NeuroChaT: A toolbox to analyse the dynamics of neuronal encoding in freely-behaving rodents in vivo

Place Cells in the Claustrum Remap Under NMDA Receptor Control

Place cells are cells that exhibit location‐dependent responses; they have mostly been studied in the hippocampus. Place cells have also been reported in the rat claustrum, an underexplored paracortical region with extensive corto‐cortical connectivity. It has been hypothesised that claustral neuronal responses are anchored to cortical visual inputs. We show rat claustral place cells remap when visual inputs are eliminated from the environment, and that this remapping is NMDA‐receptor‐dependent. Eliminating visual input decreases claustral delta‐band oscillatory activity, increases theta‐band oscillatory activity, and increases simultaneously recorded visual cortical activity. We conclude that, like the hippocampus, claustral place field remapping might be mediated by NMDA receptor activity, and is modulated by visual cortical inputs.

Anterior Thalamic Inputs Are Required for Subiculum Spatial Coding, with Associated Consequences for Hippocampal Spatial Memory

Just as hippocampal lesions are principally responsible for "temporal lobe" amnesia, lesions affecting the anterior thalamic nuclei seem principally responsible for a similar loss of memory, "diencephalic" amnesia. Compared with the former, the causes of diencephalic amnesia have remained elusive. A potential clue comes from how the two sites are interconnected, as within the hippocampal formation, only the subiculum has direct, reciprocal connections with the anterior thalamic nuclei. We found that both permanent and reversible anterior thalamic nuclei lesions in male rats cause a cessation of subicular spatial signaling, reduce spatial memory performance to chance, but leave hippocampal CA1 place cells largely unaffected. We suggest that a core element of diencephalic amnesia stems from the information loss in hippocampal output regions following anterior thalamic pathology.SIGNIFICANCE STATEMENT At present, we know little about interactions between temporal lobe and diencephalic memory systems. Here, we focused on the subiculum, as the sole hippocampal formation region directly interconnected with the anterior thalamic nuclei. We combined reversible and permanent lesions of the anterior thalamic nuclei, electrophysiological recordings of the subiculum, and behavioral analyses. Our results were striking and clear: following permanent thalamic lesions, the diverse spatial signals normally found in the subiculum (including place cells, grid cells, and head-direction cells) all disappeared. Anterior thalamic lesions had no discernible impact on hippocampal CA1 place fields. Thus, spatial firing activity within the subiculum requires anterior thalamic function, as does successful spatial memory performance. Our findings provide a key missing part of the much bigger puzzle concerning why anterior thalamic damage is so catastrophic for spatial memory in rodents and episodic memory in humans.

SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals

Neuronal signals generally represent activation of the neuronal networks and give insights into brain functionalities. They are considered as fingerprints of actions and their processing across different structures of the brain. These recordings generate a large volume of data that are susceptible to noise and artifacts. Therefore, the review of these data to ensure high quality by automatically detecting and removing the artifacts is imperative. Toward this aim, this work proposes a custom-developed automatic artifact removal toolbox named, SANTIA (SigMate Advanced: a Novel Tool for Identification of Artifacts in Neuronal Signals). Developed in Matlab, SANTIA is an open-source toolbox that applies neural network-based machine learning techniques to label and train models to detect artifacts from the invasive neuronal signals known as local field potentials.

neurotic: Neuroscience Tool for Interactive Characterization

A software tool for synchronization of video with signals would be of broad general use to behavioral neuroscientists. A new program, called neurotic (NEUROscience Tool for Interactive Characterization), allows users to review and annotate signal data synchronized with video, performs simple initial analyses including signal filtering and spike detection, is easy to use, and supports a variety of file formats. The program also facilitates collaborations by using a portable specification for loading and processing data and retrieving data files from online sources. Two examples are shown in which the software is used to explore experimental datasets with extracellular nerve or muscle recordings and simultaneous video of behavior. The configuration specification for controlling how data are located, loaded, processed, and plotted is also summarized. Algorithms for spike detection and burst detection are demonstrated. This new program could be used in many applications in which behavior and signals need to be analyzed together.