In the pupillary light response (PLR), increases in ambient light constrict the pupil to dampen increases in retinal illuminance. Here, we report that the pupillary reflex arc implements a second input-output transformation; it senses temporal contrast to enhance spatial contrast in the retinal image and increase visual acuity. The pupillary contrast response (PCoR) is driven by rod photoreceptors via type 6 bipolar cells and M1 ganglion cells.
View Article and Find Full Text PDFVGluT3-expressing mouse retinal amacrine cells (VG3s) respond to small-object motion and connect to multiple types of bipolar cells (inputs) and retinal ganglion cells (RGCs, outputs). Because these input and output connections are intermixed on the same dendrites, making sense of VG3 circuitry requires comparing the distribution of synapses across their arbors to the subcellular flow of signals. Here, we combine subcellular calcium imaging and electron microscopic connectomic reconstruction to analyze how VG3s integrate and transmit visual information.
View Article and Find Full Text PDFHow sensory systems extract salient features from natural environments and organize them across neural pathways is unclear. Combining single-cell and population two-photon calcium imaging in mice, we discover that retinal ON bipolar cells (second-order neurons of the visual system) are divided into two blocks of four types. The two blocks distribute temporal and spatial information encoding, respectively.
View Article and Find Full Text PDFCorrelated light and electron microscopy (CLEM) can be used to combine functional and molecular characterizations of neurons with detailed anatomical maps of their synaptic organization. Here we describe a multiresolution approach to CLEM (mrCLEM) that efficiently targets electron microscopy (EM) imaging to optically characterized cells while maintaining optimal tissue preparation for high-throughput EM reconstruction. This approach hinges on the ease with which arrays of sections collected on a solid substrate can be repeatedly imaged at different scales using scanning electron microscopy.
View Article and Find Full Text PDFIn humans, midget and parasol ganglion cells account for most of the input from the eyes to the brain. Yet, how they encode visual information is unknown. Here, we perform large-scale multi-electrode array recordings from retinas of treatment-naive patients who underwent enucleation surgery for choroidal malignant melanomas.
View Article and Find Full Text PDFObjective: The objective of this study was to quantify the features of stereotypy in epileptic seizures and compare it with that of stereotypy in psychogenic nonepileptic seizure-like events (PNES) confirmed by video-electroencephalography (VEEG) monitoring.
Methods: Video-electroencephalography monitoring records of 20 patients with temporal lobe seizures (TLS) and 20 with PNES were retrospectively reviewed (n = 138 seizures, 48 TLS and 90 PNES). We analyzed the semiology of 59 behaviors of interest for their presence, duration, sequence, and continuity using quantified measures that were entered into statistical analysis.
How do canonical computational elements interact to shape neural circuit function? In this issue of Neuron, Drinnenberg et al. (2018) show that parallel processing converts unitary negative feedback at the first synapse of the retina into diverse output signals to the brain.
View Article and Find Full Text PDFNeurons receive synaptic inputs on extensive neurite arbors. How information is organized across arbors and how local processing in neurites contributes to circuit function is mostly unknown. Here, we used two-photon Ca imaging to study visual processing in VGluT3-expressing amacrine cells (VG3-ACs) in the mouse retina.
View Article and Find Full Text PDFTo determine the spatiotemporal relationships among intrinsic networks of the human brain, we recruited seven neurosurgical patients (four males and three females) who were implanted with intracranial depth electrodes. We first identified canonical resting-state networks at the individual subject level using an iterative matching procedure on each subject's resting-state fMRI data. We then introduced single electrical pulses to fMRI pre-identified nodes of the default network (DN), frontoparietal network (FPN), and salience network (SN) while recording evoked responses in other recording sites within the same networks.
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