Place field assembly distribution encodes preferred locations

The hippocampus is the main locus of episodic memory formation and the neurons there encode the spatial map of the environment. Hippocampal place cells represent location, but their role in the learning of preferential location remains unclear. The hippocampus may encode locations independently from the stimuli and events that are associated with these locations. We have discovered a unique population code for the experience-dependent value of the context. The degree of reward-driven navigation preference highly correlates with the spatial distribution of the place fields recorded in the CA1 region of the hippocampus. We show place field clustering towards rewarded locations. Optogenetic manipulation of the ventral tegmental area demonstrates that the experience-dependent place field assembly distribution is directed by tegmental dopaminergic activity. The ability of the place cells to remap parallels the acquisition of reward context. Our findings present key evidence that the hippocampal neurons are not merely mapping the static environment but also store the concurrent context reward value, enabling episodic memory for past experience to support future adaptive behavior

MicroRNA-335-5p suppresses voltage-gated sodium channel expression and may be a target for seizure control

There remains an urgent need for new therapies for treatment-resistant epilepsy. Sodium channel blockers are effective for seizure control in common forms of epilepsy, but loss of sodium channel function underlies some genetic forms of epilepsy. Approaches that provide bidirectional control of sodium channel expression are needed. MicroRNAs (miRNA) are small noncoding RNAs which negatively regulate gene expression. Here we show that genome-wide miRNA screening of hippocampal tissue from a rat epilepsy model, mice treated with the antiseizure medicine cannabidiol, and plasma from patients with treatment-resistant epilepsy, converge on a single target-miR-335-5p. Pathway analysis on predicted and validated miR-335-5p targets identified multiple voltage-gated sodium channels (VGSCs). Intracerebroventricular injection of antisense oligonucleotides against miR-335-5p resulted in upregulation of Scn1a, Scn2a, and Scn3a in the mouse brain and an increased action potential rising phase and greater excitability of hippocampal pyramidal neurons in brain slice recordings, consistent with VGSCs as functional targets of miR-335-5p. Blocking miR-335-5p also increased voltage-gated sodium currents and SCN1A, SCN2A, and SCN3A expression in human induced pluripotent stem cell-derived neurons. Inhibition of miR-335-5p increased susceptibility to tonic-clonic seizures in the pentylenetetrazol seizure model, whereas adeno-associated virus 9-mediated overexpression of miR-335-5p reduced seizure severity and improved survival. These studies suggest modulation of miR-335-5p may be a means to regulate VGSCs and affect neuronal excitability and seizures. Changes to miR-335-5p may reflect compensatory mechanisms to control excitability and could provide biomarker or therapeutic strategies for different types of treatment-resistant epilepsy

Genome-wide microRNA profiling of plasma from three different animal models identifies biomarkers of temporal lobe epilepsy

Epilepsy diagnosis is complex, requires a team of specialists and relies on in-depth patient and family history, MRI-imaging and EEG monitoring. There is therefore an unmet clinical need for a non-invasive, molecular-based, biomarker to either predict the development of epilepsy or diagnose a patient with epilepsy who may not have had a witnessed seizure. Recent studies have demonstrated a role for microRNAs in the pathogenesis of epilepsy. MicroRNAs are short non-coding RNA molecules which negatively regulate gene expression, exerting profound influence on target pathways and cellular processes. The presence of microRNAs in biofluids, ease of detection, resistance to degradation and functional role in epilepsy render them excellent candidate biomarkers. Here we performed the first multi-model, genome-wide profiling of plasma microRNAs during epileptogenesis and in chronic temporal lobe epilepsy animals. From video-EEG monitored rats and mice we serially sampled blood samples and identified a set of dysregulated microRNAs comprising increased miR-93-5p, miR-142-5p, miR-182-5p, miR-199a-3p and decreased miR-574-3p during one or both phases. Validation studies found miR-93-5p, miR-199a-3p and miR-574-3p were also dysregulated in plasma from patients with intractable temporal lobe epilepsy. Treatment of mice with common anti-epileptic drugs did not alter the expression levels of any of the five miRNAs identified, however administration of an anti-epileptogenic microRNA treatment prevented dysregulation of several of these miRNAs. The miRNAs were detected within the Argonuate2-RISC complex from both neurons and microglia indicating these miRNA biomarker candidates can likely be traced back to specific brain cell types. The current studies identify additional circulating microRNA biomarkers of experimental and human epilepsy which may support diagnosis of temporal lobe epilepsy via a quick, cost-effective rapid molecular-based test

Brain cell-specific origin of circulating microRNA biomarkers in experimental temporal lobe epilepsy

The diagnosis of epilepsy is complex and challenging and would benefit from the availability of molecular biomarkers, ideally measurable in a biofluid such as blood. Experimental and human epilepsy are associated with altered brain and blood levels of various microRNAs (miRNAs). Evidence is lacking, however, as to whether any of the circulating pool of miRNAs originates from the brain. To explore the link between circulating miRNAs and the pathophysiology of epilepsy, we first sequenced argonaute 2 (Ago2)-bound miRNAs in plasma samples collected from mice subject to status epilepticus induced by intraamygdala microinjection of kainic acid. This identified time-dependent changes in plasma levels of miRNAs with known neuronal and microglial-cell origins. To explore whether the circulating miRNAs had originated from the brain, we generated mice expressing FLAG-Ago2 in neurons or microglia using tamoxifen-inducible Thy1 or Cx3cr1 promoters, respectively. FLAG immunoprecipitates from the plasma of these mice after seizures contained miRNAs, including let-7i-5p and miR-19b-3p. Taken together, these studies confirm that a portion of the circulating pool of miRNAs in experimental epilepsy originates from the brain, increasing support for miRNAs as mechanistic biomarkers of epilepsy

Dopaminergic control of the globus pallidus through activation of D2 receptors and its impact on the electrical activity of subthalamic nucleus and substantia nigra reticulata neurons.

The globus pallidus (GP) receives dopaminergic afferents from the pars compacta of substantia nigra and several studies suggested that dopamine exerts its action in the GP through presynaptic D2 receptors (D2Rs). However, the impact of dopamine in GP on the pallido-subthalamic and pallido-nigral neurotransmission is not known. Here, we investigated the role of dopamine, through activation of D2Rs, in the modulation of GP neuronal activity and its impact on the electrical activity of subthalamic nucleus (STN) and substantia nigra reticulata (SNr) neurons. Extracellular recordings combined with local intracerebral microinjection of drugs were done in male Sprague-Dawley rats under urethane anesthesia. We showed that dopamine, when injected locally, increased the firing rate of the majority of neurons in the GP. This increase of the firing rate was mimicked by quinpirole, a D2R agonist, and prevented by sulpiride, a D2R antagonist. In parallel, the injection of dopamine, as well as quinpirole, in the GP reduced the firing rate of majority of STN and SNr neurons. However, neither dopamine nor quinpirole changed the tonic discharge pattern of GP, STN and SNr neurons. Our results are the first to demonstrate that dopamine through activation of D2Rs located in the GP plays an important role in the modulation of GP-STN and GP-SNr neurotransmission and consequently controls STN and SNr neuronal firing. Moreover, we provide evidence that dopamine modulate the firing rate but not the pattern of GP neurons, which in turn control the firing rate, but not the pattern of STN and SNr neurons

Coefficient of variations of GP, STN and SNr neurons before and after dopamine or quinpirole injection into the GP.

<p>Coefficient of variations of GP, STN and SNr neurons before and after dopamine or quinpirole injection into the GP.</p

Intrapallidal microinjection of dopamine predominantly decreased the firing rate without changing the tonic firing pattern of STN neurons.

<p>(A-C) A representative example of STN neuron before (A) and after (C) microinjection of dopamine into the GP showing a decrease of its firing rate with spike train (A1C1), firing rate histogram (B) raster display of random segments of recording (A2C2), insterspike interval histogram (A3C3) and density histogram (A4C4) of the same STN neuron. (D) Circular plot representing the percentage of STN neurons showing an increase, a decrease or no change of their firing rate after the local injection of dopamine. (E-G) A representative example of STN neuron before (EF) and after (FG) microinjection of dopamine into the GP with spike train (E1G1), firing rate histogram (F), raster display of random segments of recording (E2G2), insterspike interval histogram (E3G3) and density histogram (E4G4) of the same STN neuron.</p

Comparison of Machine Learning Classification Methods for Determining the Geographical Origin of Raw Milk Using Vibrational Spectroscopy

One of the significant challenges in the food industry is the determination of the geographical origin, since products from different regions can lead to great variance in raw milk. Therefore, monitoring the origin of raw milk has become very relevant for producers and consumers worldwide. In this exploratory study, midinfrared spectroscopy combined with machine learning classification methods was investigated as a rapid and nondestructive method for the classification of milk according to its geographical origin. The curse of dimensionality makes some classification methods struggle to train efficient models. Thus, principal component analysis (PCA) has been applied to create a smaller set of features. The application of machine learning methods such as PLS-DA, PCA-LDA, SVM, and PCA-SVM demonstrates that the best results are obtained using PLS-DA, PCA-LDA, and PCA-SVM methods which show a correct classification rate (CCR) of 100% for PLS-DA and PCA-LDA and 94.95% for PCA-SVM, whereas the application of SVM without feature extraction gives a low CCR of 66.67%. These findings demonstrate that FT-MIR spectroscopy, combined with machine learning methods, is an efficient and suitable approach to classify the geographical origins of raw milk

Intrapallidal microinjection of quinpirole predominantly increased the firing rate of GP neurons in a dose-dependent manner without changing the tonic firing pattern.

<p>(A) Histograms showing the dose response effects of quinpirole (Quin 0.2, 0.4 and 0.8 μg) on the firing rate (A1) and the coefficient of variation of the interspike intervals (A2) of GP neurons. ***<i>p</i><0.001. (B-D) A representative example of GP neuron before (BC) and after (CD) microinjection of quinpirole (Quin) into the GP showing an increase of its firing rate with spike train (B1D1), firing rate histogram (C), raster display of random segments of recording (B2D2), insterspike interval histogram (B3D3) and density histogram (B4D4) of the same GP neuron. (E) Circular plot representing the percentage of GP neurons showing an increase, a decrease or no change of their firing rate after the local injection of quinpirole. (F-H) A representative example of GP neuron before (FG) and after (GH) microinjection of quinpirole (Quin) into the GP showing a decrease of its firing rate with spike train (F1H1), firing rate histogram (G), raster display of random segments of recording (F2H2), insterspike interval histogram (F3H3) and density histogram (F4H4) of the same GP neuron.</p