Layer dependent facilitation of neural activity during rhythmic movement in the human M1

Poster No:

2048 

Submission Type:

Abstract Submission 

Authors:

Yinghua Yu1,2, Ikuhiro Kida1,2, Nobuhiro Hagura1,2

Institutions:

1Center for Information and Neural Networks, NICT, Osaka, Japan, 2Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan

First Author:

Yinghua Yu  
Center for Information and Neural Networks, NICT|Graduate School of Frontier Biosciences, Osaka University
Osaka, Japan|Osaka, Japan

Co-Author(s):

Ikuhiro Kida  
Center for Information and Neural Networks, NICT|Graduate School of Frontier Biosciences, Osaka University
Osaka, Japan|Osaka, Japan
Nobuhiro Hagura  
Center for Information and Neural Networks, NICT|Graduate School of Frontier Biosciences, Osaka University
Osaka, Japan|Osaka, Japan

Introduction:

Our daily motor behaviour consist of rhythmic and discrete movement patterns. Accumulating evidences, both behavioural and neuronal, are suggesting the involvement of distinct control mechanisms underlying the generation of rhythmic and discrete movements1,2. However, the details of how the neuronal circuits of the human primary motor cortex represent this distinction are still unclear. Here, by using 7T vascular space occupancy (VASO) fMRI across M1 cortical layers, we investigated the layer-dependent neural signature of the rhythmic/ discrete movement control.

Methods:

Six participants volunteered in a two-hour scanning session using a 7T MRI scanner (Magneton, Siemens Healthcare, Erlangen, Germany) equipped with a 32-channel head coil (Nova Medical, Wilmington, MA, USA) and SC72 body gradient coil. Data acquisition procedures were same as in the previous literature3. In short: an imaging slice position in VASO fMRI sequence was approximately perpendicular to the central sulcus of the left hemisphere. The data consist of interleaved BOLD and blood volume sensitive VASO contrasts – obtained as separate yet concomitant time series. The parameters of the acquisitions were: Nominal in-plane resolution = 0.75mm, TE/TI1/TI2/TR = 24/900/2548/3296ms, ten slices with FLASH GRAPPA-2, matrix 44x132, 3D-EPI readout, FOV 31.2x93.7x21.6 mm3.
Participants pressed a button by flexing their right wrist, in response to a visual imperative stimulus (green circle) presented on the screen. Two conditions, each assigned to different runs, were prepared. In the discrete movement condition, imperative stimulus was presented with random inter-stimulus-intervals. In the rhythmic condition, the inter-stimulus-interval was fixed during the whole run. There was no other difference between the conditions; the number of movements and the instruction between the two conditions were identical. Therefore, any difference in neuronal activity pattern between the two conditions will be due to the temporal structure of the ITI distribution, which naturally leads to either rhythmic of discrete movement patterns. Each run consisted of 12 mini-blocks, with each 36 second mini-block separated with 30-second rest. Laminar analyses were conducted with the open software suite LayNii4.

Results:

We focused on the 'hand-knob' area of the precentral gyrus, which is the anatomical location corresponding to the hand area of M1. VASO response showed characteristic difference in the layer-dependent response profile for the different movement conditions. In the rhythmic movement condition, a peak of activity was observed both in the superficial and deep layer, possibly each reflecting the motor command signal to the hand (i.e. output from the deep layer) and the tactile feedback of the button press (i.e. input to the superficial layer), respectively3. In the discrete movement condition, however, such peak in the deep layer was suppressed, while similar activity level was maintained in the superficial layer. For 6 out of 6 participants, deep layer activity was higher in the rhythmic movement condition than the discrete movement condition, resulting in the significant difference between the two conditions (p< 0.01).

Conclusions:

Our results directly show that different control mechanism govern rhythmic and discrete movements, by demonstrating the distinct layer-dependent processing in the human motor cortex. Facilitated activity in the output layer of the primary motor cortex may subserve the continuous rhythmical motor output.

Motor Behavior:

Motor Planning and Execution 1

Novel Imaging Acquisition Methods:

Non-BOLD fMRI 2

Keywords:

Cortical Layers
FUNCTIONAL MRI
Motor

1|2Indicates the priority used for review

My abstract is being submitted as a Software Demonstration.

No

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 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

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

Not applicable

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
SPM
FSL

Provide references using author date format

1. Schaal, S, Dagmar S, Osu R, Kawato. Rhythmic arm movement is not discrete. Nat Neurosci. 2004. 7. 1136-1143. doi: 10.1038/nn1322.
2. Ikegami T, Hirashima M, Taga G, Nozaki D. Asymmetric transfer of visuomotor learning between discrete and rhythmic movements. J Neurosci. 2010, 30, 4515-4521. doi: 10.1523/JNEUROSCI.3066-09.2010.
3. Huber L, Handwerker DA, Jangraw DC, Chen G, Hall A, Stüber C, Gonzalez-Castillo J, Ivanov D, Marrett S, Guidi M, Goense J, Poser BA, Bandettini PA. High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. Neuron 2017, 1253–1263. doi: 10.1016/j.neuron.2017.11.005
4. Huber L (Renzo), Poser BA, Bandettini PA, et al.: LAYNII: A software suite for layer-fMRI. bioRxiv 2020:1–20. doi: 10.1101/2020.06.12.148080