Biology subjects

Soltanlou, M.

Publications and source records attributed to Soltanlou, M..

3 recordsLinked to original sources

bioRxiv2026

Choosing the best motion artefact correction: simplified and advanced how-to guides using QT-NIRS

SignificanceSelecting the appropriate motion artefact (MA) correction method for functional near-infrared spectroscopy (fNIRS) data is quite challenging, particularly in light of the need for standardised practice, replication, and transparency in the field. A clear framework for making measurable and replicable decisions is therefore essential. AimThis paper proposes a guide based on an open-source data quality assessment tool (QT-NIRS) that enables a transparent and evidence-driven choice of MA correction method. ApproachWe present the guide in two approaches: a simplified version that is easy to run for beginners, and an advanced version providing more informative output at the cost of additional computations and minor changes to the original QT-NIRS code. Due to its high flexibility and within-subject nature, the method is applicable across samples with varied characteristics. ResultsWe applied the guide to two challenging datasets from 60 British preschoolers (mean age = 3.94 years, SD = 0.49) and 39 South African school children (mean age = 12.00 years, SD = 0.51). Both simplified and advanced approaches supported similar MA correction methods. ConclusionsWhile both approaches can be used interchangeably, we recommend the advanced approach when possible due to its more informative and straightforward output, and advise caution when using the simplified version.

neuroscience↗

bioRxiv2026

Counting apples - How does the prefrontal region support early numerical understanding in preschool children?

Because early maths skills strongly predict later outcomes, it is crucial to understand the mechanisms that shape early learning in children. The recent years have seen an increase in studying the neural correlates that support the acquisition of maths skills. However, existing work in early childhood has primarily focused on core number-processing regions in the parietal regions, with comparatively little attention to the supportive role of prefrontal regions. In this study, we examined the engagement of the prefrontal regions when matching numbers and objects. Children (N=60, 25 girls, aged 2.74-5.18 years) matched auditory small (1-3) and large (5-7) numbers, as well as objects (fruits) to corresponding visual pictures while their frontoparietal brain responses were recorded using functional near-infrared spectroscopy (fNIRS). Importantly, matching large numbers was substantially more difficult than matching small numbers or objects. The analysis revealed that children had increased activation in the right middle frontal gyrus when matching large numbers, compared to small numbers. However, there was no difference in the prefrontal region between matching small numbers and objects. The connectivity analysis further revealed increased frontoparietal connectivity when matching small numbers, but not large numbers or objects. Our findings suggest that prefrontal involvement during early numerical knowledge acquisition relies primarily on domain-general mechanisms, with number-specific responses likely to emerge later in development.

neuroscience↗

bioRxiv2025

Neurocognitive mechanisms of mathematics vocabulary processing in L1 and L2 in South African first graders: An fNIRS study

SignificanceTo learn mathematics, young children require accurate interpretations of mathematics vocabulary. When school language differs from childrens home language, mathematics performance often decreases. Little is known about cortical activation during mathematics vocabulary processing in different languages. This insight will help us to better understand childrens mathematical learning in multilingual societies. Aim and approachWe investigated behavioral and brain responses (fNIRS) of 42 isiZulu and Sesotho (L1) first graders (6.75-7.83 years, 22 girls) who learn mathematics in English (L2) at school when they encounter mathematics vocabulary in L2 compared to L1; and mathematics vocabulary compared to object recognition in L1. ResultsThe results show that higher accuracy in the L1 mathematics vocabulary, as compared to the L2 mathematics vocabulary, comes with the costs of higher cognitive demands in the right superior and middle frontal gyri for first graders. Mathematics vocabulary required longer response time than object recognition and a higher activation in the right superior frontal gyrus. No parietal difference was observed between conditions. ConclusionsFirst graders with no automatization of mathematics vocabulary processing, still demand frontal cognitive resources. This study is a good example of how educational neuroimaging compliments our interpretation of behavioral outcomes and environmental factors such as multilingualism.

neuroscience↗