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Neurosurgical treatment of psychiatric disorders has been influenced by evolving neurobiological models of symptom generation. The advent of functional neuroimaging and advances in the neurosciences have revolutionized understanding of the functional neuroanatomy of psychiatric disorders. This article reviews neuroimaging studies of depression from the last 3 decades and describes an emerging neurocircuitry model of mood disorders, focusing on critical circuits of cognition and emotion, particularly those networks involved in the regulation of evaluative, expressive and experiential aspects of emotion. The relevance of this model for neurotherapeutics is discussed, as well as the role of functional neuroimaging of psychiatric disorders.
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Recent years have seen an explosion of interest in using neural oscillations to characterize the mechanisms supporting cognition and emotion. Oftentimes, oscillatory activity is indexed by mean power density in predefined frequency bands. Some investigators use broad bands originally defined by prominent surface features of the spectrum. Others rely on narrower bands originally defined by spectral factor analysis (SFA). Presently, the robustness and sensitivity of these competing band definitions remains unclear. Here, a Monte Carlo-based SFA strategy was used to decompose the tonic ("resting" or "spontaneous") electroencephalogram (EEG) into five bands: delta (1-5Hz), alpha-low (6-9Hz), alpha-high (10-11Hz), beta (12-19Hz), and gamma (>21Hz). This pattern was consistent across SFA methods, artifact correction/rejection procedures, scalp regions, and samples. Subsequent analyses revealed that SFA failed to deliver enhanced sensitivity; narrow alpha sub-bands proved no more sensitive than the classical broadband to individual differences in temperament or mean differences in task-induced activation. Other analyses suggested that residual ocular and muscular artifact was the dominant source of activity during quiescence in the delta and gamma bands. This was observed following threshold-based artifact rejection or independent component analysis (ICA)-based artifact correction, indicating that such procedures do not necessarily confer adequate protection. Collectively, these findings highlight the limitations of several commonly used EEG procedures and underscore the necessity of routinely performing exploratory data analyses, particularly data visualization, prior to hypothesis testing. They also suggest the potential benefits of using techniques other than SFA for interrogating high-dimensional EEG datasets in the frequency or time-frequency (event-related spectral perturbation, event-related synchronization/desynchronization) domains.
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We investigated whether mindfulness training (MT) influences information processing in a working memory task with complex visual stimuli. Participants were tested before (T1) and after (T2) participation in an intensive one-month MT retreat, and their performance was compared with that of an age- and education-matched control group. Accuracy did not differ across groups at either time point. Response times were faster and significantly less variable in the MT versus the control group at T2. Since these results could be due to changes in mnemonic processes, speed-accuracy trade-off, or nondecisional factors (e.g., motor execution), we used a mathematical modeling approach to disentangle these factors. The EZ-diffusion model (Wagenmakers, van der Maas, & Grasman, Psychonomic Bulletin & Review 14:(1), 3-22, 2007) suggested that MT leads to improved information quality and reduced response conservativeness, with no changes in nondecisional factors. The noisy exemplar model further suggested that the increase in information quality reflected a decrease in encoding noise and not an increase in forgetting. Thus, mathematical modeling may help clarify the mechanisms by which MT produces salutary effects on performance.
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Drawing on E. Goffman's concepts of face and strategic interaction, the authors define a tease as a playful provocation in which one person comments on something relevant to the target. This approach encompasses the diverse behaviors labeled teasing, clarifies previous ambiguities, differentiates teasing from related practices, and suggests how teasing can lead to hostile or affiliative outcomes. The authors then integrate studies of the content of teasing. Studies indicate that norm violations and conflict prompt teasing. With development, children tease in playful ways, particularly around the ages of 11 and 12 years, and understand and enjoy teasing more. Finally, consistent with hypotheses concerning contextual variation in face concerns, teasing is more frequent and hostile when initiated by high-status and familiar others and men, although gender differences are smaller than assumed. The authors conclude by discussing how teasing varies according to individual differences and culture.
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Autism is a neurodevelopmental disorder affecting behavioral and social cognition, but there is little understanding about the link between the functional deficit and its underlying neuroanatomy. We applied a 2D version of voxel-based morphometry (VBM) in differentiating the white matter concentration of the corpus callosum for the group of 16 high functioning autistic and 12 normal subjects. Using the white matter density as an index for neural connectivity, autism is shown to exhibit less white matter concentration in the region of the genu, rostrum, and splenium removing the effect of age based on the general linear model (GLM) framework. Further, it is shown that the less white matter concentration in the corpus callosum in autism is due to hypoplasia rather than atrophy.
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Diffusion tensor imaging (DTI) plays a key role in analyzing the physical structures of biological tissues, particularly in reconstructing fiber tracts of the human brain in vivo. On the one hand, eigenvalues of diffusion tensors (DTs) estimated from diffusion weighted imaging (DWI) data usually contain systematic bias, which subsequently biases the diffusivity measurements popularly adopted in fiber tracking algorithms. On the other hand, correctly accounting for the spatial information is important in the construction of these diffusivity measurements since the fiber tracts are typically spatially structured. This paper aims to establish test-based approaches to identify anisotropic water diffusion areas in the human brain. These areas in turn indicate the areas passed by fiber tracts. Our proposed test statistic not only takes into account the bias components in eigenvalue estimates, but also incorporates the spatial information of neighboring voxels. Under mild regularity conditions, we demonstrate that the proposed test statistic asymptotically follows a $\chi^2$ distribution under the null hypothesis. Simulation and real DTI data examples are provided to illustrate the efficacy of our proposed methods.
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On the basis of the proposition that love promotes commitment, the authors predicted that love would motivate approach, have a distinct signal, and correlate with commitment-enhancing processes when relationships are threatened. The authors studied romantic partners and adolescent opposite-sex friends during interactions that elicited love and threatened the bond. As expected, the experience of love correlated with approach-related states (desire, sympathy). Providing evidence for a nonverbal display of love, four affiliation cues (head nods, Duchenne smiles, gesticulation, forward leans) correlated with self-reports and partner estimates of love. Finally, the experience and display of love correlated with commitment-enhancing processes (e.g., constructive conflict resolution, perceived trust) when the relationship was threatened. Discussion focused on love, positive emotion, and relationships.
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A chief goal of this research was to determine whether stimuli and events known to enhance smoking motivation also influence a physiological variable with the potential to index approach motivation. Asymmetry of electroencephalographic (EEG) activity across the frontal regions of the 2 hemispheres (left minus right hemisphere activation) was used to index approach motivation. In theory, if EEG asymmetry sensitively indexes approach dispositions, it should be influenced by manipulations known to affect smoking motivation, that is, exposure to smoking cues and tobacco deprivation. Seventy-two smokers participated in this research and were selectively exposed to a smoking-anticipation condition (cigarettes plus expectation of imminent smoking) following either 24 hr of tobacco withdrawal or ad libitum smoking. Results indicated that EEG asymmetry was increased by smoking anticipation and that smoking itself reduced EEG asymmetry. Results also suggested that smoking anticipation increased overall (bihemispheric) EEG activation. Results were interpreted in terms of major theories of drug motivation.
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To better understand the neurobiological mechanisms by which mindfulness-based practices function in a psychotherapeutic context, this article details the definition, techniques, and purposes ascribed to mindfulness training as described by its Buddhist tradition of origin and by contemporary neurocognitive models. Included is theory of how maladaptive mental processes become habitual and automatic, both from the Buddhist and Western psychological perspective. Specific noting and labeling techniques in open monitoring meditation, described in the Theravada and Western contemporary traditions, are highlighted as providing unique access to multiple modalities of awareness. Potential explicit and implicit mechanisms are discussed by which such techniques can contribute to transforming maladaptive habits of mind and perceptual and cognitive biases, improving efficiency, facilitating integration, and providing the flexibility to switch between systems of self-processing. Finally, a model is provided to describe the timing by which noting and labeling practices have the potential to influence different stages of low- and high-level neural processing. Hypotheses are proposed concerning both levels of processing in relation to the extent of practice. Implications for the nature of subjective experience and self-processing as it relates to one's habits of mind, behavior, and relation to the external world, are also described.
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In order to gain a deeper understanding of the mindfulness construct and the mental health benefits associated with mindfulness-based programmes, the relation between mindfulness and its proposed core component attention was studied. Buddhist and Western mindfulness meditators were compared with non-meditators on tasks of sustained (SART) and executive (the Stroop Task) attention. Relations between self-reported mindfulness (FFMQ) and sustained and executive attention were also analysed. No significant differences were found between meditators and non-meditators either in sustained or executive attention. High scores on the FFMQ total scale and on Describe were related to fewer SART errors. High scores on Describe were also related to low Stroop interference. Mindfulness meditators may have an increased awareness of internal processes and the ability to quickly attend to them but this type of refined attentional ability does not seem to be related to performance on attention tests requiring responses to external targets.

Studies have suggested that the default mode network is active during mind wandering, which is often experienced intermittently during sustained attention tasks. Conversely, an anticorrelated task-positive network is thought to subserve various forms of attentional processing. Understanding how these two systems work together is central for understanding many forms of optimal and sub-optimal task performance. Here we present a basic model of naturalistic cognitive fluctuations between mind wandering and attentional states derived from the practice of focused attention meditation. This model proposes four intervals in a cognitive cycle: mind wandering, awareness of mind wandering, shifting of attention, and sustained attention. People who train in this style of meditation cultivate their abilities to monitor cognitive processes related to attention and distraction, making them well suited to report on these mental events. Fourteen meditation practitioners performed breath-focused meditation while undergoing fMRI scanning. When participants realized their mind had wandered, they pressed a button and returned their focus to the breath. The four intervals above were then constructed around these button presses. We hypothesized that periods of mind wandering would be associated with default mode activity, whereas cognitive processes engaged during awareness of mind wandering, shifting of attention and sustained attention would engage attentional subnetworks. Analyses revealed activity in brain regions associated with the default mode during mind wandering, and in salience network regions during awareness of mind wandering. Elements of the executive network were active during shifting and sustained attention. Furthermore, activations during these cognitive phases were modulated by lifetime meditation experience. These findings support and extend theories about cognitive correlates of distributed brain networks.
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The impact of using motion estimates as covariates of no interest was examined in general linear modeling (GLM) of both block design and rapid event-related functional magnetic resonance imaging (fMRI) data. The purpose of motion correction is to identify and eliminate artifacts caused by task-correlated motion while maximizing sensitivity to true activations. To optimize this process, a combination of motion correction approaches was applied to data from 33 subjects performing both a block-design and an event-related fMRI experiment, including analysis: (1) without motion correction; (2) with motion correction alone; (3) with motion-corrected data and motion covariates included in the GLM; and (4) with non-motion-corrected data and motion covariates included in the GLM. Inclusion of covariates was found to be generally useful for increasing the sensitivity of GLM results in the analysis of event-related data. When motion parameters were included in the GLM for event-related data, it made little difference if motion correction was actually applied to the data. For the block design, inclusion of motion covariates had a deleterious impact on GLM sensitivity when even moderate correlation existed between motion and the experimental design. Based on these results, we present a general strategy for block designs, event-related designs, and hybrid designs to identify and eliminate probable motion artifacts while maximizing sensitivity to true activations.
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A review of behavioral and neurobiological data on mood and mood regulation as they pertain to an understanding of mood disorders is presented. Four approaches are considered: 1) behavioral and cognitive; 2) neurobiological; 3) computational; and 4) developmental. Within each of these four sections, we summarize the current status of the field and present our vision for the future, including particular challenges and opportunities. We conclude with a series of specific recommendations for National Institute of Mental Health priorities. Recommendations are presented for the behavioral domain, the neural domain, the domain of behavioral-neural interaction, for training, and for dissemination. It is in the domain of behavioral-neural interaction, in particular, that new research is required that brings together traditions that have developed relatively independently. Training interdisciplinary clinical scientists who meaningfully draw upon both behavioral and neuroscientific literatures and methods is critically required for the realization of these goals.
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Children with an anxious temperament (AT) are at risk for developing psychiatric disorders along the internalizing spectrum, including anxiety and depression. Like these disorders, AT is a multidimensional phenotype and children with extreme anxiety show varying mixtures of physiological, behavioral, and other symptoms. Using a well-validated juvenile monkey model of AT, we addressed the degree to which this phenotypic heterogeneity reflects fundamental differences or similarities in the underlying neurobiology. The rhesus macaque is optimal for studying AT because children and young monkeys express the anxious phenotype in similar ways and have similar neurobiology. Fluorodeoxyglucose (FDG)-positron emission tomography (FDG-PET) in 238 freely behaving monkeys identified brain regions where metabolism predicted variation in three dimensions of the AT phenotype: hypothalamic-pituitary-adrenal (HPA) activity, freezing behavior, and expressive vocalizations. We distinguished brain regions that predicted all three dimensions of the phenotype from those that selectively predicted a single dimension. Elevated activity in the central nucleus of the amygdala and the anterior hippocampus was consistently found across individuals with different presentations of AT. In contrast, elevated activity in the lateral anterior hippocampus was selective to individuals with high levels of HPA activity, and decreased activity in the motor cortex (M1) was selective to those with high levels of freezing behavior. Furthermore, activity in these phenotype-selective regions mediated relations between amygdala metabolism and different expressions of anxiety. These findings provide a framework for understanding the mechanisms that lead to heterogeneity in the clinical presentation of internalizing disorders and set the stage for developing improved interventions.
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Recent theoretical and empirical work in cognitive science and neuroscience is brought into contact with the concept of the flow experience. After a brief exposition of brain function, the explicit-implicit distinction is applied to the effortless information processing that is so characteristic of the flow state. The explicit system is associated with the higher cognitive functions of the frontal lobe and medial temporal lobe structures and has evolved to increase cognitive flexibility. In contrast, the implicit system is associated with the skill-based knowledge supported primarily by the basal ganglia and has the advantage of being more efficient. From the analysis of this flexibility/efficiency trade-off emerges a thesis that identifies the flow state as a period during which a highly practiced skill that is represented in the implicit system's knowledge base is implemented without interference from the explicit system. It is proposed that a necessary prerequisite to the experience of flow is a state of transient hypofrontality that enables the temporary suppression of the analytical and meta-conscious capacities of the explicit system. Examining sensory-motor integration skills that seem to typify flow such as athletic performance, writing, and free-jazz improvisation, the new framework clarifies how this concept relates to creativity and opens new avenues of research.

Neuroimage phenotyping for psychiatric and neurological disorders is performed using voxelwise analyses also known as voxel based analyses or morphometry (VBM). A typical voxelwise analysis treats measurements at each voxel (e.g., fractional anisotropy, gray matter probability) as outcome measures to study the effects of possible explanatory variables (e.g., age, group) in a linear regression setting. Furthermore, each voxel is treated independently until the stage of correction for multiple comparisons. Recently, multi-voxel pattern analyses (MVPA), such as classification, have arisen as an alternative to VBM. The main advantage of MVPA over VBM is that the former employ multivariate methods which can account for interactions among voxels in identifying significant patterns. They also provide ways for computer-aided diagnosis and prognosis at individual subject level. However, compared to VBM, the results of MVPA are often more difficult to interpret and prone to arbitrary conclusions. In this paper, first we use penalized likelihood modeling to provide a unified framework for understanding both VBM and MVPA. We then utilize statistical learning theory to provide practical methods for interpreting the results of MVPA beyond commonly used performance metrics, such as leave-one-out-cross validation accuracy and area under the receiver operating characteristic (ROC) curve. Additionally, we demonstrate that there are challenges in MVPA when trying to obtain image phenotyping information in the form of statistical parametric maps (SPMs), which are commonly obtained from VBM, and provide a bootstrap strategy as a potential solution for generating SPMs using MVPA. This technique also allows us to maximize the use of available training data. We illustrate the empirical performance of the proposed framework using two different neuroimaging studies that pose different levels of challenge for classification using MVPA.
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Temperamentally anxious individuals can be identified in childhood and are at risk to develop anxiety and depressive disorders. In addition, these individuals tend to have extreme asymmetric right prefrontal brain activity. Although common and clinically important, little is known about the pathophysiology of anxious temperament. Regardless, indirect evidence from rodent studies and difficult to interpret primate studies is used to support the hypothesis that the amygdala plays a central role. In previous studies using rhesus monkeys, we characterized an anxious temperament endophenotype that is associated with excessive anxiety and fear-related responses and increased electrical activity in right frontal brain regions. To examine the role of the amygdala in mediating this endophenotype and other fearful responses, we prepared monkeys with selective fiber sparing ibotenic acid lesions of the amygdala. Unconditioned trait-like anxiety-fear responses remained intact in monkeys with >95% bilateral amygdala destruction. In addition, the lesions did not affect EEG frontal asymmetry. However, acute unconditioned fear responses, such as those elicited by exposure to a snake and to an unfamiliar threatening conspecific were blunted in monkeys with >70% lesions. These findings demonstrate that the primate amygdala is involved in mediating some acute unconditioned fear responses but challenge the notion that the amygdala is the key structure underlying the dispositional behavioral and physiological characteristics of anxious temperament.
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BACKGROUND: Anhedonia, a reduced ability to experience pleasure, is a chief symptom of major depressive disorder and is related to reduced frontostriatal connectivity when attempting to upregulate positive emotion. The present study examined another facet of positive emotion regulation associated with anhedonia-namely, the downregulation of positive affect-and its relation to prefrontal cortex (PFC) activity. METHODS: Neuroimaging data were collected from 27 individuals meeting criteria for major depressive disorder as they attempted to suppress positive emotion during a positive emotion regulation task. Their PFC activation pattern was compared with the PFC activation pattern exhibited by 19 healthy control subjects during the same task. Anhedonia scores were collected at three time points: at baseline (time 1), 8 weeks after time 1 (i.e., time 2), and 6 months after time 1 (i.e., time 3). Prefrontal cortex activity at time 1 was used to predict change in anhedonia over time. Analyses were conducted utilizing hierarchical linear modeling software. RESULTS: Depressed individuals who could not inhibit positive emotion-evinced by reduced right ventrolateral prefrontal cortex activity during attempts to dampen their experience of positive emotion in response to positive visual stimuli-exhibited a steeper anhedonia reduction slope between baseline and 8 weeks of treatment with antidepressant medication (p < .05). Control subjects showed a similar trend between baseline and time 3. CONCLUSIONS: To reduce anhedonia, it may be necessary to teach individuals how to counteract the functioning of an overactive pleasure-dampening prefrontal inhibitory system.
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OBJECTIVE Deficits in positive affect and their neural bases have been associated with major depression. However, whether reductions in positive affect result solely from an overall reduction in nucleus accumbens activity and fronto-striatal connectivity or the additional inability to sustain engagement of this network over time is unknown. The authors sought to determine whether treatment-induced changes in the ability to sustain nucleus accumbens activity and fronto-striatal connectivity during the regulation of positive affect are associated with gains in positive affect. METHOD Using fMRI, the authors assessed the ability to sustain activity in reward-related networks when attempting to increase positive emotion during performance of an emotion regulation paradigm in 21 depressed patients before and after 2 months of antidepressant treatment. Over the same interval, 14 healthy comparison subjects underwent scanning as well. RESULTS After 2 months of treatment, self-reported positive affect increased. The patients who demonstrated the largest increases in sustained nucleus accumbens activity over the 2 months were those who demonstrated the largest increases in positive affect. In addition, the patients who demonstrated the largest increases in sustained fronto-striatal connectivity were also those who demonstrated the largest increases in positive affect when controlling for negative affect. None of these associations were observed in healthy comparison subjects. CONCLUSIONS Treatment-induced change in the sustained engagement of fronto-striatal circuitry tracks the experience of positive emotion in daily life. Studies examining reduced positive affect in a variety of psychiatric disorders might benefit from examining the temporal dynamics of brain activity when attempting to understand changes in daily positive affect.
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Theories of knowledge such as feature lists, semantic networks, and localist neural nets typically use a single global symbol to represent a property that occurs in multiple concepts. Thus, a global symbol represents mane across HORSE, PONY, and LION. Alternatively, perceptual theories of knowledge, as well as distributed representational systems, assume that properties take different local forms in different concepts. Thus, different local forms of mane exist for HORSE, PONY, and LION, each capturing the specific form that mane takes in its respective concept. Three experiments used the property verification task to assess whether properties are represented globally or locally (e.g., Does a PONY have mane?). If a single global form represents a property, then verifying it in any concept should increase its accessibility and speed its verification later in any other concept. Verifying mane for PONY should benefit as much from having verified mane for LION earlier as from verifying mane for HORSE. If properties are represented locally, however, verifying a property should only benefit from verifying a similar form earlier. Verifying mane for PONY should only benefit from verifying mane for HORSE, not from verifying mane for LION. Findings from three experiments strongly supported local property representation and ruled out the interpretation that object similarity was responsible (e.g., the greater overall similarity between HORSE and PONY than between LION and PONY). The findings further suggest that property representation and verification are complicated phenomena, grounded in sensory-motor simulations.
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The serotonin transporter (5-HTT) plays a critical role in regulating serotonergic neurotransmission and is implicated in the pathophysiology of anxiety and affective disorders. Positron emission tomography scans using [(11)C]DASB [(11)C]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)-benzonitrile] to measure 5-HTT availability (an index of receptor density and binding) were performed in 34 rhesus monkeys in which the relationship between regional brain glucose metabolism and anxious temperament was previously established. 5-HTT availability in the amygdalohippocampal area and bed nucleus of the stria terminalis correlated positively with individual differences in a behavioral and neuroendocrine composite of anxious temperament. 5-HTT availability also correlated positively with stress-induced metabolic activity within these regions. Collectively, these findings suggest that serotonergic modulation of neuronal excitability in the neural circuitry associated with anxiety mediates the developmental risk for affect-related psychopathology.
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A variant allele in the promoter region of the serotonin transporter gene, SLC6A4, the s allele, is associated with increased vulnerability to develop anxiety-related traits and depression. Furthermore, functional magnetic resonance imaging (fMRI) studies reveal that s carriers have increased amygdala reactivity in response to aversive stimuli, which is thought to be an intermediate phenotype mediating the influences of the s allele on emotionality. We used high-resolution microPET [18F]fluoro-2-deoxy-D-glucose (FDG) scanning to assess regional brain metabolic activity in rhesus monkeys to further explore s allele-related intermediate phenotypes. Rhesus monkeys provide an excellent model to understand mechanisms underlying human anxiety, and FDG microPET allows for the assessment of brain activity associated with naturalistic environments outside the scanner. During FDG uptake, monkeys were exposed to different ethologically relevant stressful situations (relocation and threat) as well as to the less stressful familiar environment of their home cage. The s carriers displayed increased orbitofrontal cortex activity in response to both relocation and threat. However, during relocation they displayed increased amygdala reactivity and in response to threat they displayed increased reactivity of the bed nucleus of the stria terminalis. No increase in the activity of any of these regions occurred when the animals were administered FDG in their home cages. These findings demonstrate context-dependent intermediate phenotypes in s carriers that provide a framework for understanding the mechanisms underlying the vulnerabilities of s-allele carriers exposed to different types of stressors.
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Social class is shaped by an individual's material resources as well as perceptions of rank vis-à-vis others in society, and in this article, we examine how class influences behavior. Diminished resources and lower rank create contexts that constrain social outcomes for lower-class individuals and enhance contextualist tendencies--that is, a focus on external, uncontrollable social forces and other individuals who influence one's life outcomes. In contrast, abundant resources and elevated rank create contexts that enhance the personal freedoms of upper-class individuals and give rise to solipsistic social cognitive tendencies--that is, an individualistic focus on one's own internal states, goals, motivations, and emotions. Guided by this framework, we detail 9 hypotheses and relevant empirical evidence concerning how class-based contextualist and solipsistic tendencies shape the self, perceptions of the social environment, and relationships to other individuals. Novel predictions and implications for research in other socio-political contexts are considered.
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We present a new sparse shape modeling framework on the Laplace-Beltrami (LB) eigenfunctions. Traditionally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes by forming a Fourier series expansion. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we propose to filter out only the significant eigenfunctions by imposing l1-penalty. The new sparse framework can further avoid additional surface-based smoothing often used in the field. The proposed approach is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shapes in the normal population. In addition, we show how the emotional response is related to the anatomy of the subcortical structures.
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We used fMRI to examine amygdala activation in response to fearful facial expressions, measured over multiple scanning sessions. 15 human subjects underwent three scanning sessions, at 0, 2 and 8 weeks. During each session, functional brain images centered about the amygdala were acquired continuously while participants were shown alternating blocks of fearful, neutral and happy facial expressions. Intraclass correlation coefficients calculated across the sessions indicated stability of response in left amygdala to fearful faces (as a change from baseline), but considerably less left amygdala stability in responses to neutral expressions and for fear versus neutral contrasts. The results demonstrate that the measurement of fMRI BOLD responses in amygdala to fearful facial expressions might be usefully employed as an index of amygdala reactivity over extended periods. While signal change to fearful facial expressions appears robust, the experimental design employed here has yielded variable responsivity within baseline or comparison conditions. Future studies might manipulate the experimental design to either amplify or attenuate this variability, according to the goals of the research.
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