Neuromodulators have major influences on the regulation of neural circuit activity across the nervous system. Nitric oxide (NO) has been shown to be a prominent neuromodulator in many circuits and has been extensively studied in the retina. Here, it has been associated with the regulation of light adaptation, gain control, and gap junctional coupling, but its effect on the retinal output, specifically on the different types of retinal ganglion cells (RGCs), is still poorly understood. In this study, we used two-photon Ca²⁺ imaging and multi-electrode array (MEA) recordings to measure light-evoked activity of RGCs in the ganglion cell layer in the ex vivo mouse retina. This approach allowed us to investigate the neuromodulatory effects of NO on a cell type-level. Our findings reveal that NO selectively modulates the suppression of temporal responses in a distinct subset of contrast-suppressed RGC types, increasing their activity without altering the spatial properties of their receptive fields. Given that under photopic conditions, NO release is triggered by quick changes in light levels, we propose that these RGC types signal fast contrast changes to higher visual regions. Remarkably, we found that about one-third of the RGC types, recorded using two-photon Ca²⁺ imaging, exhibited consistent, cell type-specific adaptational response changes throughout an experiment, independent of NO. By employing a sequential-recording paradigm, we could disentangle those additional adaptational response changes from drug-induced modulations. Taken together, our research highlights the selective neuromodulatory effects of NO on RGCs and emphasizes the need of considering non-pharmacological activity changes, like adaptation, in such study designs.

Sleep cycles are defined as episodes of non-rapid eye movement (non-REM) sleep followed by an episode of REM sleep. Fractal or aperiodic neural activity is a well-established marker of arousal and sleep stages measured using electroencephalography. We introduce a new concept of ‘fractal cycles’ of sleep, defined as a time interval during which time series of fractal activity descend to their local minimum and ascend to the next local maximum. We assess correlations between fractal and classical (i.e. non-REM – REM) sleep cycle durations and study cycles with skipped REM sleep. The sample comprised 205 healthy adults, 21 children and adolescents and 111 patients with depression. We found that fractal and classical cycle durations (89±34 vs 90±25 min) correlated positively (r=0.5, p<0.001). Children and adolescents had shorter fractal cycles than young adults (76±34 vs 94±32 min). The fractal cycle algorithm detected cycles with skipped REM sleep in 91–98% of cases. Medicated patients with depression showed longer fractal cycles compared to their unmedicated state (107±51 vs 92±38 min) and age-matched controls (104±49 vs 88±31 min). In conclusion, fractal cycles are an objective, quantifiable, continuous and biologically plausible way to display sleep neural activity and its cycles.