Ischemic stroke, a leading cause of neurological morbidity, is characterized by extensive neuronal injury and a robust inflammatory response. Erbin, a scaffold protein involved in multiple cellular signaling pathways, regulates neuroinflammation and may confer neuroprotection against ischemia–reperfusion (I/R) injury. A mouse model of middle cerebral artery occlusion was utilized to evaluate the neuroprotective role of Erbin. Male mice were allocated into groups receiving either a lentiviral (LV) control vector or LV-mediated Erbin overexpression, followed by I/R injury induction. Neurological function, infarct volume, and expression levels of inflammatory cytokines and mitogen-activated protein kinase (MAPK) signaling proteins were analyzed. Overexpression of Erbin via LV transduction significantly reduced cerebral infarct volume and mitigated neurological impairments post-I/R injury. Furthermore, Erbin overexpression suppressed the phosphorylation of p38 and extracellular signal-regulated kinase in HT22 ...

Synaptic physiology experiments are fundamental to neuroscience research. Consequently, accurate detection of synaptic currents is crucial for conducting high-quality experiments. Traditionally, detecting inhibitory and excitatory postsynaptic currents (sIPSCs/sEPSCs) relied on hand-counting individual events. Although sEPSCs and sIPSCs are clear to the trained eye, hand analysis is time and labor intensive. Recent advances in applied machine learning promise faster, superior event detectors that may improve data quality and reduce or even completely negate the need for hand curation. While many strategies for sIPSC and sEPSC detection exist, rarely have they been quantitatively compared for accuracy within an experiment. Our study aims to establish practical ground-truth event detection in a large experimental dataset through meticulous hand counting and to assess variance in detection results across different laboratories, analysis techniques, and cell types. Using thoroughly hand-counted data as our gro...

We describe a novel method for adapting a two-photon scanning microscope to enable simultaneous detection of two-photon-generated visible fluorescence and single-photon-generated near-infrared (nIR) fluorescence. In this configuration, nIR fluorescence is routed through a single-mode optical fiber before detection by a photomultiplier tube. This fiber coupling offers two advantages: first, the optical fiber functions as a pinhole aperture, allowing for improved optical sectioning of the nIR signal; second, it minimizes nIR background fluorescence. To validate the effectiveness of this design, we conducted two sets of experiments in male and female C57B/6J mice. First, we compare two fluorescence indicators of the neurotransmitter dopamine: the genetically encoded indicator GRABDA and single-walled carbon nanotube-based optical nanosensors (nIRCats). Although nIRCats exhibit lower affinity for dopamine than GRABDA, this property allows for identification of high concentration release sites in the striatum. ...

This study used machine learning to objectively identify seizures in the electroencephalogram of a model of post-traumatic epilepsy based on fluid percussion injury in male rats. We applied transfer learning to a neural-network trained and tested on three potentially distinct electroencephalographic phenotypes: (1) late-onset convulsive seizures associated with rare post-traumatic epilepsy, (2) early-onset convulsive seizures that often occurred after sham or injury treatment (independent of post-traumatic epilepsy), and (3) spike-wave discharges (SWDs), which occurred in both injured and sham-control rats. The neural network was able to detect seizure events within individual animals and across different cohorts and showed that early and late seizures have similar electroencephalographic phenotypes. Additionally, cross-over training and testing on SWDs from injured and sham-control rats distinguished a convulsive seizure phenotype from normal SWDs. Convolutional neural network modeling of the electroencep...

Spiking thresholds in neurons or rectification at synapses are essential for neuronal computations rendering neuronal processing inherently nonlinear. Nevertheless, linear response theory has been instrumental for understanding, for example, the impact of noise or neuronal synchrony on signal transmission, or the emergence of oscillatory activity, but is valid only at low stimulus amplitudes or large levels of intrinsic noise. At higher signal-to-noise ratios, however, nonlinear response components become relevant. Theoretical results for leaky integrate-and-fire neurons in the weakly nonlinear regime suggest strong responses at the sum of two input frequencies if one of these frequencies or their sum matches the neuron’s baseline firing rate. We here analyze nonlinear responses in two types of primary electroreceptor afferents, the P-units of the active and the ampullary cells of the passive electrosensory system of the wave-type electric fish Apteronotus leptorhynchus of either sex. In our combined exper...

Complex problems often allow multiple paths to a solution. Choosing and taking the best path is an important part of the executive cognition that underpins intelligent problem-solving behavior. However, once a path is chosen, the motor system must be activated for executing it. This interface between problem-solving and self-generated action has rarely been studied. We recorded EEG movement-related potentials while 25 participants (7 males, 18 females) performed the “Tower of London” problem-solving task. In a control condition, participants merely followed instructed steps without planning for any goal and thus without any sense that their movements solved a problem. Readiness potentials (RPs) preceding actions showed a more sustained preparatory negativity for self-generated than stimulus-driven movements. Critically, this effect was most pronounced at the first move of a sequence and diminished at later stages, indicating that preparatory activity is closely linked to the planning demands of sequence in...

In the article “Is Social Media Use a Blessing or Cure for Motor Function and Skill Acquisition? An Opinion …

The retina encodes a broad range of stimuli, adapting its computations to features like brightness, contrast, and motion. However, it is unclear whether it also adapts when switching between natural scenes and white noise (WN). To address this, we analyzed the neural activity of male marmoset retinal ganglion cells (RGCs) in response to WN and naturalistic movies. We trained linear–nonlinear models on both stimuli, evaluated their performance, and compared their receptive fields across stimulus domains. We found that models with spatial filters trained on one stimulus ensemble were less accurate when predicting neural activity on the other compared to models trained directly on the target stimulus. This suggests that spatial processing adapts to stimulus statistics. Different RGC types exhibited distinct changes: The OFF midget cells’ receptive fields became enlarged under natural movies (NMs), resulting in a lower cutoff frequency. Parasol cells and large OFF cells did not significantly change their recep...

There is considerable interest in cannabinoid-based therapies to treat pain, but activation of the endogenous cannabinoid (endocannabinoid) system can elicit pro- and anti-nociceptive effects. This study tests the hypothesis that the concentration of the endocannabinoid arachidonoylethanolamine (AEA) contributes to whether pro- or anti-nociceptive effects are observed. Experiments were carried out using isolated ganglia from the medicinal leech Hirudo verbana where it is possible to selectively record from nociceptive and non-nociceptive synapses in the central nervous system (CNS). Previous studies using Hirudo have shown that endocannabinoids depress nociceptive (N) sensory cell synapses and potentiate of non-nociceptive pressure (P) sensory cell synapses. In this study, exogenously applied AEA produced depression of N synapses and potentiation of P synapses across the same range of concentrations. However, the results differed when using URB597, a drug that raises AEA by inhibiting fatty acid amine hydr...

Multi-electrode recording of neuronal activity in cultures offer opportunities for understanding how the structure of a network gives rise to function. Neuronal cultures derived from human induced pluripotent stem cells (iPSCs) from male and female individuals are often plated at highly variable cell densities across studies, but its impact on neuronal activity remains poorly understood. We found that properties such as the mean firing rate of the individual cells, the pairwise correlations between cells, and the entropy of the population all changed significantly with changes in culture density. We used a maximum entropy model to capture the structure of the population activity using only the firing rates and correlations, and we found that the model performed best at the highest densities, suggesting that changes in activity reflected differences in structure of interactions between neurons across scales of complexity. Our work thus shows that culture density is an important experimental parameter that i...