Human visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity.

The full neural circuits of conscious perception remain unknown. Using a visual perception task, we directly recorded a subcortical thalamic awareness potential (TAP). We also developed a unique paradigm to classify perceived versus not perceived stimuli using eye measurements to remove confounding signals related to reporting on conscious experiences. Using fMRI, we discovered three major brain networks driving conscious visual perception independent of report: first, increases in signal detection regions in visual, fusiform cortex, and frontal eye fields; and in arousal/salience networks involving midbrain, thalamus, nucleus accumbens, anterior cingulate, and anterior insula; second, increases in frontoparietal attention and executive control networks and in the cerebellum; finally, decreases in the default mode network. These results were largely maintained after excluding eye movement-based fMRI changes. Our findings provide evidence that the neurophysiology of consciousness is complex even without overt report, involving multiple cortical and subcortical networks overlapping in space and time.

Whole gut imaging allows quantification of all enteric neurons in the adult zebrafish intestine.

BACKGROUND: A fundamental understanding of the enteric nervous system in normal and diseased states is limited by the lack of standard measures of total enteric neuron number. The adult zebrafish is a useful model in this context as it is amenable to in toto imaging of the intestine. We leveraged this to develop a technique to image and quantify all enteric neurons within the adult zebrafish intestine and applied this method to assess the relationship between intestinal length and total enteric neuron number. METHODS: Dissected adult zebrafish intestines were immunostained in wholemount, optically cleared with refractive index-matched solution, and then imaged in tiles using light-sheet microscopy. Imaging software was used to stitch the tiles, and the full image underwent automated cell counting. Total enteric neuron number was assessed in relation to intestinal length using linear regression modeling. KEY RESULTS: Whole gut imaging of the adult zebrafish intestine permits the visualization of endogenous and immunohistochemistry-derived fluorescence throughout the intestine. While enteric neuron distribution is heterogeneous between intestinal segments, total enteric neuron number positively correlates with intestinal length. CONCLUSIONS & INFERENCES: Imaging of all enteric neurons within the adult vertebrate intestine is possible in models such as the zebrafish. In this study, we apply this to demonstrate a positive correlation between enteric neuron number and intestinal length. Quantifying total enteric numbers will facilitate future studies of enteric neuropathies and ENS structure in animal models and potentially in biopsied tissue samples.

Realistic driving simulation during generalized epileptiform discharges to identify electroencephalographic features related to motor vehicle safety: Feasibility and pilot study.

OBJECTIVE: Generalized epileptiform discharges (GEDs) can occur during seizures or without obvious clinical accompaniment. Motor vehicle driving risk during apparently subclinical GEDs is uncertain. Our goals were to develop a feasible, realistic test to evaluate driving safety during GEDs, and to begin evaluating electroencephalographic (EEG) features in relation to driving safety. METHODS: Subjects were aged ≥15 years with generalized epilepsy, GEDs on EEG, and no clinical seizures. Using a high-fidelity driving simulator (miniSim) with simultaneous EEG, a red oval visual stimulus was presented every 5 minutes for baseline testing, and with each GED. Participants were instructed to pull over as quickly and safely as possible with each stimulus. We analyzed driving and EEG signals during GEDs. RESULTS: Nine subjects were tested, and five experienced 88 GEDs total with mean duration 2.31 ± 1.89 (SD) seconds. Of these five subjects, three responded appropriately to all stimuli, one failed to respond to 75% of stimuli, and one stopped driving immediately during GEDs. GEDs with no response to stimuli were significantly longer than those with appropriate responses (8.47 ± 3.10 vs 1.85 ± 0.69 seconds, P < .001). Reaction times to stimuli during GEDs were significantly correlated with GED duration (r = 0.30, P = .04). In addition, EEG amplitude was greater for GEDs with no response to stimuli than GEDs with responses, both for overall root mean square voltage amplitude (66.14 µV vs 52.99 µV, P = .02) and for fractional power changes in the frequency range of waves (P < .05) and spikes (P < .001). SIGNIFICANCE: High-fidelity driving simulation is feasible for investigating driving behavior during GEDs. GEDs with longer duration and greater EEG amplitude showed more driving impairment. Future work with a large sample size may ultimately enable classification of GED EEG features to predict individual driving risk.