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核心语言功能背后的神经连接。

Neural connectivity underlying core language functions.

作者信息

Bohsali Anastasia A, Gullett Joseph M, FitzGerald David B, Mareci Thomas, Crosson Bruce, White Keith, Nadeau Stephen E

机构信息

Department of Veterans Affairs Rehabilitation Research and Development Brain Rehabilitation Research Center at the Malcom Randall VA Medical Center, Gainesville, FL 32608, USA; University of Florida Department of Neurology, Gainesville, FL 32610, USA.

Department of Veterans Affairs Rehabilitation Research and Development Brain Rehabilitation Research Center at the Malcom Randall VA Medical Center, Gainesville, FL 32608, USA; University of Florida Department of Clinical and Health Psychology, Gainesville, FL 32610, USA.

出版信息

Brain Lang. 2025 Mar;262:105535. doi: 10.1016/j.bandl.2025.105535. Epub 2025 Jan 23.

Abstract

INTRODUCTION

Although many white matter tracts underlying language functions have been identified, even in aggregate they do not provide a sufficiently detailed and expansive picture to enable us to fully understand the computational processes that might underly language production and comprehension. We employed diffusion tensor tractography (DTT) with a tensor distribution model to more extensively explore the white matter tracts supporting core language functions. Our study was guided by hypotheses stemming largely from the aphasia literature.

METHODS

We employed high angular resolution diffusion imaging (HARDI) with a dual region of interest tractography approach. Our diffusion tensor distribution model uses a mixture of Wishart distributions to estimate the water molecule displacement probability functions on a voxel-by-voxel basis and to model crossing/branching fibers using a multicompartmental approach.

RESULTS

We replicated the results of previously published studies of tracts underlying language function. Our study also yielded a number of novel findings: 1) extensive connectivity between Broca's region and the entirety of the middle and superior frontal gyri; 2) extensive interconnectivity between the four subcomponents of Broca's region, pars orbitalis, pars triangularis, pars opercularis, and the inferior precentral gyrus; 3) connectivity between the mid-superior temporal gyrus and the transverse gyrus; 4) connectivity between the mid-superior temporal gyrus, the transverse gyrus, and the planum temporale and the inferior and middle temporal gyri; and 5) connectivity between mid- and anterior superior temporal gyrus and all components of Broca's region.

DISCUSSION

These results, which replicate the results of prior DTT studies, also considerably extend them and thereby provide a fuller picture of the structural basis of language function and the basis for a novel model of the neural network architecture of language function. This new model is entirely consistent with discoveries from the aphasia literature and with parallel distributed processing conceptualizations of language function.

摘要

引言

尽管已经识别出许多与语言功能相关的白质束,但即便将它们汇总起来,也无法提供足够详细和全面的图景,使我们能够充分理解可能构成语言产生和理解基础的计算过程。我们采用具有张量分布模型的扩散张量纤维束成像(DTT)来更广泛地探索支持核心语言功能的白质束。我们的研究主要受源于失语症文献的假设所指导。

方法

我们采用具有双感兴趣区域纤维束成像方法的高角分辨率扩散成像(HARDI)。我们的扩散张量分布模型使用威沙特分布的混合来逐体素估计水分子位移概率函数,并使用多室方法对交叉/分支纤维进行建模。

结果

我们重复了先前发表的关于语言功能相关束的研究结果。我们的研究还产生了许多新发现:1)布洛卡区与整个额中回和额上回之间存在广泛的连接;2)布洛卡区的四个子成分,即眶部、三角部、岛盖部和中央前回下部之间存在广泛的相互连接;3)颞中回上中部与颞横回之间的连接;4)颞中回上中部、颞横回、颞平面与颞下回和颞中回之间的连接;5)颞上回中前部与布洛卡区的所有成分之间的连接。

讨论

这些结果重复了先前DTT研究的结果,同时也对其进行了相当大的扩展,从而提供了更完整的语言功能结构基础图景以及语言功能神经网络架构新模型的基础。这个新模型与失语症文献中的发现以及语言功能的并行分布式处理概念完全一致。

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