Assessing the effective connectivity of premotor areas during real vs imagined grasping: a DCM-PEB approach

Bencivenga, Federica; Sulpizio, Valentina; Tullo, Maria Giulia; Galati, Gaspare

doi:10.1016/j.neuroimage.2021.117806

Cited by 29 publications

(35 citation statements)

References 140 publications

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“…At the second (group) level, we constructed a PEB model over the first-level estimated parameters. In accordance with previous studies (Bencivenga et al, 2021; Rupprechter et al, 2020), we evaluated the explained variance by the model on the individual level - higher values reflect better model inversion (Zeidman et al, 2019a) – and then we only included subjects with >10% of explained variance in the PEB model. A total of 118 subjects (56 males, age: mean ± SEM = 21.57 ± 0.21 years) were included for further analyses.…”

Section: Methodsmentioning

confidence: 99%

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit

Zhuang

Qiao

Lei

et al. 2022

Preprint

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The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in animal models. However, the pivotal nodes and directed casual regulation within this inhibitory circuit in humans remains controversial. Here, we capitalize on the recent progress in robust and biologically plausible directed causal modelling (DCM-PEB) and a large response inhibition dataset (n=218; 104 males) acquired with concomitant functional fMRI to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP) and thalamus (rThal). The entire neural circuit exhibited high intrinsic connectivity and response inhibition critically increased causal projections from the rIFG to both rCau and rThal. Direct comparison further demonstrated that response inhibition induced an increasing rIFG inflow and increased the causal regulation of this region over the rCau and rThal. In addition, sex and performance influenced the architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model. Together these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.

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Section: Methodsmentioning

confidence: 99%

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit

Zhuang

Qiao

Lei

et al. 2022

Preprint

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“…The copyright holder for this preprint this version posted August 2, 2022. ; https://doi.org/10.1101/2022.07.30.502169 doi: bioRxiv preprint 2016). Finally, Bayesian model Average (BMA) was used to calculate the average parameter values across the 256 models from the final iteration of the automatic search procedure, and a threshold based on the model evidence was used to keep only parameters with strong evidence, i.e., posterior probability > 0.95, which indicates the probability of a parameter being present vs. absent (Bencivenga et al, 2021;Zeidman et al, 2019b).…”

Section: Dcm Analysismentioning

confidence: 99%

Decoding Subject’s Own Name in the Primary Auditory Cortex

Wang

Liu

et al. 2022

Preprint

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Current studies have shown that perception of one's own name involves multiple multimodal brain regions, while activities in unimodal sensory regions (i.e., primary auditory cortex) and their interaction with multimodal regions during self-processing remain unclear. To answer this, we combined multivariate pattern analysis and dynamic causal modelling analysis to explore the regional activation pattern and inter-region effective connection during self-name processing. We found that subject's own name and other names could be decoded from the activation pattern in the primary auditory cortex. In addition, we found an excitatory effect of SON on connections from the anterior insula/inferior frontal gyrus to the primary auditory cortex, and to the temporal parietal junction. Our findings extended the current knowledge of self-processing by showing that primary sensory cortex could discriminate one's own name from other names. Furthermore, our findings highlighted the importance of influence of the insula on the primary auditory cortex during self-processing.

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“…Figure 5 presents the topographic channel plots (topoplots) that contain the relevant activated scalp areas that are inferred from the extracted FC measures, principally contributing to the discriminability between labeled motor-related tasks. We also include the most relevant pairwise functional connectivity links between electrodes that are estimated to fulfill the 99 percentile of the normalized relevance weights values (between 0 to 1) computed from Equation (6). The background stands for the accumulated relevance that is mapped to the channel positions.…”

Section: Dbii Me Dbiii MImentioning

confidence: 99%

“…MI and ME share common sensorimotor areas, and they both involve planning and executing the same motor plan, but their neural mechanisms have some differences [3,4]. In practice, to indicate that motor learning had taken place and retained after a training phase, motor execution performance is measured [5,6]. Moreover, the brain plasticity that is induced by motor learning can be associated with significant changes in electroencephalographic (EEG) features, particularly in the preexecution phase [7,8].…”

Section: Introductionmentioning

confidence: 99%

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Single-Trial Kernel-Based Functional Connectivity for Enhanced Feature Extraction in Motor-Related Tasks

García-Murillo

Álvarez-Meza

Castellanos-Domínguez

2021

Sensors

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Motor learning is associated with functional brain plasticity, involving specific functional connectivity changes in the neural networks. However, the degree of learning new motor skills varies among individuals, which is mainly due to the between-subject variability in brain structure and function captured by electroencephalographic (EEG) recordings. Here, we propose a kernel-based functional connectivity measure to deal with inter/intra-subject variability in motor-related tasks. To this end, from spatio-temporal-frequency patterns, we extract the functional connectivity between EEG channels through their Gaussian kernel cross-spectral distribution. Further, we optimize the spectral combination weights within a sparse-based ℓ2-norm feature selection framework matching the motor-related labels that perform the dimensionality reduction of the extracted connectivity features. From the validation results in three databases with motor imagery and motor execution tasks, we conclude that the single-trial Gaussian functional connectivity measure provides very competitive classifier performance values, being less affected by feature extraction parameters, like the sliding time window, and avoiding the use of prior linear spatial filtering. We also provide interpretability for the clustered functional connectivity patterns and hypothesize that the proposed kernel-based metric is promising for evaluating motor skills.

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Assessing the effective connectivity of premotor areas during real vs imagined grasping: a DCM-PEB approach

Cited by 29 publications

References 140 publications

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit

Decoding Subject’s Own Name in the Primary Auditory Cortex

Single-Trial Kernel-Based Functional Connectivity for Enhanced Feature Extraction in Motor-Related Tasks

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