Detecting motor plasticity in the human thalamus and putamen with precision functional mapping

1099 

Abstract Submission 

Roselyne Chauvin¹, Dillan Newbold², Ashley Nielsen¹, Samuel Krimmel¹, Athanasia Metoki¹, Benjamin Kay¹, Timothy Laumann³, Evan Gordon⁴, Nico Dosenbach^1,5,3,6

¹Department of Neurology, Washington University School of Medicine, Saint Louis, MO, ²Department of Neurology, New York University Grossman School of Medicine, New York, NY, ³Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, ⁴Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, ⁵Department of Biomedical Engineering, Washington University in St. Louis, Saint Louis, MO, ⁶Department of Pediatrics, Washington University School of Medicine, Saint Louis, MO

Roselyne Chauvin  
Department of Neurology, Washington University School of Medicine
Saint Louis, MO

Dillan Newbold  
Department of Neurology, New York University Grossman School of Medicine
New York, NY

Ashley Nielsen, PhD  
Department of Neurology, Washington University School of Medicine
Saint Louis, MO

Samuel Krimmel, R  
Department of Neurology, Washington University School of Medicine
Saint Louis, MO

Athanasia Metoki  
Department of Neurology, Washington University School of Medicine
Saint Louis, MO

Benjamin Kay  
Department of Neurology, Washington University School of Medicine
Saint Louis, MO

Timothy Laumann  
Department of Psychiatry, Washington University School of Medicine
Saint Louis, MO

Evan Gordon  
Mallinckrodt Institute of Radiology, Washington University School of Medicine
Saint Louis, MO

Nico Dosenbach  
Department of Neurology, Washington University School of Medicine|Department of Biomedical Engineering, Washington University in St. Louis|Department of Psychiatry, Washington University School of Medicine|Department of Pediatrics, Washington University School of Medicine
Saint Louis, MO|Saint Louis, MO|Saint Louis, MO|Saint Louis, MO

Cortico-striato-thalamo-cortical loops have been studied to better understand motor adaptation. Plasticity has been observed in these circuits using invasive electrophysiology in patients1, and animals2. Human plasticity studies, using fMRI, have been limited by low signal-to-noise ratios in subcortex, differences in sensitivity between cortical and subcortical brain measures and plasticity paradigms that induce only small effects3,4.

To overcome these limitations, our study paired arm immobilization by casting, with repeated functional imaging in three individuals (Precision Functional Mapping; PFM5) to address low signal-to-noise ratio in the subcortex. Daily resting-state functional connectivity (FC) and motor task fMRI6,7 were used to measure functional systems pre, during, and post, 2 weeks of casting. Previously, we identified increased FC between the disused somatomotor cortex hand region and the cingulo-opercular network (CON), an executive control system. We also observed large, spontaneous pulses during casting involving the cortical component of the disused motor circuit.

We recently discovered the previously unrecognized Somato-Cognitive Action network (SCAN) 8, which is inter-digitated with effector-specific motor regions in the central sulcus and connects the CON and motor networks within the primary motor cortex. Thus, to capture disuse-driven plasticity effects in human cortex and subcortex, and integrate them with our new understanding of motor circuit, we expanded our prior investigation of the cast dataset to include analysis adapted to the signal characteristic of subcortical regions.

We analyzed the casting dataset (3 subjects, daily 30min rest+10min HCP motor task fMRI over 6 weeks). For each subject, we employed two complementary methods to measure motor plasticity. First, we quantified disuse-related changes in FC. We computed seed-based voxel correlation maps of FC with somatomotor hand region for each rest session and quantified the change between pre and during casting sessions using within-anatomical structure cluster-based correction, against randomized label null distribution. Second, we performed a detection of disuse pulse presence using a novel HRF-based local modeling method. Finally, we compared resulting subcortical plasticity maps (FC changes, disuse pulses) to conventional motor execution maps generated from pre casting task fMRI. Similarities between subcortical maps were tested against spatial null distribution using Moran algorithms9.

While the SCAN regions in the cortex did not show involvement in disuse-driven plasticity, subcortical nodes of SCAN, particularly the central thalamus and posterior putamen, exhibited strengthened FC during disuse and presence of spontaneous activity pulses, that partially overlapped anatomically (Fig. 1). Motor task fMRI validated that subcortical disuse-driven plasticity effects spatially correspond to the upper extremity movement execution circuitry (Fig. 2).

Our study highlights the significance of subcortical motor circuits in human motor plasticity and a potential role for information integration across networks in motor adaptation. Indeed, the SCAN seems to serve as its downstream actuator, turning more abstract plans into integrated whole-body actions8. While cortical SCAN regions might implement whole-body motor commands and do not show large plasticity effects, SCAN subcortical nodes could mediate the disuse-induced FC change between CON and motor effector regions. This subcortical plasticity role is supported by knowledge of thalamic involvement in memory consolidation and homeostasis during sleep10.

Executive Function, Cognitive Control and Decision Making

Neural Plasticity and Recovery of Function ¹

Activation (eg. BOLD task-fMRI)

fMRI Connectivity and Network Modeling ²

Motor Planning and Execution

FUNCTIONAL MRI

Learning

Motor

Plasticity

Thalamus