Math anxiety is a negative emotional reaction to situations involving mathematical problem solving. Math anxiety has a detrimental impact on an individual’s long-term professional success, but its neurodevelopmental origins are unknown. In a functional MRI study on 7- to 9-year-old children, we showed that math anxiety was associated with hyperactivity in right amygdala regions that are important for processing negative emotions. In addition, we found that math anxiety was associated with reduced activity in posterior parietal and dorsolateral prefrontal cortex regions involved in mathematical reasoning. Multivariate classification analysis revealed distinct multivoxel activity patterns, which were independent of overall activation levels in the right amygdala. Furthermore, effective connectivity between the amygdala and ventromedial prefrontal cortex regions that regulate negative emotions was elevated in children with math anxiety. These effects were specific to math anxiety and unrelated to general anxiety, intelligence, working memory, or reading ability. Our study identified the neural correlates of math anxiety for the first time, and our findings have significant implications for its early identification and treatment.

Background Early childhood anxiety has been linked to an increased risk for developing mood and anxiety disorders. Little, however, is known about its effect on the brain during early childhood – a period when anxiety-related traits begin to be reliably identifiable. Even less is known about the neurodevelopmental origins of individual differences in childhood anxiety. Methods We combined structural and functional magnetic resonance imaging (fMRI) with neuropsychological assessment of anxiety based on daily life experiences to investigate the effects of anxiety on the brain in seventy-six young children. We then used machine learning algorithms with balanced cross-validation to examine brain-based predictors of individual differences in childhood anxiety. Results Even in children as young as ages 7–9, high childhood anxiety is associated with enlarged amygdala volume and this enlargement is localized specifically to the basolateral amygdala. High childhood anxiety is also associated with increased connectivity between the amygdala and distributed brain systems involved in attention, emotion perception and regulation, and these effects are most prominent effect in basolateral amygdala. Critically, machine learning algorithms revealed that levels of childhood anxiety could be reliably predicted by amygdala morphometry and intrinsic functional connectivity, with the left basolateral amygdala emerging again as the strongest predictor. Conclusions Individual differences in anxiety can be reliably detected with high predictive value in amygdala-centric emotion circuits at a surprisingly young age. Our study provides important new insights into the neurodevelopmental origins of anxiety, and has significant implications for the development of predictive biomarkers to identify children at-risk for anxiety disorders.

The human brain undergoes protracted development, with dramatic changes in expression and regulation of emotion from childhood to adulthood. The amygdala is a brain structure that plays a pivotal role in emotion-related functions. Investigating developmental characteristics of the amygdala and associated functional circuits in children is important for understanding how emotion processing matures in the developing brain. The basolateral amygdala (BLA) and centromedial amygdala (CMA) are two major amygdalar nuclei that contribute to distinct functions via their unique pattern of interactions with cortical and subcortical regions. Almost nothing is currently known about the maturation of functional circuits associated with these amygdala nuclei in the developing brain. Using intrinsic connectivity analysis of functional magnetic resonance imaging data, we investigated developmental changes in functional connectivity of the BLA and CMA in twenty-four 7-to 9-y-old typically developing children compared with twenty-four 19-to 22-y-old healthy adults. Children showed significantly weaker intrinsic functional connectivity of the amygdala with subcortical, paralimbic, and limbic structures, polymodal association, and ventromedial prefrontal cortex. Importantly, target networks associated with the BLA and CMA exhibited greater overlap and weaker dissociation in children. In line with this finding, children showed greater intraamygdala connectivity between the BLA and CMA. Critically, these developmental differences were reproducibly identified in a second independent cohort of adults and children. Taken together, our findings point toward weak integration and segregation of amygdala circuits in young children. These immature patterns of amygdala connectivity have important implications for understanding typical and atypical development of emotion-related brain circuitry. F rom childhood to adulthood, the development of functional brain networks underlies the maturation of increasingly nuanced cognitive and affective abilities (1, 2). In particular, human capabilities for a wide range of affective functions change dramatically from childhood to adulthood, suggesting remarkable maturation of the brain's affective systems. The amygdala lies at the core of brain's affective processing systems (3, 4) and multiple lines of research in human adults have implicated amygdala-centered networks in emotion (5-7). The amygdalar complex encompasses multiple anatomical subregions with distinct connectivity profiles that support distinct affective functions (3,8). However, almost nothing is known about how networks associated with the amygdala mature with development. Knowledge of how major amygdalar circuits mature in children is important not only for gaining insights into typical development of affective functions, but also for understanding the ontogeny of affective dysfunction in disorders such as anxiety and depression (9, 10).The basolateral amygdala (BLA) and centromedial amygdala (CMA) are two major groups of amygdalar nuclei t...

Developmental dyscalculia (DD) is marked by specific deficits in processing numerical and mathematical information despite normal intelligence (IQ) and reading ability. We examined how brain circuits used by young children with DD to solve simple addition and subtraction problems differ from those used by typically developing (TD) children who were matched on age, IQ, reading ability, and working memory. Children with DD were slower and less accurate during problem solving than TD children, and were especially impaired on their ability to solve subtraction problems. Children with DD showed significantly greater activity in multiple parietal, occipito-temporal and prefrontal cortex regions while solving addition and subtraction problems. Despite poorer performance during subtraction, children with DD showed greater activity in multiple intra-parietal sulcus (IPS) and superior parietal lobule subdivisions in the dorsal posterior parietal cortex as well as fusiform gyrus in the ventral occipito-temporal cortex. Critically, effective connectivity analyses revealed hyper-connectivity, rather than reduced connectivity, between the IPS and multiple brain systems including the lateral fronto-parietal and default mode networks in children with DD during both addition and subtraction. These findings suggest the IPS and its functional circuits are a major locus of dysfunction during both addition and subtraction problem solving in DD, and that inappropriate task modulation and hyper-connectivity, rather than under-engagement and under-connectivity, are the neural mechanisms underlying problem solving difficulties in children with DD. We discuss our findings in the broader context of multiple levels of analysis and performance issues inherent in neuroimaging studies of typical and atypical development.

Although lesion studies over the past several decades have focused on functional dissociations in posterior parietal cortex (PPC) during arithmetic, no consistent view has emerged of its differential involvement in addition, subtraction, multiplication, and division. To circumvent problems with poor anatomical localization, we examined functional overlap and dissociations in cytoarchitectonically-defined subdivisions of the intraparietal sulcus (IPS), superior parietal lobule (SPL) and angular gyrus (AG), across these four operations. Compared to a number identification control task, all operations except addition, showed a consistent profile of left posterior IPS activation and deactivation in the right posterior AG. Multiplication and subtraction differed significantly in right, but not left, IPS and AG activity, challenging the view that the left AG differentially subserves retrieval during multiplication. Although addition and multiplication both rely on retrieval, multiplication evoked significantly greater activation in right posterior IPS, as well as the prefrontal cortex, lingual and fusiform gyri, demonstrating that addition and multiplication engage different brain processes. Comparison of PPC responses to the two pairs of inverse operations: division vs. multiplication and subtraction vs. addition revealed greater activation of left lateral SPL during division, suggesting that processing inverse relations is operation specific. Our findings demonstrate that individual IPS, SPL and AG subdivisions are differentially modulated by the four arithmetic operations and they point to significant functional heterogeneity and individual differences in activation and deactivation within the PPC. Critically, these effects are related to retrieval, calculation and inversion, the three key cognitive processes that are differentially engaged by arithmetic operations. Our findings point to distributed representation of these processes in the human PPC and also help explain why lesion and previous imaging studies have yielded inconsistent findings.

Background Autism spectrum disorders (ASD) are neurodevelopmental disorders with a prevalence of nearly 1:100. Structural imaging studies point to disruptions in multiple brain areas, yet the precise neuroanatomical nature of these disruptions remains unclear. Characterization of brain structural differences in children with ASD is critical for development of biomarkers that may eventually be used to improve diagnosis and monitor response to treatment. Methods We use voxel-based morphometry (VBM) along with a novel multivariate pattern analysis (MPA) approach and searchlight algorithm to classify structural magnetic resonance imaging data acquired from 24 children and adolescents with autism and 24 age-, gender-, and IQ-matched neurotypical participants. Results Despite modest VBM differences, MPA revealed that the groups could be distinguished with accuracies of around 90% based on gray matter in the posterior cingulate cortex (PCC), medial prefrontal cortex, and bilateral medial temporal lobes, all regions within the default mode network (DMN). Abnormalities in the PCC were associated with impaired ADI-R communication scores. Gray matter in additional prefrontal, lateral temporal, and subcortical structures also discriminated between the two groups with accuracies between 81-90%. White matter in the inferior fronto-occipital and superior longitudinal fasciculi, and the genu and splenium of the corpus callosum, achieved up to 85% classification accuracy. Conclusions Multiple brain regions, including those belonging to the DMN, exhibit aberrant structural organization in children with autism. Brain-based biomarkers derived from structural MRI data may eventually contribute to identification of the neuroanatomical basis of symptom heterogeneity and to the development of more targeted early intervention.

Children's gains in problem-solving skills during the elementary school years are characterized by shifts in the mix of problem-solving approaches, with inefficient procedural strategies being gradually replaced with direct retrieval of domain-relevant facts. We used a well-established procedure for strategy assessment during arithmetic problem solving to investigate the neural basis of this critical transition. We indexed behavioral strategy use by focusing on the retrieval frequency and examined changes in brain activity and connectivity associated with retrieval fluency during arithmetic problem solving in second- and third-grade (7- to 9-year-old) children. Children with higher retrieval fluency showed elevated signal in the right hippocampus, parahippocampal gyrus (PHG), lingual gyrus (LG), fusiform gyrus (FG), left ventrolateral PFC (VLPFC), bilateral dorsolateral PFC (DLPFC), and posterior angular gyrus. Critically, these effects were not confounded by individual differences in problem-solving speed or accuracy. Psychophysiological interaction analysis revealed significant effective connectivity of the right hippocampus with bilateral VLPFC and DLPFC during arithmetic problem solving. Dynamic causal modeling analysis revealed strong bidirectional interactions between the hippocampus and the left VLPFC and DLPFC. Furthermore, causal influences from the left VLPFC to the hippocampus served as the main top–down component, whereas causal influences from the hippocampus to the left DLPFC served as the main bottom–up component of this retrieval network. Our study highlights the contribution of hippocampal–prefrontal circuits to the early development of retrieval fluency in arithmetic problem solving and provides a novel framework for studying dynamic developmental processes that accompany children's development of problem-solving skills.

Anhedonia is the inability to experience pleasure from normally pleasant stimuli. Although anhedonia is a prominent feature of many psychiatric disorders, trait anhedonia is also observed dimensionally in healthy individuals. Currently, the neurobiological basis of anhedonia is poorly understood because it has been mainly investigated in patients with psychiatric disorders. Thus, previous studies have not been able to adequately disentangle the neural correlates of anhedonia from other clinical symptoms. In this study, trait anhedonia was assessed in well-characterized healthy participants with no history of Axis I psychiatric illness. Functional magnetic resonance imaging with musical stimuli was used to examine brain responses and effective connectivity in relation to individual differences in anhedonia [...