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public:t1i1_sequences [2016/07/01 11:13]
aguirreg
public:t1i1_sequences [2022/01/28 18:10] (current)
haggerty
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 The n labels of the T1I1 sequence can be assigned to n stimuli (alternatively, n-1 stimuli and a "null" trial) and determine the order of presentation of stimuli in a [[carry-over_designs|continuous-carry over]], BOLD fMRI experiment. T1I1 sequences offer several advantages in this context: The n labels of the T1I1 sequence can be assigned to n stimuli (alternatively, n-1 stimuli and a "null" trial) and determine the order of presentation of stimuli in a [[carry-over_designs|continuous-carry over]], BOLD fMRI experiment. T1I1 sequences offer several advantages in this context:
  
-  * The sequence is first-order counterbalanced, allowing the "direct" effect of each stimulus to be measured independently of "carry-over" effects (see [[http://dx.doi.org/10.1016/j.neuroimage.2007.02.005|Aguirre 2007]])+  * The sequence is first-order counterbalanced, allowing the "direct" effect of each stimulus to be measured independently of "carry-over" effects (see [[https://pubmed.ncbi.nlm.nih.gov/17376705/|Aguirre 2007]])
   * The stimuli are presented in permuted blocks, rendering the neural effects relatively insensitive to order effects across the entire experiment. In other words, the T1I1 sequence has relatively little power at very low frequencies, thus avoiding the elevated (1/f) noise range of BOLD fMRI.   * The stimuli are presented in permuted blocks, rendering the neural effects relatively insensitive to order effects across the entire experiment. In other words, the T1I1 sequence has relatively little power at very low frequencies, thus avoiding the elevated (1/f) noise range of BOLD fMRI.
   * Unlike m-sequences, a T1I1 sequence can be found for any number of labels greater than five.   * Unlike m-sequences, a T1I1 sequence can be found for any number of labels greater than five.
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 T1I1 sequences can be generated exhaustively for a given n, or randomly sampled from the potentially vast space of possible sequences. Dongbo Hu, working with code povided by[[http://www.bioss.ac.uk/staff/cmt/designseq.html|Nonyane and Theobald]] has written a c-code, command-line program for the production of random T1I1 sequences: T1I1 sequences can be generated exhaustively for a given n, or randomly sampled from the potentially vast space of possible sequences. Dongbo Hu, working with code povided by[[http://www.bioss.ac.uk/staff/cmt/designseq.html|Nonyane and Theobald]] has written a c-code, command-line program for the production of random T1I1 sequences:
  
-<WRAP download round box 200px center>**Download**\\ \\ [[https://cfn.upenn.edu/aguirre/public/type1index1/|Download T1I1 "seqgen" software]]</WRAP>+**Download**\\ \\ [[https://github.com/gkaguirrelab/t1i1Seqgen|T1I1 "seqgen" GitHub repository]]
  
  
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 We have provided [[premade_sequences|pre-made sequences]] for certain stimulus spaces and provide a web-based tool for generating new sequences: We have provided [[premade_sequences|pre-made sequences]] for certain stimulus spaces and provide a web-based tool for generating new sequences:
  
-<WRAP info round box 200px center>**Web tool**\\ \\ [[https://cfn.upenn.edu/aguirre/webseq/|Carry-Over designer]]</WRAP>+**Web tool**\\ \\ [[https://cfn.upenn.edu/aguirre/webseq/|Carry-Over designer]]
public/t1i1_sequences.1467371601.txt.gz · Last modified: 2016/07/01 11:13 by aguirreg