[FieldTrip] Issue running "ft_freqstatistics" on macOS with Apple silicon

[Schoffelen, J.M. (Jan Mathijs)]

Hi Camilo,

Have you recently updated your fieldtrip version? I think that the mexmaca64 compiled code was added a while back (w.r.t. the spm_bwlabel function it seems that this has been added about 8 months ago, as far as I can see in the repo’s history on github).

Best wishes,
Jan-Mathijs



On 7 Oct 2024, at 17:11, Camilo Castelblanco Riveros via fieldtrip <fieldtrip at science.ru.nl> wrote:

Hi!

Thanks in advance for your support.

Context:
I am trying to run "ft_freqstatistics" comparing conditions within an individual subject.
Issue:
When running the code, I get the following error:
---
generated 1000 random permutations
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.13 seconds
computing statistic 1000 from 1000

Error using spm_bwlabel (line 27)
spm_bwlabel.c not compiled - see Makefile
---

Troubleshooting:
1. I inspected my fieldtrip SPM toolbox (''...GitHub/fieldtrip/external/spm12'') has the spm_bwlabel files but not the spm_bwlabel.mexmaca64. I think I need the spm_bwlabel.mexmaca64 to run it on my machine; is that correct?
2. Doing some reading, I may need to compile the spm_make_standalone.m file. However, I do not know how to do it in Fieldtrip's path.

My code:
cfg = [];
cfg.parameter = 'powspctrm'; % Specify power spectrum parameter
cfg.method = 'montecarlo'; % Use permutation testing
cfg.statistic = 'depsamplesT'; % Dependent samples t-test
cfg.correctm = 'cluster'; % Use cluster-based correction
cfg.clusteralpha = 0.05; % Threshold for forming clusters
cfg.clusterstatistic = 'maxsum'; % Sum of t-values for defining clusters
cfg.alpha = 0.025; % Significance level for two-tailed test
cfg.tail = 0; % Two-tailed test
cfg.clustertail = 0; % Two-tailed cluster statistics
cfg.numrandomization = 1000; % Number of random permutationcfg.neighbours = []; % No neighborhood structure needed for iEEG
% Design matrix
design = zeros(2, ntrials_low + ntrials_high);
design(1, 1:ntrials_low) = 1; % Assign label 1 to trials in the low condition
design(1, ntrials_low+1:end) = 2; % Assign label 2 to trials in the high condition
design(2, :) = [1:ntrials_low, 1:ntrials_high]; % Assign trial indices
cfg.design = design;
cfg.uvar = 2; % unit of observation (subject)
cfg.ivar = 1; % independent variable (condition)
%7 Compute statistics[stat] = ft_freqstatistics(cfg, TFR_low, TFR_high);

With gratitude,
Camilo
================================
Camilo Castelblanco Riveros (He/His)
Ph.D. Candidate (G3)
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