Temporal order memory is impaired in autism spectrum disorder (ASD) and schizophrenia (SCZ). These disorders, more prevalent in males, result in abnormal dendritic spine pruning during adolescence in layer 3 (L3) medial prefrontal cortex (mPFC), yielding either too many (ASD) or too few (SCZ) spines. Here we tested whether altering spine density in neural circuits including the mPFC could be associated with impaired temporal order memory in male mice. We have shown that α4βδ GABA receptors (GABARs) emerge at puberty on spines of L5 prelimbic mPFC (PL) where they trigger pruning. We show here that α4βδ receptors also increase at puberty in L3 PL (P < 0.0001) and used these receptors as a target to manipulate spine density here. Pubertal injection (14 d) of the GABA agonist gaboxadol, at a dose (3 mg/kg) selective for α4βδ, reduced L3 spine density by half (P < 0.0001), while α4 knock-out increased spine density ∼ 40 % (P < 0.0001), mimicking spine densities in SCZ and ASD, respectively. In both cases, performance on the mPFC-dependent temporal order recognition task was impaired, resulting in decreases in the discrimination ratio which assesses preference for the novel object: -0.39 ± 0.15, gaboxadol versus 0.52 ± 0.09, vehicle; P = 0.0002; -0.048 ± 0.10, α4 KO versus 0.49 ± 0.04, wild-type; P < 0.0001. In contrast, the number of approaches was unaltered, reflecting unchanged locomotion. These data suggest that altering α4βδ GABAR expression/activity alters spine density in L3 mPFC and impairs temporal order memory to mimic changes in ASD and SCZ. These findings may provide insight into these disorders.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.brainres.2024.148929DOI Listing

Publication Analysis

Top Keywords

temporal order
12
α4βδ gaba
8
gaba receptors
8
prefrontal cortex
8
order memory
8
manipulation α4βδ
4
receptors alters
4
alters synaptic
4
synaptic pruning
4
pruning layer
4

Similar Publications

The increasing availability of coarse-scale climate simulations and the need for ready-to-use high-resolution variables drive the climate community to the challenge of reducing computational resources and time for downscaling purposes. To this end, statistical downscaling is gaining interest as a potential strategy for integrating high-resolution climate information obtained through dynamical downscaling over limited years, providing a clear understanding of the gains and losses in combining dynamical and statistical downscaling. In this regard, several questions can be raised: (i) what is the performance of statistical downscaling, assuming dynamical downscaling as a reference over a shared time window; (ii) how much the performance of statistical downscaling is affected by changes in the number of years available for training; (iii) how does the climate normal considered for the training affect the predictions.

View Article and Find Full Text PDF

Patterns of neuronal synchrony in higher-order networks.

Phys Life Rev

December 2024

Community Healthcare Center Dr. Adolf Drolc Maribor, Ulica talcev 9, 2000 Maribor, Slovenia; Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia; Complexity Science Hub, Metternichgasse 8, 1080 Vienna, Austria; Department of Physics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea. Electronic address:

Synchrony in neuronal networks is crucial for cognitive functions, motor coordination, and various neurological disorders. While traditional research has focused on pairwise interactions between neurons, recent studies highlight the importance of higher-order interactions involving multiple neurons. Both types of interactions lead to complex synchronous spatiotemporal patterns, including the fascinating phenomenon of chimera states, where synchronized and desynchronized neuronal activity coexist.

View Article and Find Full Text PDF

Object detection in motion management scenarios based on deep learning.

PLoS One

January 2025

School of Physical Education, Jinjiang College, Sichuan University, Chengdu, Sichuan Province, People's Republic of China.

In athletes' competitions and daily training, in order to further strengthen the athletes' sports level, it is usually necessary to analyze the athletes' sports actions at a specific moment, in which it is especially important to quickly and accurately identify the categories and positions of the athletes, sports equipment, field boundaries and other targets in the sports scene. However, the existing detection methods failed to achieve better detection results, and the analysis found that the reasons for this phenomenon mainly lie in the loss of temporal information, multi-targeting, target overlap, and coupling of regression and classification tasks, which makes it more difficult for these network models to adapt to the detection task in this scenario. Based on this, we propose for the first time a supervised object detection method for scenarios in the field of motion management.

View Article and Find Full Text PDF

Background: Alzheimer's disease (AD) is highly comorbid with Limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC), and the combined AD+LATE-NC is more common than either pathology alone. However, the topographic relationship between tau and TDP-43 in AD+LATE-NC remains unclear.

Method: We analyzed the data from the Religious Orders Study (ROS) and the Rush Memory and Aging Project (MAP) participants.

View Article and Find Full Text PDF

Background: Alzheimer's Disease is marked by the gradual aggregation of pathological proteins, Tau and beta-amyloid, throughout various areas of the brain. The progression of these pathologies follows a consistent pattern, impacting various cellular populations as it advances through each brain region. Previously, we used Bayesian algorithms to create a continuous progression score to mathematically capture the collective aggregation of multiple pathological variables within a specific brain region.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!