Dataset Information

Accurate decoding of sub-TR timing differences in stimulations of sub-voxel regions from multi-voxel response patterns.

ABSTRACT: We investigated the decoding of ocular dominance stimulations with millisecond-order timing difference from the blood oxygen level dependent (BOLD) signal in human functional magnetic resonance imaging (fMRI). In our experiment, ocular dominance columns were activated by monocular visual stimulation with 500- or 100- ms onset differences. We observed that the event-related hemodynamic response (HDR) in the human visual cortex was sensitive to the subtle onset difference. The HDR shapes were related to the stimulus timings in various manners: the timing difference was represented in either the amplitude of positive peak, amplitude of negative peak, delay of peak time, or response duration of HDR. These complex relationships were different across voxels and subjects. To find an informative feature of HDR for discriminating the subtle timing difference of ocular dominance stimulations, we examined various characteristics of HDR including response amplitude, time to peak, full width at half-maximum response, as inputs for decoding analysis. Using a canonical HDR function for estimating the voxel's response did not yield good decoding scores, suggesting that information may reside in the variability of HDR shapes. Using all the values from the deconvolved HDR also showed low performance, which could be due to an over-fitting problem with the large data dimensionality. When using either positive or negative peak amplitude of the deconvolved HDR, high decoding performance could be achieved for both the 500ms and the 100ms onset differences. The high accuracy even for the 100ms difference, given that the signal was sampled at a TR of 250ms and 2×2×3-mm voxels, implies a possibility of spatiotemporally hyper-resolution decoding. Furthermore, both down-sampling and smoothing did not affect the decoding accuracies very much. These results suggest a complex spatiotemporal relationship between the multi-voxel pattern of the BOLD response and the population activation of neuronal columns. The demonstrated possibility of decoding stimulations for columnar-level organization with 100-ms onset difference using lower resolution imaging data may broaden the scope of application of the BOLD fMRI.

SUBMITTER: Misaki M

PROVIDER: S-EPMC3582847 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Accurate decoding of sub-TR timing differences in stimulations of sub-voxel regions from multi-voxel response patterns.

Misaki Masaya M Luh Wen-Ming WM Bandettini Peter A PA

NeuroImage 20121102

We investigated the decoding of ocular dominance stimulations with millisecond-order timing difference from the blood oxygen level dependent (BOLD) signal in human functional magnetic resonance imaging (fMRI). In our experiment, ocular dominance columns were activated by monocular visual stimulation with 500- or 100- ms onset differences. We observed that the event-related hemodynamic response (HDR) in the human visual cortex was sensitive to the subtle onset difference. The HDR shapes were rela ...[more]

PMID: 23128073

Similar Datasets

Project description:During adolescence, considerable social and biological changes occur that interact with functional brain maturation, some of which are sex-specific. The amygdala is one brain area that has displayed sexual dimorphism, specifically in socio-affective (superficial amygdala [SFA]), stress (centromedial amygdala [CMA]), and learning and memory (basolateral amygdala [BLA]) processing. The amygdala has also been implicated in mood and anxiety disorders which display sex-specific features, most prominently observed during adolescence. Using functional magnetic resonance imaging (fMRI), the present study examined the interaction of age and sex on resting state functional connectivity (RSFC) of amygdala sub-regions, BLA and SFA, in a sample of healthy adolescents between the ages 10 and 16 years (n = 122, 71 boys). Whole-brain, voxel-wise partial correlation analyses were conducted to determine RSFC of bilateral BLA and SFA seed regions, created using the Eickhoff-Zilles maximum probability maps based on cytoarchitectonic mapping and FMRIB's Integrated Registration and Segmentation Tool (FIRST). Monte Carlo simulation was implemented to correct for multiple comparisons (threshold of 53 contiguous voxels with a z-value ≥ 2.25). Results indicated that with increasing age, there was a corresponding decrease in RSFC between both amygdala sub-regions and parieto-occipital cortices, with a concurrent increase in RSFC with medial prefrontal cortex (mPFC). Specifically, boys and girls demonstrated increased coupling of mPFC and left and right SFA with age, respectively; however, neither sex showed increased connectivity between mPFC and BLA, which could indicate relative immaturity of fronto-limbic networks that is similar across sex. A dissociation in connectivity between BLA- and SFA-parieto-occipital RSFC emerged, in which girls had weaker negative RSFC between SFA and parieto-occipital regions and boys had weaker negative RSFC of BLA and parieto-occipital regions with increased age, both standing in contrast to adult patterns of amygdala sub-regional RSFC. The present findings suggest relative immaturity of amygdala sub-regional RSFC with parieto-occipital cortices during adolescence, with unique patterns in both sexes that may support memory and socio-affective processing in boys and girls, respectively. Understanding the underlying normative functional architecture of brain networks associated with the amygdala during adolescence may better inform future research of the neural features associated with increased risk for internalizing psychopathology.

Dataset Information

Accurate decoding of sub-TR timing differences in stimulations of sub-voxel regions from multi-voxel response patterns.

Publications

Accurate decoding of sub-TR timing differences in stimulations of sub-voxel regions from multi-voxel response patterns.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets