Intra-burst firing characteristics as network state parameters

Introduction \ud In our group we are aiming to demonstrate learning and memory capabilities of cultured networks of cortical neurons. A first step is to identify parameters that accurately describe changes in the network due to learning. Usually, such parameters are calculated from the responses to test-stimuli before and after a learning experiment. We propose that parameters should be calculated from the spontaneous activity before and after a learning experiment, as the applying of test-stimuli itself may alter the network. Since bursting is dominant in our cultures, we have investigated its spatio-temporal structure. \ud \ud Methods \ud Networks of cortical neurons were cultured on a MEA. Over a period from 9 to 35 DIV, the spontaneous activity has been measured on a regular basis. Measurements on a single day are always continuous; otherwise cultures are kept in a stove under controlled conditions (37 ˚C, 5% CO2, 100% humidity). Network bursts were detected by analysing the Array-Wide Spiking Rate (AWSR, the sum of activity over all electrodes). Next, we estimated the instantaneous AWSR during a burst by convolving spike-occurrences with a Gaussian function. We investigated the changes in burst profiles over time by aligning them to their peak AWSR. In 4 hour recording sessions, we grouped the burst profiles over 1 hour, resulting in 4 average burst profiles per day. In addition, a sufficient amount of aligned bursts yielded enough data to calculate the contribution of each recording site. \ud \ud Results \ud The burst profiles, calculated over a period of 1 hour, generally show little variation (figure 1). In subsequent hours, the profiles gradually change shape. Over a period of days however, the shape can change dramatically (figure 2). The relatively slow changes over the period of hours indicate an underlying probabilistic structure in the AWSR during bursts. The apparent structure in the burst profiles result from the relationships between individual recording sites, and thus also on the connectivity in the neural network. This is revealed in more detail by showing the contributions of individual sites (figure 3). The spike envelopes have a shape that is too detailed to be described accurately by a small set of parameters. \ud \ud Discussion \ud The burst profiles prove to be stable over a period of one hour, and gradually change their shape over several hours, as has also been suggested in [1]. The day-to-day changes in burst profiles may be the result of these gradual changes, thereby suggesting an intrinsically changing network. However, they can also be the result of putting the cultures back in the stove. The spike envelopes per recording site offer more detailed descriptions of the network state than the burst profiles. This may however be the amount of detail required to reveal the changes made during learning experiments. A subsequent refinement can be made by identifying distinct subgroups of bursts, as has been suggested in [2]

Water vapour absorption effects on solar radiation in an Apennine valley from hygrometric measurements of precipitable water taken at various altitudes

Hygrometric ratio measurements were simultaneously taken on six autumn clear-sky days of 1981 and 1982 by employing four Volz sun-photometers and the FISBAT sun-photometer at five stations located at different altitudes along the western slope of the Leo Valley, in the Apennines (Italy). Due to the solar heating of ground, intense upslope breezes forming during the early morning caused the vertical transport of more humid air from the bottom of the valley toward the ridge of the mountain chain. Precise calibration curves of the hygrometric ratio were defined on the basis of criteria suggested by the atmospheric infrared hygrometry technique and using the calibration constants found through an accurate intercomparison procedure. Examining the sun-photometric measurements by means of these calibration curves, precipitable water was determined at all stations, with the frequency of one measurement every 15 minutes from the early morning to one hour after noon. Daily homogeneous time-patterns of precipitable water were defined at the various stations, showing that this quantity varies appreciably during the morning at all stations, sometimes presenting daily increases of more than 40% at the lower stations. Average values of absolute humidity were then determined within the four atmospheric layers defined by the station altitudes, finding that the convective transport of humid air along the valley slopes can produce important variations within the atmospheric layer below the 1.6 km height. For these moisture conditions of the atmosphere, calculations of the time-variations caused by water vapour absorption in the downwelling flux Φ1 of global solar radiation reaching the ground were made at the various stations, as well as of those in the upwelling flux Φ of solar radiation at the top-level of the atmosphere. The results indicate that: i) flux Φ1 can appreciably decrease due to water vapour absorption, by 10 to 20 W m −2 at the highest station of Mt. Cimone and by 70 to 80 W m −2 at the lowest station situated on the bottom of the Leo Valley, and ii) the changes caused by water vapour absorption in the upwelling flux Φ were estimated to range usually between about 5 W m−2 at the Mt. Cimone station and more than 25 W m−2 at the lowest station. In particular, as a consequence of the time-variations in both precipitable water and solar elevation angle, the change ΔΦ caused by water vapour in the instantaneous outgoing flux of solar radiation at noon was found to increase almost linearly as a function of precipitable water throughout the range from 0.8 to 1.8 g cm−2, with an average slope coefficient equal to 12.5 W m−2 per unit variation of precipitable water

LIDAR DERIVED SALT MARSH TOPOGRAPHY AND BIOMASS: DEFINING ACCURACY AND SPATIAL PATTERNS OF UNCERTAINTY

As valuable and vulnerable blue carbon ecosystems, salt marshes require adaptable and robust monitoring methods that span a range of spatiotemporal scales. The application of unmanned aerial vehicle (UAV) based remote sensing is a key tool in achieving this goal. Due to the particular characteristics of tidal wetlands, however, there are challenges in obtaining research and management relevant data with the requisite level of accuracy. In this study, the spatial patterns in uncertainty stemming from scan angle, binning method, vegetation structure and platform surface morphology are examined in the context of UAV light detection and ranging (LiDAR) derived digital elevation models (DEM). The results demonstrate that overlapping the UAV flight paths sufficiently to avoid sole reliance on LIDAR data with scan angles exceeding 15 degrees is advisable. Furthermore, the spatial arrangement of halophyte species and marsh morphology has a clear influence on DEM accuracy. The largest errors were associated with sudden structural transitions at the marsh channel boundaries. The DEMmean was found to be the most accurate for bare ground, while the DEMmin was the most accurate for channels and the middle to high marsh vegetation (MAEs = −0.01m). For the low to middle vegetation, all the trialled DEMs returned a similar magnitude of mean error (MAE = ± 0.03m). The accuracy difference between the two vegetation associations examined appears to be connected to variations in coverage, height and biomass. Overall, these findings reinforce the link between salt marsh biogeomorphic complexity and the spatial distribution and magnitude of LiDAR DEM erro

Aprovechamiento de vertebrados terrestres por las poblaciones humanas que habitaron la costa del Golfo San Matías (provincia de Río Negro, Argentina) durante el Holoceno medio y tardío

Tesis presentada para optar al Grado de Doctor en Ciencias NaturalesFil: Marani, Hernán A.. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentin

Limits on the cosmological abundance of supermassive compact objects from a millilensing search in gamma-ray burst data

A new search for the gravitational lens effects of a significant cosmological density of supermassive compact objects (SCOs) on gamma-ray bursts has yielded a null result. We inspected the timing data of 774 BATSE-triggered GRBs for evidence of millilensing: repeated peaks similar in light-curve shape and spectra. Our null detection leads us to conclude that, in all candidate universes simulated, $\Omega_{SCO} < 0.1$ is favored for $10^5 < M_{SCO}/M_{\odot} < 10^9$, while in some universes and mass ranges the density limits are as much as 10 times lower. Therefore, a cosmologically significant population of SCOs near globular cluster mass neither came out of the primordial universe, nor condensed at recombination.Comment: 14 pages including 3 figures, appeared 2001 January 2

Toward coherent space-time mapping of seagrass cover from satellite data: An example of a Mediterranean lagoon

Seagrass meadows are a highly productive and economically important shallow coastal habitat. Their sensitivity to natural and anthropogenic disturbances, combined with their importance for local biodiversity, carbon stocks, and sediment dynamics, motivate a frequent monitoring of their distribution. However, generating time series of seagrass cover from field observations is costly, and mapping methods based on remote sensing require restrictive conditions on seabed visibility, limiting the frequency of observations. In this contribution, we examine the effect of accounting for environmental factors, such as the bathymetry and median grain size (D50) of the substrate as well as the coordinates of known seagrass patches, on the performance of a random forest (RF) classifier used to determine seagrass cover. Using 148 Landsat images of the Venice Lagoon (Italy) between 1999 and 2020, we trained an RF classifier with only spectral features from Landsat images and seagrass surveys from 2002 and 2017. Then, by adding the features above and applying a time-based correction to predictions, we created multiple RF models with different feature combinations. We tested the quality of the resulting seagrass cover predictions from each model against field surveys, showing that bathymetry, D50, and coordinates of known patches exert an influence that is dependent on the training Landsat image and seagrass survey chosen. In models trained on a survey from 2017, where using only spectral features causes predictions to overestimate seagrass surface area, no significant change in model performance was observed. Conversely, in models trained on a survey from 2002, the addition of the out-of-image features and particularly coordinates of known vegetated patches greatly improves the predictive capacity of the model, while still allowing the detection of seagrass beds absent in the reference field survey. Applying a time-based correction eliminates small temporal variations in predictions, improving predictions that performed well before correction. We conclude that accounting for the coordinates of known seagrass patches, together with applying a time-based correction, has the most potential to produce reliable frequent predictions of seagrass cover. While this case study alone is insufficient to explain how geographic location information influences the classification process, we suggest that it is linked to the inherent spatial auto-correlation of seagrass meadow distribution. In the interest of improving remote-sensing classification and particularly to develop our capacity to map vegetation across time, we identify this phenomenon as warranting further research

Neuromelanin-containing, catecholaminergic neurons in the human brain: ontogenetic aspects, development and aging

The present review compiles data on the development and aging ofneuromelanin (NM)-containing neurons in the central nervous system. Neuromelanin is brownish-to-black pigment that accumulates in the catecholaminergic (noradrenergic and dopaminergic) neurons and is a reliable natural marker that delineates the A1-A14 catecholaminergic groups of Dahlstrom and Fuxe in the human brain. The pigmentation of noradrenergic locus ceruleus neurons starts earlier than that of dopaminergic substantia nigra, but also a considerable individual variability is present. The pigmentation is well advanced in adolescence. The data at what age the maximal pigmentation is reached are controversial, as are the data on the cell loss in the NM-containing neuronal populations by normal aging. Thus, the participation ofNM in the pathogenesis of Parkinson`s disease remains enigmatic.Biomedical Reviews 2002; 13: 39-47