It is well-known that children show gradual and protracted improvement in an array of behaviors involved in the conscious control of thought and emotion. Non-invasive neuroimaging in developing populations has revealed many neural correlates of behavior, particularly in the developing cingulate cortex and fronto-striatal circuits. These brain regions, themselves, undergo protracted molecular and cellular change in the first two decades of human development and, as such, are ideal regions of interest for cognitive- and imaging-genetic studies that seek to link processes at the biochemical and synaptic levels to brain activity and behavior. We review our research to-date that employs both adult and child-friendly versions of the Attention Network Task (ANT) in an effort to begin to describe the role of specific genes in the assembly of a functional attention system. Presently, we constrain our predictions for genetic association studies by focusing on the role of the anterior cingulate cortex (ACC) and of dopamine in the development of executive attention.
Morphological changes in the anterior cingulate cortex are found in subjects with schizophrenia, attention deficit hyperactivity disorder, and obsessive compulsive disorder. These changes are hypothesized to underlie the impairments these individuals show on tasks that require cognitive control. The anterior cingulate cortex has previously been shown to be active in situations involving high conflict, presentation of salient, distracting stimuli, and error processing, i.e. situations that occur when a shift in attention or responding is required. However, there is some uncertainty as to what specific role the anterior cingulate cortex plays in these situations. The current study used converging evidence from two behavioral paradigms to determine the effects of excitotoxic lesions in the anterior cingulate cortex on executive control. The first assay tests reversal learning, attentional set formation and shifting. The second assesses sustained attention with and without distractors. Animals with anterior cingulate cortex lesions were impaired during reinforcement reversals, discriminations that required subjects to disregard previously relevant stimulus attributes and showed a more rapid decline in attentional ability than Sham-Lx subjects when maintaining sustained attention for extended periods of time. These results are consistent with the hypothesis that the anterior cingulate cortex is involved in attending to stimulus attributes that currently predict reinforcement in the presence of previously relevant, salient distractors and maintaining sustained attention over prolonged time on task.
prefrontal cortex; cognitive control; executive function; selective attention; cingulated
Developmental dyslexia is a specific cognitive disorder in reading acquisition that has genetic and neurological origins. Despite histological evidence for brain differences in dyslexia, we recently demonstrated that in large cohort of subjects, no differences between control and dyslexic readers can be found at the macroscopic level (MRI voxel), because of large variances in brain local volumes. In the present study, we aimed at finding brain areas that most discriminate dyslexic from control normal readers despite the large variance across subjects. After segmenting brain grey matter, normalizing brain size and shape and modulating the voxels' content, normal readers' brains were used to build a 'typical' brain via bootstrapped confidence intervals. Each dyslexic reader's brain was then classified independently at each voxel as being within or outside the normal range. We used this simple strategy to build a brain map showing regional percentages of differences between groups. The significance of this map was then assessed using a randomization technique.
The right cerebellar declive and the right lentiform nucleus were the two areas that significantly differed the most between groups with 100% of the dyslexic subjects (N = 38) falling outside of the control group (N = 39) 95% confidence interval boundaries. The clinical relevance of this result was assessed by inquiring cognitive brain-based differences among dyslexic brain subgroups in comparison to normal readers' performances. The strongest difference between dyslexic subgroups was observed between subjects with lower cerebellar declive (LCD) grey matter volumes than controls and subjects with higher cerebellar declive (HCD) grey matter volumes than controls. Dyslexic subjects with LCD volumes performed worse than subjects with HCD volumes in phonologically and lexicon related tasks. Furthermore, cerebellar and lentiform grey matter volumes interacted in dyslexic subjects, so that lower and higher lentiform grey matter volumes compared to controls differently modulated the phonological and lexical performances. Best performances (observed in controls) corresponded to an optimal value of grey matter and they dropped for higher or lower volumes.
These results provide evidence for the existence of various subtypes of dyslexia characterized by different brain phenotypes. In addition, behavioural analyses suggest that these brain phenotypes relate to different deficits of automatization of language-based processes such as grapheme/phoneme correspondence and/or rapid access to lexicon entries.
Functional neuroimaging studies provide converging evidence for existence of intrinsic brain networks activated during resting states and deactivated with selective cognitive demands. Whether task-related deactivation of the default mode network signifies depressed activity relative to the remaining brain or simply lower activity relative to its resting state remains controversial. We employed 3D arterial spin labeling imaging to examine regional cerebral blood flow (CBF) during rest, a spatial working memory task, and a second rest. Change in regional CBF from rest to task showed significant normalized and absolute CBF reductions in posterior cingulate, posterior-inferior precuneus, and medial frontal lobes . A Statistical Parametric Mapping connectivity analysis, with an a priori seed in the posterior cingulate cortex, produced deactivation connectivity patterns consistent with the classic “default mode network” and activation connectivity anatomically consistent with engagement in visuospatial tasks. The large task-related CBF decrease in posterior-inferior precuneus relative to its anterior and middle portions adds evidence for the precuneus' heterogeneity. The posterior cingulate and posterior-inferior precuneus were also regions of the highest CBF at rest and during task performance. The difference in regional CBF between intrinsic (resting) and evoked (task) activity levels may represent functional readiness or reserve vulnerable to diminution by conditions affecting perfusion.
ASL; cerebral blood flow; cingulate; default mode network; precuneus
Magnetic resonance imaging studies have begun to map effects of genetic variation on trajectories of brain development. Longitudinal studies of children and adolescents demonstrate a general pattern of childhood peaks of gray matter followed by adolescent declines, functional and structural increases in connectivity and integrative processing, and a changing balance between limbic/subcortical and frontal lobe functions, which extends well into young adulthood. Twin studies have demonstrated that genetic factors are responsible for a significant amount of variation in pediatric brain morphometry. Longitudinal studies have shown specific genetic polymorphisms affect rates of cortical changes associated with maturation. Although over-interpretation and premature application of neuroimaging findings for diagnostic purposes remains a risk, converging data from multiple imaging modalities is beginning to elucidate the influences of genetic factors on brain development and implications of maturational changes for cognition, emotion, and behavior.
Magnetic resonance imaging; Brain; Development; Genes; Twins
Finite mixture models (FMMs) are an indispensable tool for unsupervised classification in brain imaging. Fitting an FMM to the data leads to a complex optimization problem. This optimization problem is difficult to solve by standard local optimization methods, such as the expectation-maximization (EM) algorithm, if a principled initialization is not available. In this paper, we propose a new global optimization algorithm for the FMM parameter estimation problem, which is based on real coded genetic algorithms. Our specific contributions are two-fold: 1) we propose to use blended crossover in order to reduce the premature convergence problem to its minimum and 2) we introduce a completely new permutation operator specifically meant for the FMM parameter estimation. In addition to improving the optimization results, the permutation operator allows for imposing biologically meaningful constraints to the FMM parameter values. We also introduce a hybrid of the genetic algorithm and the EM algorithm for efficient solution of multidimensional FMM fitting problems. We compare our algorithm to the self-annealing EM-algorithm and a standard real coded genetic algorithm with the voxel classification tasks within the brain imaging. The algorithms are tested on synthetic data as well as real three-dimensional image data from human magnetic resonance imaging, positron emission tomography, and mouse brain MRI. The tissue classification results by our method are shown to be consistently more reliable and accurate than with the competing parameter estimation methods.
Global optimization; image segmentation; magnetic resonance imaging (MRI); parameter estimation; positron emission tomography (PET)
Individual differences in cognitive performance increase from early to late adulthood, likely reflecting influences of a multitude of factors. We hypothesize that losses in neurochemical and anatomical brain resources in normal aging modulate the effects of common genetic variations on cognitive functioning. Our hypothesis is based on the assumption that the function relating brain resources to cognition is nonlinear, so that genetic differences exert increasingly large effects on cognition as resources recede from high to medium levels in the course of aging. Direct empirical support for this hypothesis comes from a study by Nagel et al. (2008), who reported that the effects of the Catechol-O-Methyltransferase (COMT) gene on cognitive performance are magnified in old age and interacted with the Brain-Derived Neurotrophic Factor (BDNF) gene. We conclude that common genetic polymorphisms contribute to the increasing heterogeneity of cognitive functioning in old age. Extensions of the hypothesis to other polymorphisms are discussed. (150 of 150 words)
genes; aging; resources; cognition; dopamine
This article reviews evidence for the presence of a compensatory, alternative, neural system and its possible link to associated processing strategies in children and adults with attention deficit hyperactivity disorder (ADHD). The article presents findings on a region by region basis that suggests ADHD should be characterized not only by neural hypo-activity, as it is commonly thought but neural hyperactivity as well, in regions of the brain that may relate to compensatory brain and behavioral functioning. In this context studies from the functional neuroimaging literature are reviewed. We hypothesize that impaired prefrontal (PFC) and anterior cingulate (ACC) cortex function in ADHD reduces the ability to optimally recruit subsidiary brain regions and strategies to perform cognitive tasks. The authors conclude that healthy individuals can recruit brain regions using visual, spatial or verbal rehearsal for tasks as needed. In contrast, individuals with ADHD may be less able to engage higher order executive systems to flexibly recruit brain regions to match given task demands. This may result in greater reliance on neuroanatomy that is associated with visual, spatial, and motoric processing rather than verbal strategies. The authors speculate that this impaired flexibility in recruiting brain regions and associated strategies limits adaptation to new cognitive demands as they present and may require more effortful processing.
Brain imaging; Cognitive strategies; Children; Adults; Impulsivity
Dissecting development of neuronal connections is critical for understanding neuronal function in both normal and diseased states. Charting the development of the multitude of connections is a monumental task, since a given neuron typically receives hundreds of convergent inputs from other neurons and provides divergent outputs for hundreds of other neurons. Although progress is being made utilizing various mutants and/or genetic constructs expressing fluorescent proteins like GFP, substantial work remains before a database documenting the development and final location of the neuronal pathways in an adult animal is completed. The vast majority of developing neurons cannot be specifically labeled with antibodies and making specific GFP-expressing constructs to tag each of them is an overwhelming task. Fortunately, fluorescent lipophilic dyes have emerged as very useful tools to systematically compare changes in neuronal networks between wild-type and mutant mice. These dyes diffuse laterally along nerve cell membranes in fixed preparations, allowing tracing of the position of a given neuron within the neuronal network in murine mutants fixed at various stages of development. Until recently, however, most evaluations have been limited to one, or at most, two color analyses. We have previously reported three color neuronal profiling using the novel lipophilic dyes NeuroVue (NV) Green, Red and Maroon (Fritzsch et al., Brain. Res. Bull. 66:249–258, 2005). Unfortunately such three color experiments have been limited by the fact that NV Green and its brighter successor, NV Emerald, both exhibit substantially decreased signal intensities when times greater than 48 hours at 37°C are required to achieve neuronal profile filling (unpublished observations). Here we describe a standardized test system developed to allow comparison of candidate dyes and its use to evaluate a series of 488 nm-excited green-emitting lipophilic dyes. The best of these, NV Jade, has spectral properties well matched to NV Red and NV Maroon, better solubility in DMF than DiO or DiA, improved thermostability compared with NV Emerald, and the ability to fill neuronal profiles at rates of 1 mm per day for periods of at least 5 days. Use of NV Jade in combination with NV Red and NV Maroon substantially improves the efficiency of connectional analysis in complex mutants and transgenic models where limited numbers of specimens are available.
NeuroVue dyes; neuronal tract tracing; murine mutants; neuroembryology
Imaging traits are thought to have more direct links to genetic variation than diagnostic measures based on cognitive or clinical assessments and provide a powerful substrate to examine the influence of genetics on human brains. Although imaging genetics has attracted growing attention and interest, most brain-wide genome-wide association studies focus on voxel-wise single-locus approaches, without taking advantage of the spatial information in images or combining the effect of multiple genetic variants. In this paper we present a fast implementation of voxel- and cluster-wise inferences based on the random field theory to fully use the spatial information in images. The approach is combined with a multi-locus model based on least square kernel machines to associate the joint effect of several single nucleotide polymorphisms (SNP) with imaging traits. A fast permutation procedure is also proposed which significantly reduces the number of permutations needed relative to the standard empirical method and provides accurate small p-value estimates based on parametric tail approximation. We explored the relation between 448,294 single nucleotide polymorphisms and 18,043 genes in 31,662 voxels of the entire brain across 740 elderly subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. We find method to be more sensitive compared with voxel-wise single-locus approaches. A number of genes were identified as having significant associations with volumetric changes. The most associated gene was GRIN2B, which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit and affects both the parietal and temporal lobes in human brains. Its role in Alzheimer's disease has been widely acknowledged and studied, suggesting the validity of the approach. The various advantages over existing approaches indicate a great potential offered by this novel framework to detect genetic influences on human brains.
Imaging genetics; Association study; Random field theory; Voxel-wise inference; Cluster size inference; Nonstationarity; Least square kernel machines; Permutation; Pareto distribution; Parametric tail approximation; ADNI; MRI; Tensor-based morphometry; Alzheimer's disease; GRIN2B
Genetic studies are rapidly identifying variants that shape risk for disorders of human cognition, but the question of how such variants predispose to neuropsychiatric disease remains. Noninvasive human brain imaging allows assessment of the brain in vivo, and the combination of genetics and imaging phenotypes remains one of the only ways to explore functional genotype-phenotype associations in human brain. Common variants in contactin-associated protein-like 2 (CNTNAP2), a neurexin superfamily member, have been associated with several allied neurodevelopmental disorders, including autism and specific language impairment, and CNTNAP2 is highly expressed in frontal lobe circuits in the developing human brain. Using functional neuroimaging, we have demonstrated a relationship between frontal lobar connectivity and common genetic variants in CNTNAP2. These data provide a mechanistic link between specific genetic risk for neurodevelopmental disorders and empirical data implicating dysfunction of long-range connections within the frontal lobe in autism. The convergence between genetic findings and cognitive-behavioral models of autism provides evidence that genetic variation at CNTNAP2 predisposes to diseases such asautism in part through modulation of frontal lobe connectivity.
Pre-psychotic and early psychotic characteristics are investigated in the high-risk (HR) populations for psychosis. There are two different approaches based either on hereditary factors (genetic high risk, G-HR) or on the clinically manifested symptoms (clinical high risk, C-HR). Common features are an increased risk for development of psychosis and similar cognitive as well as structural and functional brain abnormalities.
We reviewed the existing literature on longitudinal structural, and on functional imaging studies, which included G-HR and/or C-HR individuals for psychosis, healthy controls (HC) and/or first episode of psychosis (FEP) or schizophrenia patients (SCZ).
With respect to structural brain abnormalities, vulnerability to psychosis was associated with deficits in frontal, temporal, and cingulate regions in HR, with additional insular and caudate deficits in C-HR population. Furthermore, C-HR had progressive prefrontal deficits related to the transition to psychosis.
With respect to functional brain abnormalities, vulnerability to psychosis was associated with prefrontal, cingulate and middle temporal abnormalities in HR, with additional parietal, superior temporal, and insular abnormalities in C-HR population. Transition-to-psychosis related differences emphasized prefrontal, hippocampal and striatal components, more often detectable in C-HR population.
Multimodal studies directly associated psychotic symptoms displayed in altered prefrontal and hippocampal activations with striatal dopamine and thalamic glutamate functions.
There is an evidence for similar structural and functional brain abnormalities within the whole HR population, with more pronounced deficits in the C-HR population. The most consistent evidence for abnormality in the prefrontal cortex reported in structural, functional and multimodal studies of HR population may underlie the complexity of higher cognitive functions that are impaired during HR mental state for psychosis.
Clinical high-risk for psychosis; Genetic high-risk for psychosis; At-risk mental state; functional MRI.
Liberals and conservatives exhibit different cognitive styles and converging lines of evidence suggest that biology influences differences in their political attitudes and beliefs. In particular, a recent study of young adults suggests that liberals and conservatives have significantly different brain structure, with liberals showing increased gray matter volume in the anterior cingulate cortex, and conservatives showing increased gray matter volume in the in the amygdala. Here, we explore differences in brain function in liberals and conservatives by matching publicly-available voter records to 82 subjects who performed a risk-taking task during functional imaging. Although the risk-taking behavior of Democrats (liberals) and Republicans (conservatives) did not differ, their brain activity did. Democrats showed significantly greater activity in the left insula, while Republicans showed significantly greater activity in the right amygdala. In fact, a two parameter model of partisanship based on amygdala and insula activations yields a better fitting model of partisanship than a well-established model based on parental socialization of party identification long thought to be one of the core findings of political science. These results suggest that liberals and conservatives engage different cognitive processes when they think about risk, and they support recent evidence that conservatives show greater sensitivity to threatening stimuli.
We used functional magnetic resonance imaging (fMRI) to explore the patterns of brain activation associated with different levels of performance in exact and approximate calculation tasks in well defined cohorts of children with mathematical calculation difficulties (MD) and typically developing controls. Both groups of children activated the same network of brain regions; however, children in the MD group had significantly increased activation in parietal, frontal, and cingulate cortices during both calculation tasks. A majority of the differences occurred in anatomical brain regions associated with cognitive resources such as executive functioning and working memory that are known to support higher level arithmetic skill but are not specific to mathematical processing. We propose that these findings are evidence that children with MD use the same types of problem solving strategies as TD children, but their weak mathematical processing system causes them to employ a more developmentally immature and less efficient form of the strategies.
arithmetic; development; mathematical skill; numerical processing; school-age; mathematical disability
Child and adolescent psychiatric neuroimaging research typically lags behind similar advances in adult disorders. While the pediatric depression imaging literature is less developed, a recent surge in interest has created the need for a synthetic review of this work. Major findings from pediatric volumetric and functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and resting state functional connectivity studies converge to implicate a corticolimbic network of key areas that work together to mediate the task of emotion regulation. Imaging the brain of children and adolescents with unipolar depression began with volumetric studies of isolated brain regions that served to identify key prefrontal, cingulate and limbic nodes of depression-related circuitry elucidated from more recent advances in DTI and functional connectivity imaging. Systematic review of these studies preliminarily suggests developmental differences between findings in youth and adults, including prodromal neurobiological features, along with some continuity across development.
pediatric depression; major depressive disorder; adolescents; neuroimaging; MRI brain imaging; fMRI
This paper presents translational aspects of imaging and genetic studies of language and cognition in children with epilepsy of average intelligence. It also discusses current unanswered translational questions in each of these research areas. A brief review of multimodal imaging and language study findings shows that abnormal structure and function, as well as plasticity and reorganization in language-related cortical regions are found both in children with epilepsy with normal language skills and in those with linguistic deficits. The review on cognition highlights that multiple domains of impaired cognition and abnormalities in brain structure and/or connectivity are evident early on in childhood epilepsy and might be specific for epilepsy syndrome. The description of state of the art genetic analyses that can be used to explain the convergence of language impairment and Rolandic epilepsy includes a discussion of the methodological difficulties involved in these analyses. Two junior researchers describe how their current and planned studies address some of the unanswered translational questions regarding cognition and imaging and the genetic analysis of speech sound disorder, reading, and centrotemporal spikes in Rolandic epilepsy.
language; cognition; imaging; genetics; pediatric epilepsy
Electrophysiology, behavioral, and neuroimaging studies have revealed sex-related differences in autonomic cardiac control, as reflected in measurements of heart rate variability (HRV). Imaging studies indicate that the neurobiological correlates of autonomic nervous system (ANS) function can be investigated by measuring indices of HRV during the performance of mildly strenuous motor tasks or mildly stressful cognitive tasks. In this preliminary study, fifteen male and seven female healthy subjects underwent H215O-positron emission tomography (PET) and electrocardiograph (ECG) recording while performing a handgrip motor task and an n-back task. Indices of HRV were calculated and correlated with regional cerebral blood flow (rCBF). We hypothesized that sex differences would be evident in brain regions known to participate in autonomic regulation: the anterior insula, the anterior cingulate cortex, the orbitofrontal cortex, and the amygdala. Our study found that associations between rCBF and parasympathetic indices differed significantly between female and male subjects in the amygdala. Females showed a positive correlation between rCBF and parasympathetic indices while males exhibited negative correlations. This differential correlation of amygdala rCBF and parasympathetic activity between males and females may reflect differences in parasympathetic/sympathetic balance between sexes, consistent with known sexual dimorphism in the amygdala and closely related structures such as the hypothalamus. These preliminary imaging results are consistent with earlier reports of significant correlation between brain activity and HRV, and extend these findings by demonstrating prominent sex differences in the neural control of the ANS. While the generalizability of our results was limited by the small size of the study samples, the relatively robust effect size of the differences found between groups encourages further work in larger samples to characterize sex differences in the neural correlates of autonomic arousal.
autonomic; HRV; PET; sex; amygdala
Chromosome 22q11.2 deletion syndrome is one of the most common genetic causes of cognitive impairment and developmental disability yet little is known about the neural bases of those challenges. Here we expand upon our previous neurocognitive studies by specifically investigating the hypothesis that changes in neural connectivity relate to cognitive impairment in children with the disorder.
Whole brain analyses of multiple measures computed from diffusion tensor image data acquired from the brains of children with the disorder and typically developing controls. We also correlated diffusion tensor data with performance on a visuospatial cognitive task that taps spatial attention.
Analyses revealed four common clusters, in the parietal and frontal lobes, that showed complementary patterns of connectivity in children with the deletion and typical controls. We interpreted these results as indicating differences in connective complexity to adjoining cortical regions that are critical to the cognitive functions in which affected children show impairments. Strong, and similarly opposing patterns of correlations between diffusion values in those clusters and spatial attention performance measures considerably strengthened that interpretation.
Our results suggest that atypical development of connective patterns in the brains of children with chromosome 22q11.2 deletion syndrome indicate a neuropathology that is related to the visuospatial cognitive impairments that are commonly found in affected individuals.
Knowledge of genetic influences on cognitive aging can constrain and guide interventions aimed at limiting age-related cognitive decline in older adults. Progress in understanding the neural basis of cognitive aging also requires a better understanding of the neurogenetics of cognition. This selective review article describes studies aimed at deriving specific neurogenetic information from three parallel and interrelated phenotype-based approaches: psychometric constructs, cognitive neuroscience-based processing measures, and brain imaging morphometric data. Developments in newer genetic analysis tools, including genome wide association, are also described. In particular, we focus on models for establishing genotype–phenotype associations within an explanatory framework linking molecular, brain, and cognitive levels of analysis. Such multiple-phenotype approaches indicate that individual variation in genes central to maintaining synaptic integrity, neurotransmitter function, and synaptic plasticity are important in affecting age-related changes in brain structure and cognition. Investigating phenotypes at multiple levels is recommended as a means to advance understanding of the neural impact of genetic variants relevant to cognitive aging. Further knowledge regarding the mechanisms of interaction between genetic and preventative procedures will in turn help in understanding the ameliorative effect of various experiential and lifestyle factors on age-related cognitive decline.
aging; cognition; genetics; interventions; neuroimaging; psychometrics
Although key to understanding individual variation in task-related brain activation, the genetic contribution to these individual differences remains largely unknown. Here we report voxel-by-voxel genetic model fitting in a large sample of 319 healthy, young adult, human identical and fraternal twins (mean age 23.6±1.8 S.D.) who performed an n-back working memory task during functional magnetic resonance imaging (fMRI) at high magnetic field (4 Tesla). Patterns of task-related brain response (BOLD signal difference of 2-back minus 0-back) were significantly heritable, with the highest estimates (40 – 65%) in the inferior, middle, and superior frontal gyri, left supplementary motor area, pre- and postcentral gyri, middle cingulate cortex, superior medial gyrus, angular gyrus, superior parietal lobule, including precuneus, and superior occipital gyri. Furthermore, high test-retest reliability for a subsample of 40 twins indicates that non-genetic variance in the fMRI brain response is largely due to unique environmental influences rather than measurement error. Individual variations in activation of the working memory network are therefore significantly influenced by genetic factors. By establishing the heritability of cognitive brain function in a large sample that affords good statistical power, and using voxel-by-voxel analyses, this study provides the necessary evidence for task-related brain activation to be considered as an endophenotype for psychiatric or neurological disorders, and represents a substantial new contribution to the field of neuroimaging genetics. These genetic brain maps should facilitate discovery of gene variants influencing cognitive brain function through genome-wide association studies, potentially opening up new avenues in the treatment of brain disorders.
twin study; heritability; genetic modeling; functional MRI; working memory; voxel-based analysis
Cognitive neuroscience typically develops hypotheses to explain phenomena that are localized in space and time. Specific regions of the brain execute characteristic functions, whose causes and effects are prompt; determining these functions in spatial and temporal isolation is generally regarded as the first step toward understanding the coherent operation of the whole brain over time. In other words, if the task of cognitive neuroscience is to interpret the neural code, then the first step has been semantic, searching for the meanings (functions) of localized elements, prior to exploring neural syntax, the mutual constraints among elements synchronically and diachronically. While neuroscience has made great strides in discovering the functions of regions of the brain, less is known about the dynamic patterns of brain activity over time, in particular, whether regions activate in sequences that could be characterized syntactically. Researchers generally assume that neural semantics is a precondition for determining neural syntax. Furthermore, it is often assumed that the syntax of the brain is too complex for our present technology and understanding. A corollary of this view holds that functional MRI (fMRI) lacks the spatial and temporal resolution needed to identify the dynamic syntax of neural computation. This paper examines these assumptions with a novel analysis of fMRI image series, resting on the conjecture that any computational code will exhibit aggregate features that can be detected even if the meaning of the code is unknown. Specifically, computational codes will be sparse or dense in different degrees. A sparse code is one that uses only a few of the many possible patterns of activity (in the brain) or symbols (in a human-made code). Considering sparseness at different scales and as measured by different techniques, this approach clearly distinguishes two conventional coding systems, namely, language and music. Based on an analysis of 99 subjects in three different fMRI protocols, in comparison with 194 musical examples and 700 language passages, it is observed that fMRI activity is more similar to music than it is to language, as measured over single symbols, as well as symbol combinations in pairs and triples. Tools from cognitive musicology may therefore be useful in characterizing the brain as a dynamical system.
Brain; fMRI; language; music; consciousness
Brain imaging has provided a useful tool to examine the neural processes underlying human cognition. A critical question is whether and how task engagement influences the observed regional brain activations. Here we highlighted this issue and derived a neural measure of task engagement from the task-residual low frequency blood oxygenation level dependent (BOLD) activity in the precuneus. Using independent component analysis, we identified brain regions in the default circuit – including the precuneus and medial prefrontal cortex (mPFC) – showing greater activation during resting as compared to task-residuals in 33 individuals. Time series correlations with the posterior cingulate cortex as the seed region showed that connectivity with the precuneus was significantly stronger during resting as compared to task residuals. We hypothesized that if the task-residual BOLD activity in the precuneus reflects engagement, it should account for a certain amount of variance in task-related regional brain activation. In an additional experiment of 59 individuals performing a stop signal task, we observed that the fractional amplitude of low frequency fluctuation (fALFF) of the precuneus but not the mPFC accounted for approximately 10% of the variance in prefrontal activation related to attentional monitoring and response inhibition. Taken together, these results suggest that task-residual fALFF in the precuneus may be a potential indicator of task engagement. This measurement may serve as a useful covariate in identifying motivation-independent neural processes that underlie the pathogenesis of a psychiatric or neurological condition.
motivation; default circuit; precuneus; low frequency fluctuation; fMRI
Adolescence is a transitional period between childhood and adulthood that encompasses vast changes within brain systems that parallel some, but not all, behavioral changes. Elevations in emotional reactivity and reward processing follow an inverted U shape in terms of onset and remission, with the peak occurring during adolescence. However, cognitive processing follows a more linear course of development. This review will focus on changes within key structures and will highlight the relationships between brain changes and behavior, with evidence spanning from functional magnetic resonance imaging (fMRI) in humans to molecular studies of receptor and signaling factors in animals. Adolescent changes in neuronal substrates will be used to understand how typical and atypical behaviors arise during adolescence. We draw upon clinical and preclinical studies to provide a neural framework for defining adolescence and its role in the transition to adulthood.
Adolescence; gray matter; pruning; sex differences; white matter
Williams syndrome (WS) is a neurogenetic–neurodevelopmental disorder characterized by a highly variable and enigmatic profile of cognitive and behavioral features. Relative to overall intellect, affected individuals demonstrate disproportionately severe visual-spatial deficits and enhanced emotionality and face processing. In this study, high-resolution magnetic resonance imaging data were collected from 43 individuals with WS and 40 age- and gender-matched healthy controls. Given the distinct cognitive-behavioral dissociations associated with this disorder, we hypothesized that neuroanatomical integrity in WS would be diminished most in regions comprising the visual-spatial system and most “preserved” or even augmented in regions involved in emotion and face processing. Both volumetric analysis and voxel-based morphometry were used to provide convergent approaches for detecting the hypothesized WS neuroanatomical profile. After adjusting for overall brain volume, participants with WS showed reduced thalamic and occipital lobe gray matter volumes and reduced gray matter density in subcortical and cortical regions comprising the human visual-spatial system compared with controls. The WS group also showed disproportionate increases in volume and gray matter density in several areas known to participate in emotion and face processing, including the amygdala, orbital and medial prefrontal cortices, anterior cingulate, insular cortex, and superior temporal gyrus. These findings point to specific neuroanatomical correlates for the unique topography of cognitive and behavioral features associated with this disorder.
emotion; neuron; imaging; morphometry; visual; Williams syndrome; neuroanatomy
Huntington’s Disease (HD) is a neurodegenerative disorder characterized by early cognitive decline, which progresses at later stages to dementia and severe movement disorder. HD is caused by a cytosine-adenine-guanine triplet-repeat expansion mutation in the Huntingtin gene, allowing early diagnosis by genetic testing. This study aims to identify the relationship of N-acetylaspartate and other brain metabolites to cognitive function in HD-mutation carriers by using high field strength magnetic-resonance-spectroscopy at 7-Tesla.
Twelve individuals with the HD-mutation in premanifest or early stage of disease versus twelve healthy controls underwent 1H magnetic-resonance-spectroscopy (7.2ml voxel in the posterior cingulate cortex) at 7-Tesla, and also T1-weighted structural magnetic-resonance-imaging. All participants received standardized tests of cognitive functioning including the Montreal Cognitive Assessment and standardized quantified neurological examination within an hour before scanning.
Individuals with the HD mutation had significantly lower posterior cingulate cortex N-acetylaspartate (−9.6%, p=0.02) and glutamate levels (−10.1%, p=0.02) than controls. By contrast, in this small group, measures of brain morphology including striatal and ventricle volumes did not differ significantly. Linear regression with Montreal Cognitive Assessment scores revealed significant correlations with N-acetylaspartate (r2=0.50, p=0.01) and glutamate (r2=0.64, p=0.002) in HD subjects.
Our data suggest a relationship between reduced N-acetylaspartate and glutamate levels in the posterior cingulate cortex with cognitive decline in early stages of HD. N-acetylaspartate and glutamate magnetic-resonance-spectroscopy signals of the posterior cingulate cortex region may serve as potential biomarkers of disease progression or treatment outcome in HD and other neurodegenerative disorders with early cognitive dysfunction, when structural brain changes are still minor.
MRS; NAA; glutamate; cognition; neurodegeneration; biomarker