Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI

Cai, Yuxuan; Hofstetter, Shir; Zwaag, Wietske van der; Zuiderbaan, Wietske; Dumoulin, Serge O.

doi:10.1016/j.neuroimage.2021.118184

Cited by 29 publications

(19 citation statements)

References 62 publications

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“…This sample size is relatively small and focuses on high number of trials per participant, maximizing signal and minimizing noise (Gratton et al, 2022). Moreover, statistical power is determined both by the number of participants and the number of trials per participant (Baker et al, 2020): studies with fewer participants but more trials can have the same statistical power as more participants with fewer trials (Cai et al, 2021b). Furthermore, all the participants exhibited similar results, i.e., participants are replication units not measurement units.…”

Section: Discussionmentioning

confidence: 99%

“…Here, we use stimuli containing two dot patterns (subsets), letting us evaluate both attention towards and away from a dot subset. Using ultra-high field (7 T) fMRI (Cai et al, 2021b) and neural model-based analyses (Dumoulin and Wandell, 2008), we determined how numerosity-tuned responses change with attention to different subsets of items within the display.…”

Section: Introductionmentioning

confidence: 99%

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Attention drives human numerosity-selective responses

et al. 2022

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Attention drives human numerosity-selective responses

et al. 2022

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“…Our study has a number of additional limitations. First, as often at high-field fMRI, we used fewer participants scanned twice rather than more participants (Baker et al 2020;Cai et al 2021) due to the difficulty of finding participants that can limit head movement to ensure stability at 0.8mm resolution. This may limit the degree to which we can extrapolate our findings to the general population, although the similarity of our results with those of a larger group acquired at 3T at the macroscopic level (Thomas et al 2018), and the limited spread of our participant's r-values illustrates that the effects we report were quite robustly observed across participants.…”

Section: Discussionmentioning

confidence: 99%

Predictive coding during action observation - a depth-resolved intersubject functional correlation study at 7T

Cerliani

Bhandari

Angelis

et al. 2021

Preprint

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While the brain regions involved in action observation are relatively well documented in humans and primates, how these regions communicate to help understand and predict actions remains poorly understood. Traditional views emphasized a feed-forward architecture in which visual features are organized into increasingly complex representations that feed onto motor programs in parietal and then premotor cortices where the matching of observed actions upon the observer's own motor programs contributes to action understanding. Predictive coding models place less emphasis on feed-forward connections and propose that feed-back connections from premotor regions back to parietal and visual neurons represent predictions about upcoming actions that can supersede visual inputs when actions become predictable, with visual input then merely representing prediction errors. Here we leverage the notion that feed-back connections target deeper cortical layers than feed-forward connections to help adjudicate across these views. Specifically, we test whether observing sequences of hand actions in their natural order, which permits participants to predict upcoming actions, triggers more feed-back input to parietal regions than seeing the same actions in a scrambled sequence that hinders making predictions. Using submillimeter fMRI acquisition at 7T, we find that watching predictable sequences triggers more action-related activity (as measured using intersubject functional correlation) in deep layers of the parietal cortical area PFt than watching the exact same actions in scrambled and hence unpredictable sequence. In addition, functional connectivity analysis performed using intersubject functional connectivity confirms that this deep, action-related signals in PFt could originate from ventral premotor region BA44. This data showcases the utility of intersubject functional correlation in combination with 7T MRI to explore the architecture of social cognition under more naturalistic conditions, and provides evidence for models that emphasize the importance of feed-back connections in action prediction.

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“…These results are in correspondence with the findings of Tak et al which showed that 7T data have a high reproducibility of effective connectivity [ 69 ]. In particular, a higher field strength would enhance the signal-to-noise ratio (SNR), the contrast-to-noise ratio (CNR), and the spatial resolution, as well as it would increase the blood oxygen level dependent (BOLD) effect, making the signal changes in brain function imaging more obvious [ 45 , 69 , 70 , 71 ]. Our result suggests that synchrony and metastability achieve fair levels of consistency in describing spontaneous brain activity, and that the reliabilities of synchrony and metastability are better at higher field strengths.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, previous studies have argued that the shorter repetition times (TR), the higher temporal resolution, and the more time points, which has a higher statistical power. Moreover, high temporal resolution increases BOLD sensitivity [ 45 , 46 ], so will the temporal resolution affect the test–retest reliability of synchrony and metastability? The high spatial resolution would yield a marked increase in functional contrast relative to low resolution [ 47 ], so how about the effect of reliability of synchrony and metastability?…”

Section: Introductionmentioning

confidence: 99%

Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

Yang

Wei

et al. 2021

Brain Sciences

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In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals.

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Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI

Cited by 29 publications

References 62 publications

Attention drives human numerosity-selective responses

Attention drives human numerosity-selective responses

Predictive coding during action observation - a depth-resolved intersubject functional correlation study at 7T

Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

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