What Does "Being an Expert" Mean to the Brain? Functional Specificity and Connectivity in Expertise

Highly Superior Autobiographical Memory (HSAM): A Systematic Review

Individuals possessing a Highly Superior Autobiographical Memory (HSAM) demonstrate an exceptional ability to recall their own past, excelling most when dates from their lifetime are used as retrieval cues. Fully understanding how neurocognitive mechanisms support exceptional memory could lead to benefits in areas of healthcare in which memory plays a central role and in legal fields reliant on witnesses' memories. Predominantly due to the rareness of the phenomenon, existing HSAM literature is highly heterogenous in its methodologies used. Therefore, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we performed the first systematic review on this topic, to collate the existing behavioural, neuroanatomical, and functional HSAM data. Results from the 20 experimental selected studies revealed that HSAM is categorised by rapidly retrieved, detailed and accurate autobiographical memories, and appears to avoid the normal aging process. Functional neuroimaging studies showed HSAM retrieval seems characterised by an intense overactivation of the usual autobiographical memory network, including posterior visual areas (e.g., the precuneus). Structural neuroanatomical differences do not appear to characterise HSAM, but altered hippocampal resting-state connectivity was commonly observed. We discuss theories of HSAM in relation to autobiographical encoding, consolidation, and retrieval, and suggest future directions for this research.

Identifying the Neural Bases of Math Competence Based on Structural and Functional Properties of the Human Brain

Human populations show large individual differences in math performance and math learning abilities. Early math skill acquisition is critical for providing the foundation for higher quantitative skill acquisition and succeeding in modern society. However, the neural bases underlying individual differences in math competence remain unclear. Modern neuroimaging techniques allow us to not only identify distinct local cortical regions but also investigate large-scale neural networks underlying math competence both structurally and functionally. To gain insights into the neural bases of math competence, this review provides an overview of the structural and functional neural markers for math competence in both typical and atypical populations of children and adults. Although including discussion of arithmetic skills in children, this review primarily focuses on the neural markers associated with complex math skills. Basic number comprehension and number comparison skills are outside the scope of this review. By synthesizing current research findings, we conclude that neural markers related to math competence are not confined to one particular region; rather, they are characterized by a distributed and interconnected network of regions across the brain, primarily focused on frontal and parietal cortices. Given that human brain is a complex network organized to minimize the cost of information processing, an efficient brain is capable of integrating information from different regions and coordinating the activity of various brain regions in a manner that maximizes the overall efficiency of the network to achieve the goal. We end by proposing that frontoparietal network efficiency is critical for math competence, which enables the recruitment of task-relevant neural resources and the engagement of distributed neural circuits in a goal-oriented manner. Thus, it will be important for future studies to not only examine brain activation patterns of discrete regions but also examine distributed network patterns across the brain, both structurally and functionally.

Contemporary pedagogy? The use of theory in practice: An evidence-informed perspective

Utilizing cognitive psychology as a foundation, this paper offers a deeper consideration of contemporary theoretical influences on coaching pedagogy. Countering recent dichotomies suggested between pedagogic approaches, we reintroduce key findings from the cognitive tradition and their implications for practice which coaches may find useful. Using cognitive load, novice and expert differences, desirable difficulty, and fidelity, we suggest that the lines drawn between different "pedagogies" may not be as sharp as suggested. Instead, we suggest that coaches avoid defining themselves as being aligned to a specific pedagogical or paradigmatic stance. We conclude by advocating for research informed practice, absent of strict theoretical boundaries and instead, considering contemporary pedagogy as drawing on the needs of the context, the experience of the coach and the best available evidence.

The neural correlates of retrieval and procedural strategies in mental arithmetic: A functional neuroimaging meta-analysis

Mental arithmetic is a complex skill of great importance for later academic and life success. Many neuroimaging studies and several meta-analyses have aimed to identify the neural correlates of mental arithmetic. Previous meta-analyses of arithmetic grouped all problem types into a single meta-analytic map, despite evidence suggesting that different types of arithmetic problems are solved using different strategies. We used activation likelihood estimation (ALE) to conduct quantitative meta-analyses of mental arithmetic neuroimaging (n = 31) studies, and subsequently grouped contrasts from the 31 studies into problems that are typically solved using retrieval strategies (retrieval problems) (n = 18) and problems that are typically solved using procedural strategies (procedural problems) (n = 19). Foci were compiled to generate probabilistic maps of activation for mental arithmetic (i.e., all problem types), retrieval problems, and procedural problems. Conjunction and contrast analyses were conducted to examine overlapping and distinct activation for retrieval and procedural problems. The conjunction analysis revealed overlapping activation for retrieval and procedural problems in the bilateral inferior parietal lobules, regions typically associated with magnitude processing. Contrast analyses revealed specific activation in the left angular gyrus for retrieval problems and specific activation in the inferior frontal gyrus and cingulate gyrus for procedural problems. These findings indicate that the neural bases of arithmetic systematically differs according to problem type, providing new insights into the dynamic and task-dependent neural underpinnings of the calculating brain.

Functional Connectivity Signatures Underlying Simultaneous Language Translation in Interpreters and Non-Interpreters of Mandarin and English: An fNIRS Study

Recent neuroimaging research has suggested that interpreters and non-interpreters elicit different brain activation patterns during simultaneous language translation. However, whether these two groups have different functional connectivity during such a task, and how the neural coupling is among brain subregions, are still not well understood. In this study, we recruited Mandarin (L1)/English (L2) interpreters and non-interpreter bilinguals, whom we asked to perform simultaneous language translation and reading tasks. Functional near-infrared spectroscopy (fNIRS) was used to collect cortical brain data for participants during each task, using 68 channels that covered the prefrontal cortex and the bilateral perisylvian regions. Our findings revealed both interpreter and non-interpreter groups recruited the right dorsolateral prefrontal hub when completing the simultaneous language translation tasks. We also found different functional connectivity between the groups. The interpreter group was characterized by information exchange between the frontal cortex and Wernicke’s area. In comparison, the non-interpreter group revealed neural coupling between the frontal cortex and Broca’s area. These findings indicate expertise modulates functional connectivity, possibly because of more developed cognitive skills associated with executive functions in interpreters.

Resting-State Functional Connectivity in Mathematical Expertise

To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians and non-mathematicians were distinguished depending on features of functional connectivity. We showed diverging involvement of the frontal-thalamic-temporal connections for mathematicians and the medial-frontal areas to precuneus and the lateral orbital gyrus to thalamus connections for non-mathematicians. Moreover, mathematicians who had higher scores in mathematical knowledge showed a weaker connection strength between the left and right caudate nucleus, demonstrating the connections' characteristics related to mathematical expertise. Separate functional networks between the two groups were validated with a maximum classification accuracy of 91.19% using the distinct resting-state fMRI-based functional connectivity features. We suggest the advantageous role of preconfigured resting-state functional connectivity, as well as the neural efficiency for experts' successful performance.

Increased Neural Efficiency in Visual Word Recognition: Evidence from Alterations in Event-Related Potentials and Multiscale Entropy

Visual word recognition is a relatively effortless process, but recent research suggests the system involved is malleable, with evidence of increases in behavioural efficiency after prolonged lexical decision task (LDT) performance. However, the extent of neural changes has yet to be characterized in this context. The neural changes that occur could be related to a shift from initially effortful performance that is supported by control-related processing, to efficient task performance that is supported by domain-specific processing. To investigate this, we replicated the British Lexicon Project, and had participants complete 16 h of LDT over several days. We recorded electroencephalography (EEG) at three intervals to track neural change during LDT performance and assessed event-related potentials and brain signal complexity. We found that response times decreased during LDT performance, and there was evidence of neural change through N170, P200, N400, and late positive component (LPC) amplitudes across the EEG sessions, which suggested a shift from control-related to domain-specific processing. We also found widespread complexity decreases alongside localized increases, suggesting that processing became more efficient with specific increases in processing flexibility. Together, these findings suggest that neural processing becomes more efficient and optimized to support prolonged LDT performance.

Neurobiological origins of individual differences in mathematical ability

Mathematical ability is heritable and related to several genes expressing proteins in the brain. It is unknown, however, which intermediate neural phenotypes could explain how these genes relate to mathematical ability. Here, we examined genetic effects on cerebral cortical volume of 3-6-year-old children without mathematical training to predict mathematical ability in school at 7-9 years of age. To this end, we followed an exploration sample (n = 101) and an independent replication sample (n = 77). We found that ROBO1, a gene known to regulate prenatal growth of cerebral cortical layers, is associated with the volume of the right parietal cortex, a key region for quantity representation. Individual volume differences in this region predicted up to a fifth of the behavioral variance in mathematical ability. Our findings indicate that a fundamental genetic component of the quantity processing system is rooted in the early development of the parietal cortex.

Brain Responses to Emotional Infant Faces in New Mothers and Nulliparous Women

The experience of motherhood is one of the most salient events in a woman’s life. Motherhood is associated with a series of neurophysiological, psychological, and behavioral changes that allow women to better adapt to their new role as mothers. Infants communicate their needs and physiological states mainly through salient emotional expressions, and maternal responses to infant signals are critical for infant survival and development. In this study, we investigated the whole brain functional response to emotional infant faces in 20 new mothers and 22 nulliparous women during functional magnetic resonance imaging scans. New mothers showed higher brain activation in regions involved in infant facial expression processing and empathic and mentalizing networks than nulliparous women. Furthermore, magnitudes of the activation of the left parahippocampal gyrus and the left fusiform gyrus, recruited during facial expression processing, were positively correlated with empathic concern (EC) scores in new mothers when viewing emotional (happy-sad) faces contrasted to neutral faces. Taken together, these results indicate that the experience of being a mother affects human brain responses in visual and social cognitive brain areas and in brain areas associated with theory-of-mind related and empathic processing.

Hierarchy processing in human neurobiology: how specific is it?

Although human and non-human animals share a number of perceptual and cognitive abilities, they differ in their ability to process hierarchically structured sequences. This becomes most evident in the human capacity to process natural language characterized by structural hierarchies. This capacity is neuroanatomically grounded in the posterior part of left Broca's area (Brodmann area (BA) 44), located in the inferior frontal gyrus, and its dorsal white matter fibre connection to the temporal cortex. Within this neural network, BA 44 itself subserves hierarchy building and the strength of its connection to the temporal cortex correlates with the processing of syntactically complex sentences. Whether these brain structures are also relevant for other human cognitive abilities is a current debate. Here, this question will be evaluated with respect to those human cognitive abilities that are assumed to require hierarchy building, such as music, mathematics and Theory of Mind. Rather than supporting a domain-general view, the data indicate domain-selective neural networks as the neurobiological basis for processing hierarchy in different cognitive domains. Recent cross-species white matter comparisons suggest that particular connections within the networks may make the crucial difference in the brain structure of human and non-human primates, thereby enabling cognitive functions specific to humans. This article is part of the theme issue 'What can animal communication teach us about human language?'

Multimodal neurocognitive markers of interoceptive tuning in smoked cocaine

Contemporary neurocognitive models of drug addiction have associated this condition with changes in interoception -namely, the sensing and processing of body signals that fulfill homeostatic functions relevant for the onset and maintenance of addictive behavior. However, most previous evidence is inconsistent, behaviorally unspecific, and virtually null in terms of direct electrophysiological and multimodal markers. To circumvent these limitations, we conducted the first assessment of the relation between cardiac interoception and smoked cocaine dependence (SCD) in a sample of (a) 25 participants who fulfilled criteria for dependence on such a drug, (b) 22 participants addicted to insufflated clorhidrate cocaine (only for behavioral assessment), and (c) 25 healthy controls matched by age, gender, education, and socioeconomic status. We use a validated heartbeat-detection (HBD) task and measured modulations of the heart-evoked potential (HEP) during interoceptive accuracy and interoceptive learning conditions. We complemented this behavioral and electrophysiological data with offline structural (MRI) and functional connectivity (fMRI) analysis of the main interoceptive hubs. HBD and HEP results convergently showed that SCD subjects presented ongoing psychophysiological measures of enhanced interoceptive accuracy. This pattern was associated with a structural and functional tuning of interoceptive networks (reduced volume and specialized network segregation). Taken together, our findings provide the first evidence of an association between cardiac interoception and smoked cocaine, partially supporting models that propose hyper-interoception as a key aspect of addiction. More generally, our study shows that multimodal assessments of interoception could substantially inform the clinical and neurocognitive characterization of psychophysiological and neurocognitive adaptations triggered by addiction.

Mathematical expertise modulates the architecture of dorsal and cortico-thalamic white matter tracts

To what extent are levels of cognitive expertise reflected in differential structural connectivity of the brain? We addressed this question by analyzing the white matter brain structure of experts (mathematicians) versus non-experts (non-mathematicians) using probabilistic tractography. Having mathematicians and non-mathematicians as participant groups enabled us to directly compare profiles of structural connectivity arising from individual levels of expertise in mathematics. Tracking from functional seed regions activated during the processing of complex arithmetic formulas revealed an involvement of various fiber bundles such the inferior fronto-occipital fascicle, arcuate fasciculus/superior longitudinal fasciculus (AF/SLF), cross-hemispheric connections of frontal lobe areas through the corpus callosum and cortico-subcortical connectivity via the bilateral thalamic radiation. With the aim of investigating expertise-dependent structural connectivity, the streamline density was correlated with the level of expertise, defined by automaticity of processing complex mathematics. The results showed that structural integrity of the AF/SLF was higher in individuals with higher automaticity, while stronger cortico-thalamic connectivity was associated with lower levels of automaticity. Therefore, we suggest that expertise in the domain of mathematics is reflected in plastic changes of the brain's white matter structure, possibly reflecting a general principle of cognitive expertise.

Distinct neural processes support post-success and post-error slowing in the stop signal task

Executive control requires behavioral adaptation to environmental contingencies. In the stop signal task (SST), participants exhibit slower go trial reaction time (RT) following a stop trial, whether or not they successfully interrupt the motor response. In previous fMRI studies, we demonstrated activation of the right-hemispheric ventrolateral prefrontal cortex, in the area of inferior frontal gyrus, pars opercularis (IFGpo) and anterior insula (AI), during post-error slowing (PES). However, in similar analyses we were not able to identify regional activities during post-success slowing (PSS). Here, we revisited this issue in a larger sample of participants (n=100) each performing the SST for 40 min during fMRI. We replicated IFGpo/AI activation to PES (p≤0.05, FWE corrected). Further, PSS engages decreased activation in a number of cortical regions including the left inferior frontal cortex (IFC; p≤0.05, FWE corrected). We employed Granger causality mapping to identify areas that provide inputs each to the right IFGpo/AI and left IFC, and computed single-trial amplitude (STA) of stop trials of these input regions as well as the STA of post-stop trials of the right IFGpo/AI and left IFC. The STAs of the right inferior precentral sulcus and supplementary motor area (SMA) and right IFGpo/AI were positively correlated and the STAs of the left SMA and left IFC were positively correlated (slope>0, p's≤0.01, one-sample t test), linking regional responses during stop success and error trials to those during PSS and PES. These findings suggest distinct neural mechanisms to support PSS and PES.