Dissociated multi-unit activity and local field potentials: a theory inspired analysis of a motor decision task.

Local field potentials (LFP) and multi-unit activity (MUA) recorded in vivo are known to convey different information about the underlying neural activity. Here we extend and support the idea that single-electrode LFP-MUA task-related modulations can shed light on the involved large-scale, multi-modular neural dynamics. We first illustrate a theoretical scheme and associated simulation evidence, proposing that in a multi-modular neural architecture local and distributed dynamic properties can be extracted from the local spiking activity of one pool of neurons in the network. From this new perspective, the spectral features of the field potentials reflect the time structure of the ongoing fluctuations of the probed local neuronal pool on a wide frequency range. We then report results obtained recording from the dorsal premotor (PMd) cortex of monkeys performing a countermanding task, in which a reaching movement is performed, unless a visual stop signal is presented. We find that the LFP and MUA spectral components on a wide frequency band (3-2000 Hz) are very differently modulated in time for successful reaching, successful and wrong stop trials, suggesting an interplay of local and distributed components of the underlying neural activity in different periods of the trials and for different behavioural outcomes. Besides, the MUA spectral power is shown to possess a time-dependent structure, which we suggest could help in understanding the successive involvement of different local neuronal populations. Finally, we compare signals recorded from PMd and dorso-lateral prefrontal (PFCd) cortex in the same experiment, and speculate that the comparative time-dependent spectral analysis of LFP and MUA can help reveal patterns of functional connectivity in the brain

Population dynamics of interacting spiking neurons

A dynamical equation is derived for the spike emission rate nu(t) of a homogeneous network of integrate-and-fire (IF) neurons in a mean-field theoretical framework, where the activity of the single cell depends both on the mean afferent current (the "field") and on its fluctuations. Finite-size effects are taken into account, by a stochastic extension of the dynamical equation for the nu; their effect on the collective activity is studied in detail. Conditions for the local stability of the collective activity are shown to be naturally and simply expressed in terms of (the slope of) the single neuron, static, current-to-rate transfer function. In the framework of the local analysis, we studied the spectral properties of the time-dependent collective activity of the finite network in an asynchronous state; finite-size fluctuations act as an ongoing self-stimulation, which probes the spectral structure of the system on a wide frequency range. The power spectrum of nu exhibits modes ranging from very high frequency (depending on spike transmission delays), which are responsible for instability, to oscillations at a few Hz, direct expression of the diffusion process describing the population dynamics. The latter "diffusion" slow modes do not contribute to the stability conditions. Their characteristic times govern the transient response of the network; these reaction times also exhibit a simple dependence on the slope of the neuron transfer function. We speculate on the possible relevance of our results for the change in the characteristic response time of a neural population during the learning process which shapes the synaptic couplings, thereby affecting the slope of the transfer function. There is remarkable agreement of the theoretical predictions with simulations of a network of IF neurons with a constant leakage term for the membrane potential

Learning selective top-down control enhances performance in a visual categorization task.

We model the putative neuronal and synaptic mechanisms involved in learning a visual categorization task, taking inspiration from single-cell recordings in inferior temporal cortex (ITC). Our working hypothesis is that learning the categorization task involves both bottom-up, ITC to prefrontal cortex (PFC), and top-down (PFC to ITC) synaptic plasticity and that the latter enhances the selectivity of the ITC neurons encoding the task-relevant features of the stimuli, thereby improving the signal-to-noise ratio. We test this hypothesis by modeling both areas and their connections with spiking neurons and plastic synapses, ITC acting as a feature-selective layer and PFC as a category coding layer. This minimal model gives interesting clues as to properties and function of the selective feedback signal from PFC to ITC that help solving a categorization task. In particular, we show that, when the stimuli are very noisy because of a large number of nonrelevant features, the feedback structure helps getting better categorization performance and decreasing the reaction time. It also affects the speed and stability of the learning process and sharpens tuning curves of ITC neurons. Furthermore, the model predicts a modulation of neural activities during error trials, by which the differential selectivity of ITC neurons to task-relevant and task-irrelevant features diminishes or is even reversed, and modulations in the time course of neural activities that appear when, after learning, corrupted versions of the stimuli are input to the network

FROM THE ELABORATION PROCESS OF POINT CLOUD TO INFORMATION SYSTEMS BOTH FOR PLANNING AND DESIGN MANAGEMENT OF CULTURAL HERITAGE

Abstract. Nowadays we are able to produce geometric models of historical building at different scale of detail using photos and measurements. More and more we are facing with lack of preservation actions and maintenance activities, bad foreseen policies, unexpected natural events, that are forcing professionals and researchers to operate without usual data. In these cases, we need consistent repository to collect and distribute data to produce information. Furthermore, we need to "give intelligence" to these repositories in order to query them with respect geometrical instances, topological issues, historical features.We dispose of tons of xyz points: how can we pass from the point cloud to a building information model, then to a geographic information system, not necessarily in this order? A simple Scan-to-BIM-to-GIS and Scan-to-GIS-to-BIM process were tested in order to consequently evaluate, with purposes of preservation and of enhancing of resilience, some practices that could became the best, also in terms of time and cost saving.The work we propose is a part of an ongoing research focused on the application of H-BIM approach for the management of historical building heritage, focused on a district management (H-DIM, at an urban level). In particular, with regard to the resilience theme, both the acquisition phase and the archive research process are of great importance for protecting our undefended building heritage.Regarding the case study of the paper, UNESCO sites represent important areas for collective interests of humanity. This contribution proposes a possible solution applying a digital cultural heritage to the historical part of the Municipality of Serralunga d'Alba belonging to the UNESCO site called Vineyard Landscape of Langhe-Roero and Monferrato.</p

Scaling of a large-scale simulation of synchronous slow-wave and asynchronous awake-like activity of a cortical model with long-range interconnections

Cortical synapse organization supports a range of dynamic states on multiple spatial and temporal scales, from synchronous slow wave activity (SWA), characteristic of deep sleep or anesthesia, to fluctuating, asynchronous activity during wakefulness (AW). Such dynamic diversity poses a challenge for producing efficient large-scale simulations that embody realistic metaphors of short- and long-range synaptic connectivity. In fact, during SWA and AW different spatial extents of the cortical tissue are active in a given timespan and at different firing rates, which implies a wide variety of loads of local computation and communication. A balanced evaluation of simulation performance and robustness should therefore include tests of a variety of cortical dynamic states. Here, we demonstrate performance scaling of our proprietary Distributed and Plastic Spiking Neural Networks (DPSNN) simulation engine in both SWA and AW for bidimensional grids of neural populations, which reflects the modular organization of the cortex. We explored networks up to 192x192 modules, each composed of 1250 integrate-and-fire neurons with spike-frequency adaptation, and exponentially decaying inter-modular synaptic connectivity with varying spatial decay constant. For the largest networks the total number of synapses was over 70 billion. The execution platform included up to 64 dual-socket nodes, each socket mounting 8 Intel Xeon Haswell processor cores @ 2.40GHz clock rates. Network initialization time, memory usage, and execution time showed good scaling performances from 1 to 1024 processes, implemented using the standard Message Passing Interface (MPI) protocol. We achieved simulation speeds of between 2.3x10^9 and 4.1x10^9 synaptic events per second for both cortical states in the explored range of inter-modular interconnections.Comment: 22 pages, 9 figures, 4 table

Non\u2011syndromic isolated dominant optic atrophy caused by the p.R468C mutation in the AFG3 like matrix AAA peptidase subunit 2 gene

Autosomal dominant optic atrophy (DOA) is the most frequent form of hereditary optic atrophy, a disease presenting with considerable inter- and intra-familial clinical variability. Although a number of mutations in different genes are now known to cause DOA, many cases remain undiagnosed. In an attempt to identify the underlying genetic defect, whole exome sequencing was performed in a 19-year-old male that had been affected by isolated DOA since childhood. The exome sequencing revealed a pathogenic mutation (p.R468C, c.1402C>T) in the AFG3 like matrix AAA peptidase subunit 2 (AFG3L2) gene, a gene known to be associated with spinocerebellar ataxia. The patient did not show any signs other than DOA. Thus, the result demonstrates the possibility that mutations in the AFG3L2 gene may be a cause of isolated autosomal DOA

Design and Experimental Performance Characterization of a Three-Blade Horizontal-Axis Hydrokinetic Water Turbine in a Low-Velocity Channel

The present work describes the design process of a 3D-printed prototype of a three-blade horizontal-axis hydrokinetic water turbine (HAHWT). The employed blade profile is an EPPLER818, which was previously studied through the Q-Blade software according to the velocity range presumed (v < 1 m/s) in the experiments. The prototype performance was studied in a recirculating water channel at the Polytechnic Engineering School of Mieres (Oviedo University), with a gate of variable height at the channel end, which allows for performing different hydrodynamic scenarios upon varying the considered flow rate. The results show that the extracted power increases due to the equally increased blockage ratio, which represents the ratio between the turbine area and the channel area. However, an excessive increase in the blockage ratio corresponds to a power reduction effect due to the reduction in the effective area and the generation of a two-phase air-water condition

Mice with reduced expression of the telomere-associated protein Ft1 develop p53-sensitive progeroid traits

Human AKTIP and mouse Ft1 are orthologous ubiquitin E2 variant proteins involved in telomere maintenance and DNA replication. AKTIP also interacts with A- and B-type lamins. These features suggest that Ft1 may be implicated in aging regulatory pathways. Here, we show that cells derived from hypomorph Ft1 mutant (Ft1kof/kof ) mice exhibit telomeric defects and that Ft1kof/kof animals develop progeroid traits, including impaired growth, skeletal and skin defects, abnormal heart tissue, and sterility. We also demonstrate a genetic interaction between Ft1 and p53. The analysis of mice carrying mutations in both Ft1 and p53 (Ft1kof/kof ; p53ko/ko and Ft1kof/kof ; p53+/ko ) showed that reduction in p53 rescues the progeroid traits of Ft1 mutants, suggesting that they are at least in part caused by a p53-dependent DNA damage response. Conversely, Ft1 reduction alters lymphomagenesis in p53 mutant mice. These results identify Ft1 as a new player in the aging process and open the way to the analysis of its interactions with other progeria genes using the mouse model

Decreased subunit stability as a novel mechanism for potassium current impairment by a KCNQ2 C terminus mutation causing benign familial neonatal convulsions.

KCNQ2 and KCNQ3 K+ channel subunits underlie the muscarinic-regulated K+ current (I(KM)), a widespread regulator of neuronal excitability. Mutations in KCNQ2- or KCNQ3-encoding genes cause benign familiar neonatal convulsions (BFNCs), a rare autosomal-dominant idiopathic epilepsy of the newborn. In the present study, we have investigated, by means of electrophysiological, biochemical, and immunocytochemical techniques in transiently transfected cells, the consequences prompted by a BFNC-causing 1-bp deletion (2043deltaT) in the KCNQ2 gene; this frameshift mutation caused the substitution of the last 163 amino acids of the KCNQ2 C terminus and the extension of the subunit by additional 56 residues. The 2043deltaT mutation abolished voltage-gated K+ currents produced upon homomeric expression of KCNQ2 subunits, dramatically reduced the steady-state cellular levels of KCNQ2 subunits, and prevented their delivery to the plasma membrane. Metabolic labeling experiments revealed that mutant KCNQ2 subunits underwent faster degradation; 10-h treatment with the proteasomal inhibitor MG132 (20 microm) at least partially reversed such enhanced degradation. Co-expression with KCNQ3 subunits reduced the degradation rate of mutant KCNQ2 subunits and led to their expression on the plasma membrane. Finally, co-expression of KCNQ2 2043deltaT together with KCNQ3 subunits generated functional voltage-gated K+ currents having pharmacological and biophysical properties of heteromeric channels. Collectively, the present results suggest that mutation-induced reduced stability of KCNQ2 subunits may cause epilepsy in neonates