Topic: Ca2+ imaging

The nervous system must perceive and learn durations to guide adaptive behavior. Prior work to investigate the neural substrates of interval timing has focused largely on relatively simple timing tasks whereby subjects learn to discriminate and reproduce the duration of events occurring at a single fixed interval. Although episodic memory requires accurate temporal coding and is mediated by structures in the medial temporal lobe (MTL), including the medial entorhinal cortex (MEC), a well-established role for MTL circuits in interval timing behavior is conspicuously lacking. MEC seems well-suit

Applying information theoretic measures to neuronal activity data enables the quantification of neuronal encoding quality. However, when the sample size is limited, a naïve estimation of information typically contains an upward bias, which may lead to misinterpretation of coding characteristics. This bias is exacerbated in Ca2+ imaging because of the temporal sparsity of detected Ca2+ signals. Here, we introduce methods to correct the bias in the naïve estimation of information from limited sample sizes and temporally sparse activity. We demonstrate the higher accuracy of our methods over prev

Correlated fluctuations of neural activity, termed noise correlations (NCs), are widespread in cortex and affected by sensory and non-sensory variables. Past work suggests that divisive normalization (DN), a cortical computation responsible for coordinating neural activity, could explain those modulations of neuronal covariability. However, quantifying the relation between DN and NCs remains challenging, as most successful descriptive models of neural variability do not account for DN. We propose a pairwise stochastic DN model that accounts for the effect of DN on covariability. In the model,

Hippocampal place-cell activity is thought to support the formation of a cognitive map that allows the association of an event to its spatial context. It has long been thought that within familiar spatial contexts, such neuronal representations should be stable over time, and that individual place cells should retain their coding properties. However, recent findings have demonstrated that hippocampal codes gradually change over timescales of minutes to weeks. Several studies have suggested that this gradual drift in the ensemble activity patterns of hippocampal neurons could serve as a mechani

The posterior insular cortex (pInsCx) is a multimodal hub processing sensory information and aversive states. However, little is known about how specific inhibitory interneurons in the pInsCx code for fear-learning-related stimuli. Here, we performed longitudinal in-vivo Ca2+ imaging in the pInsCx during a three-day fear learning protocol with a miniature microscope; GCaMP6m was expressed in either PV+, or SOM+, or VIP+ interneurons, or in CaMKII+ (principal) neurons. We observed that positive US responses were more common in interneurons (~ 50%) than in principal neurons (~ 13%). There were v

In recent years, a pivotal role of gliotransmission in homeostatic synaptic plasticity has been highlighted and glial-derived ATP arises as a key contributor. However, very little is known about the glial non-vesicular ATP-release pathway and how ATP participates in the modulation of synaptic strength. In this work, we have analyzed the functional changes occurring in neurons upon chronic activity blockade and the role of the purinergic signaling, connexin43 and pannexin1 hemichannels in this process. By using hippocampal dissociated cultures, we showed that blocking connexin43 and pannexin1 h

Our understanding of how sensorimotor information is integrated across dendritic trees is limited by our ability to image these distributed 3D structures in awake animals. We overcome the existing limitations of rapidly measuring 3D dendritic activity and avoiding signal distortion by brain motion artefacts by utilizing our novel nonlinear 3D acousto-optic lens two-photon microscope with real-time 3D brain motion correction and innovative Ca2+ imaging analysis pipelines. This enable the study of sensorimotor information representation in dendritic activity patterns of awake mice during natural

Environmental enrichment improves hippocampus-dependent spatial learning and memory. However, how enrichment influences hippocampal network activity remains still largely unclear.Using cFos labeling, we showed that exploration of a novel context leads to increased cFos activity in hippocampal principal neurons in mice housed under both standard and enrichment conditions. Remarkably, the number of cFos-expressing cells was lower in enriched mice. Additionally, we recorded Ca2+ responses in CA1 pyramidal cells (PCs) using miniature microscope in mice performing exploration. We observed lower eve

The functional transmission of information between different synapses is crucial, and the potential for such transmission in a mixed-cultured neural network of chick and rat has been demonstrated. We analyzed the correlation between neural electrical activity bursts using clustering and neural Ca2+ signal peaks obtained from Ca2+ imaging method. This analysis showed that information transmission occurs between chick neurons and rat neurons in a mixed-cultured neuronal network of chick and rat.We also cultured glial cells from both chickens and rats, combined with a glial cell-derived condition

N-Methyl-D-aspartate receptors (NMDAR), a class of ionotropic glutamate receptors, play a critical role in synaptic transmission and plasticity in the central nervous system. A unique subtype of these receptors, GluN1/3A, predominantly expressed during early brain development, has been recently proposed as an excitatory glycine receptor. Our investigation aims to deliver a comprehensive characterization of the mechanism of action of recently reported selective GluN3A inhibitors by using a stable cell line expressing recombinant GluN1/3A receptors. Furthermore, we are describing an assay for ev

Reservoir computing facilitates the integration of high-dimensional spatiotemporal dynamics with information processing [1]. Here we investigated the correlation between neuronal dynamics and machine learning task performance, utilizing a cultured neuronal network with a modular structure. The results show that the modularity of the neuronal network enhances classification performance in tasks involving multiple speech signals [3].Figure 1 outlines the experimental setup, employing a modular cultured neuronal network of rat cortical neurons on a patterned substrate. Neural activity was measure

Spontaneous network activity is a conserved feature of the developing brain, and accumulating evidence indicates that it plays a critical role in neuronal circuit maturation. In the neonatal mouse hippocampus, spontaneous network activity in vitro comprises intermittent giant depolarizing potentials (GDPs) that alternate with periods of asynchronous activity. Spontaneous activity depends on depolarizing GABA, mediating mixed excitatory and inhibitory actions. However, little is known about how different GABAA receptor (GABAAR) subunit compositions contribute to spontaneous activity. Here, we i