Brain responses to complex division problems in children, adolescents and adults.
Poster No:
960
Submission Type:
Abstract Submission
Authors:
Asya Istomina1, Andrei Faber1, Maxim Ublinskiy2, Andrei Manzhurtsev2, Marie Arsalidou3
Institutions:
1HSE University, Moscow, Russian Federation, 2Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russian Federation, 3York University, Toronto, Ontario
First Author:
Co-Author(s):
Maxim Ublinskiy
Clinical and Research Institute of Emergency Pediatric Surgery and Trauma
Moscow, Russian Federation
Clinical and Research Institute of Emergency Pediatric Surgery and Trauma
Moscow, Russian Federation
Andrei Manzhurtsev
Clinical and Research Institute of Emergency Pediatric Surgery and Trauma
Moscow, Russian Federation
Clinical and Research Institute of Emergency Pediatric Surgery and Trauma
Moscow, Russian Federation
Introduction:
Complex computational mathematics plays a pivotal role as the foundation for numerous academic disciplines. Proficiency in mathematics frequently serves as a prerequisite for further education [1, 2]. Division, among mathematical operations, is considered the most difficult and least explored. Functional magnetic resonance imaging (fMRI) studies consistently show that solving division problems elicits activation in fronto-parietal areas in adults [3, 4]. However, results in children are less consistent, and to our knowledge, no study has examined division problem-solving involving 2-digit and 3-digit problems in children, adolescents, and adults.
Methods:
Structural (TR = 2300 ms; matrix = 240 × 222, voxel size = 1.0 × 1.0 × 1.0 mm; FOV = 240 × 240 × 170 mm; TE = 3.9 ms; FA = 8°) and functional (TR = 2500 ms; TE = 35 ms; FOV = 230 × 230 × 150; 260 measurements per run; voxel size = 3.0 × 3.0 × 3.0 mm) brain data were collected from 20 children (9 female, aged 11–13 years), 20 adolescents (9 female, aged 14–16 years), and 20 adults (12 females, aged 18–29 years) using a Philips Achieva dStream 3.0T magnetic resonance scanner. Participants performed 2-digit and 3-digit division tasks in a block design, with each block lasting 32 seconds. They were instructed to provide as many correct answers as possible. All materials and procedures were approved by the local ethics committee.
AFNI software (version AFNI for Mac OS versions 23.2.04; [5]) was utilized to preprocess and analyze the data. A high-resolution T1-weighted anatomical scan underwent nonlinear warp estimation using the 3dQwarp AFNI function [6]. Functional data underwent correction for differences in slice-time acquisition, head motion, linear trends, and low-frequency noise. These images were registered to each participant's T1-weighted anatomical warped image, normalized to the Montreal Neurological Institute (MNI) coordinate system, and spatially smoothed using an 8-mm Full Width at Half Maximum Gaussian smoothing kernel. Individual participants' whole-brain responses were modeled using a general linear model (GLM), with each experimental condition serving as a regressor. Individual parametric maps were then combined into a mixed-effects group GLM employing the 3dMEMA function in AFNI [7]. Statistical maps were corrected for multiple comparisons using a false discovery rate (FDR) q-value of 0.05.
AFNI software (version AFNI for Mac OS versions 23.2.04; [5]) was utilized to preprocess and analyze the data. A high-resolution T1-weighted anatomical scan underwent nonlinear warp estimation using the 3dQwarp AFNI function [6]. Functional data underwent correction for differences in slice-time acquisition, head motion, linear trends, and low-frequency noise. These images were registered to each participant's T1-weighted anatomical warped image, normalized to the Montreal Neurological Institute (MNI) coordinate system, and spatially smoothed using an 8-mm Full Width at Half Maximum Gaussian smoothing kernel. Individual participants' whole-brain responses were modeled using a general linear model (GLM), with each experimental condition serving as a regressor. Individual parametric maps were then combined into a mixed-effects group GLM employing the 3dMEMA function in AFNI [7]. Statistical maps were corrected for multiple comparisons using a false discovery rate (FDR) q-value of 0.05.
Results:
Behavioral scores revealed that children exhibited significantly lower accuracy and longer latencies compared to adolescents and adults. FMRI results indicated that solving difficult division problems elicited activity in both common and distinct regions across the age groups. Common areas included the middle and superior frontal gyri, bilateral supplementary motor areas, and the inferior parietal lobule, consistent with previous research on mathematical operations [8, 9, 10]. However, distinct areas in adults engaged the bilateral middle and superior temporal gyri, while in children and adolescents, temporal activation was observed in the left hemisphere. Activation in the left middle and superior temporal cortices was associated with storing arithmetic facts in long-term memory [11]. Left lateralized engagement of the insular cortex was observed in adolescents and adults but not in children.
Conclusions:
In conclusion, these findings suggest that cognitive strategies may not be fully developed in children. The agreement in brain areas among adults or between adults and adolescents, contrasted with their absence in children and adolescents, provides insights into neural processing during challenging mathematical tasks. These highlights reveal developmental distinctions in brain function and cognitive abilities across these age groups.
This work was supported by operation grant from The Brain Program of the IDEAS Research Center.
This work was supported by operation grant from The Brain Program of the IDEAS Research Center.
Higher Cognitive Functions:
Higher Cognitive Functions Other 1
Novel Imaging Acquisition Methods:
BOLD fMRI 2
Keywords:
Cognition
Data analysis
FUNCTIONAL MRI
Learning
MRI
NORMAL HUMAN
Open-Source Software
Statistical Methods
1|2Indicates the priority used for review
Provide references using author date format
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