Neural correlates of decision making on whole body yaw rotation: An fNIRS study

Winkel, Ksander N. de; Nesti, Alessandro; Ayaz, Hasan; Bülthoff, Heinrich H.

doi:10.1016/j.neulet.2017.04.053

Cited by 14 publications

(6 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To our knowledge, these observations provide the first human electrophysiological evidence for the contribution of such cognitive processes for planning motor actions based on idiothetic information. These results, therefore, build on recent studies describing cortical activities evoked by body rotations (e.g., Gale et al, 2016) or activities strictly linked to spatial, non-motor updating processes (Gutteling and Medendorp, 2016; Gutteling et al, 2017; de Winkel et al, 2017).…”

Section: General Discussion and Conclusionsupporting

confidence: 78%

Two Neural Circuits to Point Towards Home Position After Passive Body Displacements

Blouin

Saradjian

Pialasse

et al. 2019

Front. Neural Circuits

View full text Add to dashboard Cite

A challenge in motor control research is to understand the mechanisms underlying the transformation of sensory information into arm motor commands. Here, we investigated these transformation mechanisms for movements whose targets were defined by information issued from body rotations in the dark (i.e., idiothetic information). Immediately after being rotated, participants reproduced the amplitude of their perceived rotation using their arm (Experiment 1). The cortical activation during movement planning was analyzed using electroencephalography and source analyses. Task-related activities were found in regions of interest (ROIs) located in the prefrontal cortex (PFC), dorsal premotor cortex, dorsal region of the anterior cingulate cortex (ACC) and the sensorimotor cortex. Importantly, critical regions for the cognitive encoding of space did not show significant task-related activities. These results suggest that arm movements were planned using a sensorimotor-type of spatial representation. However, when a 8 s delay was introduced between body rotation and the arm movement (Experiment 2), we found that areas involved in the cognitive encoding of space [e.g., ventral premotor cortex (vPM), rostral ACC, inferior and superior posterior parietal cortex (PPC)] showed task-related activities. Overall, our results suggest that the use of a cognitive-type of representation for planning arm movement after body motion is necessary when relevant spatial information must be stored before triggering the movement.

show abstract

Section: General Discussion and Conclusionsupporting

confidence: 78%

Two Neural Circuits to Point Towards Home Position After Passive Body Displacements

Blouin

Saradjian

Pialasse

et al. 2019

Front. Neural Circuits

View full text Add to dashboard Cite

show abstract

“…From the reviewed studies only two studies used Hb Total . 56 justified their use of the signal as it incorporates the characteristics of neurovascular coupling from HbO 2 and HHb, while 57 did not provide any reasoning for its use. Hemoglobin difference (Hb Diff ¼ HbO 2 − HHb) allows a measurement of oxygenation and identification of the mismatch between HbO 2 and HHb.…”

Section: Introductionmentioning

confidence: 99%

Investigation of functional near-infrared spectroscopy signal quality and development of the hemodynamic phase correlation signal

et al. 2022

View full text Add to dashboard Cite

Significance: There is a longstanding recommendation within the field of fNIRS to use oxygenated (HbO 2 ) and deoxygenated (HHb) hemoglobin when analyzing and interpreting results. Despite this, many fNIRS studies do focus on HbO 2 only. Previous work has shown that HbO 2 on its own is susceptible to systemic interference and results may mostly reflect that rather than functional activation. Studies using both HbO 2 and HHb to draw their conclusions do so with varying methods and can lead to discrepancies between studies. The combination of HbO 2 and HHb has been recommended as a method to utilize both signals in analysis.Aim: We present the development of the hemodynamic phase correlation (HPC) signal to combine HbO 2 and HHb as recommended to utilize both signals in the analysis. We use synthetic and experimental data to evaluate how the HPC and current signals used for fNIRS analysis compare.Approach: About 18 synthetic datasets were formed using resting-state fNIRS data acquired from 16 channels over the frontal lobe. To simulate fNIRS data for a block-design task, we superimposed a synthetic task-related hemodynamic response to the resting state data. This data was used to develop an HPC-general linear model (GLM) framework. Experiments were conducted to investigate the performance of each signal at different SNR and to investigate the effect of false positives on the data. Performance was based on each signal's mean T-value across channels. Experimental data recorded from 128 participants across 134 channels during a fingertapping task were used to investigate the performance of multiple signals [HbO 2 , HHb, HbT, HbD, correlation-based signal improvement (CBSI), and HPC] on real data. Signal performance was evaluated on its ability to localize activation to a specific region of interest.Results: Results from varying the SNR show that the HPC signal has the highest performance for high SNRs. The CBSI performed the best for medium-low SNR. The next analysis evaluated how false positives affect the signals. The analyses evaluating the effect of false positives showed that the HPC and CBSI signals reflect the effect of false positives on HbO 2 and HHb. The analysis of real experimental data revealed that the HPC and HHb signals provide localization to the primary motor cortex with the highest accuracy. Conclusions:We developed a new hemodynamic signal (HPC) with the potential to overcome the current limitations of using HbO 2 and HHb separately. Our results suggest that the HPC signal provides comparable accuracy to HHb to localize functional activation while at the same time being more robust against false positives.

show abstract

“…Behavior decision: Modality-independent decision-making is underlying the accumulation of sensory evidence and the duration of stimuli, mastermind by the frontal lobe network (de Winkel et al, 2017 ; Ma et al, 2021 ). In the learning task of knowledge transfer, the subjects decided on the beneficial contents from many stimulus materials.…”

Section: Discussionmentioning

confidence: 99%

Functional Brain Network Analysis of Knowledge Transfer While Engineering Problem-Solving

Wang

Jiang

et al. 2021

Front. Hum. Neurosci.

View full text Add to dashboard Cite

As a complex cognitive activity, knowledge transfer is mostly correlated to cognitive processes such as working memory, behavior control, and decision-making in the human brain while engineering problem-solving. It is crucial to explain how the alteration of the functional brain network occurs and how to express it, which causes the alteration of the cognitive structure of knowledge transfer. However, the neurophysiological mechanisms of knowledge transfer are rarely considered in existing studies. Thus, this study proposed functional connectivity (FC) to describe and evaluate the dynamic brain network of knowledge transfer while engineering problem-solving. In this study, we adopted the modified Wisconsin Card-Sorting Test (M-WCST) reported in the literature. The neural activation of the prefrontal cortex was continuously recorded for 31 participants using functional near-infrared spectroscopy (fNIRS). Concretely, we discussed the prior cognitive level, knowledge transfer distance, and transfer performance impacting the wavelet amplitude and wavelet phase coherence. The paired t-test results showed that the prior cognitive level and transfer distance significantly impact FC. The Pearson correlation coefficient showed that both wavelet amplitude and phase coherence are significantly correlated to the cognitive function of the prefrontal cortex. Therefore, brain FC is an available method to evaluate cognitive structure alteration in knowledge transfer. We also discussed why the dorsolateral prefrontal cortex (DLPFC) and occipital face area (OFA) distinguish themselves from the other brain areas in the M-WCST experiment. As an exploratory study in NeuroManagement, these findings may provide neurophysiological evidence about the functional brain network of knowledge transfer while engineering problem-solving.

show abstract

Neural correlates of decision making on whole body yaw rotation: An fNIRS study

Cited by 14 publications

References 41 publications

Two Neural Circuits to Point Towards Home Position After Passive Body Displacements

Two Neural Circuits to Point Towards Home Position After Passive Body Displacements

Investigation of functional near-infrared spectroscopy signal quality and development of the hemodynamic phase correlation signal

Functional Brain Network Analysis of Knowledge Transfer While Engineering Problem-Solving

Contact Info

Product

Resources

About