The Use of Trace Eyeblink Classical Conditioning to Assess Hippocampal Dysfunction in a Rat Model of Fetal Alcohol Spectrum Disorders

Neurobehavioral alterations induced by third-trimester gestation-equivalent ethanol exposure are inhibited by folate administration

Prenatal ethanol exposure (PEE) causes several neurobehavioral impairments in the fetus. Postnatal days (PDs) 4-9 in rodents are considered equivalent to the third trimester of gestation in humans. This period is characterized by high rates of synaptogenesis and myelination and the maturation of key structures and transmitter systems. Nutritional supplements, such as folate, have gained attention as putative treatments to mitigate detrimental effects of PEE. Folate is crucial for DNA synthesis and amino acid metabolism and heightens antioxidant defenses. The present study examined neurobehavioral effects of the concurrent administration of folate (20 mg/kg/day) and ethanol (5 g/kg/day) during PDs 4-9 in male and female Wistar rats. During PDs 16-18, the rat pups were tested for anxiety-like and exploratory activity in the light-dark box (LDB), open field (OF), and concentric square field (CSF) tests. After weaning, they were tested for sucrose preference and ethanol intake. Neonatal ethanol exposure reduced body weight in infancy but did not enhance ethanol self-administration or significantly affect performance in the OF or LDB. Neonatal ethanol exposure also reduced sucrose intake in the preference test and increased shelter-seeking in the CSF, and folate significantly inhibited these effects. The present findings suggest that folate, a treatment that is devoid of serious side effects, can ameliorate some neurobehavioral effects of PEE.

Behavioral and Transcriptome Profiling of Heterozygous Rab10 Knock-Out Mice

A central question in the field of aging research is to identify the cellular and molecular basis of neuroresilience. One potential candidate is the small GTPase, Rab10. Here, we used Rab10+/- mice to investigate the molecular mechanisms underlying Rab10-mediated neuroresilience. Brain expression analysis of 880 genes involved in neurodegeneration showed that Rab10+/- mice have increased activation of pathways associated with neuronal metabolism, structural integrity, neurotransmission, and neuroplasticity compared with their Rab10+/+ littermates. Lower activation was observed for pathways involved in neuroinflammation and aging. We identified and validated several differentially expressed genes (DEGs), including Stx2, Stx1b, Vegfa, and Lrrc25 (downregulated) and Prkaa2, Syt4, and Grin2d (upregulated). Behavioral testing showed that Rab10+/- mice perform better in a hippocampal-dependent spatial task (object in place test), while their performance in a classical conditioning task (trace eyeblink classical conditioning, TECC) was significantly impaired. Therefore, our findings indicate that Rab10 differentially controls the brain circuitry of hippocampal-dependent spatial memory and higher-order behavior that requires intact cortex-hippocampal circuitry. Transcriptome and biochemical characterization of these mice suggest that glutamate ionotropic receptor NMDA type subunit 2D (GRIN2D or GluN2D) is affected by Rab10 signaling. Further work is needed to evaluate whether GRIN2D mediates the behavioral phenotypes of the Rab10+/- mice. We conclude that Rab10+/- mice described here can be a valuable tool to study the mechanisms of resilience in Alzheimer's disease (AD) model mice and to identify novel therapeutical targets to prevent cognitive decline associated with normal and pathologic aging.

Green model to adapt classical conditioning learning in the hippocampus

Compared with the biological paradigms of classical conditioning, non-adaptive computational models are not capable of realistically simulating the biological behavioural functions of the hippocampal regions, because of their implausible requirement for a large number of learning trials, which can be on the order of hundreds. Additionally, these models did not attain a unified, final stable state even after hundreds of learning trials. Conversely, the output response has a different threshold for similar tasks in various models with prolonged transient response of unspecified status via the training or even testing phases. Accordingly, a green model is a combination of adaptive neuro-computational hippocampal and cortical models that is proposed by adaptively updating the whole weights in all layers for both intact networks and lesion networks using instar and outstar learning rules with adaptive resonance theory (ART). The green model sustains and expands the classical conditioning biological paradigms of the non-adaptive models. The model also overcomes the irregular output response behaviour by using the proposed feature of adaptivity. Further, the model successfully simulates the hippocampal regions without passing the final output response back to the whole network, which is considered to be biologically implausible. The results of the Green model showed a significant improvement confirmed by empirical studies of different tasks. In addition, the results indicated that the model outperforms the previously published models. All the obtained results successfully and quickly attained a stable, desired final state (with a unified concluding state of either "1" or "0") with a significantly shorter transient duration.