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, 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, crossover training and testing on spike-wave discharges from injured and sham-control rats distinguished a convulsive-seizure phenotype from normal spike-wave discharges. Convolutional neural network mo...

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 pair-wise 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, 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 impa...

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) synapses and potentiate of non-nociceptive pressure (P) 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 hydrolase (FAAH), the enzyme t...

Neurons couple to various degrees to the activity level of the local neighboring population whereby strongly coupled 'choristers' and weakly coupled 'soloists' have been identified as two extremes of a continuous spectrum. At the same time neuronal populations undergo coordinated ON and OFF cortical state activity fluctuations, which are locally modulated by attention. The population coupling of soloists and choristers suggests that soloists should show limited alignment with cortical state fluctuations, while choristers should exhibit profound alignment. To test this, we recorded neurons across cortical layers in macaque areas V1 and V4 (n=2 males), while animals performed a feature based spatial attention task. As expected, we found a wide range of population coupling strength of neurons. In line with our prediction, coupling of choristers to cortical state changes (ON-OFF transitions) was generally stronger than that of soloists. The strength of population coupling of neurons was similar during spontane...

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, and while 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...

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/6 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. S...

The refinement of gross motor skills, such as locomotion, during development is conserved across vertebrate species. Our previous work demonstrated, in larval zebrafish, that dopaminergic signaling through the dopamine D2-like family of receptors, specifically the dopamine 4 receptor subtype, was necessary for the developmental transformation of behaviorally relevant locomotor activity from an immature to a mature pattern between 3- and 4-days post-fertilization. In this study, we used a complement of tools, including electrophysiology, pharmacology, in vivo calcium imaging, liquid chromatography-mass spectrometry, and quantitative reverse transcription polymerase chain reaction to characterize the functional and molecular mechanisms responsible for this dopaminergic-mediated refinement of spinal locomotor activity. The results demonstrate that the dopamine 4 receptor subtype is functional in, at least, a subset of immature larvae. Further, gene expression of all D2-like receptor subtypes, levels of dopami...

Cortical neurons in sensory areas undergo a protracted process of postnatal maturation that includes changes in membrane properties, synaptic drive and connectivity. The completion of this process is associated with the closure of critical periods for experience-dependent plasticity in visual, auditory and somatosensory cortices. Whether these findings extend to the postnatal development of cortical circuits for taste is currently unknown. Taste receptor cells in the taste buds reliably fire action potentials in response to taste stimuli by the third postnatal week and show extended refinement of membrane excitability into adulthood. Taste responsive neurons in the nucleus of the solitary tract show reorganization of peripheral nerve terminals (NTS) over a timeline comparable to taste buds. However, no study to date investigated the postnatal development of neurons in the gustatory cortex (GC). Here, we focused on pyramidal neurons in the deep layers of GC in acute slices from male and female mice and comp...

JNeurosci Reviewing Editors Bruno Averbeck and Anne-Marie Oswald discuss best practices for writing computational neuroscience papers for The Journal of Neuroscience. They offer tips and strategies for how to organize the paper and clearly present technical material to the broad neuroscience community that is the readership of the journal.

Iris Groen discussed her paper, “Temporal Dynamics of Neural Responses in Human Visual Cortex,” published in Vol. 42, Issue 40 of JNeurosci, with Megan Sansevere from SfN’s Journals’ staff.