White matter structural bases for phase accuracy during tapping synchronization
Abstract
We determined the intersubject association between the rhythmic entrainment abilities of human subjects during a synchronization-continuation tapping task (SCT) and the macro- and microstructural properties of their superficial (SWM) and deep (DWM) white matter. Diffusion-weighted images were obtained from 32 subjects who performed the SCT with auditory or visual metronomes and five tempos ranging from 550 to 950 ms. We developed a method to determine the density of short-range fibers that run underneath the cortical mantle, interconnecting nearby cortical regions (U-fibers). Notably, individual differences in the density of U-fibers in the right audiomotor system were correlated with the degree of phase accuracy between the stimuli and taps across subjects. These correlations were specific to the synchronization epoch with auditory metronomes and tempos around 1.5 Hz. In addition, a significant association was found between phase accuracy and the density and bundle diameter of the corpus callosum, forming an interval-selective map where short and long intervals were behaviorally correlated with the anterior and posterior portions of the corpus callosum. These findings suggest that the structural properties of the SWM and DWM in the audiomotor system support the tapping synchronization abilities of subjects, as cortical U-fiber density is linked to the preferred tapping tempo and the bundle properties of the corpus callosum define an interval-selective topography.
Data availability
Data is available at OSF: https://osf.io/ynvf3/?view_only=0f30de38694a4ce38f69807dd07c1604
Article and author information
Author details
Funding
Consejo Nacional de Humanidades Ciencia y Tecnologia (A1-S-8330)
- Hugo Merchant
Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (PAPIIT IG200424)
- Hugo Merchant
Secretaria de Ciencia y Tecnología. Ciudad de México (2342)
- Hugo Merchant
Consejo Nacional de Humanidades Ciencia y Tecnologia (C1782)
- Luis Concha
Consejo Nacional de Humanidades Ciencia y Tecnologia (FC-218-2023)
- Luis Concha
Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (PAPIIT AG200117)
- Luis Concha
Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (PAPIIT AG200117)
- Luis Concha
Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (IN213423)
- Luis Concha
Consejo Nacional de Ciencia y Tecnología (280464)
- Pamela Garcia-Saldivar
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Thirty-two healthy human subjects without musical training volunteered to participate and gave informed consent, which complied with the Declaration of Helsinki and was approved by our Institutional Review Board. This study was approved by the Ethics Committee of the Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla with the number 049H-RM.
Copyright
© 2024, Garcia-Saldivar et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 536
- views
-
- 93
- downloads
-
- 1
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Biochemistry and Chemical Biology
- Computational and Systems Biology
Protein–protein interactions are fundamental to understanding the molecular functions and regulation of proteins. Despite the availability of extensive databases, many interactions remain uncharacterized due to the labor-intensive nature of experimental validation. In this study, we utilized the AlphaFold2 program to predict interactions among proteins localized in the nuage, a germline-specific non-membrane organelle essential for piRNA biogenesis in Drosophila. We screened 20 nuage proteins for 1:1 interactions and predicted dimer structures. Among these, five represented novel interaction candidates. Three pairs, including Spn-E_Squ, were verified by co-immunoprecipitation. Disruption of the salt bridges at the Spn-E_Squ interface confirmed their functional importance, underscoring the predictive model’s accuracy. We extended our analysis to include interactions between three representative nuage components—Vas, Squ, and Tej—and approximately 430 oogenesis-related proteins. Co-immunoprecipitation verified interactions for three pairs: Mei-W68_Squ, CSN3_Squ, and Pka-C1_Tej. Furthermore, we screened the majority of Drosophila proteins (~12,000) for potential interaction with the Piwi protein, a central player in the piRNA pathway, identifying 164 pairs as potential binding partners. This in silico approach not only efficiently identifies potential interaction partners but also significantly bridges the gap by facilitating the integration of bioinformatics and experimental biology.
-
- Computational and Systems Biology
- Neuroscience
Accumulating evidence to make decisions is a core cognitive function. Previous studies have tended to estimate accumulation using either neural or behavioral data alone. Here, we develop a unified framework for modeling stimulus-driven behavior and multi-neuron activity simultaneously. We applied our method to choices and neural recordings from three rat brain regions—the posterior parietal cortex (PPC), the frontal orienting fields (FOF), and the anterior-dorsal striatum (ADS)—while subjects performed a pulse-based accumulation task. Each region was best described by a distinct accumulation model, which all differed from the model that best described the animal’s choices. FOF activity was consistent with an accumulator where early evidence was favored while the ADS reflected near perfect accumulation. Neural responses within an accumulation framework unveiled a distinct association between each brain region and choice. Choices were better predicted from all regions using a comprehensive, accumulation-based framework and different brain regions were found to differentially reflect choice-related accumulation signals: FOF and ADS both reflected choice but ADS showed more instances of decision vacillation. Previous studies relating neural data to behaviorally inferred accumulation dynamics have implicitly assumed that individual brain regions reflect the whole-animal level accumulator. Our results suggest that different brain regions represent accumulated evidence in dramatically different ways and that accumulation at the whole-animal level may be constructed from a variety of neural-level accumulators.