The Ising Model for Neural Data: Model Quality and Approximate Methods for Extracting Functional Connectivity

We study pairwise Ising models for describing the statistics of multi-neuron spike trains, using data from a simulated cortical network. We explore efficient ways of finding the optimal couplings in these models and examine their statistical properties. To do this, we extract the optimal couplings for subsets of size up to 200 neurons, essentially exactly, using Boltzmann learning. We then study the quality of several approximate methods for finding the couplings by comparing their results with those found from Boltzmann learning. Two of these methods- inversion of the TAP equations and an approximation proposed by Sessak and Monasson- are remarkably accurate. Using these approximations for larger subsets of neurons, we find that extracting couplings using data from a subset smaller than the full network tends systematically to overestimate their magnitude. This effect is described qualitatively by infinite-range spin glass theory for the normal phase. We also show that a globally-correlated input to the neurons in the network lead to a small increase in the average coupling. However, the pair-to-pair variation of the couplings is much larger than this and reflects intrinsic properties of the network. Finally, we study the quality of these models by comparing their entropies with that of the data. We find that they perform well for small subsets of the neurons in the network, but the fit quality starts to deteriorate as the subset size grows, signalling the need to include higher order correlations to describe the statistics of large networks.Comment: 12 pages, 10 figure

Supervision of Music in the Elementary School

Thesis (M.A.)--Boston University N.B.: Page ii is a blank page. Page iv does not exist

Distribution of KRAS, DDR2, and TP53 gene mutations in lung cancer: An analysis of Iranian patients

Purpose Lung cancer is the deadliest known cancer in the world, with the highest number of mutations in proto-oncogenes and tumor suppressor genes. Therefore, this study was conducted to determine the status of hotspot regions in DDR2 and KRAS genes for the first time, as well as in TP53 gene, in lung cancer patients within the Iranian population. Experimental design The mutations in exon 2 of KRAS, exon 18 of DDR2, and exons 5�6 of TP53 genes were screened in lung cancer samples, including non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) using PCR and sequencing techniques. Results Analysis of the KRAS gene showed only a G12C variation in one large cell carcinoma (LCC) patient, whereas variants were not found in adenocarcinoma (ADC) and squamous cell carcinoma (SCC) cases. The Q808H variation in the DDR2 gene was detected in one SCC sample, while no variant was seen in the ADC and LCC subtypes. Variations in the TP53 gene were seen in all NSCLC subtypes, including six ADC (13.63), seven SCC (15.9) and two LCC (4.54). Forty-eight variants were found in the TP53 gene. Of these, 15 variants were found in coding regions V147A, V157F, Q167Q, D186G, H193R, T211T, F212L and P222P, 33 variants in intronic regions rs1625895 (HGVS: c.672+62A>G), rs766856111 (HGVS: c.672+6G>A) and two new variants (c.560-12A>G and c.672+86T>C). Conclusions In conclusion, KRAS, DDR2, and TP53 variants were detected in 2, 2.17 and 79.54 of all cases, respectively. The frequency of DDR2 mutation is nearly close to other studies, while KRAS and TP53 mutation frequencies are lower and higher than other populations, respectively. Three new putative pathogenic variants, for the first time, have been detected © 2018 Fathi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Beyond inverse Ising model: structure of the analytical solution for a class of inverse problems

I consider the problem of deriving couplings of a statistical model from measured correlations, a task which generalizes the well-known inverse Ising problem. After reminding that such problem can be mapped on the one of expressing the entropy of a system as a function of its corresponding observables, I show the conditions under which this can be done without resorting to iterative algorithms. I find that inverse problems are local (the inverse Fisher information is sparse) whenever the corresponding models have a factorized form, and the entropy can be split in a sum of small cluster contributions. I illustrate these ideas through two examples (the Ising model on a tree and the one-dimensional periodic chain with arbitrary order interaction) and support the results with numerical simulations. The extension of these methods to more general scenarios is finally discussed.Comment: 15 pages, 6 figure

An associative network with spatially organized connectivity

We investigate the properties of an autoassociative network of threshold-linear units whose synaptic connectivity is spatially structured and asymmetric. Since the methods of equilibrium statistical mechanics cannot be applied to such a network due to the lack of a Hamiltonian, we approach the problem through a signal-to-noise analysis, that we adapt to spatially organized networks. The conditions are analyzed for the appearance of stable, spatially non-uniform profiles of activity with large overlaps with one of the stored patterns. It is also shown, with simulations and analytic results, that the storage capacity does not decrease much when the connectivity of the network becomes short range. In addition, the method used here enables us to calculate exactly the storage capacity of a randomly connected network with arbitrary degree of dilution.Comment: 27 pages, 6 figures; Accepted for publication in JSTA

The storage capacity of Potts models for semantic memory retrieval

We introduce and analyze a minimal network model of semantic memory in the human brain. The model is a global associative memory structured as a collection of N local modules, each coding a feature, which can take S possible values, with a global sparseness a (the average fraction of features describing a concept). We show that, under optimal conditions, the number c of modules connected on average to a module can range widely between very sparse connectivity (c/N -> 0) and full connectivity (c = N), maintaining a global network storage capacity (the maximum number p of stored and retrievable concepts) that scales like c*S^2/a, with logarithmic corrections consistent with the constraint that each synapse may store up to a fraction of a bit.Comment: Accepted for publication in J-STAT, July 200

Continues renal replacement therapy (CRRT) with disposable hemoperfusion cartridge: A promising option for severe COVID-19

Cytokine release syndrome is prevalent in severe cases of COVID-19. In this syndrome, an uncontrolled response of immune system occurs. Extracorporeal blood purification has been proven to effectively remove the released inflammatory cytokines. Here, we reported a successful case to represent our experience of extracorporeal blood purification in a patient with severe COVID-19. © 2020 The Author

Region graph partition function expansion and approximate free energy landscapes: Theory and some numerical results

Graphical models for finite-dimensional spin glasses and real-world combinatorial optimization and satisfaction problems usually have an abundant number of short loops. The cluster variation method and its extension, the region graph method, are theoretical approaches for treating the complicated short-loop-induced local correlations. For graphical models represented by non-redundant or redundant region graphs, approximate free energy landscapes are constructed in this paper through the mathematical framework of region graph partition function expansion. Several free energy functionals are obtained, each of which use a set of probability distribution functions or functionals as order parameters. These probability distribution function/functionals are required to satisfy the region graph belief-propagation equation or the region graph survey-propagation equation to ensure vanishing correction contributions of region subgraphs with dangling edges. As a simple application of the general theory, we perform region graph belief-propagation simulations on the square-lattice ferromagnetic Ising model and the Edwards-Anderson model. Considerable improvements over the conventional Bethe-Peierls approximation are achieved. Collective domains of different sizes in the disordered and frustrated square lattice are identified by the message-passing procedure. Such collective domains and the frustrations among them are responsible for the low-temperature glass-like dynamical behaviors of the system.Comment: 30 pages, 11 figures. More discussion on redundant region graphs. To be published by Journal of Statistical Physic

Public–Private Partnership in Tunisia: Enfidha Airport Assessment of an Infrastructure Achievement

One of the largest recent private-sector investments and the first airport private-sector concession in the Maghreb is Enfidha Airport, a key factor in the success of the Tunisian Government’s public– private partnership (PPP) strategy. However, since Tunisia’s Jasmine Revolution, political and social turmoil is sweeping the country and worsening the economic indicators. This article aims to assess this PPP infrastructure, allowing us to determine if it is profitable in the long term and contributes therefore to the economic growth. The case study reveals the key role of the economic, social, and political environment in Tunisia, the dawn of the Arab Spring

Survey of diversity, distribution, abundance and biomass of macrobenthic fauna in the southern Caspian Sea

Sediments samples were collected using Veen Grab Sampler (0.1 square meter) at 8 transects namely Astara, Anzali, Sefidroud, Tonekabon, Noshahr, Babolsar, Amirabad, Torkman in the southern of Caspian Sea. Five stations were selected at 5, 10, 20, 50 and 100 meter depths in each transect. Sediments were sampled triplicate at each station. Samples also were collected during four seasons (spring (May), summer (July), fall (November) and winter (January)) in 2009. Results of this study showed that species composition of Macrobenthos consisted of 32 species which belonged to 7 families of Polychaeta, Crustacea and Bivalvia at studied area. In addition, Oligochaeta identified in “Class”, Chironomidae considered in Insecta categories “Family” and Streblospio spp. (Polychaeta) was recognized in “Genus”. Gammaridae and Pseudocumidae of Crustacea with 12 and 10 species had the highest species diversity compared to other groups, respectively. Polychaeta was consisted 75.5 percent of total abundance of macrobenthos which the major abundance (equal 62.4% of total abundance) were belong to Streblospio spp. from Spionidae family, while its biomass was equals 5.11% of total macrobenthos. In contrast, Cerastoderma lamarcki species from Bivalvia Class with only 1.7% of total abundance of macrobenthos allocated 69 percent of total biomass. In the southern of Caspian Sea, average total abundance was significantly less at 4 western transects (Astara, Anzali, Sefidroud, Tonekabon) compared to 4 eastern transects (Noshahr, Babolsar, Amirabad, Torkman) (p<0.05). The highest average abundance of macrobenthos (10655±1246SE ind/m^2) was observed at transect of Torkman, and lowest value (4032 ± 686SE ind/m^2) was recorded at transect of Sefidroud (p< 0.05). Generally, minimum species diversity were obtained at 20 m depth in all transects and the maximum value was observed at 5 m depth in most of transects (p<0.05). In contrary, maximum average abundance of Macrobenthoses was at 20 m depth in transects of Anzali, Sefidroud, Tonekabon, Nowshahr and Amirabad compared to other depths. Macrobenthoses abundance average in 5 m depth (except Astara and Torkman) was less than other depths in 6 transect (p < 0.05). Total average abundance and biomass of macrobenthos was 5976±583SE ind/m^2 and 43.675 ± 11.402SE gr/ m^2, respectively. Maximum and minimum of abundance of macrobenthos were observed in summer (7714±778 ind/m^2) and winter (4071 ± 340 ind/m^2), respectively. Maximum and minimum of biomass of macrobenthos were obtained in fall (50.271±13.258SE gr/ m^2) and in summer (35.123 ± 8.903SE gr/ m^2), respectively (p< 0.05). Percent of total organic matter (TOM) were low in 5 and 10 m depths and increased toward offshore depths. TOM percent was 2.06±0.11SE at 10 m depth and increased to 4.62 ±0.17SE in 100 m depth. Percent of silt and clay (grains size less than 63 micron) had positive significantly correlation with percent of TOM (p<0.01).While they had negative significantly correlation with percent of sand (grains size between 63 and 1000 micron) (p<0.01). Percent of silt and clay like organic matter, had ascending trend toward to depth increased and varied from 44.4 ± 4.06SE percent in 5 m depth to 96.5 ± 0.59SE percent in 100 m depth. In contrast, percent of sand decreased toward depth and varied from 54.5 ± 4.13SE percent in 5 m depth to 2.8 ± 0.53SE percent in 100 m depth. Result of current study showed that total abundance of macrobenthoses had positive significantly correlation with TOM percent (p<0.01) and silt/clay percent (p<0.05). Abundance of Oligochaeta had positive significantly correlation (p< 0.01) with TOM and silt/clay percent. Two groups of Polychaeta, Gammaridae and Cerastoderma lamarcki had negative significantly correlation with TOM and silt/clay percent (p< 0.01), and every four aforementioned groups had positive significantly correlation with sand percent (p< 0.01). Overall, different correlation between abundance of various macrobenthos groups and TOM percent and type of grain size of sediment could be related to fluctuation of abundance of various macrobenthos groups at difference transects and depths. On the other hand, in study area were occurred simultaneously some phenomena such as increased abundance of Oligochaeta and Polychaeta, dominance of Streblospio Genuse (Polychaeta group), and decreases abundance of Bivalvia and appearance of Menemiopsis leidyi which need to study more and monitoring of this area