Posts Tagged "Networks"

Functional brain networks before the onset of psychosis: A prospective fMRI study with graph theoretical analysis

Louis-David Lord, Paul Allen, Paul Expert, Oliver Howes, Matthew Broome, Renaud Lambiotte, Paolo Fusar-Poli, Isabel Valli, Philip McGuire, Federico E Turkheimer, NeuroImage: Clinical, Volume 1, Issue 1, 2012, Pages 91–98 Individuals with an at-risk mental state (ARMS) have a risk of developing a psychotic disorder significantly greater than the general population. However, it is not currently possible to predict which ARMS individuals will develop psychosis from clinical assessment alone. Comparison of ARMS subjects who do, and do not, develop psychosis can reveal which factors are critical for the onset of illness. In the present study, 37 patients with an ARMS were followed clinically at least 24 months subsequent to initial referral. Functional MRI data were collected at the beginning of the follow-up period during performance of an executive task known to recruit frontal lobe networks and to be impaired in psychosis. Graph theoretical analysis was used to compare the organization of a functional brain network in ARMS patients who developed a psychotic disorder following the scan (ARMS-T) to those who did not become ill during the same follow-up period (ARMS-NT) and aged-matched controls. The global properties of each group’s representative network were studied (density, efficiency, global average path length) as well as regionally-specific contributions of network nodes to the organization of the system (degree, farness-centrality, betweenness-centrality). We focused our analysis on the dorsal anterior cingulate cortex (ACC), a region known to support executive function that is structurally and functionally impaired in ARMS patients. In the absence of between-group differences in global network organization, we report a significant reduction in the topological centrality of the ACC in the ARMS-T group relative to both ARMS-NT and controls. These results provide evidence that abnormalities in the functional organization of the brain predate the onset of psychosis, and suggest that loss of ACC topological centrality is a potential biomarker for transition to...

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Plotting

Posted by on Mar 23, 2013 in Network | 0 comments

Almost all scientists need to plot at some point.  When preparing for publication, journals can be extremely precise about their requirements that can really stretch a plotting package (Physical Review E gets my vote for giving the author the most painful experience on this front).  Yet I still struggle to find the perfect package.  Recent licence changes at my home institution means I have lost access to one of my preferred packages. So this has led me to think about some of the different plotting packages that I am aware of, though some I have had next to no experience. The spreadsheets are the easiest to use.  I tend to use them for instant data analysis and for playing with ideas. For serious work I find they fall very short. Nothing else is particularly easy to learn so I suggest you just have to pick one. Cost and licence availability are therefore the biggest influence on my choice. I tend to use packages that I can have on all my computers: home, portable, work.  Also it is good if my students can use these packages as then I can help them.  This means free and preferably open source software is what I tend to use.  Even when there is a licence at Imperial they can be restrictive on who can have it and how many copies. In addition institutions can drop licences at any time.  I currently use R for the statistics and general data analysis so I have had to use its plotting anyway.  Its a bit painful to learn but it does what I want now.  Gnuplot makes for a good standalone package if you don’t need the features of the other packages. Matlab has the best interface I know for changing the look of a plot but I have never really used Matlab and I can’t have it on all my machines. Gnuplot: basically a plotting programme but can do fits and knows about mathematical functions. Free though not open source. Command line driven i.e. needs scripts. Well established so many online examples. Can do very complicated plots. Mathematical formulae can be included in plots using LaTeX style notation. Origin: This is a commercial statistics package. Imperial Physics Dept may have a licence. Looks much more like excel so this is the easiest package to use when manipulating data – the others work through the command line. Plots can also be altered using WYSIWYG GUI interface much like Matlab (though not as nice as MatLab). I have not used this. R Statistics package: analysing statistics is its prime use. Produces good plots and these are easily extended with standard libraries. Command line driven, very well established so lots of help online and many books in library. Its heritage can make it difficult to learn – it is not like C++/Java/Python. Main advantage is that it is free, open source and cross platform. Mathematical formulae can be included in plots. See my page on R statistics pacake for some of the ways I get R to do my plots but also see the R Plots Gallery. Matlab: Numerical analysis heritage with excellent plots. Language is similar to R so its not C++/Java/Python and tricky to learn. Lots of help in books and online. Big advantage is that it does offer considerable chances to manipulate the figures using WYSIWYG GUI interface e.g. change normal/log axes, change fonts of characters so it is very useful for changing a plot for publication. Octave: Open source free Matlab like package but I have not used this. Mathematica: primarily a symbolic manipulation programme...

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Can you game google scholar?

Posted by on Jan 10, 2013 in Network | 0 comments

The answer appears to be yes, according to a recent paper entitled Manipulating Google Scholar Citations and Google Scholar Metrics: simple, easy and tempting  by Emilio Delgado López-Cózar, Nicolás Robinson-García, and Daniel Torres-Salinas from the Universities of Granada and Nararra in Spain.  I thought their experiment was illuminating and, while it is an obvious one to try, the results seemed pretty clear to me. The rest of the paper is generally informative and useful too. For instance there is a list of other studies which have looked at how to manipulate bibliographic indices. For the experiment, six false “papers” were created, with authorship assigned to imaginary author.  Each of the six documents cited the same set of 129 genuine papers.  The cited papers all had at least one coauthor from the same EC3 research group as the authors of the study.  This could generate 774 (=129 x 6) new but artificial citations to members of the EC3 group (more if some papers had more than  one EC3 group member but this is not noted) . These six fake documents were then placed on web pages in an academic domain, much as many academics can do freely. Twenty five days later, these were picked up by google scholar and large increases in citations to the papers of the authors of this study are shown. The basic conclusion does seem clear.  As its stands it is easy for many academic authors to boost their google scholar counts using false documents.  In that sense, as things stand, it seems one should not use these google scholar counts for any serious analysis without at least some checks on the citations themselves.  Of course, google scholar makes that easy to do and free. However I do not feel we should rush to dismiss Google Scholar too quickly.  Any system can be gamed.  Useful references are given in the paper to other examples and studies of bibliometric manipulation, in both human edited/refereed sources and in uncontrolled electronic cases.  A major point of the paper is to point out that it is possible in both cases, just that it is much easier to do for web pages and google scholar.  What is less clear from the paper is that the solutions may be similar to those employed by traditional indices of refereed sources.  As the authors point out, the manipulation of the refereed/edited literature can and is spotted – journals are excluded from traditional bibliographic databases if they are caught manipulating indices.  The easiest way to do it is to look for sudden and unexpected increases in statistics.  One should always treat statistics with care and there needs to be some sort of assurance that the numbers are sound.  Looking for unusual behaviour, studying outliers should always be done as a check whenever statistics are being used.  The authors themselves present the very data that should be able to flag a problem in their case.  As they point out, their indices under google scholar went up by amazing amounts in a short time.  Given this indicator of an issue, it would be trivial to discover the source of the problem as google makes it trivial to find the source of the new citations.  Then of course, if such manipulation was being used for an important process, e.g. promotion or getting another job,  it becomes fraud and the research community and society at large already has severe sanctions to deal with such situations.  It may be easy to do but the sanctions may be enough to limit the problem. So to my mind the main message of this paper is not so much that google can be manipulated easily, but...

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Myths and Networks

Posted by on Aug 21, 2012 in Network | 0 comments

I have just read an intriguing paper by Carron and Kenna entitled the  ‘Universal properties of mythological networks‘. In it they analyse the character networks  in three ancient stories, Beowulf , the Iliad and the Irish story Táin Bó Cuailnge.  That is the characters form the nodes of a network and they are connected if they appear together in the same part of the story. It has caused quite a bit of activity.  It has prompted two posts on The Networks Network already and has even sparked activity in the UK newspapers (see John Sutherland writing in the Guardian Wednesday 25 July 2012 and the follow up comment by Ralph Kenna one of the authors).  Well summer is the traditional silly season for newspapers. However I think it is too easy to dismiss the article. I think Tom Brugmans posting on The Networks Network has it right that  “as an exploratory exercise it would have been fine”.  I disagreed with much in the paper, but it did intrigue me and many papers fail to do even this much.  So overall I think it was a useful publication. I think there are ideas there waiting to be developed further. I like the general idea that there might be some information in the character networks which would enable one to say if it was based on fact or was pure fiction. That is if the character networks have the same characteristics as a social network it would support the idea that it was based on historical events. I was intrigued by some of the measures suggested as a way to differentiate between different types of literary work.  However like both Tom Brugmans and Marco Büchler, I was unconvinced the authors’ measures really do the job suggested. I’d really like to see a lot more evidence from many more texts before linking a particular measurement to a particular feature in character networks. For instance Carron and Kenna suggest that in hierarchical networks for every node the degree times the clustering coefficient is a constant, eqn (2).  That is each of your friends is always connected to the same (on average) number of your friends.  By way of contrast, in a classical (Erdos-Reyni) random graph the clustering coefficient is a constant. However I don’t see that as hierarchical but an indication that everyone lives in similar size communities, some sort of fiction character Dunbar number. I’m sure you could have a very flat arrangement of communities and get the same result. Perhaps we mean different things by hierarchical. Another claim was that in collaboration networks less than 90% of nodes are in the giant component.  The Newman paper referred to is about scientific collaboration derived from coauthorships which is very different from the actual social network of scientists (science is not done in isolation no one is really isolated). I’m not sure the Newman paper tells us anything about character structure in fictional or non-fictional texts.  I can not see why one would introduce any set of characters in any story (fictional or not) who are disconnected from the rest. Perhaps some clever tale with two strands separated in time yet connected in terms other than social relationships (e.g. through geography or action) – David Mitchell’s “Cloud Atlas” comes to my mind  – but these are pretty contrived structures. I think a real problem in the detail of the paper, as Marco Büchler points out, is that these texts and their networks are just too small.  There is no way one can talk rigorously about power laws, and certainly not to two decimal place accuracy. I thought Michael Stumpf and Mason Porter’s commentary (Critical Truths about Power Laws) was not needed since every one knew the issues by...

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The Pools of Academic Goodwill

Posted by on Aug 7, 2012 in Network | 0 comments

Much of academia is not run like a commercial business, or at least not yet. Many of the jobs I do are not paid for by the recipient of my efforts: referee reports for journals, examining of some PhDs and writing references are three examples which come to mind straight away. Rather than being directly paid for these tasks by the recipient, my home institution understands that they are paying for me to spend some of my time on external matters. Of course my university also draws from that pool as do I – journals use referees for my papers, my students need examiners, I needed references to pursue my own academic career. Overall, everything probably balances out. For some of this work I may get paid, though anyone in the commercial world would probably find the rates at best to be humorous and at worst insulting. For a PhD viva in the UK I get around £150 (around U$200), which is about 24 hours work at the rate of the UK’s minimum wage. I reckon it takes me three working days to read a thesis (if there are no problems and if I am relatively familiar with the work) so that leaves the actual exam unpaid even at minimum wage rates. I was recently an examiner for a PhD in Vienna. The trip alone took more than 24 hours and in this case it was expenses only. Some types of external academic work may have some benefits for me. I read the Viennese PhD thesis from cover to cover: it was a pleasure that I would never have had if I had not been an examiner on this particular thesis. Such detailed reading time is a precious commodity these days. Some of this work can be used to support the case for my own career progression. Here, being an external examiner for another University’s undergraduate programme is an example of a measure of esteem that might count in my favour in a review meeting. Of course the link between such work and promotion is a very tenuous link, while the work itself is quite demanding and invariably underpaid. Again we all do this work as we understand that we need examiners for our own PhD students and for our own undergraduate exams, we will draw from the pool of academic goodwill. A more interesting case is the value of the work done by academic refereeing for journals which has been estimated at about £1.9bn per year, and £165 million for the UK alone. There is real value in this work spent commenting on academic papers yet while journals charge others  for their service and they make profits, none of the fees charged by journals make it to referees.  So journals also draw on academic goodwill. In the book Whackademia Richard Hil says that academics are no longer trusted as professionals but are to be monitored and measured. He suggests that before this, internal pressure and support from within an academic community ensured everyone made their contribution, even if this was in different ways. Richard Hil suggests that the new neo-liberal business-like approach encourages an individualism that destroys fails to value contributions to a shared pool of academic goodwill and so actually reduces overall returns.  We have to maximise our individual measured outputs so everything else, useful or not, gets dropped. So if the UK government, and maybe others, want to push a more business approach on universities they ought to think carefully. Perhaps they should first try to value the cost of business style consultancy over academic goodwill. Via:...

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