optimizing on nested cross-validation (CV)

[susank2000]

Although i can train models using chronological CV (using commands, 'chron', 6, 2), I keep receiving an error if i try using nested cross-validation for either evaluating and/or optimizing my models. The input data was formatted in EEGLAB, so i'm not sure why the indexing may be causing issues. The parameter commands I've specified include: ('subchron', 2, 6, 0) OR ('subchron', 2, 6, 2).

Any insight would be appreciated. Thanks!

The value assigned to idxset in set_partition must be a row vector, but was: [1;2;3;4;5;6;7;8;9;10;11;12;13;14;85;86;87;88;89;90;91;92;93;94;95;96;97;98].
occurred in:
check_shape: 42
check_value: 735
assign_value: 669
assign_nvps: 645
arg_define: 184
set_partition: 50
hlp_wrapresults: 52
exp_eval: 131
@(f,a,frame__f8)feval(f,a{:}): 0
hlp_scope: 53
exp_eval_optimized: 52
utl_resolve_streams: 87
utl_preprocess_bundle: 39
@(testset,model)args.predict_func(utl_preprocess_bundle(testset,model),model): 904
evaluate_internal: 68
cached_evaluate: 42
utl_evaluate_fold: 34
par_beginschedule: 166
par_schedule: 71
utl_crossval: 311
@(varargin)utl_crossval(nestedcv_opts{:},'args',varargin): 0
hlp_wrapresults: 52
par_beginschedule: 166
par_schedule: 71
utl_gridsearch: 149
utl_searchmodel: 172
hlp_getresult: 47
par_beginschedule: 166
run_computation: 932
@(f,a,frame__f7)feval(f,a{:}): 0
hlp_scope: 53
bci_train: 856
do_run: 75
utl_run_batchjob: 33
par_beginschedule: 166
par_schedule: 71
bci_batchtrain: 421