Decoding neuronal ensembles in the human hippocampus

BACKGROUND: The hippocampus underpins our ability to navigate, to form and recollect memories, and to imagine future experiences. How activity across millions of hippocampal neurons supports these functions is a fundamental question in neuroscience, wherein the size, sparseness, and organization of the hippocampal neural code are debated. RESULTS: Here, by using multivariate pattern classification and high spatial resolution functional MRI, we decoded activity across the population of neurons in the human medial temporal lobe while participants navigated in a virtual reality environment. Remarkably, we could accurately predict the position of an individual within this environment solely from the pattern of activity in his hippocampus even when visual input and task were held constant. Moreover, we observed a dissociation between responses in the hippocampus and parahippocampal gyrus, suggesting that they play differing roles in navigation. CONCLUSIONS: These results show that highly abstracted representations of space are expressed in the human hippocampus. Furthermore, our findings have implications for understanding the hippocampal population code and suggest that, contrary to current consensus, neuronal ensembles representing place memories must be large and have an anisotropic structure

Multilevel modelling of the incidence of visceral leishmaniasis in Teresina, Brazil

Epidemics of visceral leishmaniasis (VL) in major Brazilian cities are new phenomena since 1980. As determinants of transmission in urban settings probably operate at different geographic scales, and information is not available for each scale, a multilevel approach was used to examine the effect of canine infection and environmental and socio-economic factors on the spatial variability of incidence rates of VL in the city of Teresina. Details on an outbreak of greater than 1200 cases of VL in Teresina during 1993-1996 were available at two hierarchical levels: census tracts (socio-economic characteristics, incidence rates of human VL) and districts, which encompass census tracts (prevalence of canine infection). Remotely sensed data obtained by satellite generated environmental information at both levels. Data from census tracts and districts were analysed simultaneously by multilevel modelling. Poor socio-economic conditions and increased vegetation were associated with a high incidence of human VL. Increasing prevalence of canine infection also predicted a high incidence of human VL, as did high prevalence of canine infection before and during the epidemic. Poor socio-economic conditions had an amplifying effect on the association between canine infection and the incidence of human VL. Focusing interventions on areas with characteristics identified by multilevel analysis could be a cost-effective strategy for controlling VL. Because risk factors for infectious diseases operate simultaneously at several levels and ecological data usually are available at different geographical scales, multilevel modelling is a valuable tool for epidemiological investigation of disease transmission

Using late-time optical and near-infrared spectra to constrain Type Ia supernova explosion properties

The late-time spectra of Type Ia supernovae (SNe Ia) are powerful probes of the underlying physics of their explosions. We investigate the late-time optical and near-infrared spectra of seven SNe Ia obtained at the VLT with XShooter at $>$200 d after explosion. At these epochs, the inner Fe-rich ejecta can be studied. We use a line-fitting analysis to determine the relative line fluxes, velocity shifts, and line widths of prominent features contributing to the spectra ([Fe II], [Ni II], and [Co III]). By focussing on [Fe II] and [Ni II] emission lines in the ~7000-7500 \AA\ region of the spectrum, we find that the ratio of stable [Ni II] to mainly radioactively-produced [Fe II] for most SNe Ia in the sample is consistent with Chandrasekhar-mass delayed-detonation explosion models, as well as sub-Chandrasekhar mass explosions that have metallicity values above solar. The mean measured Ni/Fe abundance of our sample is consistent with the solar value. The more highly ionised [Co III] emission lines are found to be more centrally located in the ejecta and have broader lines than the [Fe II] and [Ni II] features. Our analysis also strengthens previous results that SNe Ia with higher Si II velocities at maximum light preferentially display blueshifted [Fe II] 7155 \AA\ lines at late times. Our combined results lead us to speculate that the majority of normal SN Ia explosions produce ejecta distributions that deviate significantly from spherical symmetry.Comment: 17 pages, 12 figure, accepted for publication in MNRA

Terpyridyl complexes as antimalarial agents

A number of transition metals and their terpyridyl complexes have been evaluated for antimalarial activity on the strain 3D7. The metals, ligands and complexes were each in turn investigated for their efficacy. All activities were in the sub-micromolar range (0.1-1 µM). Their modes of action were compared with that of chloroquine to discover whether or not they were capable of inhibiting haemozoin formation. The data indicate that efficacy could be a result of several mechanisms and that speciation of the metal complex and the manner in which the agents are added to the parasitic broth have a profound effect on the activity of the agents. We believe that our study offers a template by which other researchers should approach their experiments using transition metal complex agents

OGLE16aaa - a Signature of a Hungry Super Massive Black Hole

We present the discovery and first three months of follow-up observations of a currently on-going unusual transient detected by the OGLE-IV survey, located in the centre of a galaxy at redshift z=0.1655. The long rise to absolute magnitude of -20.5 mag, slow decline, very broad He and H spectral features make OGLE16aaa similar to other optical/UV Tidal Disruption Events (TDEs). Weak narrow emission lines in the spectrum and archival photometric observations suggest the host galaxy is a weak-line Active Galactic Nucleus (AGN), which has been accreting at higher rate in the past. OGLE16aaa, along with SDSS J0748, seems to form a sub-class of TDEs by weakly or recently active super-massive black holes (SMBHs). This class might bridge the TDEs by quiescent SMBHs and flares observed as "changing-look QSOs", if we interpret the latter as TDEs. If this picture is true, the previously applied requirement for identifying a flare as a TDE that it had to come from an inactive nucleus, could be leading to observational bias in TDE selection, thus affecting TDE-rate estimations.Comment: Accepted in MNRAS Letter

Interacting supernovae and supernova impostors. SN 2007sv: the major eruption of a massive star in UGC 5979

We report the results of the photometric and spectroscopic monitoring campaign of the transient SN 2007sv. The observables are similar to those of type IIn supernovae, a well-known class of objects whose ejecta interact with pre-existing circum-stellar material. The spectra show a blue continuum at early phases and prominent Balmer lines in emission, however, the absolute magnitude at the discovery of SN 2007sv (M_R = - 14.25 +/- 0.38) indicate it to be most likely a supernova impostor. This classification is also supported by the lack of evidence in the spectra of very high velocity material as expected in supernova ejecta. In addition we find no unequivocal evidence of broad lines of alpha - and/or Fe-peak elements. The comparison with the absolute light curves of other interacting objects (including type IIn supernovae) highlights the overall similarity with the prototypical impostor SN 1997bs. This supports our claim that SN 2007sv was not a genuine supernova, and was instead a supernova impostor, most likely similar to the major eruption of a luminous blue variable.Comment: Accepted for publication in MNRAS. 15 pages, 11 figures, 5 table

Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security.

Requirements elicitation, analysis and modeling are critical activities for software success. However, software systems are increasingly complex, harder to develop due to an ever-growing number of requirements from numerous and heterogeneous stakeholders, concerning dozens of requirements types, from functional to qualitative, including adaptation, security and privacy, ethical, acceptance and more. In such settings, requirements engineers need support concerning such increasingly complex activities, and Requirements Engineering (RE) modeling tools have been developed for this. However, such tools, although effective, are complex, time-consuming and requiring steep learning curves. The consequent lack of acceptance and abandonment in using such tools, by engineers, paves the way to the application of RE techniques in a more error-prone, low-quality way, increasing the possibility to have failures in software systems delivered. In this paper, we identify main areas of lack of acceptance, affecting RE engineers, for such tools, and propose an approach for making modeling tools more effective in engaging the engineer in performing RE in a tool-based way, receiving adequate feedback and staying motivated to use modeling tools. This is accomplished by performing acceptance requirements analysis (through the Agon Framework) and using gamification to increase the engagement of engineers during the usage of RE modeling tools. Towards this end, we performed a case study, within the VisiOn European Project, for enhancing a tool for modeling privacy and security requirements. Our case study provides preliminary evidence that our approach supports in making RE modeling tools more engaging from the engineer perspective

Physical principles for scalable neural recording

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices