Fast, scalable, Bayesian spike identification for multi-electrode arrays

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes overlap, and accounts for intrinsic variability of spikes from each unit. As MEAs grow larger, it is important to find spike-identification methods that are scalable, that is, the computational cost of spike fitting should scale well with the number of units observed. Our algorithm accomplishes this goal, and is fast, because it exploits the spatial locality of each unit and the basic biophysics of extracellular signal propagation. Human intervention is minimized and streamlined via a graphical interface. We illustrate our method on data from a mammalian retina preparation and document its performance on simulated data consisting of spikes added to experimentally measured background noise. The algorithm is highly accurate

Modeling convergent ON and OFF pathways in the early visual system

For understanding the computation and function of single neurons in sensory systems, one needs to investigate how sensory stimuli are related to a neuron’s response and which biological mechanisms underlie this relationship. Mathematical models of the stimulus–response relationship have proved very useful in approaching these issues in a systematic, quantitative way. A starting point for many such analyses has been provided by phenomenological “linear–nonlinear” (LN) models, which comprise a linear filter followed by a static nonlinear transformation. The linear filter is often associated with the neuron’s receptive field. However, the structure of the receptive field is generally a result of inputs from many presynaptic neurons, which may form parallel signal processing pathways. In the retina, for example, certain ganglion cells receive excitatory inputs from ON-type as well as OFF-type bipolar cells. Recent experiments have shown that the convergence of these pathways leads to intriguing response characteristics that cannot be captured by a single linear filter. One approach to adjust the LN model to the biological circuit structure is to use multiple parallel filters that capture ON and OFF bipolar inputs. Here, we review these new developments in modeling neuronal responses in the early visual system and provide details about one particular technique for obtaining the required sets of parallel filters from experimental data

Bacteria are important dimethylsulfoniopropionate producers in marine aphotic and high-pressure environments

Dimethylsulfoniopropionate (DMSP) is an important marine osmolyte. Aphotic environments are only recently being considered as potential contributors to global DMSP production. Here, our Mariana Trench study reveals a typical seawater DMSP/dimethylsulfide (DMS) profile, with highest concentrations in the euphotic zone and decreased but consistent levels below. The genetic potential for bacterial DMSP synthesis via the dsyB gene and its transcription is greater in the deep ocean, and is highest in the sediment.s DMSP catabolic potential is present throughout the trench waters, but is less prominent below 8000 m, perhaps indicating a preference to store DMSP in the deep for stress protection. Deep ocean bacterial isolates show enhanced DMSP production under increased hydrostatic pressure. Furthermore, bacterial dsyB mutants are less tolerant of deep ocean pressures than wild-type strains. Thus, we propose a physiological function for DMSP in hydrostatic pressure protection, and that bacteria are key DMSP producers in deep seawater and sediment

Short-Lived Trace Gases in the Surface Ocean and the Atmosphere

The two-way exchange of trace gases between the ocean and the atmosphere is important for both the chemistry and physics of the atmosphere and the biogeochemistry of the oceans, including the global cycling of elements. Here we review these exchanges and their importance for a range of gases whose lifetimes are generally short compared to the main greenhouse gases and which are, in most cases, more reactive than them. Gases considered include sulphur and related compounds, organohalogens, non-methane hydrocarbons, ozone, ammonia and related compounds, hydrogen and carbon monoxide. Finally, we stress the interactivity of the system, the importance of process understanding for modeling, the need for more extensive field measurements and their better seasonal coverage, the importance of inter-calibration exercises and finally the need to show the importance of air-sea exchanges for global cycling and how the field fits into the broader context of Earth System Science

Differential arousal regulation by prokineticin 2 signaling in the nocturnal mouse and the diurnal monkey

The temporal organization of activity/rest or sleep/wake rhythms for mammals is regulated by the interaction of light/dark cycle and circadian clocks. The neural and molecular mechanisms that confine the active phase to either day or night period for the diurnal and the nocturnal mammals are unclear. Here we report that prokineticin 2, previously shown as a circadian clock output molecule, is expressed in the intrinsically photosensitive retinal ganglion cells, and the expression of prokineticin 2 in the intrinsically photosensitive retinal ganglion cells is oscillatory in a clock-dependent manner. We further show that the prokineticin 2 signaling is required for the activity and arousal suppression by light in the mouse. Between the nocturnal mouse and the diurnal monkey, a signaling receptor for prokineticin 2 is differentially expressed in the retinorecipient suprachiasmatic nucleus and the superior colliculus, brain projection targets of the intrinsically photosensitive retinal ganglion cells. Blockade with a selective antagonist reveals the respectively inhibitory and stimulatory effect of prokineticin 2 signaling on the arousal levels for the nocturnal mouse and the diurnal monkey. Thus, the mammalian diurnality or nocturnality is likely determined by the differential signaling of prokineticin 2 from the intrinsically photosensitive retinal ganglion cells onto their retinorecipient brain targets