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Biosystems SI: Patterns in Evolution

Biosystems SI: Patterns in Evolution | Papers | Scoop.it

The papers collected in this issue, present concrete approaches for understanding pattern formation in the evolutionary process and suggest mathematical models to describe the emergence of reproducible patterns of variation.


Biosystems
Volume 123, Pages 1-114 (September 2014)
SI :Patterns in Evolution

Edited by Abir Igamberdiev and Alexei Sharov

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In a Mother’s Milk, Nutrients, and a Message, Too

In a Mother’s Milk, Nutrients, and a Message, Too | Papers | Scoop.it

Milk is not just food. The more closely scientists examine it, the more complexity they find.

Along with nutrients like protein and calcium, milk contains immune factors that protect infants from disease. It hosts a menagerie of microbes, too, some of which may colonize the guts of babies and help them digest food. Milk even contains a special sugar that can fertilize that microbial garden.

Now, it turns out, milk also contains messages.

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How well-connected is the surface of the global ocean?

The Ekman dynamics of the ocean surface circulation is known to contain attracting regions such as the great oceanic gyres and the associated garbage patches. Less well-known are the extents of the basins of attractions of these regions and how strongly attracting they are. Understanding the shape and extent of the basins of attraction sheds light on the question of the strength of connectivity of different regions of the ocean, which helps in understanding the flow of buoyant material like plastic litter. Using short flow time trajectory data from a global ocean model, we create a Markov chain model of the surface ocean dynamics. The surface ocean is not a conservative dynamical system as water in the ocean follows three-dimensional pathways, with upwelling and downwelling in certain regions. Using our Markov chain model, we easily compute net surface upwelling and downwelling, and verify that it matches observed patterns of upwelling and downwelling in the real ocean. We analyze the Markov chain to determine multiple attracting regions. Finally, using an eigenvector approach, we (i) identify the five major ocean garbage patches, (ii) partition the ocean into basins of attraction for each of the garbage patches, and (iii) partition the ocean into regions that demonstrate transient dynamics modulo the attracting garbage patches.


How well-connected is the surface of the global ocean?
Gary Froyland, Robyn M. Stuart and Erik van Sebille

Chaos 24, 033126 (2014); http://dx.doi.org/10.1063/1.4892530

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Risking It All: Why are public health authorities not concerned about Ebola in the US?

US public health authorities claim imposing quarantines on healthcare workers returning from West Africa is incorrect according to science. Their positions rely upon a set of studies and experience about outbreaks and transmission mechanisms in Africa as well as assumptions about what those studies imply about outbreaks in the US. According to this view the probability of a single infection is low and that of a major outbreak is non-existent. In a series of brief reports we will provide insight into why properties of networks of contagion that are not considered in traditional statistics suggest that risks are higher than those assumptions suggest. We begin with the difference between thin and fat tailed distributions applied to the number of infected individuals that can arise from a single one. Traditional epidemiological models consider the contagion process as described by R0, the average number of new infected individuals arising from a single case. However, in a complex interdependent society it is possible for the actual number due to a single individual to dramatically differ from the average number, with severe consequences for the ability to contain an outbreak when it is just beginning. Our analysis raises doubts about the scientific validity of policy recommendations of public health authorities. We also point out that existing CDC public health policies and actions are inconsistent with their claims.


Y. Bar-Yam, Risking It All: Why are public health authorities not concerned about Ebola in the US? Part I. Fat tailed distributions. New England Complex Systems Institute

http://necsi.edu/research/social/pandemics/publichealth1.html

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Complexity, Selectivity and Asymmetry in the Conformation of the Power Phenomenon. Analysis of Chilean Society

In this work we analyzed the relationships between powerful politicians and businessmen of Chile in order to study the phenomenon of social power. We developed our study according to Complex Network Theory but also using traditional sociological theories of Power and Elites. Our analyses suggest that the studied network displays common properties of Complex Networks, such as scaling in connectivity distribution, properties of small-world networks, and modular structure, among others. We also observed that social power (a proposed metric is presented in this work) is also distributed inhomogeneously. However, the most interesting observation is that this inhomogeneous power and connectivity distribution, among other observed properties, may be the result of a dynamic and unregulated process of network growth in which powerful people tend to link to similar others. The compatibility between people, increasingly selective as the network grows, could generate the presence of extremely powerful people, but also a constant inequality of power where the difference between the most powerful is the same as among the least powerful. Our results are also in accordance with sociological theories.


Complexity, Selectivity and Asymmetry in the Conformation of the Power Phenomenon. Analysis of Chilean Society
Juan Pablo Cárdenas, Gerardo Vidal, Gastón Olivares

http://arxiv.org/abs/1409.7862

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How Do Agents Make Decisions?

When designing an agent-based simulation, an important question to answer is how to model the decision making processes of the agents in the system. A large number of agent decision making models can be found in the literature, each inspired by different aims and research questions. In this paper we provide a review of 14 agent decision making architectures that have attracted interest. They range from production-rule systems to psychologically- and neurologically-inspired approaches. For each of the architectures we give an overview of its design, highlight research questions that have been answered with its help and outline the reasons for the choice of the decision making model provided by the originators. Our goal is to provide guidelines about what kind of agent decision making model, with which level of simplicity or complexity, to use for which kind of research question.


Tina Balke and Nigel Gilbert (2014)
How Do Agents Make Decisions? A Survey
Journal of Artificial Societies and Social Simulation 17 (4) 13

http://jasss.soc.surrey.ac.uk/17/4/13.html

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Double Percolation Phase Transition in Clustered Complex Networks

Double Percolation Phase Transition in Clustered Complex Networks | Papers | Scoop.it

The percolation properties of networks are strongly affected by their topological features. A new study shows that percolation can proceed at different rates in the core and periphery of a complex, clustered network.


Double Percolation Phase Transition in Clustered Complex Networks
Pol Colomer-de-Simón and Marián Boguñá
Phys. Rev. X 4, 041020 (2014)

http://dx.doi.org/10.1103/PhysRevX.4.041020

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Homological scaffolds of brain functional networks

Networks, as efficient representations of complex systems, have appealed to scientists for a long time and now permeate many areas of science, including neuroimaging (Bullmore and Sporns 2009 Nat. Rev. Neurosci. 10, 186–198. (http://dx.doi.org/10.1038/nrn2618 ). Traditionally, the structure of complex networks has been studied through their statistical properties and metrics concerned with node and link properties, e.g. degree-distribution, node centrality and modularity. Here, we study the characteristics of functional brain networks at the mesoscopic level from a novel perspective that highlights the role of inhomogeneities in the fabric of functional connections. This can be done by focusing on the features of a set of topological objects—homological cycles—associated with the weighted functional network. We leverage the detected topological information to define the homological scaffolds, a new set of objects designed to represent compactly the homological features of the correlation network and simultaneously make their homological properties amenable to networks theoretical methods. As a proof of principle, we apply these tools to compare resting-state functional brain activity in 15 healthy volunteers after intravenous infusion of placebo and psilocybin—the main psychoactive component of magic mushrooms. The results show that the homological structure of the brain's functional patterns undergoes a dramatic change post-psilocybin, characterized by the appearance of many transient structures of low stability and of a small number of persistent ones that are not observed in the case of placebo.


Homological scaffolds of brain functional networks
G. Petri, P. Expert, F. Turkheimer, R. Carhart-Harris, D. Nutt, P. J. Hellyer and F. Vaccarino

http://dx.doi.org/10.1098/rsif.2014.0873
J. R. Soc. Interface 6 December 2014 vol. 11 no. 101 20140873

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Visualizing the “Heartbeat” of a City with Tweets

Visualizing the “Heartbeat” of a City with Tweets | Papers | Scoop.it

Describing the dynamics of a city is a crucial step to both understanding the human activity in urban environments and to planning and designing cities accordingly. Here we describe the collective dynamics of New York City and surrounding areas as seen through the lens of Twitter usage. In particular, we observe and quantify the patterns that emerge naturally from the hourly activities in different areas of New York City, and discuss how they can be used to understand the urban areas. Using a dataset that includes more than 6 million geolocated Twitter messages we construct a movie of the geographic density of tweets. We observe the diurnal “heartbeat” of the NYC area. The largest scale dynamics are the waking and sleeping cycle and commuting from residential communities to office areas in Manhattan. Hourly dynamics reflect the interplay of commuting, work and leisure, including whether people are preoccupied with other activities or actively using Twitter. Differences between weekday and weekend dynamics point to changes in when people wake and sleep, and engage in social activities. We show that by measuring the average distances to the heart of the city one can quantify the weekly differences and the shift in behavior during weekends. We also identify locations and times of high Twitter activity that occur because of specific activities. These include early morning high levels of traffic as people arrive and wait at air transportation hubs, and on Sunday at the Meadowlands Sports Complex and Statue of Liberty. We analyze the role of particular individuals where they have large impacts on overall Twitter activity. Our analysis points to the opportunity to develop insight into both geographic social dynamics and attention through social media analysis.


U. França, H. Sayama, C. McSwiggen, R. Daneshvar and Y. Bar-Yam, Visualizing the “Heartbeat” of a City with Tweets.

http://www.necsi.edu/research/social/nypattern.html

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Local and global epidemic outbreaks in populations moving in inhomogeneous environments

Local and global epidemic outbreaks in populations moving in inhomogeneous environments | Papers | Scoop.it

We study disease spreading in a system of agents moving in a space where the force of infection is not homogeneous. Agents are random walkers that additionally execute long-distance jumps, and the plane in which they move is divided into two regions where the force of infection takes different values. We show the onset of a local epidemic threshold and a global one and explain them in terms of mean-field approximations. We also elucidate the critical role of the agent velocity, jump probability, and density parameters in achieving the conditions for local and global outbreaks. Finally, we show that the results are independent of the specific microscopic rules adopted for agent motion, since a similar behavior is also observed for the distribution of agent velocity based on a truncated power law, which is a model often used to fit real data on motion patterns of animals and humans.


Local and global epidemic outbreaks in populations moving in inhomogeneous environments
Phys. Rev. E 90, 042813 – Published 21 October 2014
Arturo Buscarino, Luigi Fortuna, Mattia Frasca, and Alessandro Rizzo

http://dx.doi.org/10.1103/PhysRevE.90.042813

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The Aging Brain

Should we consider aging a natural part of life or an illness? When it comes to the brain, research has tended to focus on the negative side of aging—Alzheimer's disease, for example. Yet all of us know individuals who continue to be mentally sharp their whole lives. And history repeatedly offers proof—Titian, Socrates, da Vinci, and so on—that great creativity and insight can come with maturity.

This special issue of Science therefore looks at the mechanisms and contexts of successful brain aging. The developmental trajectory of the brain through the entire life span is affected by genetic, physical, and psychological factors. One thing we know already is that our mental lives benefit when we lead lives that are not only physically healthy but also intellectually challenging and socially engaged (...)

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Dynamics of Interacting Diseases

Dynamics of Interacting Diseases | Papers | Scoop.it


Forecasting epidemic outbreaks has long been the goal of health researchers. By modeling the interactions of two diseases occurring simultaneously, scientists show that specific parameters control the thresholds of epidemics.


Dynamics of Interacting Diseases
Joaquín Sanz, Cheng-Yi Xia, Sandro Meloni, and Yamir Moreno
Phys. Rev. X 4, 041005 (2014)

http://dx.doi.org/10.1103/PhysRevX.4.041005
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San Francisco Is Smarter Than You Are

San Francisco Is Smarter Than You Are | Papers | Scoop.it

Its achievements are undeniable. Having hosted what some historians call the greatest creation of wealth in human history,1 the San Francisco Bay Area had the fastest growth rate in the United States in 2012,2 the highest per-capita gross domestic product,3 one of the highest average IQs,4 and has been called one of the country’s greenest cities.5 If cities were people, then San Francisco would certainly be called a genius. But are we willing to extend that term to a city, or should we insist that genius is contained within the confines of the human head?

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Life cycles, fitness decoupling and the evolution of multicellularity

Cooperation is central to the emergence of multicellular life; however, the means by which the earliest collectives (groups of cells) maintained integrity in the face of destructive cheating types is unclear. One idea posits cheats as a primitive germ line in a life cycle that facilitates collective reproduction. Here we describe an experiment in which simple cooperating lineages of bacteria were propagated under a selective regime that rewarded collective-level persistence. Collectives reproduced via life cycles that either embraced, or purged, cheating types. When embraced, the life cycle alternated between phenotypic states. Selection fostered inception of a developmental switch that underpinned the emergence of collectives whose fitness, during the course of evolution, became decoupled from the fitness of constituent cells. Such development and decoupling did not occur when groups reproduced via a cheat-purging regime. Our findings capture key events in the evolution of Darwinian individuality during the transition from single cells to multicellularity.


Life cycles, fitness decoupling and the evolution of multicellularity
• Katrin Hammerschmidt, Caroline J. Rose, Benjamin Kerr & Paul B. Rainey

Nature 515, 75–79 (06 November 2014) http://dx.doi.org/10.1038/nature13884

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There Is No ‘Healthy’ Microbiome

There Is No ‘Healthy’ Microbiome | Papers | Scoop.it

IN the late 17th century, the Dutch naturalist Anton van Leeuwenhoek looked at his own dental plaque through a microscope and saw a world of tiny cells “very prettily a-moving.” He could not have predicted that a few centuries later, the trillions of microbes that share our lives — collectively known as the microbiome — would rank among the hottest areas of biology.

These microscopic partners help us by digesting our food, training our immune systems and crowding out other harmful microbes that could cause disease. In return, everything from the food we eat to the medicines we take can shape our microbial communities — with important implications for our health. Studies have found that changes in our microbiome accompany medical problems from obesity to diabetes to colon cancer.

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Rowan Norrie's curator insight, November 10, 2014 6:14 AM

The fascinating world of the microbiome and the opportunities it heralds for future medicine

Dmitry Alexeev's curator insight, November 12, 2014 3:45 AM

Our microbes are truly part of us, and just as we are vast in our variety, so, too, are they. We must embrace this complexity if we hope to benefit from it.

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Controllability of asynchronous Boolean multiplex control networks

In this article, the controllability of asynchronous Boolean multiplex control networks (ABMCNs) is studied. First, the model of Boolean multiplex control networks under Harvey’ asynchronous update is presented. By means of semi-tensor product approach, the logical dynamics is converted into linear representation, and a generalized formula of control-depending network transition matrices is achieved. Second, a necessary and sufficient condition is proposed to verify that only control-depending fixed points of ABMCNs can be controlled with probability one. Third, using two types of controls, the controllability of system is studied and formulae are given to show: (a) when an initial state is given, the reachable set at time s under a group of specified controls; (b) the reachable set at time s under arbitrary controls; (c) the specific probability values from a given initial state to destination states. Based on the above formulae, an algorithm to calculate overall reachable states from a specified initial state is presented. Moreover, we also discuss an approach to find the particular control sequence which steers the system between two states with maximum probability. Examples are shown to illustrate the feasibility of the proposed scheme.


Controllability of asynchronous Boolean multiplex control networks Start Chao Luo, Xingyuan Wang and Hong Liu

Chaos 24, 033108 (2014); http://dx.doi.org/10.1063/1.4887278

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Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic

The quick spread of an Ebola outbreak in West Africa has led a number of countries and airline companies to issue travel bans to the affected areas. Considering data up to 31 Aug 2014, we assess the impact of the resulting traffic reductions with detailed numerical simulations of the international spread of the epidemic. Traffic reductions are shown to delay by only a few weeks the risk that the outbreak extends to new countries.


Poletto C, Gomes MF, Pastore y Piontti A, Rossi L, Bioglio L, Chao DL, Longini IM, Halloran ME, Colizza V, Vespignani A. Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic. Euro Surveill. 2014;19(42):pii=20936. Available online: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=20936

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Modeling Social Dynamics in a Collaborative Environment

Wikipedia is a prime example of today's value production in a collaborative environment. Using this example, we model the emergence, persistence and resolution of severe conflicts during collaboration by coupling opinion formation with article editing in a bounded confidence dynamics. The complex social behavior involved in editing articles is implemented as a minimal model with two basic elements; (i) individuals interact directly to share information and convince each other, and (ii) they edit a common medium to establish their own opinions. Opinions of the editors and that represented by the article are characterised by a scalar variable. When the pool of editors is fixed, three regimes can be distinguished: (a) a stable mainstream article opinion is continuously contested by editors with extremist views and there is slow convergence towards consensus, (b) the article oscillates between editors with extremist views, reaching consensus relatively fast at one of the extremes, and (c) the extremist editors are converted very fast to the mainstream opinion and the article has an erratic evolution. When editors are renewed with a certain rate, a dynamical transition occurs between different kinds of edit wars, which qualitatively reflect the dynamics of conflicts as observed in real Wikipedia data.


Modeling Social Dynamics in a Collaborative Environment

Gerardo Iñiguez, János Török, Taha Yasseri, Kimmo Kaski, János Kertész

http://arxiv.org/abs/1403.3568

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Multi-layer weighted social network model

Recent empirical studies using large-scale datasets have validated the Granovetter hypothesis on the structure of the society in that there are strongly wired communities connected by weak ties. However, as interaction between individuals takes place in diverse contexts, these communities turn out to be overlapping. This implies that the society has a multi-layered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, sufficient amount of inter-layer correlation is needed to maintain the relationship between topology and link weights but these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multi-layer WSN model, where the indirect inter-layer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at the same time, the Granovetterian structure is preserved.


Y Murase, J Török, H-H Jo, K Kaski, J Kertész
http://arXiv.org/abs/1408.1190

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Erosion of synchronization in networks of coupled oscillators

We report erosion of synchronization in networks of coupled phase oscillators, a phenomenon where perfect phase synchronization is unattainable in steady-state, even in the limit of infinite coupling. An analysis reveals that the total erosion it is separable into the product terms characterizing coupling frustration and structural heterogeneity, both of which amplify erosion. The latter, however, can differ significantly from degree heterogeneity. Finally, we show that erosion is marked by the reorganization of oscillators according to their node degrees rather than their natural frequencies.


Erosion of synchronization in networks of coupled oscillators
Per Sebastian Skardal, Dane Taylor, Jie Sun, Alex Arenas

http://arxiv.org/abs/1410.7559

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The hipster effect: When anticonformists all look the same

In such different domains as statistical physics and spin glasses, neurosciences, social science, economics and finance, large ensemble of interacting individuals taking their decisions either in accordance (mainstream) or against (hipsters) the majority are ubiquitous. Yet, trying hard to be different often ends up in hipsters consistently taking the same decisions, in other words all looking alike. We resolve this apparent paradox studying a canonical model of statistical physics, enriched by incorporating the delays necessary for information to be communicated. We show a generic phase transition in the system: when hipsters are too slow in detecting the trends, they will keep making the same choices and therefore remain correlated as time goes by, while their trend evolves in time as a periodic function. This is true as long as the majority of the population is made of hipsters. Otherwise, hipsters will be, again, largely aligned, towards a constant direction which is imposed by the mainstream choices. Beyond the choice of the best suit to wear this winter, this study may have important implications in understanding dynamics of inhibitory networks of the brain or investment strategies finance, or the understanding of emergent dynamics in social science, domains in which delays of communication and the geometry of the systems are prominent.


The hipster effect: When anticonformists all look the same
Jonathan Touboul

http://arxiv.org/abs/1410.8001

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Synchronicity among Biological and Computational Levels of an Organism: Quantum Biology and Complexity

This paper argues that there is a synchronicity among biological and computational levels on an organism and provides arguments and proofs based on experimental research gathered in the literature. The leading thread is the interplay between quantum biology (QB) and complexity. As the paper asks whether QB does contribute to complexity science (CS), five arguments are provided: (i) Firstly a state-of-the art of QB and its relationship to CS is sketched out. Thereafter, the attention is directed to answering the question set out; (ii) Secondly, it digs into the understanding of life toward deeper levels of reality; (iii) It is shown that non-trivial quantum effects shed insightful lights on the information processing of and within living beings; (iv) Once the distinction is made between increasing levels of complexity and increasing levels of organization, the focus lies in the importance of QB for organization, and not so much for complexity as such; (v) The role of information rises at the center of all concerns, and the intertwining of complexity and information processing. At the end some conclusions are drawn.


Synchronicity among Biological and Computational Levels of an Organism: Quantum Biology and Complexity
Carlos E. Maldonado, Nelson A. Gómez-Cruz

Procedia Computer Science
Volume 36, 2014, Pages 177–184
Complex Adaptive Systems Philadelphia, PA November 3-5, 2014

http://dx.doi.org/10.1016/j.procs.2014.09.076

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A typology of street patterns

We propose a quantitative method to classify cities according to their street pattern. We use the conditional probability distribution of shape factor of blocks with a given area and define what could constitute the ‘fingerprint’ of a city. Using a simple hierarchical clustering method, these fingerprints can then serve as a basis for a typology of cities. We apply this method to a set of 131 cities in the world, and at an intermediate level of the dendrogram, we observe four large families of cities characterized by different abundances of blocks of a certain area and shape. At a lower level of the classification, we find that most European cities and American cities in our sample fall in their own sub-category, highlighting quantitatively the differences between the typical layouts of cities in both regions. We also show with the example of New York and its different boroughs, that the fingerprint of a city can be seen as the sum of the ones characterizing the different neighbourhoods inside a city. This method provides a quantitative comparison of urban street patterns, which could be helpful for a better understanding of the causes and mechanisms behind their distinct shapes.


A typology of street patterns
Rémi Louf, Marc Barthelemy

http://dx.doi.org/10.1098/rsif.2014.0924

J. R. Soc. Interface 6 December 2014 vol. 11 no. 101 20140924

Also at http://arxiv.org/abs/1410.2094

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The atoms of neural computation

The human cerebral cortex is central to a wide array of cognitive functions, from vision to language, reasoning, decision-making, and motor control. Yet, nearly a century after the neuroanatomical organization of the cortex was first defined, its basic logic remains unknown. One hypothesis is that cortical neurons form a single, massively repeated “canonical” circuit, characterized as a kind of a “nonlinear spatiotemporal filter with adaptive properties” (1). In this classic view, it was “assumed that these…properties are identical for all neocortical areas.” Nearly four decades later, there is still no consensus about whether such a canonical circuit exists, either in terms of its anatomical basis or its function. Likewise, there is little evidence that such uniform architectures can capture the diversity of cortical function in simple mammals, let alone characteristically human processes such as language and abstract thinking (2). Analogous software implementations in artificial intelligence (e.g., deep learning networks) have proven effective in certain pattern classification tasks, such as speech and image recognition, but likewise have made little inroads in areas such as reasoning and natural language understanding. Is the search for a single canonical cortical circuit misguided?


The atoms of neural computation
Gary Marcus, Adam Marblestone, Thomas Dean


Science 31 October 2014:
Vol. 346 no. 6209 pp. 551-552
http://dx.doi.org/10.1126/science.1261661

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The top 100 papers

The discovery of high-temperature superconductors, the determination of DNA’s double-helix structure, the first observations that the expansion of the Universe is accelerating — all of these breakthroughs won Nobel prizes and international acclaim. Yet none of the papers that announced them comes anywhere close to ranking among the 100 most highly cited papers of all time.
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