The shape of memory in temporal networks

Temporal networks are widely used models for describing the architecture of complex systems. Network memory -- that is the dependence of a temporal network's structure on its past -- has been shown to play a prominent role in diffusion, epidemics and other processes occurring over the network, and even to alter its community structure. Recent works have proposed to estimate the length of memory in a temporal network by using high-order Markov models. Here we show that network memory is inherently multidimensional and cannot be meaningfully reduced to a single scalar quantity. Accordingly, we introduce a mathematical framework for defining and efficiently estimating the microscopic shape of memory, which fully characterises how the activity of each link intertwines with the activities of all other links. We validate our methodology on a wide range of synthetic models of temporal networks with tuneable memory, and subsequently study the heterogeneous shapes of memory emerging in various real-world networks.Comment: 35 pages (5 main, 30 supplementary), 14 figures (3 main, 11 supplementary), 3 tables (all supplementary), uses tikz-network.sty and tikz_network.p

Triadic percolation induces dynamical topological patterns in higher-order networks

Triadic interactions are higher-order interactions that occur when a set of nodes affects the interaction between two other nodes. Examples of triadic interactions are present in the brain when glia modulate the synaptic signals among neuron pairs or when interneuron axon-axonic synapses enable presynaptic inhibition and facilitation, and in ecosystems when one or more species can affect the interaction among two other species. On random graphs, triadic percolation has been recently shown to turn percolation into a fully-fledged dynamical process in which the size of the giant component undergoes a route to chaos. However, in many real cases, triadic interactions are local and occur on spatially embedded networks. Here we show that triadic interactions in spatial networks induce a very complex spatio-temporal modulation of the giant component which gives rise to triadic percolation patterns with significantly different topology. We classify the observed patterns (stripes, octopus, and small clusters) with topological data analysis and we assess their information content (entropy and complexity). Moreover, we illustrate the multistability of the dynamics of the triadic percolation patterns and we provide a comprehensive phase diagram of the model. These results open new perspectives in percolation as they demonstrate that in presence of spatial triadic interactions, the giant component can acquire a time-varying topology. Hence, this work provides a theoretical framework that can be applied to model realistic scenarios in which the giant component is time-dependent as in neuroscience.Comment: 59 pages, 11 figure

Complex networks with tuneable dimensions as a universality playground

Universality is one of the key concepts in understanding critical phenomena. However, for interacting inhomogeneous systems described by complex networks a clear understanding of the relevant parameters for universality is still missing. Here we discuss the role of a fundamental network parameter, the spectral dimension, neglected in previous investigations. For this purpose, we construct a complex network model where the probability of a bond between two nodes is proportional to a power law of the nodes' distances. By explicit computation we prove that the spectral dimension for this model can be tuned continuously from 1 to infinity, and we discuss related network connectivity measures. We propose our model as a tool to probe universal behaviour on inhomogeneous structures and comment on the possibility that the universal behaviour of correlated models on such networks mimics the one of continuous field theories in fractional euclidean dimensions. We suggest that similar structures could be engineered in atomic, molecular and optical devices in order to tune universal properties to a desired value.Comment: 13 pages, 12 figures. Expanded discussion of the anomalous dimension effec

Expanding the Clinical and Molecular Heterogeneity of Nonsyndromic Inherited Retinal Dystrophies

A cohort of 172 patients diagnosed clinically with nonsyndromic retinal dystrophies, from 110 families underwent full ophthalmologic examination, including retinal imaging, electrophysiology, and optical coherence tomography, when feasible. Molecular analysis was performed using targeted next-generation sequencing (NGS). Variants were filtered and prioritized according to the minimum allele frequency, and finally classified according to the American College of Medical Genetics and Genomics guidelines. Multiplex ligation-dependent probe amplification and array comparative genomic hybridization were performed to validate copy number variations identified by NGS. The diagnostic yield of this study was 62% of studied families. Thirty novel mutations were identified. The study found phenotypic intra- and interfamilial variability in families with mutations in C1QTNF5, CERKL, and PROM1; biallelic mutations in PDE6B in a unilateral retinitis pigmentosa patient; interocular asymmetry RP in 50% of the symptomatic RPGR-mutated females; the first case with possible digenism between CNGA1 and CNGB1; and a ROM1 duplication in two unrelated retinitis pigmentosa families. Ten unrelated cases were reclassified. This study highlights the clinical utility of targeted NGS for nonsyndromic inherited retinal dystrophy cases and the importance of full ophthalmologic examination, which allows new genotypeephenotype associations and expands the knowledge of this group of disorders. Identifying the cause of disease is essential to improve patient management, provide accurate genetic counseling, and take advantage of gene therapyebased treatments. (J Mol Diagn 2020, 22: 532e543; https:// doi.org/10.1016/j.jmoldx.2020.01.003)Supported by grants from the Instituto de Salud Carlos III (ISCIII) of the Spanish Ministry of Health, including the Center for Biomedical Research Network on Rare Diseases (CIBERER), Fondo de Investigacion Sanitaria grant PI16/00539; the Spanish National Organization for the Blind (Fundación ONCE); and Fundación Mutua Madrileña. G.G.-G. is sponsored by the CIBERER, and A.R.-M. is supported by the Río Hortega program from ISCIII.Medicin

Reproductive long-term effects, endocrine response and fatty acid profile of rabbit does fed diets supplemented with n-3 fatty acids

The effect of a diet enriched with polyunsaturated n -3 fatty acids (PUFA) on endocrine, reproductive, and productive responses of rabbit females and the litters has been studied. Nulliparous does ( n = 125) were fed ad libitum from rearing to second weaning two diets supplemented with different fat sources: 7.5 g/kg lard for the control diet (group C; n = 63) or 15 g/kg of a commercial supplement containing a 50% ether extract and 35% of total fatty acids (FAs) as PUFA n -3 (Group P; n = 62). Dietary treatments did not affect apparent digestibility coefficients of nutrients, or reproductive variables of does including milk pro- duction, mortality and average daily gain of kits over two lactations. However, on Day 5 and 7 post-induction of ovulation, progesterone of Group P tended to increase to a greater extent than in does of Group C. Total PUFAs, n -6 and n -3 and eicosapentanoic (EPA) contents were greater in adipose tissues of does in Group P than in Group C. Docosapentaenoic acid (DPA), EPA, and docosahexaenoic acid (DHA) concentrations were greater in peri-ovarian than in scapular fat with abdominal fat being intermediate in concentration. In PUFA sup- plemented does, kit mortality at the second parturition tended to be less than in control does. Also, kits born to does of the PUFA-supplemented group weighed more and were of greater length than from does of control group. In conclusion, effectiveness of dietary intervention on reproductive and performance response is greater in the second parity, which suggests an accumulative long-term beneficial effect of n -3 FA supplementation in reproductive rabbit doe

Spatial and temporal variability of discards indicators and fishery factors affecting otter-trawl fishery in the spanish Mediterranean sea

A set of diversity indices were studied from data of observers on board two Mediterranean trawlers from 2001 to 2009. These diversity indices comprise relationships between total catch, landing and discard fractions to explore the accuracy of the estimates and to analyse the series trends using different methods, such as ARIMA. The hypothesis tested was that diversity indicators give a good representation of the changes produced in impacted bottom‐trawl areas, providing a reasonable fit of the data. ARIMA models are useful because they handle time-correlated modelling and forecasting. These techniques can also reveal changes in total catch as well changes in catch composition, probably induced by changes in effort fishery, seasonal (time) fluctuations, and environmental or climatic processes. Contrasted trends were also compared with survey data by MEDITS Mediterranean trawl survey time‐series indicator

How Memory Conforms to Brain Development

Nature exhibits countless examples of adaptive networks, whose topology evolves constantly coupled with the activity due to its function. The brain is an illustrative example of a system in which a dynamic complex network develops by the generation and pruning of synaptic contacts between neurons while memories are acquired and consolidated. Here, we consider a recently proposed brain developing model to study how mechanisms responsible for the evolution of brain structure affect and are affected by memory storage processes. Following recent experimental observations, we assume that the basic rules for adding and removing synapses depend on local synaptic currents at the respective neurons in addition to global mechanisms depending on the mean connectivity. In this way a feedback loop between “form” and “function” spontaneously emerges that influences the ability of the system to optimally store and retrieve sensory information in patterns of brain activity or memories. In particular, we report here that, as a consequence of such a feedback-loop, oscillations in the activity of the system among the memorized patterns can occur, depending on parameters, reminding mind dynamical processes. Such oscillations have their origin in the destabilization of memory attractors due to the pruning dynamics, which induces a kind of structural disorder or noise in the system at a long-term scale. This constantly modifies the synaptic disorder induced by the interference among the many patterns of activity memorized in the system. Such new intriguing oscillatory behavior is to be associated only to long-term synaptic mechanisms during the network evolution dynamics, and it does not depend on short-term synaptic processes, as assumed in other studies, that are not present in our model.Financial support from the Spanish Ministry of Science and Technology, and the Agencia Española de Investigación (AEI) under grant FIS2017-84256-P (FEDER funds) and from the Obra Social La Caixa (ID 100010434, with code LCF/BQ/ES15/10360004). This study has been also partially financed by the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía and European Regional Development Fund (ERDF), with reference SOMM17/6105/UGR

The role of epidemic spreading in seizure dynamics and epilepsy surgery

AbstractEpilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but only leads to seizure freedom for roughly two in three patients. To address this problem, we designed a patient-specific epilepsy surgery model combining large-scale magnetoencephalography (MEG) brain networks with an epidemic spreading model. This simple model was enough to reproduce the stereo-tactical electroencephalography (SEEG) seizure propagation patterns of all patients (N = 15), when considering the resection areas (RA) as the epidemic seed. Moreover, the goodness of fit of the model predicted surgical outcome. Once adapted for each patient, the model can generate alternative hypothesis of the seizure onset zone and test different resection strategies in silico. Overall, our findings indicate that spreading models based on patient-specific MEG connectivity can be used to predict surgical outcomes, with better fit results and greater reduction on seizure propagation linked to higher likelihood of seizure freedom after surgery. Finally, we introduced a population model that can be individualized by considering only the patient-specific MEG network, and showed that it not only conserves but improves the group classification. Thus, it may pave the way to generalize this framework to patients without SEEG recordings, reduce the risk of overfitting and improve the stability of the analyses

Incidence, risk factors, clinical characteristics and outcomes of deep venous thrombosis in patients with COVID-19 attending the Emergency Department: results of the UMC-19-S8

Background and importance: A higher incidence of venous thromboembolism [both pulmonary embolism and deep vein thrombosis (DVT)] in patients with coronavirus disease 2019 (COVID-19) has been described. But little is known about the true frequency of DVT in patients who attend emergency department (ED) and are diagnosed with COVID-19. Objective: We investigated the incidence, risk factors, clinical characteristics and outcomes of DVT in patients with COVID-19 attending the ED before hospitalization. Methods: We retrospectively reviewed all COVID patients diagnosed with DVT in 62 Spanish EDs (20% of Spanish EDs, case group) during the first 2 months of the COVID-19 outbreak. We compared DVT-COVID-19 patients with COVID-19 without DVT patients (control group). Relative frequencies of DVT were estimated in COVID and non-COVID patients visiting the ED and annual standardized incidences were estimated for both populations. Sixty-three patient characteristics and four outcomes were compared between cases and controls. Results: We identified 112 DVT in 74 814 patients with COVID-19 attending the ED [1.50‰; 95% confidence interval (CI), 1.23-1.80‰]. This relative frequency was similar than that observed in non-COVID patients [2109/1 388 879; 1.52‰; 95% CI, 1.45-1.69‰; odds ratio (OR) = 0.98 [0.82-1.19]. Standardized incidence of DVT was higher in COVID patients (98,38 versus 42,93/100,000/year; OR, 2.20; 95% CI, 2.03-2.38). In COVID patients, the clinical characteristics associated with a higher risk of presenting DVT were older age and having a history of venous thromboembolism, recent surgery/immobilization and hypertension; chest pain and desaturation at ED arrival and some analytical disturbances were also more frequently seen, d-dimer >5000 ng/mL being the strongest. After adjustment for age and sex, hospitalization, ICU admission and prolonged hospitalization were more frequent in cases than controls, whereas mortality was similar (OR, 1.37; 95% CI, 0.77-2.45). Conclusions: DVT was an unusual form of COVID presentation in COVID patients but was associated with a worse prognosis