From marie at PSY.GLA.AC.UK Mon Nov 5 17:09:25 2007 From: marie at PSY.GLA.AC.UK (Marie Smith) Date: Mon, 5 Nov 2007 16:09:25 +0000 Subject: 3 RA job adverts Message-ID: > UNIVERSITY OF GLASGOW > DEPARTMENT OF PSYCHOLOGY > Postdoctoral Research Assistants (3 posts) > £29139 - £32796 Per Annum > REF #See Below > ESRC/MRC project “Social Interactions: A Cognitive Neurosciences > Approach” > > The project will investigate (1) the immediate processing of social > signals from the voice, face and bodily movement, (2) how such > signals support interactive alignment of social behaviours > (associated with pupil dilation, blinking, yawning etc.), and, (3) > the mechanisms that underlie joint attention and action. > > (1) Ref: 13805/DPO/A3 > > Applications are invited for a Research Assistant to work with > Professor Pascal Belin. The successful candidate will contribute to > the design of auditory behavioural, fMRI and EEG experiments; > collect the data with a state of the art fMRI system; apply cutting > edge techniques to analyse brain signals in the time and frequency > domain and relate them to behavioural measures of voice perception. > This post is available from 1 January 2008, funding is available > for up to three years in the first instance. > > You will be qualified, with a PhD in cognitive neuroscience or a > related discipline. You will also have experience of running > psychophysical, cognitive and brainimaging experiments, with > experience in fMRI data collection and analysis. You will have good > programming skills, particularly with MATLAB and will be > experienced in sound processing, signal analysis in the time and > frequency domain. You should also have a strong interest in > pursuing a research career. > > Informal enquiries may be made to Professor Pascal Belin (+44 (0) > 141 330 4629) > email: p.belin at psy.gla.ac.uk . > > > (2) Ref: 13808/DPO/A3 > > Applications are invited for a Research Assistant to work with > Professors Philippe Schyns and Joachim Gross. The successful > candidate will contribute to the design of event-related MEG > experiments; collect the data with a state of the art MEG system; > apply cutting edge techniques to analyse brain signals in the time > and frequency domain; solve the inverse problem in order to > identify processing networks; and reverse correlate brain activity > with facial features. This post is available from 1 January 2008. > > You will be qualified, with a PhD, or equivalent, in cognitive > neuroscience or a related discipline. You will also have experience > of running psychophysical, cognitive and brainimaging experiments, > with experience in MEG and/or EEG date collection and analysis. You > will have excellent programming skills, particularly with MATLAB > and will be experienced in image processing, signal analysis in the > time and frequency domain, the inverse-problem and beamforming / > source localisation methods. Finally you should have a strong > interest in pursuing a research career. > > Informal enquiries may be made to Professor P Schyns, (+44 (0)141 > 330 4937); > e-mail p.schyns at psy.gla.ac.uk and/or Professor J Gross (+44 (0)141 > 330 3947) email j.gross at psy.gla.ac.uk . > > > (3) Ref: 13804/DPO/A3 > > Applications are invited for a Research Assistant to work with Dr. > Hartmut Leuthold. The successful candidate will contribute to > running experiments on joint attention and action and have a > special interest and/or experience in Cognitive Neuroscience (e.g., > in EEG, fMRI, MEG, TMS). > > You will be qualified, with a PhD, or equivalent, in cognitive > neuroscience or a related discipline. You will also have experience > of running psychophysical, cognitive and brainimaging experiments, > with experience in MEG and/or EEG date collection and analysis. You > will have good programming skills, particularly with MATLAB. You > should also have a strong interest in pursuing a research career. > > Informal enquiries may be made to Dr. Hartmut Leuthold (+44 (0)141 > 330 6847) email h.leuthold at psy.gla.ac.uk . > > General enquiries for all 3 posts to Heather Robertson > (h.robertson at psy.gla.ac.uk), Department of Psychology, Tel No 0141 > 330 6173. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From soren.r.christensen at GSK.COM Mon Nov 5 18:05:35 2007 From: soren.r.christensen at GSK.COM (Soren Rahn Christensen) Date: Mon, 5 Nov 2007 17:05:35 +0000 Subject: Soren R Christensen is out of the office. Message-ID: I will be out of the office starting 01-Nov-2007 and will not return until 12-Nov-2007. Back Monday 12th October. I will read e-mail, though. ----------------------------------------------------------- This e-mail was sent by GlaxoSmithKline Services Unlimited (registered in England and Wales No. 1047315), which is a member of the GlaxoSmithKline group of companies. The registered address of GlaxoSmithKline Services Unlimited is 980 Great West Road, Brentford, Middlesex TW8 9GS. ----------------------------------------------------------- ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From matuhasi at KUHP.KYOTO-U.AC.JP Tue Nov 6 07:38:53 2007 From: matuhasi at KUHP.KYOTO-U.AC.JP (=?SHIFT_JIS?Q?Masao_Matsuhashi?=) Date: Tue, 6 Nov 2007 07:38:53 +0100 Subject: Phantom Dipole on VectorView Message-ID: Dear Fieldtrip users (especialy the Neuromag users), I want to use Fieldtrip to analyze my Vectorview data. Fist I tried a phantom recording and performed an ECD analysis, but the result does not match. Please see the example below. The difference within 5 mm may be ok, but the y-axis... Would you please tell me what is wrong? One concern may be that the Neuromag coordinate frame is different from CTF coordinate, but this does not matter if I do not try to overlay the source onto MRI, am I right? SSP significantly distorts the waveform of this huge field, so I am fine without it. Thank you in advance, Masao Phantom Dipole #10 at (0.0, -4.86, 2.35) Estimated position: (-0.598803 -6.67657 2.81002) Raw data file: Dip10_1000nA_std_03_raw.fif MATLAB Version 7.5.0.342 (R2007b) fieldtrip-20071105 =================== Procedure =============================== sRawFIFF_name='Dip10_1000nA_std_03_raw.fif'; pre=0.05; post=0.1; % create trial info hdr = read_fcdc_header(sRawFIFF_name); prep=round(pre*hdr.Fs); postp=round(post*hdr.Fs); data= read_fcdc_data(sRawFIFF_name,'chanindx',315); data=reshape(data,numel(data),1); trig = find(diff(data)>0); trig = trig(2:end-1); %read data cfg = []; cfg.trl = [trig-prep,trig+postp,repmat(-prep,size(trig))]; cfg.dataset = sRawFIFF_name; cfg.datatype = 'continuous'; cfg.blc = 'yes'; cfg.blcwindow = [-pre 0]; cfg.channel = 'all'; % 'MEG' does not work data = preprocessing(cfg); % average cfg = []; avg = timelockanalysis(cfg, data); % show waveform figure plot(1000*avg.time, avg.avg) % convert time to ms xlabel('time (ms)') ylabel('field amplitude (T)') axis tight grid on % fit a dipole cfg = []; cfg.latency = [0.019]; cfg.numdipoles = 1; cfg.gradfile = sRawFIFF_name; cfg.vol.o = [0,0,0]; % in cm cfg.vol.r = 7; % should not matter cfg.grid.xgrid = -7:1:7; cfg.grid.ygrid = -7:1:7; cfg.grid.zgrid = -1:1:8; dip = dipolefitting(cfg, avg) =================== Output =================================== ntrl = 111 reading and preprocessing reading and preprocessing trial 1 from 111 reading and preprocessing trial 2 from 111 ... reading and preprocessing trial 111 from 111 the input is raw data with 315 channels and 111 trials applying preprocessing options averaging trials averaging trial 1 of 111 averaging trial 2 of 111 ... averaging trial 111 of 111 the input is timelock data with 315 channels and 158 timebins using headmodel specified in the configuration reading gradiometers from file Dip10_1000nA_std_03_raw.fif selected 306 channels selected 1 topographies 900 dipoles inside, 1348 dipoles outside brain scanning grid scanning grid location 1/900 scanning grid location 2/900 ... scanning grid location 900/900 found minimum after scanning on grid point [0 -6 3] First-order Iteration Func-count f(x) Step-size optimality 0 4 0.848031 0.0232 1 12 0.842257 10 0.0127 2 16 0.837597 1 0.00289 3 20 0.837204 1 0.00185 4 24 0.837115 1 0.000602 5 28 0.837106 1 0.000173 6 32 0.837105 1 4.07e-006 7 36 0.837105 1 1.86e-007 8 40 0.837105 1 1.04e-007 9 48 0.837105 0.407507 2.98e-008 Optimization cannot make further progress: relative change in x less than options.TolX. found minimum after non-linear optimization on [-0.598803 -6.67657 2.81002] dip = label: {1x306 cell} dip: [1x1 struct] Vdata: [306x1 double] Vmodel: [306x1 double] time: 0.0191 dimord: 'chan_time' grad: [1x1 struct] cfg: [1x1 struct] =================== End ====================================== ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From bps231 at NYU.EDU Wed Nov 7 01:18:35 2007 From: bps231 at NYU.EDU (Bernhard Staresina) Date: Wed, 7 Nov 2007 01:18:35 +0100 Subject: error in timelockstatistics Message-ID: Dear Fieldtrip experts, I have a brief question about “timelockstatistics”. Using only data from one electrode (i.e., I compute temporal, not spatial clusters for my stats), I get the following error message when I run the analysis: ========== ??? Reference to non-existent field 'inside'. Error in ==> fieldtrip-0.9.8/private/clusterstat at 125 tmp(cfg.inside) = postailobs; Error in ==> statistics_montecarlo at 319 stat = clusterstat(cfg, statrand, statobs); Error in ==> fieldtrip-0.9.8/private/statistics_wrapper at 245 [stat, cfg] = statmethod(cfg, dat, cfg.design); Error in ==> timelockstatistics at 102 [stat] = statistics_wrapper(cfg, varargin{:}); ========== When I follow the error messages, it turns out that changing the lines 30-37 in clusterstat.m from ========== if isfield(cfg, 'neighbours') && ~isempty(cfg.neighbours) channeighbstructmat = makechanneighbstructmat(cfg); issource = 0; else issource = 1; % cfg contains dim and inside that are needed for reshaping the data to a volume, and inside should behave as a index vector cfg = fixinside(cfg, 'index'); end ========== to ========== % if isfield(cfg, 'neighbours') && ~isempty(cfg.neighbours) channeighbstructmat = makechanneighbstructmat(cfg); issource = 0; % else % issource = 1; % % cfg contains dim and inside that are needed for reshaping the data to a volume, and inside should behave as a index vector % cfg = fixinside(cfg, 'index'); % end ========== seems to solve the problem – at least I get reasonable results without an error message. I’d rather not change the code, however, so if you could point me to any possible reason for this I’d be very grateful. Thanks in advance, Bernhard PS: Here are the configuration settings that produced the error before modifying the code: cfg = []; cfg.method = 'montecarlo'; cfg.statistic = 'indepsamplesT'; cfg.clusteralpha = 0.1; cfg.clusterstatistic = 'maxsum'; cfg.clustertail = 0; cfg.minnbchan = 0; cfg.ivar = 1; cfg.numrandomization = 100; design = zeros(1,size(cond1.trial,1)+size(cond2.trial,1)); design(1,1:size(cond1.trial,1)) = 1; design(1,(size(cond1.trial,1)+1:(size(cond1.trial,1)+size(cond2.trial,1)))) = 2; cfg.design = design; cfg.neighbours={}; cfg.channel = {'MT2'}; cfg.latency = [-0.3 1.0]; [stat] = timelockstatistics(cfg, cond1, cond2) ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From andrew.smart at NYU.EDU Mon Nov 12 20:41:00 2007 From: andrew.smart at NYU.EDU (Andrew Smart) Date: Mon, 12 Nov 2007 20:41:00 +0100 Subject: comparing groups of different sizes Message-ID: Hi, I would like to compare a clinical group with a control group in one condition using the cluster- based permuation test to see if there are significant differences between the groups. I tried the following design matrix acting as if the control and clinical group were two conditions, but get the error that the matrix is improperly specified: adhd=5; control=6; design=zeros(2,adhd+control); for i=1:adhd design(1,i)=i; end for i=1:control design(1,adhd+i)=i; end design(2,1:adhd)=1; design(2,adhd+1:2*adhd+1) = 2; cfg.design = design; cfg.uvar = 1; cfg.ivar = 2; [stat_controlvsadhd] = timelockstatistics(cfg, grandavgadhdnoise,grandavgcontrolnoise); Do you have any suggestions? Thank you Andrew ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From lwn_07 at YAHOO.COM.CN Tue Nov 13 09:59:30 2007 From: lwn_07 at YAHOO.COM.CN (=?GB2312?Q?Weina_Li?=) Date: Tue, 13 Nov 2007 09:59:30 +0100 Subject: Help_about 'time-frequency represengtations of power' Message-ID: hello! I am a new learner in MEG signal processing by using fieldtrip. And I need some help in understanding the tutorials of time-frequency represengtations of power. In the tutorials of calculating TFRs with frequency dependent window length,there is a sentence "The analysis is best done by first selecting the numbers of cycles per time window which will be the same for all frequencies"; and "When choosing this parameter it is important that a full number of cycles fit within the time-window for a given frequency". ---so what is 'cycles' mean? How can explain it? and "cfg.t_ftimwin = 7./cfg.foi; % 7 cycles per time window" ---then does the cycles has any relation to the frequency of interest? How should I select the number of cycles, is there a rule? Thanks! Weina Li Chongqing,China ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From maris at NICI.RU.NL Wed Nov 21 10:48:55 2007 From: maris at NICI.RU.NL (Eric Maris) Date: Wed, 21 Nov 2007 10:48:55 +0100 Subject: comparing groups of different sizes In-Reply-To: Message-ID: Hi Andrew, > I would like to compare a clinical group with a control group in one condition using > the cluster- > based permuation test to see if there are significant differences between the groups. > > I tried the following design matrix acting as if the control and clinical group were > two conditions, > but get the error that the matrix is improperly specified: > > adhd=5; > control=6; > > design=zeros(2,adhd+control); > > for i=1:adhd > design(1,i)=i; > end > for i=1:control > design(1,adhd+i)=i; > end Try this: for i=1:control design(1,adhd+i)=i+adhd; end Or, even simpler: design(1,:)=[1:(adhd+control)]; Good luck, Eric Maris dr. Eric Maris NICI/Biological Psychology and F.C. Donders Center for Cognitive NeuroImaging University of Nijmegen P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 (NICI) T:+31 24 3610754 (FCDC) F:+31 24 3616066 (NICI) E: maris at nici.ru.nl MSc Cognitive Neuroscience : www.ru.nl/master/cns/ > > design(2,1:adhd)=1; > design(2,adhd+1:2*adhd+1) = 2; > > cfg.design = design; > cfg.uvar = 1; > cfg.ivar = 2; > > [stat_controlvsadhd] = timelockstatistics(cfg, > grandavgadhdnoise,grandavgcontrolnoise); > > Do you have any suggestions? > > Thank you > Andrew > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/fcdonders/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From h.morgan at BANGOR.AC.UK Wed Nov 28 11:29:39 2007 From: h.morgan at BANGOR.AC.UK (Helen Morgan) Date: Wed, 28 Nov 2007 11:29:39 +0100 Subject: Time frequency statistics - comparing 3 conditions Message-ID: Hi, I wonder if anyone can give me some advice about the appropriate type of analysis for my data set. I am currently analysing data from a repeated-measures design, in which there are three conditions: two are single tasks, and the third is a dual task consisting of both single tasks. I have obtained TFRs (using the multitaper method) for each condition, showing relative increase/decrease in power. However, I am uncertain which type of statistical analysis to use for this data. The single tasks seem to produce a different pattern of activity, and I have compared them with a cluster-based permutation test using a t-statistic (using 'freqstatistics' with the 'montecarlo' method). However, the dual task is expected to consist of a combination of the activity patterns for both single tasks (and possibly some kind of additional integration process). so comparing this to each of the two single tasks using a t-statistic may not be suitable. An F test does not provide enough information and would need to be followed by t-tests anyway. The other alternative seems to be using a statistic based on linear regression; that is, to evaluate whether the dual task activity is a mix of both single tasks. Can anyone recommend an unbiased way to analyse this kind of data using the functions implemented in fieldtrip? I would be very grateful for any ideas. Thanks, Helen ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From michael.wibral at WEB.DE Wed Nov 28 12:56:50 2007 From: michael.wibral at WEB.DE (Michael Wibral) Date: Wed, 28 Nov 2007 12:56:50 +0100 Subject: Time frequency statistics - comparing 3 conditions Message-ID: Hi Helen, you wrote:" The other alternative seems to be using a statistic based on linear regression; that is, to evaluate whether the dual task activity is a mix of both single tasks..." comparing TFRs of this kind of triple task sets is actually a fundamental mathematical problem. Say you have task 3 that is a combination of tasks 1and 2 and you want to test wether activity(3) is more or less than the sum of activity(1) and activity(2). The problem is that when you compute TFRs you are adding/avaraging the amplitude/power values over trials or tasks which is phase INSENSITIVE as is everything that you do afterwards (i.e. summing or regressing). This is fundamentally different in task 3: here the activties induced by both subtasks are added phase sensitively within each trials, i.e. the signals are added physically inside the head, no matter how you later analyse them. Later power/amplitude analysis will not get rid of any phase sensitive effects in this "in-the-head addition" first step. In mathematical terms: While it is true that FFT(a+b) = FFT(a) + FFT(b) this holds only for the complex values (linearity of the fourier transform); for the amplitudes (or power) the following is true: |FFT(a+b)| <= |FFT(a)| + |FFT(b)| (i.e. this is your null hypothesis) Hence, you can only test whether this expectation is violated by an interaction of the two tasks in terms of power INCREASES: |FFT(task3)|>|FFT(task1)|+|FFT(task2)| ? (alternative hypothesis) Any differences in the opposite direction (i.e. power decreases) are meaningless! You can of course sum the full (complex valued) FFTs in each trial of task 1 and 2 over first to mimick the phase sensitivity of the "in-the-head" summation when both task elements are performed in task3. You could subsequently take the average (of the comlex valued summation results) over trials and compare this to the average of the FFTs (complex valued) of task3. For the comparison you would of course have to take something like the real part, (imaginary part, amplitude, power,...) where '>' or '<' make sense. However, in the end this would be more or less the same as comparing the ERPs (because they are just the phase sensitive sums): ERP(task1 + task2) <=> ERP(task3)? I hope the above made some sense. If not don't not hesitate to ask any further questions. If any list member would like to comment on this I'd be happy to hear some feedback. Best Regards, Michael P.S.: The math of the problem is the same that prevents the separation of time-frequency power in evoked (possible) and 'purely induced' activity (impossible) that people sometimes ask for. > -----Ursprüngliche Nachricht----- > Von: FieldTrip discussion list > Gesendet: 28.11.07 11:33:05 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: [FIELDTRIP] Time frequency statistics - comparing 3 conditions > > Hi, > I wonder if anyone can give me some advice about the appropriate type of > analysis for my data set. > I am currently analysing data from a repeated-measures design, in which > there are three conditions: two are single tasks, and the third is a dual > task consisting of both single tasks. I have obtained TFRs (using the > multitaper method) for each condition, showing relative increase/decrease in > power. However, I am uncertain which type of statistical analysis to use for > this data. The single tasks seem to produce a different pattern of activity, > and I have compared them with a cluster-based permutation test using a > t-statistic (using 'freqstatistics' with the 'montecarlo' method). However, > the dual task is expected to consist of a combination of the activity > patterns for both single tasks (and possibly some kind of additional > integration process). so comparing this to each of the two single tasks > using a t-statistic may not be suitable. An F test does not provide enough > information and would need to be followed by t-tests anyway. The other > alternative seems to be using a statistic based on linear regression; that > is, to evaluate whether the dual task activity is a mix of both single tasks. > Can anyone recommend an unbiased way to analyse this kind of data using the > functions implemented in fieldtrip? I would be very grateful for any ideas. > Thanks, > Helen > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 443 bytes Desc: not available URL: From marie at PSY.GLA.AC.UK Mon Nov 5 17:09:25 2007 From: marie at PSY.GLA.AC.UK (Marie Smith) Date: Mon, 5 Nov 2007 16:09:25 +0000 Subject: 3 RA job adverts Message-ID: > UNIVERSITY OF GLASGOW > DEPARTMENT OF PSYCHOLOGY > Postdoctoral Research Assistants (3 posts) > £29139 - £32796 Per Annum > REF #See Below > ESRC/MRC project “Social Interactions: A Cognitive Neurosciences > Approach” > > The project will investigate (1) the immediate processing of social > signals from the voice, face and bodily movement, (2) how such > signals support interactive alignment of social behaviours > (associated with pupil dilation, blinking, yawning etc.), and, (3) > the mechanisms that underlie joint attention and action. > > (1) Ref: 13805/DPO/A3 > > Applications are invited for a Research Assistant to work with > Professor Pascal Belin. The successful candidate will contribute to > the design of auditory behavioural, fMRI and EEG experiments; > collect the data with a state of the art fMRI system; apply cutting > edge techniques to analyse brain signals in the time and frequency > domain and relate them to behavioural measures of voice perception. > This post is available from 1 January 2008, funding is available > for up to three years in the first instance. > > You will be qualified, with a PhD in cognitive neuroscience or a > related discipline. You will also have experience of running > psychophysical, cognitive and brainimaging experiments, with > experience in fMRI data collection and analysis. You will have good > programming skills, particularly with MATLAB and will be > experienced in sound processing, signal analysis in the time and > frequency domain. You should also have a strong interest in > pursuing a research career. > > Informal enquiries may be made to Professor Pascal Belin (+44 (0) > 141 330 4629) > email: p.belin at psy.gla.ac.uk . > > > (2) Ref: 13808/DPO/A3 > > Applications are invited for a Research Assistant to work with > Professors Philippe Schyns and Joachim Gross. The successful > candidate will contribute to the design of event-related MEG > experiments; collect the data with a state of the art MEG system; > apply cutting edge techniques to analyse brain signals in the time > and frequency domain; solve the inverse problem in order to > identify processing networks; and reverse correlate brain activity > with facial features. This post is available from 1 January 2008. > > You will be qualified, with a PhD, or equivalent, in cognitive > neuroscience or a related discipline. You will also have experience > of running psychophysical, cognitive and brainimaging experiments, > with experience in MEG and/or EEG date collection and analysis. You > will have excellent programming skills, particularly with MATLAB > and will be experienced in image processing, signal analysis in the > time and frequency domain, the inverse-problem and beamforming / > source localisation methods. Finally you should have a strong > interest in pursuing a research career. > > Informal enquiries may be made to Professor P Schyns, (+44 (0)141 > 330 4937); > e-mail p.schyns at psy.gla.ac.uk and/or Professor J Gross (+44 (0)141 > 330 3947) email j.gross at psy.gla.ac.uk . > > > (3) Ref: 13804/DPO/A3 > > Applications are invited for a Research Assistant to work with Dr. > Hartmut Leuthold. The successful candidate will contribute to > running experiments on joint attention and action and have a > special interest and/or experience in Cognitive Neuroscience (e.g., > in EEG, fMRI, MEG, TMS). > > You will be qualified, with a PhD, or equivalent, in cognitive > neuroscience or a related discipline. You will also have experience > of running psychophysical, cognitive and brainimaging experiments, > with experience in MEG and/or EEG date collection and analysis. You > will have good programming skills, particularly with MATLAB. You > should also have a strong interest in pursuing a research career. > > Informal enquiries may be made to Dr. Hartmut Leuthold (+44 (0)141 > 330 6847) email h.leuthold at psy.gla.ac.uk . > > General enquiries for all 3 posts to Heather Robertson > (h.robertson at psy.gla.ac.uk), Department of Psychology, Tel No 0141 > 330 6173. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From soren.r.christensen at GSK.COM Mon Nov 5 18:05:35 2007 From: soren.r.christensen at GSK.COM (Soren Rahn Christensen) Date: Mon, 5 Nov 2007 17:05:35 +0000 Subject: Soren R Christensen is out of the office. Message-ID: I will be out of the office starting 01-Nov-2007 and will not return until 12-Nov-2007. Back Monday 12th October. I will read e-mail, though. ----------------------------------------------------------- This e-mail was sent by GlaxoSmithKline Services Unlimited (registered in England and Wales No. 1047315), which is a member of the GlaxoSmithKline group of companies. The registered address of GlaxoSmithKline Services Unlimited is 980 Great West Road, Brentford, Middlesex TW8 9GS. ----------------------------------------------------------- ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From matuhasi at KUHP.KYOTO-U.AC.JP Tue Nov 6 07:38:53 2007 From: matuhasi at KUHP.KYOTO-U.AC.JP (=?SHIFT_JIS?Q?Masao_Matsuhashi?=) Date: Tue, 6 Nov 2007 07:38:53 +0100 Subject: Phantom Dipole on VectorView Message-ID: Dear Fieldtrip users (especialy the Neuromag users), I want to use Fieldtrip to analyze my Vectorview data. Fist I tried a phantom recording and performed an ECD analysis, but the result does not match. Please see the example below. The difference within 5 mm may be ok, but the y-axis... Would you please tell me what is wrong? One concern may be that the Neuromag coordinate frame is different from CTF coordinate, but this does not matter if I do not try to overlay the source onto MRI, am I right? SSP significantly distorts the waveform of this huge field, so I am fine without it. Thank you in advance, Masao Phantom Dipole #10 at (0.0, -4.86, 2.35) Estimated position: (-0.598803 -6.67657 2.81002) Raw data file: Dip10_1000nA_std_03_raw.fif MATLAB Version 7.5.0.342 (R2007b) fieldtrip-20071105 =================== Procedure =============================== sRawFIFF_name='Dip10_1000nA_std_03_raw.fif'; pre=0.05; post=0.1; % create trial info hdr = read_fcdc_header(sRawFIFF_name); prep=round(pre*hdr.Fs); postp=round(post*hdr.Fs); data= read_fcdc_data(sRawFIFF_name,'chanindx',315); data=reshape(data,numel(data),1); trig = find(diff(data)>0); trig = trig(2:end-1); %read data cfg = []; cfg.trl = [trig-prep,trig+postp,repmat(-prep,size(trig))]; cfg.dataset = sRawFIFF_name; cfg.datatype = 'continuous'; cfg.blc = 'yes'; cfg.blcwindow = [-pre 0]; cfg.channel = 'all'; % 'MEG' does not work data = preprocessing(cfg); % average cfg = []; avg = timelockanalysis(cfg, data); % show waveform figure plot(1000*avg.time, avg.avg) % convert time to ms xlabel('time (ms)') ylabel('field amplitude (T)') axis tight grid on % fit a dipole cfg = []; cfg.latency = [0.019]; cfg.numdipoles = 1; cfg.gradfile = sRawFIFF_name; cfg.vol.o = [0,0,0]; % in cm cfg.vol.r = 7; % should not matter cfg.grid.xgrid = -7:1:7; cfg.grid.ygrid = -7:1:7; cfg.grid.zgrid = -1:1:8; dip = dipolefitting(cfg, avg) =================== Output =================================== ntrl = 111 reading and preprocessing reading and preprocessing trial 1 from 111 reading and preprocessing trial 2 from 111 ... reading and preprocessing trial 111 from 111 the input is raw data with 315 channels and 111 trials applying preprocessing options averaging trials averaging trial 1 of 111 averaging trial 2 of 111 ... averaging trial 111 of 111 the input is timelock data with 315 channels and 158 timebins using headmodel specified in the configuration reading gradiometers from file Dip10_1000nA_std_03_raw.fif selected 306 channels selected 1 topographies 900 dipoles inside, 1348 dipoles outside brain scanning grid scanning grid location 1/900 scanning grid location 2/900 ... scanning grid location 900/900 found minimum after scanning on grid point [0 -6 3] First-order Iteration Func-count f(x) Step-size optimality 0 4 0.848031 0.0232 1 12 0.842257 10 0.0127 2 16 0.837597 1 0.00289 3 20 0.837204 1 0.00185 4 24 0.837115 1 0.000602 5 28 0.837106 1 0.000173 6 32 0.837105 1 4.07e-006 7 36 0.837105 1 1.86e-007 8 40 0.837105 1 1.04e-007 9 48 0.837105 0.407507 2.98e-008 Optimization cannot make further progress: relative change in x less than options.TolX. found minimum after non-linear optimization on [-0.598803 -6.67657 2.81002] dip = label: {1x306 cell} dip: [1x1 struct] Vdata: [306x1 double] Vmodel: [306x1 double] time: 0.0191 dimord: 'chan_time' grad: [1x1 struct] cfg: [1x1 struct] =================== End ====================================== ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From bps231 at NYU.EDU Wed Nov 7 01:18:35 2007 From: bps231 at NYU.EDU (Bernhard Staresina) Date: Wed, 7 Nov 2007 01:18:35 +0100 Subject: error in timelockstatistics Message-ID: Dear Fieldtrip experts, I have a brief question about “timelockstatistics”. Using only data from one electrode (i.e., I compute temporal, not spatial clusters for my stats), I get the following error message when I run the analysis: ========== ??? Reference to non-existent field 'inside'. Error in ==> fieldtrip-0.9.8/private/clusterstat at 125 tmp(cfg.inside) = postailobs; Error in ==> statistics_montecarlo at 319 stat = clusterstat(cfg, statrand, statobs); Error in ==> fieldtrip-0.9.8/private/statistics_wrapper at 245 [stat, cfg] = statmethod(cfg, dat, cfg.design); Error in ==> timelockstatistics at 102 [stat] = statistics_wrapper(cfg, varargin{:}); ========== When I follow the error messages, it turns out that changing the lines 30-37 in clusterstat.m from ========== if isfield(cfg, 'neighbours') && ~isempty(cfg.neighbours) channeighbstructmat = makechanneighbstructmat(cfg); issource = 0; else issource = 1; % cfg contains dim and inside that are needed for reshaping the data to a volume, and inside should behave as a index vector cfg = fixinside(cfg, 'index'); end ========== to ========== % if isfield(cfg, 'neighbours') && ~isempty(cfg.neighbours) channeighbstructmat = makechanneighbstructmat(cfg); issource = 0; % else % issource = 1; % % cfg contains dim and inside that are needed for reshaping the data to a volume, and inside should behave as a index vector % cfg = fixinside(cfg, 'index'); % end ========== seems to solve the problem – at least I get reasonable results without an error message. I’d rather not change the code, however, so if you could point me to any possible reason for this I’d be very grateful. Thanks in advance, Bernhard PS: Here are the configuration settings that produced the error before modifying the code: cfg = []; cfg.method = 'montecarlo'; cfg.statistic = 'indepsamplesT'; cfg.clusteralpha = 0.1; cfg.clusterstatistic = 'maxsum'; cfg.clustertail = 0; cfg.minnbchan = 0; cfg.ivar = 1; cfg.numrandomization = 100; design = zeros(1,size(cond1.trial,1)+size(cond2.trial,1)); design(1,1:size(cond1.trial,1)) = 1; design(1,(size(cond1.trial,1)+1:(size(cond1.trial,1)+size(cond2.trial,1)))) = 2; cfg.design = design; cfg.neighbours={}; cfg.channel = {'MT2'}; cfg.latency = [-0.3 1.0]; [stat] = timelockstatistics(cfg, cond1, cond2) ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From andrew.smart at NYU.EDU Mon Nov 12 20:41:00 2007 From: andrew.smart at NYU.EDU (Andrew Smart) Date: Mon, 12 Nov 2007 20:41:00 +0100 Subject: comparing groups of different sizes Message-ID: Hi, I would like to compare a clinical group with a control group in one condition using the cluster- based permuation test to see if there are significant differences between the groups. I tried the following design matrix acting as if the control and clinical group were two conditions, but get the error that the matrix is improperly specified: adhd=5; control=6; design=zeros(2,adhd+control); for i=1:adhd design(1,i)=i; end for i=1:control design(1,adhd+i)=i; end design(2,1:adhd)=1; design(2,adhd+1:2*adhd+1) = 2; cfg.design = design; cfg.uvar = 1; cfg.ivar = 2; [stat_controlvsadhd] = timelockstatistics(cfg, grandavgadhdnoise,grandavgcontrolnoise); Do you have any suggestions? Thank you Andrew ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From lwn_07 at YAHOO.COM.CN Tue Nov 13 09:59:30 2007 From: lwn_07 at YAHOO.COM.CN (=?GB2312?Q?Weina_Li?=) Date: Tue, 13 Nov 2007 09:59:30 +0100 Subject: Help_about 'time-frequency represengtations of power' Message-ID: hello! I am a new learner in MEG signal processing by using fieldtrip. And I need some help in understanding the tutorials of time-frequency represengtations of power. In the tutorials of calculating TFRs with frequency dependent window length,there is a sentence "The analysis is best done by first selecting the numbers of cycles per time window which will be the same for all frequencies"; and "When choosing this parameter it is important that a full number of cycles fit within the time-window for a given frequency". ---so what is 'cycles' mean? How can explain it? and "cfg.t_ftimwin = 7./cfg.foi; % 7 cycles per time window" ---then does the cycles has any relation to the frequency of interest? How should I select the number of cycles, is there a rule? Thanks! Weina Li Chongqing,China ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From maris at NICI.RU.NL Wed Nov 21 10:48:55 2007 From: maris at NICI.RU.NL (Eric Maris) Date: Wed, 21 Nov 2007 10:48:55 +0100 Subject: comparing groups of different sizes In-Reply-To: Message-ID: Hi Andrew, > I would like to compare a clinical group with a control group in one condition using > the cluster- > based permuation test to see if there are significant differences between the groups. > > I tried the following design matrix acting as if the control and clinical group were > two conditions, > but get the error that the matrix is improperly specified: > > adhd=5; > control=6; > > design=zeros(2,adhd+control); > > for i=1:adhd > design(1,i)=i; > end > for i=1:control > design(1,adhd+i)=i; > end Try this: for i=1:control design(1,adhd+i)=i+adhd; end Or, even simpler: design(1,:)=[1:(adhd+control)]; Good luck, Eric Maris dr. Eric Maris NICI/Biological Psychology and F.C. Donders Center for Cognitive NeuroImaging University of Nijmegen P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 (NICI) T:+31 24 3610754 (FCDC) F:+31 24 3616066 (NICI) E: maris at nici.ru.nl MSc Cognitive Neuroscience : www.ru.nl/master/cns/ > > design(2,1:adhd)=1; > design(2,adhd+1:2*adhd+1) = 2; > > cfg.design = design; > cfg.uvar = 1; > cfg.ivar = 2; > > [stat_controlvsadhd] = timelockstatistics(cfg, > grandavgadhdnoise,grandavgcontrolnoise); > > Do you have any suggestions? > > Thank you > Andrew > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/fcdonders/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From h.morgan at BANGOR.AC.UK Wed Nov 28 11:29:39 2007 From: h.morgan at BANGOR.AC.UK (Helen Morgan) Date: Wed, 28 Nov 2007 11:29:39 +0100 Subject: Time frequency statistics - comparing 3 conditions Message-ID: Hi, I wonder if anyone can give me some advice about the appropriate type of analysis for my data set. I am currently analysing data from a repeated-measures design, in which there are three conditions: two are single tasks, and the third is a dual task consisting of both single tasks. I have obtained TFRs (using the multitaper method) for each condition, showing relative increase/decrease in power. However, I am uncertain which type of statistical analysis to use for this data. The single tasks seem to produce a different pattern of activity, and I have compared them with a cluster-based permutation test using a t-statistic (using 'freqstatistics' with the 'montecarlo' method). However, the dual task is expected to consist of a combination of the activity patterns for both single tasks (and possibly some kind of additional integration process). so comparing this to each of the two single tasks using a t-statistic may not be suitable. An F test does not provide enough information and would need to be followed by t-tests anyway. The other alternative seems to be using a statistic based on linear regression; that is, to evaluate whether the dual task activity is a mix of both single tasks. Can anyone recommend an unbiased way to analyse this kind of data using the functions implemented in fieldtrip? I would be very grateful for any ideas. Thanks, Helen ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From michael.wibral at WEB.DE Wed Nov 28 12:56:50 2007 From: michael.wibral at WEB.DE (Michael Wibral) Date: Wed, 28 Nov 2007 12:56:50 +0100 Subject: Time frequency statistics - comparing 3 conditions Message-ID: Hi Helen, you wrote:" The other alternative seems to be using a statistic based on linear regression; that is, to evaluate whether the dual task activity is a mix of both single tasks..." comparing TFRs of this kind of triple task sets is actually a fundamental mathematical problem. Say you have task 3 that is a combination of tasks 1and 2 and you want to test wether activity(3) is more or less than the sum of activity(1) and activity(2). The problem is that when you compute TFRs you are adding/avaraging the amplitude/power values over trials or tasks which is phase INSENSITIVE as is everything that you do afterwards (i.e. summing or regressing). This is fundamentally different in task 3: here the activties induced by both subtasks are added phase sensitively within each trials, i.e. the signals are added physically inside the head, no matter how you later analyse them. Later power/amplitude analysis will not get rid of any phase sensitive effects in this "in-the-head addition" first step. In mathematical terms: While it is true that FFT(a+b) = FFT(a) + FFT(b) this holds only for the complex values (linearity of the fourier transform); for the amplitudes (or power) the following is true: |FFT(a+b)| <= |FFT(a)| + |FFT(b)| (i.e. this is your null hypothesis) Hence, you can only test whether this expectation is violated by an interaction of the two tasks in terms of power INCREASES: |FFT(task3)|>|FFT(task1)|+|FFT(task2)| ? (alternative hypothesis) Any differences in the opposite direction (i.e. power decreases) are meaningless! You can of course sum the full (complex valued) FFTs in each trial of task 1 and 2 over first to mimick the phase sensitivity of the "in-the-head" summation when both task elements are performed in task3. You could subsequently take the average (of the comlex valued summation results) over trials and compare this to the average of the FFTs (complex valued) of task3. For the comparison you would of course have to take something like the real part, (imaginary part, amplitude, power,...) where '>' or '<' make sense. However, in the end this would be more or less the same as comparing the ERPs (because they are just the phase sensitive sums): ERP(task1 + task2) <=> ERP(task3)? I hope the above made some sense. If not don't not hesitate to ask any further questions. If any list member would like to comment on this I'd be happy to hear some feedback. Best Regards, Michael P.S.: The math of the problem is the same that prevents the separation of time-frequency power in evoked (possible) and 'purely induced' activity (impossible) that people sometimes ask for. > -----Ursprüngliche Nachricht----- > Von: FieldTrip discussion list > Gesendet: 28.11.07 11:33:05 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: [FIELDTRIP] Time frequency statistics - comparing 3 conditions > > Hi, > I wonder if anyone can give me some advice about the appropriate type of > analysis for my data set. > I am currently analysing data from a repeated-measures design, in which > there are three conditions: two are single tasks, and the third is a dual > task consisting of both single tasks. I have obtained TFRs (using the > multitaper method) for each condition, showing relative increase/decrease in > power. However, I am uncertain which type of statistical analysis to use for > this data. The single tasks seem to produce a different pattern of activity, > and I have compared them with a cluster-based permutation test using a > t-statistic (using 'freqstatistics' with the 'montecarlo' method). However, > the dual task is expected to consist of a combination of the activity > patterns for both single tasks (and possibly some kind of additional > integration process). so comparing this to each of the two single tasks > using a t-statistic may not be suitable. An F test does not provide enough > information and would need to be followed by t-tests anyway. The other > alternative seems to be using a statistic based on linear regression; that > is, to evaluate whether the dual task activity is a mix of both single tasks. > Can anyone recommend an unbiased way to analyse this kind of data using the > functions implemented in fieldtrip? I would be very grateful for any ideas. > Thanks, > Helen > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 443 bytes Desc: not available URL: From marie at PSY.GLA.AC.UK Mon Nov 5 17:09:25 2007 From: marie at PSY.GLA.AC.UK (Marie Smith) Date: Mon, 5 Nov 2007 16:09:25 +0000 Subject: 3 RA job adverts Message-ID: > UNIVERSITY OF GLASGOW > DEPARTMENT OF PSYCHOLOGY > Postdoctoral Research Assistants (3 posts) > £29139 - £32796 Per Annum > REF #See Below > ESRC/MRC project “Social Interactions: A Cognitive Neurosciences > Approach” > > The project will investigate (1) the immediate processing of social > signals from the voice, face and bodily movement, (2) how such > signals support interactive alignment of social behaviours > (associated with pupil dilation, blinking, yawning etc.), and, (3) > the mechanisms that underlie joint attention and action. > > (1) Ref: 13805/DPO/A3 > > Applications are invited for a Research Assistant to work with > Professor Pascal Belin. The successful candidate will contribute to > the design of auditory behavioural, fMRI and EEG experiments; > collect the data with a state of the art fMRI system; apply cutting > edge techniques to analyse brain signals in the time and frequency > domain and relate them to behavioural measures of voice perception. > This post is available from 1 January 2008, funding is available > for up to three years in the first instance. > > You will be qualified, with a PhD in cognitive neuroscience or a > related discipline. You will also have experience of running > psychophysical, cognitive and brainimaging experiments, with > experience in fMRI data collection and analysis. You will have good > programming skills, particularly with MATLAB and will be > experienced in sound processing, signal analysis in the time and > frequency domain. You should also have a strong interest in > pursuing a research career. > > Informal enquiries may be made to Professor Pascal Belin (+44 (0) > 141 330 4629) > email: p.belin at psy.gla.ac.uk . > > > (2) Ref: 13808/DPO/A3 > > Applications are invited for a Research Assistant to work with > Professors Philippe Schyns and Joachim Gross. The successful > candidate will contribute to the design of event-related MEG > experiments; collect the data with a state of the art MEG system; > apply cutting edge techniques to analyse brain signals in the time > and frequency domain; solve the inverse problem in order to > identify processing networks; and reverse correlate brain activity > with facial features. This post is available from 1 January 2008. > > You will be qualified, with a PhD, or equivalent, in cognitive > neuroscience or a related discipline. You will also have experience > of running psychophysical, cognitive and brainimaging experiments, > with experience in MEG and/or EEG date collection and analysis. You > will have excellent programming skills, particularly with MATLAB > and will be experienced in image processing, signal analysis in the > time and frequency domain, the inverse-problem and beamforming / > source localisation methods. Finally you should have a strong > interest in pursuing a research career. > > Informal enquiries may be made to Professor P Schyns, (+44 (0)141 > 330 4937); > e-mail p.schyns at psy.gla.ac.uk and/or Professor J Gross (+44 (0)141 > 330 3947) email j.gross at psy.gla.ac.uk . > > > (3) Ref: 13804/DPO/A3 > > Applications are invited for a Research Assistant to work with Dr. > Hartmut Leuthold. The successful candidate will contribute to > running experiments on joint attention and action and have a > special interest and/or experience in Cognitive Neuroscience (e.g., > in EEG, fMRI, MEG, TMS). > > You will be qualified, with a PhD, or equivalent, in cognitive > neuroscience or a related discipline. You will also have experience > of running psychophysical, cognitive and brainimaging experiments, > with experience in MEG and/or EEG date collection and analysis. You > will have good programming skills, particularly with MATLAB. You > should also have a strong interest in pursuing a research career. > > Informal enquiries may be made to Dr. Hartmut Leuthold (+44 (0)141 > 330 6847) email h.leuthold at psy.gla.ac.uk . > > General enquiries for all 3 posts to Heather Robertson > (h.robertson at psy.gla.ac.uk), Department of Psychology, Tel No 0141 > 330 6173. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From soren.r.christensen at GSK.COM Mon Nov 5 18:05:35 2007 From: soren.r.christensen at GSK.COM (Soren Rahn Christensen) Date: Mon, 5 Nov 2007 17:05:35 +0000 Subject: Soren R Christensen is out of the office. Message-ID: I will be out of the office starting 01-Nov-2007 and will not return until 12-Nov-2007. Back Monday 12th October. I will read e-mail, though. ----------------------------------------------------------- This e-mail was sent by GlaxoSmithKline Services Unlimited (registered in England and Wales No. 1047315), which is a member of the GlaxoSmithKline group of companies. The registered address of GlaxoSmithKline Services Unlimited is 980 Great West Road, Brentford, Middlesex TW8 9GS. ----------------------------------------------------------- ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From matuhasi at KUHP.KYOTO-U.AC.JP Tue Nov 6 07:38:53 2007 From: matuhasi at KUHP.KYOTO-U.AC.JP (=?SHIFT_JIS?Q?Masao_Matsuhashi?=) Date: Tue, 6 Nov 2007 07:38:53 +0100 Subject: Phantom Dipole on VectorView Message-ID: Dear Fieldtrip users (especialy the Neuromag users), I want to use Fieldtrip to analyze my Vectorview data. Fist I tried a phantom recording and performed an ECD analysis, but the result does not match. Please see the example below. The difference within 5 mm may be ok, but the y-axis... Would you please tell me what is wrong? One concern may be that the Neuromag coordinate frame is different from CTF coordinate, but this does not matter if I do not try to overlay the source onto MRI, am I right? SSP significantly distorts the waveform of this huge field, so I am fine without it. Thank you in advance, Masao Phantom Dipole #10 at (0.0, -4.86, 2.35) Estimated position: (-0.598803 -6.67657 2.81002) Raw data file: Dip10_1000nA_std_03_raw.fif MATLAB Version 7.5.0.342 (R2007b) fieldtrip-20071105 =================== Procedure =============================== sRawFIFF_name='Dip10_1000nA_std_03_raw.fif'; pre=0.05; post=0.1; % create trial info hdr = read_fcdc_header(sRawFIFF_name); prep=round(pre*hdr.Fs); postp=round(post*hdr.Fs); data= read_fcdc_data(sRawFIFF_name,'chanindx',315); data=reshape(data,numel(data),1); trig = find(diff(data)>0); trig = trig(2:end-1); %read data cfg = []; cfg.trl = [trig-prep,trig+postp,repmat(-prep,size(trig))]; cfg.dataset = sRawFIFF_name; cfg.datatype = 'continuous'; cfg.blc = 'yes'; cfg.blcwindow = [-pre 0]; cfg.channel = 'all'; % 'MEG' does not work data = preprocessing(cfg); % average cfg = []; avg = timelockanalysis(cfg, data); % show waveform figure plot(1000*avg.time, avg.avg) % convert time to ms xlabel('time (ms)') ylabel('field amplitude (T)') axis tight grid on % fit a dipole cfg = []; cfg.latency = [0.019]; cfg.numdipoles = 1; cfg.gradfile = sRawFIFF_name; cfg.vol.o = [0,0,0]; % in cm cfg.vol.r = 7; % should not matter cfg.grid.xgrid = -7:1:7; cfg.grid.ygrid = -7:1:7; cfg.grid.zgrid = -1:1:8; dip = dipolefitting(cfg, avg) =================== Output =================================== ntrl = 111 reading and preprocessing reading and preprocessing trial 1 from 111 reading and preprocessing trial 2 from 111 ... reading and preprocessing trial 111 from 111 the input is raw data with 315 channels and 111 trials applying preprocessing options averaging trials averaging trial 1 of 111 averaging trial 2 of 111 ... averaging trial 111 of 111 the input is timelock data with 315 channels and 158 timebins using headmodel specified in the configuration reading gradiometers from file Dip10_1000nA_std_03_raw.fif selected 306 channels selected 1 topographies 900 dipoles inside, 1348 dipoles outside brain scanning grid scanning grid location 1/900 scanning grid location 2/900 ... scanning grid location 900/900 found minimum after scanning on grid point [0 -6 3] First-order Iteration Func-count f(x) Step-size optimality 0 4 0.848031 0.0232 1 12 0.842257 10 0.0127 2 16 0.837597 1 0.00289 3 20 0.837204 1 0.00185 4 24 0.837115 1 0.000602 5 28 0.837106 1 0.000173 6 32 0.837105 1 4.07e-006 7 36 0.837105 1 1.86e-007 8 40 0.837105 1 1.04e-007 9 48 0.837105 0.407507 2.98e-008 Optimization cannot make further progress: relative change in x less than options.TolX. found minimum after non-linear optimization on [-0.598803 -6.67657 2.81002] dip = label: {1x306 cell} dip: [1x1 struct] Vdata: [306x1 double] Vmodel: [306x1 double] time: 0.0191 dimord: 'chan_time' grad: [1x1 struct] cfg: [1x1 struct] =================== End ====================================== ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From bps231 at NYU.EDU Wed Nov 7 01:18:35 2007 From: bps231 at NYU.EDU (Bernhard Staresina) Date: Wed, 7 Nov 2007 01:18:35 +0100 Subject: error in timelockstatistics Message-ID: Dear Fieldtrip experts, I have a brief question about “timelockstatistics”. Using only data from one electrode (i.e., I compute temporal, not spatial clusters for my stats), I get the following error message when I run the analysis: ========== ??? Reference to non-existent field 'inside'. Error in ==> fieldtrip-0.9.8/private/clusterstat at 125 tmp(cfg.inside) = postailobs; Error in ==> statistics_montecarlo at 319 stat = clusterstat(cfg, statrand, statobs); Error in ==> fieldtrip-0.9.8/private/statistics_wrapper at 245 [stat, cfg] = statmethod(cfg, dat, cfg.design); Error in ==> timelockstatistics at 102 [stat] = statistics_wrapper(cfg, varargin{:}); ========== When I follow the error messages, it turns out that changing the lines 30-37 in clusterstat.m from ========== if isfield(cfg, 'neighbours') && ~isempty(cfg.neighbours) channeighbstructmat = makechanneighbstructmat(cfg); issource = 0; else issource = 1; % cfg contains dim and inside that are needed for reshaping the data to a volume, and inside should behave as a index vector cfg = fixinside(cfg, 'index'); end ========== to ========== % if isfield(cfg, 'neighbours') && ~isempty(cfg.neighbours) channeighbstructmat = makechanneighbstructmat(cfg); issource = 0; % else % issource = 1; % % cfg contains dim and inside that are needed for reshaping the data to a volume, and inside should behave as a index vector % cfg = fixinside(cfg, 'index'); % end ========== seems to solve the problem – at least I get reasonable results without an error message. I’d rather not change the code, however, so if you could point me to any possible reason for this I’d be very grateful. Thanks in advance, Bernhard PS: Here are the configuration settings that produced the error before modifying the code: cfg = []; cfg.method = 'montecarlo'; cfg.statistic = 'indepsamplesT'; cfg.clusteralpha = 0.1; cfg.clusterstatistic = 'maxsum'; cfg.clustertail = 0; cfg.minnbchan = 0; cfg.ivar = 1; cfg.numrandomization = 100; design = zeros(1,size(cond1.trial,1)+size(cond2.trial,1)); design(1,1:size(cond1.trial,1)) = 1; design(1,(size(cond1.trial,1)+1:(size(cond1.trial,1)+size(cond2.trial,1)))) = 2; cfg.design = design; cfg.neighbours={}; cfg.channel = {'MT2'}; cfg.latency = [-0.3 1.0]; [stat] = timelockstatistics(cfg, cond1, cond2) ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From andrew.smart at NYU.EDU Mon Nov 12 20:41:00 2007 From: andrew.smart at NYU.EDU (Andrew Smart) Date: Mon, 12 Nov 2007 20:41:00 +0100 Subject: comparing groups of different sizes Message-ID: Hi, I would like to compare a clinical group with a control group in one condition using the cluster- based permuation test to see if there are significant differences between the groups. I tried the following design matrix acting as if the control and clinical group were two conditions, but get the error that the matrix is improperly specified: adhd=5; control=6; design=zeros(2,adhd+control); for i=1:adhd design(1,i)=i; end for i=1:control design(1,adhd+i)=i; end design(2,1:adhd)=1; design(2,adhd+1:2*adhd+1) = 2; cfg.design = design; cfg.uvar = 1; cfg.ivar = 2; [stat_controlvsadhd] = timelockstatistics(cfg, grandavgadhdnoise,grandavgcontrolnoise); Do you have any suggestions? Thank you Andrew ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From lwn_07 at YAHOO.COM.CN Tue Nov 13 09:59:30 2007 From: lwn_07 at YAHOO.COM.CN (=?GB2312?Q?Weina_Li?=) Date: Tue, 13 Nov 2007 09:59:30 +0100 Subject: Help_about 'time-frequency represengtations of power' Message-ID: hello! I am a new learner in MEG signal processing by using fieldtrip. And I need some help in understanding the tutorials of time-frequency represengtations of power. In the tutorials of calculating TFRs with frequency dependent window length,there is a sentence "The analysis is best done by first selecting the numbers of cycles per time window which will be the same for all frequencies"; and "When choosing this parameter it is important that a full number of cycles fit within the time-window for a given frequency". ---so what is 'cycles' mean? How can explain it? and "cfg.t_ftimwin = 7./cfg.foi; % 7 cycles per time window" ---then does the cycles has any relation to the frequency of interest? How should I select the number of cycles, is there a rule? Thanks! Weina Li Chongqing,China ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From maris at NICI.RU.NL Wed Nov 21 10:48:55 2007 From: maris at NICI.RU.NL (Eric Maris) Date: Wed, 21 Nov 2007 10:48:55 +0100 Subject: comparing groups of different sizes In-Reply-To: Message-ID: Hi Andrew, > I would like to compare a clinical group with a control group in one condition using > the cluster- > based permuation test to see if there are significant differences between the groups. > > I tried the following design matrix acting as if the control and clinical group were > two conditions, > but get the error that the matrix is improperly specified: > > adhd=5; > control=6; > > design=zeros(2,adhd+control); > > for i=1:adhd > design(1,i)=i; > end > for i=1:control > design(1,adhd+i)=i; > end Try this: for i=1:control design(1,adhd+i)=i+adhd; end Or, even simpler: design(1,:)=[1:(adhd+control)]; Good luck, Eric Maris dr. Eric Maris NICI/Biological Psychology and F.C. Donders Center for Cognitive NeuroImaging University of Nijmegen P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 (NICI) T:+31 24 3610754 (FCDC) F:+31 24 3616066 (NICI) E: maris at nici.ru.nl MSc Cognitive Neuroscience : www.ru.nl/master/cns/ > > design(2,1:adhd)=1; > design(2,adhd+1:2*adhd+1) = 2; > > cfg.design = design; > cfg.uvar = 1; > cfg.ivar = 2; > > [stat_controlvsadhd] = timelockstatistics(cfg, > grandavgadhdnoise,grandavgcontrolnoise); > > Do you have any suggestions? > > Thank you > Andrew > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/fcdonders/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From h.morgan at BANGOR.AC.UK Wed Nov 28 11:29:39 2007 From: h.morgan at BANGOR.AC.UK (Helen Morgan) Date: Wed, 28 Nov 2007 11:29:39 +0100 Subject: Time frequency statistics - comparing 3 conditions Message-ID: Hi, I wonder if anyone can give me some advice about the appropriate type of analysis for my data set. I am currently analysing data from a repeated-measures design, in which there are three conditions: two are single tasks, and the third is a dual task consisting of both single tasks. I have obtained TFRs (using the multitaper method) for each condition, showing relative increase/decrease in power. However, I am uncertain which type of statistical analysis to use for this data. The single tasks seem to produce a different pattern of activity, and I have compared them with a cluster-based permutation test using a t-statistic (using 'freqstatistics' with the 'montecarlo' method). However, the dual task is expected to consist of a combination of the activity patterns for both single tasks (and possibly some kind of additional integration process). so comparing this to each of the two single tasks using a t-statistic may not be suitable. An F test does not provide enough information and would need to be followed by t-tests anyway. The other alternative seems to be using a statistic based on linear regression; that is, to evaluate whether the dual task activity is a mix of both single tasks. Can anyone recommend an unbiased way to analyse this kind of data using the functions implemented in fieldtrip? I would be very grateful for any ideas. Thanks, Helen ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. From michael.wibral at WEB.DE Wed Nov 28 12:56:50 2007 From: michael.wibral at WEB.DE (Michael Wibral) Date: Wed, 28 Nov 2007 12:56:50 +0100 Subject: Time frequency statistics - comparing 3 conditions Message-ID: Hi Helen, you wrote:" The other alternative seems to be using a statistic based on linear regression; that is, to evaluate whether the dual task activity is a mix of both single tasks..." comparing TFRs of this kind of triple task sets is actually a fundamental mathematical problem. Say you have task 3 that is a combination of tasks 1and 2 and you want to test wether activity(3) is more or less than the sum of activity(1) and activity(2). The problem is that when you compute TFRs you are adding/avaraging the amplitude/power values over trials or tasks which is phase INSENSITIVE as is everything that you do afterwards (i.e. summing or regressing). This is fundamentally different in task 3: here the activties induced by both subtasks are added phase sensitively within each trials, i.e. the signals are added physically inside the head, no matter how you later analyse them. Later power/amplitude analysis will not get rid of any phase sensitive effects in this "in-the-head addition" first step. In mathematical terms: While it is true that FFT(a+b) = FFT(a) + FFT(b) this holds only for the complex values (linearity of the fourier transform); for the amplitudes (or power) the following is true: |FFT(a+b)| <= |FFT(a)| + |FFT(b)| (i.e. this is your null hypothesis) Hence, you can only test whether this expectation is violated by an interaction of the two tasks in terms of power INCREASES: |FFT(task3)|>|FFT(task1)|+|FFT(task2)| ? (alternative hypothesis) Any differences in the opposite direction (i.e. power decreases) are meaningless! You can of course sum the full (complex valued) FFTs in each trial of task 1 and 2 over first to mimick the phase sensitivity of the "in-the-head" summation when both task elements are performed in task3. You could subsequently take the average (of the comlex valued summation results) over trials and compare this to the average of the FFTs (complex valued) of task3. For the comparison you would of course have to take something like the real part, (imaginary part, amplitude, power,...) where '>' or '<' make sense. However, in the end this would be more or less the same as comparing the ERPs (because they are just the phase sensitive sums): ERP(task1 + task2) <=> ERP(task3)? I hope the above made some sense. If not don't not hesitate to ask any further questions. If any list member would like to comment on this I'd be happy to hear some feedback. Best Regards, Michael P.S.: The math of the problem is the same that prevents the separation of time-frequency power in evoked (possible) and 'purely induced' activity (impossible) that people sometimes ask for. > -----Ursprüngliche Nachricht----- > Von: FieldTrip discussion list > Gesendet: 28.11.07 11:33:05 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: [FIELDTRIP] Time frequency statistics - comparing 3 conditions > > Hi, > I wonder if anyone can give me some advice about the appropriate type of > analysis for my data set. > I am currently analysing data from a repeated-measures design, in which > there are three conditions: two are single tasks, and the third is a dual > task consisting of both single tasks. I have obtained TFRs (using the > multitaper method) for each condition, showing relative increase/decrease in > power. However, I am uncertain which type of statistical analysis to use for > this data. The single tasks seem to produce a different pattern of activity, > and I have compared them with a cluster-based permutation test using a > t-statistic (using 'freqstatistics' with the 'montecarlo' method). However, > the dual task is expected to consist of a combination of the activity > patterns for both single tasks (and possibly some kind of additional > integration process). so comparing this to each of the two single tasks > using a t-statistic may not be suitable. An F test does not provide enough > information and would need to be followed by t-tests anyway. The other > alternative seems to be using a statistic based on linear regression; that > is, to evaluate whether the dual task activity is a mix of both single tasks. > Can anyone recommend an unbiased way to analyse this kind of data using the > functions implemented in fieldtrip? I would be very grateful for any ideas. > Thanks, > Helen > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 443 bytes Desc: not available URL: