====== Pre-made sequences for some stimulus spaces ======

Given a similarity space, a hemodynamic response function, and a time of presentation, [[public:selection_of_efficient_type_1_index_1_sequences|an optimal Type I Index 1 sequence may be found]] to measure carry over effects (e.g., neural adaptation). Below are optimal sequences found using the [[https://cfn.upenn.edu/aguirre/code/simulation/sequence/evaluator/|code available here]]. For each example space, optimal sequences have been generated for stimulus durations of 1.5, 3.0, and 4.5 seconds. Also provided for each sequence is the Efficiency (E) which is the proportion of neural variance that passes through the hemodynamic response function. It is calculated for a covariate that models a linear carry-over effect in the neural data proportional to the distance in the stimulus space between successive stimuli. For comparison, a typical block design has E=0.85.

Note that the assignment of stimui from the space to the numbers from the sequence is not arbitrary. For the one-dimensional spaces, the stimuli are labeled 1...8 proceeding left to right. For the 2D grid space, the stimuli are labeled 1...4 in the first row, then 5...8 in the second row, etc. The labels for the 3D grid and di-octagonal space are illustrated in the table below.

^links to sequences^example stimulus space^similarity matrix^
|8 element linear\\ {{:public:seqs:8x8linmono_dur15_eff044.txt|1.5s, E = 0.44}}\\ {{:public:seqs:8x8linmono_dur30_eff061.txt|3.0s, E = 0.61}}\\ {{:public:seqs:8x8linmono_dur45_eff071.txt|4.5s, E = 0.71}}|{{:public:seqs:8lin.png}}|{{:public:seqs:8x8_lin_simspace.png}}|
|8 element circular\\ {{:public:seqs:8x8lincirc_dur15_eff072.txt|1.5s, E = 0.72}}\\ {{:public:seqs:8x8linmono_dur30_eff061.txt|3.0s, E = 0.75}}\\ {{:public:seqs:8x8lincirc_dur45_eff072.txt|4.5s, E = 0.72}}|{{:public:seqs:8circ.png}}|{{:public:seqs:8x8_circ_simspace.png}}|
|16 element, 4x4 arrangement, city-block geometry\\ {{:public:seqs:16x16city4x4_dur15_eff033.txt|1.5s, E = 0.33}}\\ {{:public:seqs:16x16city4x4_dur30_eff053.txt|3.0s, E = 0.53}}\\ {{:public:seqs:16x16city4x4_dur45_eff065.txt|4.5s, E = 0.65}}|{{:public:seqs:16city.png}}|{{:public:seqs:16x16_cit_simspace.png}}|
|16 element, 4x4 arrangement, Euclidean geometry\\ {{:public:seqs:16x16euclid4x4_dur15_eff033.txt|1.5s, E = 0.33}}\\ {{:public:seqs:16x16euclid4x4_dur30_eff050.txt|3.0s, E = 0.50}}\\ {{:public:seqs:16x16euclid4x4_dur45_eff063.txt|4.5s, E = 0.63}}|{{:public:seqs:blob1.png}}|{{:public:seqs:16x16_euc_simspace.png}}|
|27 element, 3x3x3 arrangement, Euclidean geometry\\ {{:public:seqs:27x27euclid3x3x3_dur15_eff027.txt|1.5s, E = 0.27}}\\ {{:public:seqs:27x27euclid3x3x3_dur30_eff048.txt|3.0s, E = 0.48}}\\ {{:public:seqs:27x27euclid3x3x3_dur45_eff060.txt|4.5s, E = 0.60}}|{{:public:seqs:3x3x3cube.gif}}|{{:public:seqs:27x27_euc_simspace.png}}|
|16 element, di-octagon arrangement, Euclidean geometry\\ {{:public:seqs:dioct16_dur15_eff034.txt|1.5s, E = 0.34}}\\ {{:public:seqs:dioct16_dur30_eff054.txt|3.0s, E = 0.54}}\\ {{:public:seqs:dioct16_dur45_eff067.txt|4.5s, E = 0.67}}|{{:public:seqs:dioctspace.png}}|{{:public:seqs:dioctsim.png}}|