Parcellation-based modeling of the dorsal premotor area

Sheets, John R.; Briggs, Robert G.; Bai, Michael Y.; Poologaindran, Anujan; Young, Isabella M.; Conner, Andrew K.; Baker, Cordell M; Glenn, Chad A.; Sughrue, Michael E.

doi:10.1016/j.jns.2020.116907

Cited by 8 publications

(5 citation statements)

References 70 publications

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“…Based on our study, different phenotypes according to the Barthel scale varied in their total number of abnormal functional connections to cortical parcellations. The connectivity of these parcellations in the sensorimotor network has been well-described previously ( 52 , 53 ) and are well-known regions involved in motor functioning ( 54 ). In particular, the mean total of hypoconnected parcels contralateral to the lesion side differed between specific trajectories.…”

Section: Discussionmentioning

confidence: 54%

Connectomic insight into unique stroke patient recovery after rTMS treatment

Chen,

Dadario,

Cook

et al. 2023

Front. Neurol.

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An improved understanding of the neuroplastic potential of the brain has allowed advancements in neuromodulatory treatments for acute stroke patients. However, there remains a poor understanding of individual differences in treatment-induced recovery. Individualized information on connectivity disturbances may help predict differences in treatment response and recovery phenotypes. We studied the medical data of 22 ischemic stroke patients who received MRI scans and started repetitive transcranial magnetic stimulation (rTMS) treatment on the same day. The functional and motor outcomes were assessed at admission day, 1 day after treatment, 30 days after treatment, and 90 days after treatment using four validated standardized stroke outcome scales. Each patient underwent detailed baseline connectivity analyses to identify structural and functional connectivity disturbances. An unsupervised machine learning (ML) agglomerative hierarchical clustering method was utilized to group patients according to outcomes at four-time points to identify individual phenotypes in recovery trajectory. Differences in connectivity features were examined between individual clusters. Patients were a median age of 64, 50% female, and had a median hospital length of stay of 9.5 days. A significant improvement between all time points was demonstrated post treatment in three of four validated stroke scales utilized. ML-based analyses identified distinct clusters representing unique patient trajectories for each scale. Quantitative differences were found to exist in structural and functional connectivity analyses of the motor network and subcortical structures between individual clusters which could explain these unique trajectories on the Barthel Index (BI) scale but not on other stroke scales. This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment.

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Section: Discussionmentioning

confidence: 54%

Connectomic insight into unique stroke patient recovery after rTMS treatment

Chen,

Dadario,

Cook

et al. 2023

Front. Neurol.

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“…Another application of the DSI in resolving the tissue microstructure is cortical parcellation and connectivity reconstruction. Recent studies used the DSI to segment the ventral [58] and dorsal premotor areas [59] (VPM/DPM); they found that the VPM consists of four subregions, 6v, 4, 3b, and 3a, and the DPM is divided into three areas, 6a, 6d, and 6v. These brain regions showed consistent inter-hemispheric connection but different intra-hemispheric connection patterns.…”

Section: Cortical Parcellation and Connectivity Reconstructionmentioning

confidence: 99%

Research Progress in Diffusion Spectrum Imaging

Sun,

Huang,

Wang

et al. 2023

Brain Sciences

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Studies have demonstrated that many regions in the human brain include multidirectional fiber tracts, in which the diffusion of water molecules within image voxels does not follow a Gaussian distribution. Therefore, the conventional diffusion tensor imaging (DTI) that hypothesizes a single fiber orientation within a voxel is intrinsically incapable of revealing the complex microstructures of brain tissues. Diffusion spectrum imaging (DSI) employs a pulse sequence with different b-values along multiple gradient directions to sample the diffusion information of water molecules in the entire q-space and then quantitatively estimates the diffusion profile using a probability density function with a high angular resolution. Studies have suggested that DSI can reliably observe the multidirectional fibers within each voxel and allow fiber tracking along different directions, which can improve fiber reconstruction reflecting the true but complicated brain structures that were not observed in the previous DTI studies. Moreover, with increasing angular resolution, DSI is able to reveal new neuroimaging biomarkers used for disease diagnosis and the prediction of disorder progression. However, so far, this method has not been used widely in clinical studies, due to its overly long scanning time and difficult post-processing. Within this context, the current paper aims to conduct a comprehensive review of DSI research, including the fundamental principles, methodology, and application progress of DSI tractography. By summarizing the DSI studies in recent years, we propose potential solutions towards the existing problem in the methodology and applications of DSI technology as follows: (1) using compressed sensing to undersample data and to reconstruct the diffusion signal may be an efficient and promising method for reducing scanning time; (2) the probability density function includes more information than the orientation distribution function, and it should be extended in application studies; and (3) large-sample study is encouraged to confirm the reliability and reproducibility of findings in clinical diseases. These findings may help deepen the understanding of the DSI method and promote its development in clinical applications.

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“…To validate the tractography results, we sought to demonstrate the location of white matter tracts connecting to the MTG with gross anatomic dissections for qualitative visual agreement. [17][18][19][20][21] Ten specimens were used for this study from previously otherwise healthy individuals, obtained from our institution's Willed Body Program with approval from the Oklahoma State Anatomic Board. The methods utilized for postmortem dissection of the cadaveric brains and preservation of relevant white matter tracts of interest have been previously described.…”

Section: Postmortem Dissectionsmentioning

confidence: 99%

“…The methods utilized for postmortem dissection of the cadaveric brains and preservation of relevant white matter tracts of interest have been previously described. [17][18][19][20]22 All white matter tracts were dissected in both hemispheres.…”

Section: Postmortem Dissectionsmentioning

confidence: 99%

“…15,16 The tractography strategy utilized to analyze these data has been previously described elsewhere. [17][18][19][20] Tractography was completed along the length of the gyrus from the anterior temporal pole to the bend of the superior temporal sulcus into the parietal lobe. Small U-shaped fibers identified during fiber tracking analysis were isolated sequentially along the length of the MTG using the same 2 ROI approach, which was used to isolate larger fiber bundles.…”

Section: Tractographymentioning

confidence: 99%

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The Unique Fiber Anatomy of Middle Temporal Gyrus Default Mode Connectivity

Briggs

Tanglay

Dadario

et al. 2021

ONSURG

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BACKGROUND The middle temporal gyrus (MTG) is understood to play a role in language-related tasks such as lexical comprehension and semantic cognition. However, a more specific understanding of its key white matter connections could promote the preservation of these functions during neurosurgery. OBJECTIVE To provide a detailed description of the underlying white matter tracts associated with the MTG to improve semantic preservation during neurosurgery. METHODS Tractography was performed using diffusion imaging obtained from 10 healthy adults from the Human Connectome Project. All tracts were mapped between cerebral hemispheres with a subsequent laterality index calculated based on resultant tract volumes. Ten postmortem dissections were performed for ex vivo validation of the tractography based on qualitative visual agreement. RESULTS We identified 2 major white matter bundles leaving the MTG: the inferior longitudinal fasciculus and superior longitudinal fasciculus. In addition to long association fibers, a unique linear sequence of U-shaped fibers was identified, possibly representing a form of visual semantic transfer down the temporal lobe. CONCLUSION We elucidate the underlying fiber-bundle anatomy of the MTG, an area highly involved in the brain's language network. Improved understanding of the unique, underlying white matter connections in and around this area may augment our overall understanding of language processing as well as the involvement of higher order cerebral networks like the default mode network in these functions.

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Parcellation-based modeling of the dorsal premotor area

Cited by 8 publications

References 70 publications

Connectomic insight into unique stroke patient recovery after rTMS treatment

Connectomic insight into unique stroke patient recovery after rTMS treatment

Research Progress in Diffusion Spectrum Imaging

The Unique Fiber Anatomy of Middle Temporal Gyrus Default Mode Connectivity

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