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de Bruijn cycles for neural decoding.

Abstract：

:Stimulus counterbalance is critical for studies of neural habituation, bias, anticipation, and (more generally) the effect of stimulus history and context. We introduce de Bruijn cycles, a class of combinatorial objects, as the ideal source of pseudo-random stimulus sequences with arbitrary levels of counterbalance. Neuro-vascular imaging studies (such as BOLD fMRI) have an additional requirement imposed by the filtering and noise properties of the method: only some temporal frequencies of neural modulation are detectable. Extant methods of generating counterbalanced stimulus sequences yield neural modulations that are weakly (or not at all) detected by BOLD fMRI. We solve this limitation using a novel "path-guided" approach for the generation of de Bruijn cycles. The algorithm encodes a hypothesized neural modulation of specific temporal frequency within the seemingly random order of events. By positioning the modulation between the signal and noise bands of the neuro-vascular imaging method, the resulting sequence markedly improves detection power. These sequences may be used to study stimulus context and history effects in a manner not previously possible.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Aguirre GK,Mattar MG,Magis-Weinberg L

doi

10.1016/j.neuroimage.2011.02.005

subject

Has Abstract

pub_date

2011-06-01 00:00:00

pages

1293-300

issue

3

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(11)00143-1

journal_volume

56

pub_type

杂志文章

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