A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory

Star-galaxy separation in the AKARI NEP Deep Field

Context: It is crucial to develop a method for classifying objects detected in deep surveys at infrared wavelengths. We specifically need a method to separate galaxies from stars using only the infrared information to study the properties of galaxies, e.g., to estimate the angular correlation function, without introducing any additional bias. Aims. We aim to separate stars and galaxies in the data from the AKARI North Ecliptic Pole (NEP) Deep survey collected in nine AKARI / IRC bands from 2 to 24 {\mu}m that cover the near- and mid-infrared wavelengths (hereafter NIR and MIR). We plan to estimate the correlation function for NIR and MIR galaxies from a sample selected according to our criteria in future research. Methods: We used support vector machines (SVM) to study the distribution of stars and galaxies in the AKARIs multicolor space. We defined the training samples of these objects by calculating their infrared stellarity parameter (sgc). We created the most efficient classifier and then tested it on the whole sample. We confirmed the developed separation with auxiliary optical data obtained by the Subaru telescope and by creating Euclidean normalized number count plots. Results: We obtain a 90% accuracy in pinpointing galaxies and 98% accuracy for stars in infrared multicolor space with the infrared SVM classifier. The source counts and comparison with the optical data (with a consistency of 65% for selecting stars and 96% for galaxies) confirm that our star/galaxy separation methods are reliable. Conclusions: The infrared classifier derived with the SVM method based on infrared sgc- selected training samples proves to be very efficient and accurate in selecting stars and galaxies in deep surveys at infrared wavelengths carried out without any previous target object selection.Comment: 8 pages, 8 figure

Diversity amongst human cortical pyramidal neurons revealed via their sag currents and frequency preferences

In the human neocortex coherent interlaminar theta oscillations are driven by deep cortical layers, suggesting neurons in these layers exhibit distinct electrophysiological properties. To characterize this potential distinctiveness, we use in vitro whole-cell recordings from cortical layers 2 and 3 (L2&3), layer 3c (L3c) and layer 5 (L5) of the human cortex. Across all layers we observe notable heterogeneity, indicating human cortical pyramidal neurons are an electrophysiologically diverse population. L5 pyramidal cells are the most excitable of these neurons and exhibit the most prominent sag current (abolished by blockade of the hyperpolarization activated cation current, Ih). While subthreshold resonance is more common in L3c and L5, we rarely observe this resonance at frequencies greater than 2 Hz. However, the frequency dependent gain of L5 neurons reveals they are most adept at tracking both delta and theta frequency inputs, a unique feature that may indirectly be important for the generation of cortical theta oscillations

Addressing the Language Binding Problem With Dynamic Functional Connectivity During Meaningful Spoken Language Comprehension

During speech, how does the brain integrate information processed on different timescales and in separate brain areas so we can understand what is said? This is the language binding problem. Dynamic functional connectivity (brief periods of synchronization in the phase of EEG oscillations) may provide some answers. Here we investigate time and frequency characteristics of oscillatory power and phase synchrony (dynamic functional connectivity) during speech comprehension. Twenty adults listened to meaningful English sentences and non-sensical “Jabberwocky” sentences in which pseudo-words replaced all content words, while EEG was recorded. Results showed greater oscillatory power and global connectivity strength (mean phase lag index) in the gamma frequency range (30–80 Hz) for English compared to Jabberwocky. Increased power and connectivity relative to baseline was also seen in the theta frequency range (4–7 Hz), but was similar for English and Jabberwocky. High-frequency gamma oscillations may reflect a mechanism by which the brain transfers and integrates linguistic information so we can extract meaning and understand what is said. Slower frequency theta oscillations may support domain-general processing of the rhythmic features of speech. Our findings suggest that constructing a meaningful representation of speech involves dynamic interactions among distributed brain regions that communicate through frequency-specific functional networks

Supernova dust for the extinction law in a young infrared galaxy at z = 1

We apply the supernova(SN) extinction curves to reproduce the observed properties of SST J1604+4304 which is a young infrared (IR) galaxy at z = 1. The SN extinction curves used in this work were obtained from models of unmixed ejecta of type II supernovae(SNe II) for the Salpeter initial mass function (IMF) with a mass range from 8 to 30 M_sun or 8 to 40 M_sun. The effect of dust distributions on the attenuation of starlight is investigated by performing the chi-square fitting method against various dust distributions. These are the commonly used uniform dust screen, the clumpy dust screen, and the internal dust geometry. We add to these geometries three scattering properties, namely, no-scattering, isotropic scattering, and forward-only scattering. Judging from the chi-square values, we find that the uniform screen models with any scattering property provide good approximations to the real dust geometry. Internal dust is inefficient to attenuate starlight and thus cannot be the dominant source of the extinction. We show that the SN extinction curves reproduce the data of SST J1604+4304 comparable to or better than the Calzetti extinction curve. The Milky Way extinction curve is not in satisfactory agreement with the data unless several dusty clumps are in the line of sight. This trend may be explained by the abundance of SN-origin dust in these galaxies; SN dust is the most abundant in the young IR galaxy at z = 1, abundant in local starbursts, and less abundant in the Galaxy. If dust in SST J1604+4304 is dominated by SN dust, the dust production rate is about 0.1 M_sun per SN.Comment: 12 pages, 8 figures, 1 tabl

Herschel-ATLAS/GAMA: A difference between star formation rates in strong-line and weak-line radio galaxies

We have constructed a sample of radio-loud objects with optical spectroscopy from the Galaxy and Mass Assembly (GAMA) project over the Herschel Astrophysical Terahertz Large Area Survey (Herschel-ATLAS) Phase 1 fields. Classifying the radio sources in terms of their optical spectra, we find that strong-emission-line sources ('high-excitation radio galaxies') have, on average, a factor of ~4 higher 250-μm Herschel luminosity than weak-line ('lowexcitation') radio galaxies and are also more luminous than magnitude-matched radio-quiet galaxies at the same redshift. Using all five H-ATLAS bands, we show that this difference in luminosity between the emission-line classes arises mostly from a difference in the average dust temperature; strong-emission-line sources tend to have comparable dust masses to, but higher dust temperatures than, radio galaxies with weak emission lines. We interpret this as showing that radio galaxies with strong nuclear emission lines are much more likely to be associated with star formation in their host galaxy, although there is certainly not a one-to-one relationship between star formation and strong-line active galactic nuclei (AGN) activity. The strong-line sources are estimated to have star formation rates at least a factor of 3-4 higher than those in the weak-line objects. Our conclusion is consistent with earlier work, generally carried out using much smaller samples, and reinforces the general picture of high-excitation radio galaxies as being located in lower-mass, less evolved host galaxies than their low-excitation counterparts.Peer reviewe

Implantable photonic neural probes for light-sheet fluorescence brain imaging

Significance: Light-sheet fluorescence microscopy (LSFM) is a powerful technique for highspeed volumetric functional imaging. However, in typical light-sheet microscopes, the illumination and collection optics impose significant constraints upon the imaging of non-transparent brain tissues. We demonstrate that these constraints can be surmounted using a new class of implantable photonic neural probes.Aim: Mass manufacturable, silicon-based light-sheet photonic neural probes can generate planar patterned illumination at arbitrary depths in brain tissues without any additional micro-optic components.Approach: We develop implantable photonic neural probes that generate light sheets in tissue. The probes were fabricated in a photonics foundry on 200-mm-diameter silicon wafers. The light sheets were characterized in fluorescein and in free space. The probe-enabled imaging approach was tested in fixed, in vitro, and in vivo mouse brain tissues. Imaging tests were also performed using fluorescent beads suspended in agarose.Results: The probes had 5 to 10 addressable sheets and average sheet thicknesses Conclusions: The neural probes can lead to new variants of LSFM for deep brain imaging and experiments in freely moving animals

AzTEC millimeter survey of the COSMOS field - III. Source catalog over 0.72 sq. deg. and plausible boosting by large-scale structure

We present a 0.72 sq. deg. contiguous 1.1mm survey in the central area of the COSMOS field carried out to a 1sigma ~ 1.26 mJy/beam depth with the AzTEC camera mounted on the 10m Atacama Submillimeter Telescope Experiment (ASTE). We have uncovered 189 candidate sources at a signal-to-noise ratio S/N >= 3.5, out of which 129, with S/N >= 4, can be considered to have little chance of being spurious (< 2 per cent). We present the number counts derived with this survey, which show a significant excess of sources when compared to the number counts derived from the ~0.5 sq. deg. area sampled at similar depths in the Scuba HAlf Degree Extragalactic Survey (SHADES, Austermann et al. 2010). They are, however, consistent with those derived from fields that were considered too small to characterize the overall blank-field population. We identify differences to be more significant in the S > 5 mJy regime, and demonstrate that these excesses in number counts are related to the areas where galaxies at redshifts z < 1.1 are more densely clustered. The positions of optical-IR galaxies in the redshift interval 0.6 < z < 0.75 are the ones that show the strongest correlation with the positions of the 1.1mm bright population (S > 5 mJy), a result which does not depend exclusively on the presence of rich clusters within the survey sampled area. The most likely explanation for the observed excess in number counts at 1.1mm is galaxy-galaxy and galaxy-group lensing at moderate amplification levels, that increases in amplitude as one samples larger and larger flux densities. This effect should also be detectable in other high redshift populations.Comment: 21 pages, 17 figures, accepted for publication in MNRA

AzTEC Millimetre Survey of the COSMOS Field - II. Source Count Overdensity and Correlations with Large-Scale Structure

We report an over-density of bright sub-millimetre galaxies (SMGs) in the 0.15 sq. deg. AzTEC/COSMOS survey and a spatial correlation between the SMGs and the optical-IR galaxy density at z <~ 1.1. This portion of the COSMOS field shows a ~ 3-sigma over-density of robust SMG detections when compared to a background, or "blankfield", population model that is consistent with SMG surveys of fields with no extragalactic bias. The SMG over-density is most significant in the number of very bright detections (14 sources with measured fluxes S(1.1mm) > 6 mJy), which is entirely incompatible with sample variance within our adopted blank-field number densities and infers an over-density significance of >> 4. We find that the over-density and spatial correlation to optical-IR galaxy density are most consistent with lensing of a background SMG population by foreground mass structures along the line of sight, rather than physical association of the SMGs with the z <~ 1.1 galaxies/clusters. The SMG positions are only weakly correlated with weak-lensing maps, suggesting that the dominant sources of correlation are individual galaxies and the more tenuous structures in the region and not the massive and compact clusters. These results highlight the important roles cosmic variance and large-scale structure can play in the study of SMGs.Comment: 12 pages, 11 figures, 2 tables, accepted for publication in MNRA

The origin of dust in galaxies revisited: the mechanism determining dust content

The origin of cosmic dust is a fundamental issue in planetary science. This paper revisits the origin of dust in galaxies, in particular, in the Milky Way, by using a chemical evolution model of a galaxy composed of stars, interstellar medium, metals (elements heavier than helium), and dust. We start from a review of time-evolutionary equations of the four components, and then, we present simple recipes for the stellar remnant mass and yields of metal and dust based on models of stellar nucleosynthesis and dust formation. After calibrating some model parameters with the data from the solar neighborhood, we have confirmed a shortage of the stellar dust production rate relative to the dust destruction rate by supernovae if the destruction efficiency suggested by theoretical works is correct. If the dust mass growth by material accretion in molecular clouds is active, the observed dust amount in the solar neighborhood is reproduced. We present a clear analytic explanation of the mechanism for determining dust content in galaxies after the activation of accretion growth: a balance between accretion growth and supernova destruction. Thus, the dust content is independent of the uncertainty of the stellar dust yield after the growth activation. The timing of the activation is determined by a critical metal mass fraction which depends on the growth and destruction efficiencies. The solar system formation seems to have occurred well after the activation and plenty of dust would have existed in the proto-solar nebula.Comment: 12 pages, 11 figure