Layer-specific activation in human primary motor cortex during object manipulation

Poster No:

1989 

Submission Type:

Abstract Submission 

Authors:

Yinghua Yu1, Masaki Fukunaga2, Jiajia Yang1

Institutions:

1Okayama University, Okayama, Okayama, 2National Institute for Physiological Sciences, Okazaki, Aichi

First Author:

Yinghua Yu  
Okayama University
Okayama, Okayama

Co-Author(s):

Masaki Fukunaga  
National Institute for Physiological Sciences
Okazaki, Aichi
Jiajia Yang, Ph.D.  
Okayama University
Okayama, Okayama

Introduction:

Object manipulation is a fundamental human skill that requires multiple processes, such as object cognition, motor preparation, and movement control. Previous studies have highlighted that the primary motor cortex (M1) is crucial in object manipulation in humans and non-human primates (O'Shea, H., & Redmond, S.J., 2021). Consistent with state trajectories produced by the motor system, many signals are thought to arise from M1, and the activity of M1 during movement depends strongly on the initial condition (i.e., the state of motor preparation) before the movement onset (Kao, T.C., et al 2021). However, it is still unknown how motor preparation modulates the activity in M1 across cortical layers during object manipulation. In the present study, to explore the layer-specific contributions of motor preparation in human M1, we acquired high-resolution (0.68 mm) fMRI at 7T and sought to identify layer-specific activity in M1.

Methods:

Three participants were asked to participate in the fMRI experiment, which consisted of four inverted T-shape object manipulation tasks. The weight of the inverted T-shaped object can be adjusted by placing a mass in one of three locations (Figure 1A). The predictable random mass task (PRM) started with a visual cue on the screen, which indicated the mass location, and the participants were asked to predicate the mass location and lift the object as straight as possible (Figure 1B). The procedure for the unpredictable random mass task (URM) was the same as that for the PRM task, but the visual cue did not represent the mass location. In other words, the participants can not predict the mass location before they lift the object. For the predictable center mass task (PCM), the mass is only placed at the center location, and the participants can lift the object without rotating it. Finally, for the no mass task (NM), the object will always be presented without mass. The layer-specific fMRI data acquisition procedures at 7T were used as described in the previous study [3]. The interleaved BOLD and VASO contrasts obtained as separate yet concomitant time series. The effective TR is 3570 ms. The nominal resolution was 0.68 mm across cortical depths with 1.2-mm thick slices (Figure 1C). The fMRI data preprocessing and general linear model analysis were conducted using AFNI and FSL. Layer-specific analyses were conducted with the open software suite LayNii [4]. The study protocol was approved by the local medical ethics committee at the Okayama University and National Institute for Physiological Sciences.

Results:

Object manipulation task-induced fMRI signal change in the M1 was found in all participants. As shown in Figure 1D, layer-specific activity for VASO-fMRI modulations across tasks also could be detected in all participants, and the color maps represented one representative individual activation map smoothing along the cortical depths. Averaged profiles of layer-specific BOLD and VASO responses for the four task conditions are shown in the lower panel of Figure 1D. We found that both BOLD and VASO responses in the superficial layers of the NM task were lower than in the other three tasks, but the trend of VASO responses was more straightforward than that of BOLD responses.
Supporting Image: ohbm_motor_2025.png
   ·Figure
 

Conclusions:

In the present study, we used sub-millimeter BOLD and VASO fMRI at 7T to explore how the motor cortex contributes to object manipulation. We found that the superficial layers of human M1 seem to play a crucial role in motor preparation as well as movement control. Even we also can see some differences in the superficial layers across three object manipulation tasks with mass. Still, the results were not clear enough for us to discuss the contribution of motor preparation and movement control components. Our findings provide insights into how these layer-specific circuits represent the object manipulation details, and we regard these findings as an important step toward understanding object manipulation processing dynamics.

Higher Cognitive Functions:

Executive Function, Cognitive Control and Decision Making

Motor Behavior:

Motor Planning and Execution 2

Novel Imaging Acquisition Methods:

Non-BOLD fMRI 1

Keywords:

Cortical Layers
FUNCTIONAL MRI
Motor

1|2Indicates the priority used for review

Abstract Information

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Please indicate below if your study was a "resting state" or "task-activation” study.

Task-activation

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Was this research conducted in the United States?

No

Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

No

Please indicate which methods were used in your research:

Functional MRI

For human MRI, what field strength scanner do you use?

7T

Which processing packages did you use for your study?

AFNI
FSL
Other, Please list  -   LayNII

Provide references using APA citation style.

1. O’Shea, H., & Redmond, S. J. (2021). A review of the neurobiomechanical processes underlying secure gripping in object manipulation. Neuroscience and Biobehavioral Reviews, 123, 286–300.
2. Kao, T. C., et al (2021). Optimal anticipatory control as a theory of motor preparation: A thalamo-cortical circuit model. Neuron, 109(9), 1567-1581.
3. Huber, L., et al (2017). High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. Neuron, 96(6), 1253–1263.
4. Huber, L., et al (2021). LayNii: A software suite for layer-fMRI. NeuroImage, 237, 118091.

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