scholarly journals Does higher sampling rate (Multiband + SENSE) benefit the detection of task correlated BOLD for cognitive neuroscience applications at 3T?

2019 ◽  
Author(s):  
Ritu Bhandari ◽  
Evgeniya Kirilina ◽  
Matthan Caan ◽  
Judith Suttrup ◽  
Teresa de Sanctis ◽  
...  

AbstractMultiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3T scanner using five sequences up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movies showing complex actions with hand object interactions and (ii) control movies without hand object interaction. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit.

2019 ◽  
Author(s):  
Ritu Bhandari ◽  
Valeria Gazzola ◽  
Christian Keysers

AbstractMultiband (MB) acceleration of functional magnetic resonance imaging has become more widely available to neuroscientists. Here we compare MB factors of 1, 2 and 4 while participants view complex hand actions vs. simpler hand movements to localize the action observation network. While in a previous study, we show that MB4 shows moderate improvements in the group-level statistics, here we explore the impact it has on single subject statistics. We find that MB4 provides an increase in p values at the first level that is of medium effect size compared to MB1, providing moderate evidence across a number of voxels that MB4 indeed improves single subject statistics. This effect was localized mostly within regions that belong to the action observation network. In parallel, we find that Cohen’s d at the single subject level actually decreases using MB4 compared to MB1. Intriguingly, we find that subsampling MB4 sequences, by only considering every fourth acquired volume, also leads to increased Cohen’s d values, suggesting that the FAST algorithm we used to correct for temporal auto-correlation may over-penalize sequences with higher temporal autocorrelation, thereby underestimating the potential gains in single subject statistics offered by MB acceleration, and alternative methods should be explored. In summary, considering the moderate gains in statistical values observed both at the group level in our previous study and at the single subject level in this study, we believe that MB technology is now ripe for neuroscientists to start using MB4 acceleration for their studies, be it to accurately map activity in single subjects of interest (e.g. for presurgical planning or to explore rare patients) or for the purpose of group studies.


2011 ◽  
Vol 29 (supplement) ◽  
pp. 352-377 ◽  
Author(s):  
Seon Hee Jang ◽  
Frank E Pollick

The study of dance has been helpful to advance our understanding of how human brain networks of action observation are influenced by experience. However previous studies have not examined the effect of extensive visual experience alone: for example, an art critic or dance fan who has a rich experience of watching dance but negligible experience performing dance. To explore the effect of pure visual experience we performed a single experiment using functional Magnetic Resonance Imaging (fMRI) to compare the neural processing of dance actions in 3 groups: a) 14 ballet dancers, b) 10 experienced viewers, c) 12 novices without any extensive dance or viewing experience. Each of the 36 participants viewed short 2-second displays of ballet derived from motion capture of a professional ballerina. These displays represented the ballerina as only points of light at the major joints. We wished to study the action observation network broadly and thus included two different types of display and two different tasks for participants to perform. The two different displays were: a) brief movies of a ballet action and b) frames from the ballet movies with the points of lights connected by lines to show a ballet posture. The two different tasks were: a) passively observe the display and b) imagine performing the action depicted in the display. The two levels of display and task were combined factorially to produce four experimental conditions (observe movie, observe posture, motor imagery of movie, motor imagery of posture). The set of stimuli used in the experiment are available for download after this paper. A random effects ANOVA was performed on brain activity and an effect of experience was obtained in seven different brain areas including: right Temporoparietal Junction (TPJ), left Retrosplenial Cortex (RSC), right Primary Somatosensory Cortex (S1), bilateral Primary Motor Cortex (M1), right Orbitofrontal Cortex (OFC), right Temporal Pole (TP). The patterns of activation were plotted in each of these areas (TPJ, RSC, S1, M1, OFC, TP) to investigate more closely how the effect of experience changed across these areas. For this analysis, novices were treated as baseline and the relative effect of experience examined in the dancer and experienced viewer groups. Interpretation of these results suggests that both visual and motor experience appear equivalent in producing more extensive early processing of dance actions in early stages of representation (TPJ and RSC) and we hypothesise that this could be due to the involvement of autobiographical memory processes. The pattern of results found for dancers in S1 and M1 suggest that their perception of dance actions are enhanced by embodied processes. For example, the S1 results are consistent with claims that this brain area shows mirror properties. The pattern of results found for the experienced viewers in OFC and TP suggests that their perception of dance actions are enhanced by cognitive processes. For example, involving aspects of social cognition and hedonic processing – the experienced viewers find the motor imagery task more pleasant and have richer connections of dance to social memory. While aspects of our interpretation are speculative the core results clearly show common and distinct aspects of how viewing experience and physical experience shape brain responses to watching dance.


Author(s):  
Gloria Pizzamiglio ◽  
Zuo Zhang ◽  
James Kolasinski ◽  
Jane M. Riddoch ◽  
Richard E. Passingham ◽  
...  

2016 ◽  
Vol 28 (1) ◽  
pp. 20-40 ◽  
Author(s):  
Velia Cardin ◽  
Eleni Orfanidou ◽  
Lena Kästner ◽  
Jerker Rönnberg ◽  
Bencie Woll ◽  
...  

The study of signed languages allows the dissociation of sensorimotor and cognitive neural components of the language signal. Here we investigated the neurocognitive processes underlying the monitoring of two phonological parameters of sign languages: handshape and location. Our goal was to determine if brain regions processing sensorimotor characteristics of different phonological parameters of sign languages were also involved in phonological processing, with their activity being modulated by the linguistic content of manual actions. We conducted an fMRI experiment using manual actions varying in phonological structure and semantics: (1) signs of a familiar sign language (British Sign Language), (2) signs of an unfamiliar sign language (Swedish Sign Language), and (3) invented nonsigns that violate the phonological rules of British Sign Language and Swedish Sign Language or consist of nonoccurring combinations of phonological parameters. Three groups of participants were tested: deaf native signers, deaf nonsigners, and hearing nonsigners. Results show that the linguistic processing of different phonological parameters of sign language is independent of the sensorimotor characteristics of the language signal. Handshape and location were processed by different perceptual and task-related brain networks but recruited the same language areas. The semantic content of the stimuli did not influence this process, but phonological structure did, with nonsigns being associated with longer RTs and stronger activations in an action observation network in all participants and in the supramarginal gyrus exclusively in deaf signers. These results suggest higher processing demands for stimuli that contravene the phonological rules of a signed language, independently of previous knowledge of signed languages. We suggest that the phonological characteristics of a language may arise as a consequence of more efficient neural processing for its perception and production.


2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Takuya Ito ◽  
Kaustubh R. Kulkarni ◽  
Douglas H. Schultz ◽  
Ravi D. Mill ◽  
Richard H. Chen ◽  
...  

2019 ◽  
Author(s):  
Ravi D. Mill ◽  
Brian A. Gordon ◽  
David A. Balota ◽  
Jeffrey M. Zacks ◽  
Michael W. Cole

AbstractAlzheimer’s disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the timecourse of illness. Study of these fMRI correlates of unhealthy aging has been conducted in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC network alterations associated with Alzheimer’s disease disrupt the ability for activations to flow between brain regions, leading to aberrant task activations. We apply this activity flow modeling framework in a large sample of clinically unimpaired older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) risk factors for AD. We identified healthy task activations in individuals at low risk for AD, and then by estimating activity flow using at-risk AD restFC data we were able to predict the altered at-risk AD task activations. Thus, modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy aged activations. These results provide evidence that activity flow over altered intrinsic functional connections may act as a mechanism underlying Alzheimer’s-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights linking restFC with cognitive task activations, this approach has potential clinical utility as it enables prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.Significance StatementDeveloping analytic approaches that can reliably predict features of Alzheimer’s disease is a major goal for cognitive and clinical neuroscience, with particular emphasis on identifying such diagnostic features early in the timeline of disease. We demonstrate the utility of an activity flow modeling approach, which predicts fMRI cognitive task activations in subjects identified as at-risk for Alzheimer’s disease. The approach makes activation predictions by transforming a healthy aged activation template via the at-risk subjects’ individual pattern of fMRI resting-state functional connectivity (restFC). The observed prediction accuracy supports activity flow as a mechanism linking age-related alterations in restFC and task activations, thereby providing a theoretical basis for incorporating restFC into imaging biomarker and personalized medicine interventions.


Author(s):  
S. Vidhusha ◽  
A. Kavitha

Autism spectrum disorders are connected with disturbances of neural connectivity. Functional connectivity is typically examined during a cognitive task, but also exists in the absence of a task. While a number of studies have performed functional connectivity analysis to differentiate controls and autism individuals, this work focuses on analyzing the brain activation patterns not only between controls and autistic subjects, but also analyses the brain behaviour present within autism spectrum. This can bring out more intuitive ways to understand that autism individuals differ individually. This has been performed between autism group relative to the control group using inter-hemispherical analysis. Indications of under connectivity were exhibited by the Granger Causality (GC) and Conditional Granger Causality (CGC) in autistic group. Results show that as connectivity decreases, the GC and CGC values also get decreased. Further, to demark the differences present within the spectrum of autistic individuals, GC and CGC values have been calculated.


2013 ◽  
Vol 35 (1) ◽  
pp. 22-28 ◽  
Author(s):  
Miyuki Tamura ◽  
Yoshiya Moriguchi ◽  
Shigekazu Higuchi ◽  
Akiko Hida ◽  
Minori Enomoto ◽  
...  

2011 ◽  
Vol 7 (1) ◽  
pp. 64-80 ◽  
Author(s):  
Daniel J. Shaw ◽  
Marie-Helene Grosbras ◽  
Gabriel Leonard ◽  
G. Bruce Pike ◽  
Tomáš Paus

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