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Carry-over fMRI experiments present stimuli in an unbroken, continuous sequence, and can be used to estimate simultaneously the mean difference in neural activity between stimuli (for the purpose of distributed pattern analysis) as well as the effect of stimulus history and context (carry-over effects).

All studies of neural adaptation are measures of carry-over effects, as are studies of anticipation, priming, bias (Kahn et al, 2010), contrast (Gescheider, 1988), and temporal non-linearity. These effects are measured efficiently and without bias in the setting of counter-balanced stimulus sequences.

Continuous carry-over designs with serially balanced sequences are particularly well suited to the characterization of “similarity spaces,” in which the perceptual similarity of stimuli is related to the structure of neural representation both within and across voxels.

This page provides the resources necessary to understand the approach and to design your own experiments.

Three papers describe the basic and extended methodology:

• GK Aguirre (2007) Continuous carry-over designs for fMRI. Neuroimage, 35, 1480-1494.
  The basic method and construction of regression matrices to characterize focal and distributed neural similarity
• GK Aguirre, MG Mattar, L Magis-Weinberg. (2011) de Bruijn cycles for neural decoding. NeuroImage 56: 1293-1300
  [ Press Release ]
  A generalized solution for counter-balanced sequences is introduced, and an algorithm (“path-guiding”) for optimized sequences for BOLD fMRI
• DM Drucker, WT Kerr, GK Aguirre. (2009) Distinguishing conjoint and independent neural tuning for stimulus features with fMRI adaptation. Journal of Neurophysiology. June;101(6):3310-24
  An extension of the approach to study the metric properties of population neural coding for similarity

There are on-line slide presentations of the approach:

• Introduction to continuous carry-over designs for fMRI, a talk presented at Human Brain Mapping 2007 (and in a revised form in 2009)

Applications of the technique can be found by searching:

• |Google Scholar|
• |Scopus|

Carry-over experiments require that the stimuli are presented in a counter-balanced sequence, meaning every stimulus precedes and follows every other. Higher level counterbalancing is useful to guard against some modeling assumptions of the approach. Sequences that efficiently provide this control of stimulus order are called de Bruijn sequences. In 2011 we introduced a method for the creation of de Bruijn sequences ("path-guided") with enhanced power for BOLD fMRI experiments.

Within the larger class of de Bruijn sequences are M-Sequences, and Type 1 Index 1 sequences, which may be used for carry-over designs as well. Below are links for separate pages that explore the properties of these different sequence types.

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Path-guided de Bruijn information and software</WRAP> <WRAP info round box 20% left>Link to Software

m-sequence information and software</WRAP> <WRAP info round box 20% center>Link to Software

Type 1 Index 1 sequences and software</WRAP>

We have provided for download the data, covariates, and results, from a continuous carry-over study.

There is a page that describes the creation of carry-over covariates, and includes links to MATLAB code for this purpose.