Amyloid-β Protein Precursor Deficiency Changes Neuronal Electrical Activity and Levels of Mitochondrial Proteins in the Medial Prefrontal Cortex

Background: Neuropathological features of Alzheimer’s disease are characterized by the deposition of amyloid-β (Aβ) plaques and impairments in synaptic activity and memory. However, we know little about the physiological role of amyloid-β protein precursor (AβPP) from which Aβ derives. Objective: Evaluate APP deficiency induced alterations in neuronal electrical activity and mitochondrial protein expression. Methods: Utilizing electrophysiological, biochemical, pharmacological, and behavioral tests, we revealed aberrant local field potential (LFP), extracellular neuronal firing and levels of mitochondrial proteins. Result: We show that APP knockout (APP -/- ) leads to increased gamma oscillations in the medial prefrontal cortex (mPFC) at 1-2 months old, which can be restored by baclofen (Bac), a γ-aminobutyric acid type B receptor (GABABR) agonist. A higher dose and longer exposure time is required for Bac to suppress neuronal firing in APP -/- mice than in wild type animals, indicating enhanced GABABR mediated activity in the mPFC of APP -/- mice. In line with increased GABABR function, the glutamine synthetase inhibitor, L-methionine sulfonate, significantly increases GABABR levels in the mPFC of APP -/- mice and this is associated with a significantly lower incidence of death. The results suggest that APP -/- mice developed stronger GABABR mediated inhibition. Using HEK 293 as an expression system, we uncover that AβPP functions to suppress GABABR expression. Furthermore, APP -/- mice show abnormal expression of several mitochondrial proteins. Conclusion: APP deficiency leads to both abnormal network activity involving defected GABABR and mitochondrial dysfunction, suggesting critical role of AβPP in synaptic and network function.

Recognition of Epileptic Seizures in EEG Records: A Transfer Learning Approach

Introduction: Seizure is a transient phenomenon with genesis in excessive abnormal or synchronous neuronal electrical activity in the brain, while epilepsy is defined as a brain dysfunction characterized by persistent predisposition to generate seizures. The identification of epileptogenic electroencephalographic patterns can be performed using machine learning.the present study aimed to develop a transfer learning based classifier able to detect epileptic seizures in images generated from electroencephalographic data graphic representation.Material and Methods: We used the Epileptic Seizure Recognition Data Set,which consists of 500 brain activity records for 23.6 seconds comprising 23 chunks of 178 data points, and transformed the resulting 11500 instances into images by graphically plotting its data points. Those images were then splitted in training and test set and used to build and assess, respectvely, a transfer learning-based deep neural network, which classified the images according the presence or absence of epileptic seizures.Results: The model achieved 100% accuracy, sensitivity and specificity, with a AUC-score of 1.0, demonstrating the great potential of transfer learning for the analysis of graphically represented electroencephalographic data.Conclusion: It is opportune to raise new studies involving transfer learning for the analysis of signal data, with the aim of improving, disseminating and validating its use for daily clinical practice.

Certain ortho-hydroxylated brominated ethers are promiscuous kinase inhibitors that impair neuronal signaling and neurodevelopmental processes

The developing nervous system is remarkably sensitive to environmental signals, including disruptive toxins, such as polybrominated diphenyl ethers (PBDEs). PBDEs are an environmentally pervasive class of brominated flame retardants whose neurodevelopmental toxicity mechanisms remain largely unclear. Using dissociated cortical neurons from embryonic Rattus norvegicus, we found here that chronic exposure to 6-OH–BDE-47, one of the most prevalent hydroxylated PBDE metabolites, suppresses both spontaneous and evoked neuronal electrical activity. On the basis of our previous work on mitogen-activated protein kinase (MAPK)/extracellular signal-related kinase (ERK) (MEK) biology and our observation that 6-OH–BDE-47 is structurally similar to kinase inhibitors, we hypothesized that certain hydroxylated PBDEs mediate neurotoxicity, at least in part, by impairing the MEK–ERK axis of MAPK signal transduction. We tested this hypothesis on three experimental platforms: 1) in silico, where modeling ligand–protein docking suggested that 6-OH–BDE-47 is a promiscuous ATP-competitive kinase inhibitor; 2) in vitro in dissociated neurons, where 6-OH–BDE-47 and another specific hydroxylated BDE metabolite similarly impaired phosphorylation of MEK/ERK1/2 and activity-induced transcription of a neuronal immediate early gene; and 3) in vivo in Drosophila melanogaster, where developmental exposures to 6-OH–BDE-47 and a MAPK inhibitor resulted in offspring displaying similarly increased frequency of mushroom-body β–lobe midline crossing, a metric of axonal guidance. Taken together, our results support that certain ortho-hydroxylated PBDE metabolites are promiscuous kinase inhibitors and can cause disruptions of critical neurodevelopmental processes, including neuronal electrical activity, pre-synaptic functions, MEK–ERK signaling, and axonal guidance.

Spontaneous Electromagnetic Induction Modulating the Neuronal Dynamical Response

Spontaneous electromagnetic induction originating from neuronal electrical activity is believed to reflect the memory ability in the neural system and significantly modulates neural information transmission, but its fundamental effect on the neuronal dynamic properties is still not well understood. In this paper, we use a memristor to couple neuronal electrical activity and magnetic fields and study how the spontaneous electromagnetic induction modulates the neuronal dynamical response to external stimulation. It is found that the negative feedback of electromagnetic induction on the neuron significantly reduces the dynamical response range, decreases the oscillation amplitude and induces a higher firing frequency. Meanwhile, the memory effect on electromagnetic induction can induce two kinds of bistability, including the coexistence of a stable limit cycle and a fixed point, and the coexistence of two stable limit cycles. Furthermore, high electric driving for electromagnetic induction produces complex firing patterns with single, double and multiple frequencies. Our results not only further confirm the efficacy of spontaneous electromagnetic induction in modulating the neuronal dynamical properties but also provide insights into the possibilities of choosing suitable parameter spaces in studying the effects of external magnetic induction on brain functions.