scholarly journals Algebra dissociates from arithmetic in the brain semantic network

2022 ◽  
Vol 18 (1) ◽  
Author(s):  
Dazhi Cheng ◽  
Mengyi Li ◽  
Jiaxin Cui ◽  
Li Wang ◽  
Naiyi Wang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Supplementary Motor Area ◽  
Semantic Network ◽  
Brain Activation ◽  
Motor Area ◽  
Angular Gyrus ◽  
Single Trial ◽  
Positive Functional ◽  
Brain Behavior ◽  
The Brain

Abstract Background Mathematical expressions mainly include arithmetic (such as 8 − (1 + 3)) and algebra (such as a − (b + c)). Previous studies have shown that both algebraic processing and arithmetic involved the bilateral parietal brain regions. Although previous studies have revealed that algebra was dissociated from arithmetic, the neural bases of the dissociation between algebraic processing and arithmetic is still unclear. The present study uses functional magnetic resonance imaging (fMRI) to identify the specific brain networks for algebraic and arithmetic processing. Methods Using fMRI, this study scanned 30 undergraduates and directly compared the brain activation during algebra and arithmetic. Brain activations, single-trial (item-wise) interindividual correlation and mean-trial interindividual correlation related to algebra processing were compared with those related to arithmetic. The functional connectivity was analyzed by a seed-based region of interest (ROI)-to-ROI analysis. Results Brain activation analyses showed that algebra elicited greater activation in the angular gyrus and arithmetic elicited greater activation in the bilateral supplementary motor area, left insula, and left inferior parietal lobule. Interindividual single-trial brain-behavior correlation revealed significant brain-behavior correlations in the semantic network, including the middle temporal gyri, inferior frontal gyri, dorsomedial prefrontal cortices, and left angular gyrus, for algebra. For arithmetic, the significant brain-behavior correlations were located in the phonological network, including the precentral gyrus and supplementary motor area, and in the visuospatial network, including the bilateral superior parietal lobules. For algebra, significant positive functional connectivity was observed between the visuospatial network and semantic network, whereas for arithmetic, significant positive functional connectivity was observed only between the visuospatial network and phonological network. Conclusion These findings suggest that algebra relies on the semantic network and conversely, arithmetic relies on the phonological and visuospatial networks.

scholarly journals Algebra dissociates from arithmetic in the brain semantic network

2021 ◽  
Author(s):  
Dazhi Cheng ◽  
Mengyi Li ◽  
Naiyi Wang ◽  
Liangyuan Ouyang ◽  
Xinlin Zhou
Keyword(s):  
Supplementary Motor Area ◽  
Semantic Network ◽  
Brain Activation ◽  
Brain Regions ◽  
Motor Area ◽  
Angular Gyrus ◽  
Precentral Gyrus ◽  
Single Trial ◽  
Brain Behavior ◽  
The Brain

Abstract Background Mathematical expressions mainly include arithmetic (such as 8 − (1 + 3)) and algebraic expressions (such as a − (b + c)). Previous studies shown that both algebraic processing and arithmetic involved the bilateral parietal brain regions. Although behavioral and neuropsychological studies have revealed the dissociation between algebra and arithmetic, how algebraic processing is dissociated from arithmetic in brain networks is still unclear. Methods Using functional magnetic resonance imaging (fMRI), this study scanned 30 undergraduates and directly compared the brain activation during algebra and arithmetic. Brain activations, single-trial (item-wise) interindividual correlation and mean-trial interindividual correlation related to algebra processing were compared with those related to arithmetic. Results Brain activation analyses showed that algebra elicited greater activation in the angular gyrus and arithmetic elicited greater activation in the bilateral supplementary motor area, left insula, and left inferior parietal lobule. Interindividual single-trial brain-behavior correlation revealed significant brain-behavior correlations in the semantic network, including the middle temporal gyri, inferior frontal gyri, dorsomedial prefrontal cortices, and left angular gyrus, for algebra. For arithmetic, the significant brain-behavior correlations were located in the phonological network, including the precentral gyrus and supplementary motor area, and in the visuospatial network, including the bilateral superior parietal lobules. Conclusion These findings suggest that algebra relies on the semantic network and arithmetic relies on the phonological and visuospatial networks.

scholarly journals The Brain Resting-State Functional Connectivity Underlying Violence Proneness: Is It a Reliable Marker for Neurocriminology? A Systematic Review

2019 ◽  
Vol 9 (1) ◽  
pp. 11 ◽  
Author(s):  
Ángel Romero-Martínez ◽  
Macarena González ◽  
Marisol Lila ◽  
Enrique Gracia ◽  
Luis Martí-Bonmatí ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Effective Treatment ◽  
Resting State ◽  
Brain Structures ◽  
Prevention Programs ◽  
Angular Gyrus ◽  
Resting State Functional Connectivity ◽  
Treatment And Prevention ◽  
Reliable Marker ◽  
The Brain

Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has tried to demonstrate whether the intrinsic activity within the brain at rest in the absence of any external stimulation (resting-state functional connectivity; RSFC) could be employed as a reliable marker for several cognitive abilities and personality traits that are important in behavior regulation, particularly, proneness to violence. Aims: This review aims to highlight the association between the RSFC among specific brain structures and the predisposition to experiencing anger and/or responding to stressful and distressing situations with anger in several populations. Methods: The scientific literature was reviewed following the PRISMA quality criteria for reviews, using the following digital databases: PubMed, PsycINFO, Psicodoc, and Dialnet. Results: The identification of 181 abstracts and retrieval of 34 full texts led to the inclusion of 17 papers. The results described in our study offer a better understanding of the brain networks that might explain the tendency to experience anger. The majority of the studies highlighted that diminished RSFC between the prefrontal cortex and the amygdala might make people prone to reactive violence, but that it is also necessary to contemplate additional cortical (i.e. insula, gyrus [angular, supramarginal, temporal, fusiform, superior, and middle frontal], anterior and posterior cingulated cortex) and subcortical brain structures (i.e. hippocampus, cerebellum, ventral striatum, and nucleus centralis superior) in order to explain a phenomenon as complex as violence. Moreover, we also described the neural pathways that might underlie proactive violence and feelings of revenge, highlighting the RSFC between the OFC, ventral striatal, angular gyrus, mid-occipital cortex, and cerebellum. Conclusions. The results from this synthesis and critical analysis of RSFC findings in several populations offer guidelines for future research and for developing a more accurate model of proneness to violence, in order to create effective treatment and prevention programs.

scholarly journals Resting State Functional Connectivity Predicts Future Changes in Sedentary Behavior

2021 ◽  
Author(s):  
Timothy P. Morris ◽  
Aaron Kucyi ◽  
Sheeba Arnold Anteraper ◽  
Maiya Rachel Geddes ◽  
Alfonso Nieto-Castañon ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Exercise Intervention ◽  
Supplementary Motor Area ◽  
Anterior Insula ◽  
Motor Area ◽  
Anterior Cingulate ◽  
Sedentary Behaviors ◽  
Resting State Functional Connectivity ◽  
The Right

AbstractInformation about a person’s available energy resources is integrated in daily behavioral choices that weigh motor costs against expected rewards. It has been posited that humans have an innate attraction towards effort minimization and that executive control is required to overcome this prepotent disposition. With sedentary behaviors increasing at the cost of millions of dollars spent in health care and productivity losses due to physical inactivity-related deaths, understanding the predictors of sedentary behaviors will improve future intervention development and precision medicine approaches. In 64 healthy older adults participating in a 6-month aerobic exercise intervention, we use neuroimaging (resting state functional connectivity), baseline measures of executive function and accelerometer measures of time spent sedentary to predict future changes in objectively measured time spent sedentary in daily life. Using cross-validation and bootstrap resampling, our results demonstrate that functional connectivity between 1) the anterior cingulate cortex and the supplementary motor area and 2) the right anterior insula and the left temporoparietal/temporooccipital junction, predict changes in time spent sedentary, whereas baseline cognitive, behavioral and demographic measures do not. Previous research has shown activation in and between the anterior cingulate and supplementary motor area as well as in the right anterior insula during effort avoidance and tasks that integrate motor costs and reward benefits in effort-based decision making. Our results add important knowledge toward understanding mechanistic associations underlying complex sedentary behaviors.

An Exploratory Pilot Study of Brain Activation and Functional Connectivity Induced by the “Goldberg” Variations 276 years after their Commission

2019 ◽  
Vol 34 (4) ◽  
pp. 191-197
Author(s):  
Christof Karmonik ◽  
Makiko Hirata ◽  
Saba Elias ◽  
J Todd Frazier
Keyword(s):  
Pilot Study ◽  
Functional Connectivity ◽  
Brain Connectivity ◽  
Brain Activation ◽  
Johann Sebastian Bach ◽  
Technical Development ◽  
The Subject ◽  
Goldberg Variations ◽  
The Brain

Around 1741, composer Johann Sebastian Bach published a long and complicated keyboard piece, calling it Aria with diverse variations for a harpsichord with two manuals. It was the capstone of a publication project called German Clavier-Übung (Keyboard Practice) where Bach wanted to show what was possible at the keyboard in terms of technical development, virtuosic finesse and compositional sophistication. The music is meticulously patterned, beginning with a highly ornamented Aria, the bass line of which fuels the 30 variations that follow. The piece is clearly divided into two parts with the second half beginning with an overture with a fanfare opening, in variation 16. The piece ends as it begins, with the return of the Aria. Here, we present an investigation into activation and connectivity in the brain of a pianist, who listened to her own recording of the “Goldberg” variation while undergoing a fMRI examination. Similarity of brain connectivity is quantified and compared with the subjective scores provided by the subject.

scholarly journals Functional connectivity of supplementary motor area during finger-tapping in major depression

2020 ◽  
Vol 99 ◽  
pp. 152166
Author(s):  
Pegah Sarkheil ◽  
Panayiotis Odysseos ◽  
Ira Bee ◽  
Mikhail Zvyagintsev ◽  
Irene Neuner ◽  
...  
Keyword(s):  
Major Depression ◽  
Functional Connectivity ◽  
Supplementary Motor Area ◽  
Motor Area ◽  
Finger Tapping

scholarly journals PO-057 Motor Functional Connectivity Analysis of Brain Control Network on High Level Athletes with fMRI Research

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Jiaxin Li ◽  
Chengbo Du ◽  
Mengjiao Chen ◽  
Ke Li ◽  
Jiao Xue ◽  
...  
Keyword(s):  
College Students ◽  
Functional Connectivity ◽  
Brain Function ◽  
Supplementary Motor Area ◽  
Premotor Area ◽  
High Level ◽  
Exercise Fatigue ◽  
The Brain ◽  
Central Buckle

Objective The nervous system is the control center that performs the function of the human body, including each nucleus of the cerebral cortex and basal ganglia, which can control the motion of the body through three pathways-direct pathway, indirect pathway and hyperdirect pathway. Long-term physical exercise can effectively improve the human respiratory and circulatory system function indicators and promote the development of nervous system.In order to discuss the mechanisms of the high level athletes' control of the brain function network and provide the experimental basis for the study of the motor control of the central nervous system, this research collects the activation images of the cortex and basal ganglia nuclei of the ordinary college students and the high level athletes and analyzes the function connection coefficient between the groups. Methods The subjects were 15 high level athletes and 15 ordinary college students. the changes of the brain structure and DTI fiber in the state of quiet and fatigue were collected by the functional magnetic resonance imaging (fMRI). Matlab software was used to compare images and data and to calculate the correlation coefficient between the related nuclear groups. Results (1) Compared with ordinary college students, the functional connectivity coefficient between the left thalamus and the left hippocampus is different in high level athletes (P<0.05). (2) The high level athletes’ functional connectivity in the left premotor area-right premotor area, left premotor area-right striatum, right premotor area-left central buckle in supplementary motor area, right premotor area-right central buckle in supplementary motor area, right premotor area-right striatum and right premotor area-left cerebellum were changed significantly after exercise fatigue (P<0.05). Conclusions The plasticity of brain function can be affected by long-term exercise training, which depends on sport training level. After exercise fatigue, the network connection system and nerve projection density change between cortical and subcortical nuclei, suggesting that exercise fatigue will change the functional connection between parts of the brain.（NSFC：31401018 SKXJX2014014).

scholarly journals Large-scale intrinsic connectivity is consistent across varying task demands

2018 ◽  
Author(s):  
Paulina Kieliba ◽  
Sasidhar Madugula ◽  
Nicola Filippini ◽  
Eugene P. Duff ◽  
Tamar R. Makin
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Brain Activation ◽  
Whole Brain ◽  
Activation Patterns ◽  
Intrinsic Connectivity ◽  
Connectivity Patterns ◽  
Brain Functional Connectivity ◽  
The Brain

AbstractMeasuring whole-brain functional connectivity patterns based on task-free (‘restingstate’) spontaneous fluctuations in the functional MRI (fMRI) signal is a standard approach to probing habitual brain states, independent of task-specific context. This view is supported by spatial correspondence between task- and rest-derived connectivity networks. Yet, it remains unclear whether intrinsic connectivity observed in a resting-state acquisitions is persistent during task. Here, we sought to determine how changes in ongoing brain activation, elicited by task performance, impact the integrity of whole-brain functional connectivity patterns. We employed a ‘steadystates’ paradigm, in which participants continuously executed a specific task (without baseline periods). Participants underwent separate task-based (visual, motor and visuomotor) or task-free (resting) steady-state scans, each performed over a 5-minute period. This unique design allowed us to apply a set of traditional resting-state analyses to various task-states. In addition, a classical fMRI block-design was employed to identify individualized brain activation patterns for each task, allowing to characterize how differing activation patterns across the steady-states impact whole-brain intrinsic connectivity patterns. By examining correlations across segregated brain regions (nodes) and the whole brain (using independent component analysis), we show that the whole-brain network architecture characteristic of the resting-state is robustly preserved across different steady-task states, despite striking inter-task changes in brain activation (signal amplitude). Subtler changes in functional connectivity were detected locally, within the active networks. Together, we show that intrinsic connectivity underlying the canonical resting-state networks is relatively stable even when participants are engaged in different tasks and is not limited to the resting-state.New and NoteworthyDoes intrinsic functional connectivity (FC) reflect the canonical or transient state of the brain? We tested the consistency of the intrinsic connectivity networks across different task-conditions. We show that despite local changes in connectivity, at the whole-brain level there is little modulation in FC patterns, despite profound and large-scale activation changes. We therefore conclude that intrinsic FC largely reflects the a priori habitual state of the brain, independent of the specific cognitive context.

scholarly journals Single-trial neural dynamics influence auditory category learning

2020 ◽  
Author(s):  
Kelsey Mankel ◽  
Philip I. Pavlik ◽  
Gavin M. Bidelman
Keyword(s):  
Computational Modeling ◽  
Category Learning ◽  
Brain Activity ◽  
Educational Data Mining ◽  
Training Session ◽  
Performance Model ◽  
Learning Performance ◽  
Single Trial ◽  
Brain Behavior ◽  
The Brain

AbstractPercepts are naturally grouped into meaningful categories to process continuous stimulus variations in the environment. Theories of category acquisition have existed for decades, but how they arise in the brain due to learning is not well understood. Here, advanced computational modeling techniques borrowed from educational data mining and cognitive psychology were used to trace the development of auditory categories within a short-term training session. Nonmusicians were rapidly trained for 20 min on musical interval identification (i.e., minor and major 3rd interval dyads) while their brain activity was recorded via EEG. Categorization performance and neural responses were then assessed for the trained (3rds) and novel untrained (major/minor 6ths) continua. Computational modeling was used to predict behavioral identification responses and whether the inclusion of single-trial features of the neural data could predict successful learning performance. Model results revealed meaningful brain-behavior relationships in auditory category learning detectible on the single-trial level; smaller P2 amplitudes were associated with a greater probability of correct interval categorization after learning. These findings highlight the nuanced dynamics of brain-behavior coupling that help explain the temporal emergence of auditory categorical learning in the brain.

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