial layers are regulated primarily by VGluT2-mediated excitatory neurotransmission. Moreover, developmental changes in the densities of PV- and SOM-positive interneurons and the emergence of the VGluT2-positive patch structures during adolescence may be associated with the functional development of spatial codes in the superficial layers of the presubiculum

Spontaneous Plasticity of Multineuronal Activity Patterns in Activated Hippocampal Networks

Using functional multineuron imaging with single-cell resolution, we examined how hippocampal networks by themselves change the spatiotemporal patterns of spontaneous activity during the course of emitting spontaneous activity. When extracellular ionic concentrations were changed to those that mimicked in vivo conditions, spontaneous activity was increased in active cell number and activity frequency. When ionic compositions were restored to the control conditions, the activity level returned to baseline, but the weighted spatial dispersion of active cells, as assessed by entropy-based metrics, did not. Thus, the networks can modify themselves by altering the internal structure of their correlated activity, even though they as a whole maintained the same level of activity in space and time

Machine learning-based segmentation of the rodent hippocampal CA2 area from Nissl-stained sections

The hippocampus is a center of learning, memory, and spatial navigation. This region is divided into the CA1, CA2, and CA3 areas, which are anatomically different from each other. Among these divisions, the CA2 area is unique in terms of functional relevance to sociality. The CA2 area is often manually detected based on the size, shape, and density of neurons in the hippocampal pyramidal cell layer, but this manual segmentation relying on cytoarchitecture is impractical to apply to a large number of samples and dependent on experimenters’ proficiency. Moreover, the CA2 area has been defined based on expression pattern of molecular marker proteins, but it generally takes days to complete immunostaining for such proteins. Thus, we asked whether the CA2 area can be systematically segmented based on cytoarchitecture alone. Since the expression pattern of regulator of G-protein signaling 14 (RGS14) signifies the CA2 area, we visualized the CA2 area in the mouse hippocampus by RGS14-immunostaining and Nissl-counterstaining and manually delineated the CA2 area. We then established “CAseg,” a machine learning-based automated algorithm to segment the CA2 area with the F1-score of approximately 0.8 solely from Nissl-counterstained images that visualized cytoarchitecture. CAseg was extended to the segmentation of the prairie vole CA2 area, which raises the possibility that the use of this algorithm can be expanded to other species. Thus, CAseg will be beneficial for investigating unique properties of the hippocampal CA2 area

A new device for the simultaneous recording of cerebral, cardiac, and muscular electrical activity in freely moving rodents

AbstractWe present a new technique for the simultaneous capture of bioelectrical time signals from the brain and peripheral organs of freely moving rodents. The recording system integrates all systemic signals into an electrical interface board that is mounted on an animal's head for an extended period. The interface board accommodates up to 48 channels, enabling us to analyze neuronal activity patterns in multiple brain regions by comparing a variety of physiological body states over weeks and months. This technique will advance the understanding of the neurophysiological correlate of mind–body associations in health and disease

Phylogeny and ontogeny of mental time

Humans have mental time in our mind, apart from physical time that is a part of system that governs the physical world, and memory is our key cognitive ability for recognizing the passage of time. Recent studies have suggested that the memory system of several nonhuman animals may have an incidental nature, which is also a feature of episodic memory. In addition, apes, which are phylogenetically close to humans, have an ability to remember a single past event. In the case of humans, preverbal infants under the age of two are able to retain long-term memory of a single event and apply it to predict a future event. Thus, nonhuman animals and preverbal human infants both have their own specific mental time travel abilities, and there is a phylogenetic and ontogenic basis of full-fledged mental time travel that can be found in human adults

Empirical Bayesian significance measure of neuronal spike response

Background: Functional connectivity analyses of multiple neurons provide a powerful bottom-up approach to reveal functions of local neuronal circuits by using simultaneous recording of neuronal activity. A statistical methodology, generalized linear modeling (GLM) of the spike response function, is one of the most promising methodologies to reduce false link discoveries arising from pseudo-correlation based on common inputs. Although recent advancement of fluorescent imaging techniques has increased the number of simultaneously recoded neurons up to the hundreds or thousands, the amount of information per pair of neurons has not correspondingly increased, partly because of the instruments' limitations, and partly because the number of neuron pairs increase in a quadratic manner. Consequently, the estimation of GLM suffers from large statistical uncertainty caused by the shortage in effective information. Results: In this study, we propose a new combination of GLM and empirical Bayesian testing for the estimation of spike response functions that enables both conservative false discovery control and powerful functional connectivity detection. We compared our proposed method's performance with those of sparse estimation of GLM and classical Granger causality testing. Our method achieved high detection performance of functional connectivity with conservative estimation of false discovery rate and q values in case of information shortage due to short observation time. We also showed that empirical Bayesian testing on arbitrary statistics in place of likelihood-ratio statistics reduce the computational cost without decreasing the detection performance. When our proposed method was applied to a functional multi-neuron calcium imaging dataset from the rat hippocampal region, we found significant functional connections that are possibly mediated by AMPA and NMDA receptors. Conclusions: The proposed empirical Bayesian testing framework with GLM is promising especially when the amount of information per a neuron pair is small because of growing size of observed network

Subtle modulation of ongoing calcium dynamics in astrocytic microdomains by sensory inputs.

Astrocytes communicate with neurons through their processes. In vitro experiments have demonstrated that astrocytic processes exhibit calcium activity both spontaneously and in response to external stimuli; however, it has not been fully determined whether and how astrocytic subcellular domains respond to sensory input in vivo. We visualized the calcium signals in astrocytes in the primary visual cortex of awake, head‐fixed mice. Bias‐free analyses of two‐photon imaging data revealed that calcium activity prevailed in astrocytic subcellular domains, was coordinated with variable spot‐like patterns, and was dominantly spontaneous. Indeed, visual stimuli did not affect the frequency of calcium domain activity, but it increased the domain size, whereas tetrodotoxin reduced the sizes of spontaneous calcium domains and abolished their visual responses. The "evoked" domain activity exhibited no apparent orientation tuning and was distributed unevenly within the cell, constituting multiple active hotspots that were often also recruited in spontaneous activity. The hotspots existed dominantly in the somata and endfeet of astrocytes. Thus, the patterns of astrocytic calcium dynamics are intrinsically constrained and are subject to minor but significant modulation by sensory input

Active Hippocampal Networks Undergo Spontaneous Synaptic Modification

The brain is self-writable; as the brain voluntarily adapts itself to a changing environment, the neural circuitry rearranges its functional connectivity by referring to its own activity. How the internal activity modifies synaptic weights is largely unknown, however. Here we report that spontaneous activity causes complex reorganization of synaptic connectivity without any external (or artificial) stimuli. Under physiologically relevant ionic conditions, CA3 pyramidal cells in hippocampal slices displayed spontaneous spikes with bistable slow oscillations of membrane potential, alternating between the so-called UP and DOWN states. The generation of slow oscillations did not require fast synaptic transmission, but their patterns were coordinated by local circuit activity. In the course of generating spontaneous activity, individual neurons acquired bidirectional long-lasting synaptic modification. The spontaneous synaptic plasticity depended on a rise in intracellular calcium concentrations of postsynaptic cells, but not on NMDA receptor activity. The direction and amount of the plasticity varied depending on slow oscillation patterns and synapse locations, and thus, they were diverse in a network. Once this global synaptic refinement occurred, the same neurons now displayed different patterns of spontaneous activity, which in turn exhibited different levels of synaptic plasticity. Thus, active networks continuously update their internal states through ongoing synaptic plasticity. With computational simulations, we suggest that with this slow oscillation-induced plasticity, a recurrent network converges on a more specific state, compared to that with spike timing-dependent plasticity alone