Neuroimaging
Increased amygdala activation to averted versus direct gaze in humans is independent of valence of facial expression.
Publication Date: 2009 Oct 30 PMID: 19883773
Authors: Straube, T. - Langohr, B. - Schmidt, S. - Mentzel, H. J. - Miltner, W. H.
Journal: Neuroimage
A recent study in monkeys [Hoffman et al. (2007) Curr Biol. 17(9): 766-72] showed that averted gaze displayed by conspecifics activates the amygdala regardless of the valence of facial expression (angry, neutral, appeasing). In contrast to this result, previous findings on amygdala activation to gaze information in humans have been mainly interpreted in terms of threat-related processing of facial signals. In the present event-related functional magnetic resonance imaging study with humans, we investigated brain responses to angry, happy, and neutral faces with either direct or averted gaze. Averted vs. direct gaze induced increased amygdala responses regardless of facial expression. This finding suggests a critical role of the amygdala in gaze processing independently of the valence of facial expression. Furthermore, the effect of gaze on amygdalar responses seems to be preserved across nonhuman and human primates.
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Authors: Straube, T. - Langohr, B. - Schmidt, S. - Mentzel, H. J. - Miltner, W. H.
Journal: Neuroimage
A recent study in monkeys [Hoffman et al. (2007) Curr Biol. 17(9): 766-72] showed that averted gaze displayed by conspecifics activates the amygdala regardless of the valence of facial expression (angry, neutral, appeasing). In contrast to this result, previous findings on amygdala activation to gaze information in humans have been mainly interpreted in terms of threat-related processing of facial signals. In the present event-related functional magnetic resonance imaging study with humans, we investigated brain responses to angry, happy, and neutral faces with either direct or averted gaze. Averted vs. direct gaze induced increased amygdala responses regardless of facial expression. This finding suggests a critical role of the amygdala in gaze processing independently of the valence of facial expression. Furthermore, the effect of gaze on amygdalar responses seems to be preserved across nonhuman and human primates.
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Emotional Priming Effects during Stroop Task Performance.
Publication Date: 2009 Oct 30 PMID: 19883772
Authors: Hart, S. J. - Green, S. R. - Casp, M. - Belger, A.
Journal: Neuroimage
The ability to make decisions within an emotional context requires a balance between two functionally integrated neural systems that primarily support executive control and affective processing. Several studies have demonstrated effects of emotional interference presented during an ongoing cognitive task, but it is unclear how activating the emotional circuitry prior to a cognitive task may enhance or disrupt the executive system. In this study we used fMRI to examine the effects of emotional priming on executive processing during a number Stroop task. Our results indicated that during trials with less executive requirements, there was a greater aversive emotional attenuation effect in a network of regions including the ventrolateral prefrontal cortex (vlPFC), insula and cingulate gyrus. This attenuation effect was counteracted during trials with increased executive demand, suggesting that while pre-activation of the emotional system may lead to an automatic attenuation of activity in multiple regions, requirements for executive function may override the aversive emotional attenuation effect. Furthermore, this override effect was found to be associated with faster reaction times during executive processing. These findings demonstrate that activity in the vlPFC, cingulate and insula is dynamically adjusted in order to optimize performance, and illustrate the importance of the timing of each system's engagement in determining how competing cognitive and emotional information is processed.
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Authors: Hart, S. J. - Green, S. R. - Casp, M. - Belger, A.
Journal: Neuroimage
The ability to make decisions within an emotional context requires a balance between two functionally integrated neural systems that primarily support executive control and affective processing. Several studies have demonstrated effects of emotional interference presented during an ongoing cognitive task, but it is unclear how activating the emotional circuitry prior to a cognitive task may enhance or disrupt the executive system. In this study we used fMRI to examine the effects of emotional priming on executive processing during a number Stroop task. Our results indicated that during trials with less executive requirements, there was a greater aversive emotional attenuation effect in a network of regions including the ventrolateral prefrontal cortex (vlPFC), insula and cingulate gyrus. This attenuation effect was counteracted during trials with increased executive demand, suggesting that while pre-activation of the emotional system may lead to an automatic attenuation of activity in multiple regions, requirements for executive function may override the aversive emotional attenuation effect. Furthermore, this override effect was found to be associated with faster reaction times during executive processing. These findings demonstrate that activity in the vlPFC, cingulate and insula is dynamically adjusted in order to optimize performance, and illustrate the importance of the timing of each system's engagement in determining how competing cognitive and emotional information is processed.
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Neural Systems of Social Comparison and the "Above-Average" Effect.
Publication Date: 2009 Oct 30 PMID: 19883771
Authors: Beer, J. S. - Hughes, B. L.
Journal: Neuroimage
Extant neural models of self-evaluation are dominated by associations with medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC) function and have mostly been developed from studies differentiating self-evaluation from evaluation of other people. Although self-evaluation is robustly characterized by systematic biases, current neural models of self-evaluation cannot speak to their neurobiology because of a lack of research. The few extant studies have made claims about associations between bias and ventral anterior cingulate cortex (vACC) function but have confounded bias with the valence of experimental stimuli. In Study 1, fMRI was used to examine the neurobiology of the "above average" effect, a robust self-evaluation bias. The majority of people judge their personality to be more desirable (i.e. more positive and less negative traits) than their peers' personalities. MPFC and PCC were significantly more activated by a condition that reduced susceptibility to "above average" judgments. However, MPFC and PFCC activity were not modulated by individual differences in "above average" judgments. VACC activity distinguished positive from negative valence but did not predict individual differences in "above average" judgments. Instead, the extent to which participants viewed themselves as "above average" was negatively correlated with orbitofrontal cortex (OFC) and, to a lesser extent, dorsal anterior cingulate cortex (dACC) activation. A complementary study found that mental load increases "above average" judgments (Study 2). These findings are the first to directly examine the neural systems involved in social judgment bias and have implications for the association between frontal lobe dysfunction and poor insight.
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Authors: Beer, J. S. - Hughes, B. L.
Journal: Neuroimage
Extant neural models of self-evaluation are dominated by associations with medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC) function and have mostly been developed from studies differentiating self-evaluation from evaluation of other people. Although self-evaluation is robustly characterized by systematic biases, current neural models of self-evaluation cannot speak to their neurobiology because of a lack of research. The few extant studies have made claims about associations between bias and ventral anterior cingulate cortex (vACC) function but have confounded bias with the valence of experimental stimuli. In Study 1, fMRI was used to examine the neurobiology of the "above average" effect, a robust self-evaluation bias. The majority of people judge their personality to be more desirable (i.e. more positive and less negative traits) than their peers' personalities. MPFC and PCC were significantly more activated by a condition that reduced susceptibility to "above average" judgments. However, MPFC and PFCC activity were not modulated by individual differences in "above average" judgments. VACC activity distinguished positive from negative valence but did not predict individual differences in "above average" judgments. Instead, the extent to which participants viewed themselves as "above average" was negatively correlated with orbitofrontal cortex (OFC) and, to a lesser extent, dorsal anterior cingulate cortex (dACC) activation. A complementary study found that mental load increases "above average" judgments (Study 2). These findings are the first to directly examine the neural systems involved in social judgment bias and have implications for the association between frontal lobe dysfunction and poor insight.
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Reply to Friston and David.
Publication Date: 2009 Oct 30 PMID: 19883770
Authors: Roebroeck, A. - Formisano, E. - Goebel, R.
Journal: Neuroimage
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Authors: Roebroeck, A. - Formisano, E. - Goebel, R.
Journal: Neuroimage
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The effect of metric selection on the analysis of diffusion tensor MRI data.
Publication Date: 2009 Oct 29 PMID: 19879947
Authors: Pasternak, O. - Sochen, N. - Basser, P. J.
Journal: Neuroimage
The measurement of the distance between diffusion tensors is the foundation on which any subsequent analysis or processing of these quantities, such as registration, regularization, interpolation, or statistical inference is based. In recent years a family of Riemannian tensor metrics based on geometric considerations has been introduced for this purpose. In this work we examine the properties one would use to select metrics for diffusion tensors, diffusion coefficients, and diffusion weighted MR image data. We show that empirical evidence supports the use of a Euclidean metric for diffusion tensors, based upon Monte Carlo simulations. Our findings suggest that affine-invariance is not a desirable property for a diffusion tensor metric because it leads to substantial biases in tensor data. Rather, the relationship between distribution and distance is suggested as a novel criterion for metric selection.
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Authors: Pasternak, O. - Sochen, N. - Basser, P. J.
Journal: Neuroimage
The measurement of the distance between diffusion tensors is the foundation on which any subsequent analysis or processing of these quantities, such as registration, regularization, interpolation, or statistical inference is based. In recent years a family of Riemannian tensor metrics based on geometric considerations has been introduced for this purpose. In this work we examine the properties one would use to select metrics for diffusion tensors, diffusion coefficients, and diffusion weighted MR image data. We show that empirical evidence supports the use of a Euclidean metric for diffusion tensors, based upon Monte Carlo simulations. Our findings suggest that affine-invariance is not a desirable property for a diffusion tensor metric because it leads to substantial biases in tensor data. Rather, the relationship between distribution and distance is suggested as a novel criterion for metric selection.
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Neural Foundations of Risk-Return Trade-Off in Investment Decisions.
Publication Date: 2009 Oct 28 PMID: 19879367
Authors: Mohr, P. N. - Biele, G. - Krugel, L. K. - Li, S. C. - Heekeren, H. R.
Journal: Neuroimage
Many decisions people make can be described as decisions under risk. Understanding the mechanisms that drive these decisions is an important goal in decision neuroscience. Two competing classes of risky decision making models have been proposed to describe human behavior, namely utility-based models and risk-return models. Here we used a novel investment decision task that uses streams of (past) returns as stimuli to investigate how consistent the two classes of models are with the neurobiological processes underlying investment decisions (where outcomes usually follow continuous distributions). By showing (a) that risk-return models can explain choices behaviorally and (b) that the components of risk-return models (value, risk, and risk attitude) are represented in the brain during choices, we provide evidence that risk-return models describe the neural processes underlying investment decisions well. Most importantly, the observed correlation between risk and brain activity in the anterior insula during choices strongly supports risk-return models more than utility-based models because risk is an explicit component of risk-return models but not of the utility-based models.
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Authors: Mohr, P. N. - Biele, G. - Krugel, L. K. - Li, S. C. - Heekeren, H. R.
Journal: Neuroimage
Many decisions people make can be described as decisions under risk. Understanding the mechanisms that drive these decisions is an important goal in decision neuroscience. Two competing classes of risky decision making models have been proposed to describe human behavior, namely utility-based models and risk-return models. Here we used a novel investment decision task that uses streams of (past) returns as stimuli to investigate how consistent the two classes of models are with the neurobiological processes underlying investment decisions (where outcomes usually follow continuous distributions). By showing (a) that risk-return models can explain choices behaviorally and (b) that the components of risk-return models (value, risk, and risk attitude) are represented in the brain during choices, we provide evidence that risk-return models describe the neural processes underlying investment decisions well. Most importantly, the observed correlation between risk and brain activity in the anterior insula during choices strongly supports risk-return models more than utility-based models because risk is an explicit component of risk-return models but not of the utility-based models.
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Functional MRI of Postnatal Visual Development in Normal and Hypoxic-ischemic Injured Superior Colliculi.
Publication Date: 2009 Oct 28 PMID: 19879366
Authors: Chan, K. C. - Xing, K. K. - Cheung, M. M. - Zhou, I. Y. - Wu, E. X.
Journal: Neuroimage
The superior colliculus (SC) is a laminated subcortical structure in the mammalian midbrain, whose superficial layers receive visual information from the retina and the visual cortex. To date, its functional organization and development in the visual system remain largely unknown. This study employed blood oxygenation level-dependent (BOLD) functional MRI to evaluate the visual responses of the SC in normally developing and severe neonatal hypoxic-ischemic (HI) injured rat brains from the time of eyelid opening to adulthood. MRI was performed to the normal animals (n=7) at postnatal days (P) 14, 21, 28 and 60. In the HI-injured group (n=7), the ipsilesional primary and secondary visual cortices were completely damaged after unilateral ligation of the left common carotid artery at P7 followed by hypoxia for 2 hours, and MRI was performed at P60. Upon unilateral flash illumination, the normal contralateral SC underwent a systematic increase in BOLD signal amplitude with age especially after the third postnatal week. However, no significant difference in BOLD signal increase was found between P14 and P21. These findings implied the presence of neurovascular coupling at the time of eyelid opening, and the progressive development of hemodynamic regulation in the subcortical visual system. In the HI-injured group at P60, the BOLD signal increases in both SC remained at the same level as the normal group at P28 though they were significantly lower than the normal group at P60. These observations suggested the residual visual functions on both sides of the subcortical brain, despite the damages to the entire ipsilesional visual cortex. The results of this study constitute important evidence on the progressive maturation of visual functions and hemodynamic responses in the normal subcortical brain, and its functional plasticity upon neonatal HI injury.
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Authors: Chan, K. C. - Xing, K. K. - Cheung, M. M. - Zhou, I. Y. - Wu, E. X.
Journal: Neuroimage
The superior colliculus (SC) is a laminated subcortical structure in the mammalian midbrain, whose superficial layers receive visual information from the retina and the visual cortex. To date, its functional organization and development in the visual system remain largely unknown. This study employed blood oxygenation level-dependent (BOLD) functional MRI to evaluate the visual responses of the SC in normally developing and severe neonatal hypoxic-ischemic (HI) injured rat brains from the time of eyelid opening to adulthood. MRI was performed to the normal animals (n=7) at postnatal days (P) 14, 21, 28 and 60. In the HI-injured group (n=7), the ipsilesional primary and secondary visual cortices were completely damaged after unilateral ligation of the left common carotid artery at P7 followed by hypoxia for 2 hours, and MRI was performed at P60. Upon unilateral flash illumination, the normal contralateral SC underwent a systematic increase in BOLD signal amplitude with age especially after the third postnatal week. However, no significant difference in BOLD signal increase was found between P14 and P21. These findings implied the presence of neurovascular coupling at the time of eyelid opening, and the progressive development of hemodynamic regulation in the subcortical visual system. In the HI-injured group at P60, the BOLD signal increases in both SC remained at the same level as the normal group at P28 though they were significantly lower than the normal group at P60. These observations suggested the residual visual functions on both sides of the subcortical brain, despite the damages to the entire ipsilesional visual cortex. The results of this study constitute important evidence on the progressive maturation of visual functions and hemodynamic responses in the normal subcortical brain, and its functional plasticity upon neonatal HI injury.
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Neural Mechanisms of the Influence of Popularity on Adolescent Ratings of Music.
Publication Date: 2009 Oct 28 PMID: 19879365
Authors: Berns, G. S. - Capra, C. M. - Moore, S. - Noussair, C.
Journal: Neuroimage
It is well-known that social influences affect consumption decisions. We used functional magnetic resonance imaging (fMRI) to elucidate the neural mechanisms associated with social influence with regard to a common consumer good: music. Our study population was adolescents, age 12-17. Music is a common purchase in this age group, and it is widely believed that adolescent behavior is influenced by perceptions of popularity in their reference group. Using 15-second clips of songs from MySpace.com, we obtained behavioral measures of preferences and neurobiological responses to the songs. The data were gathered with, and without, the overall popularity of the song revealed. Song popularity had a significant effect on the participants' likability ratings of the songs. fMRI results showed a strong correlation between the participants' rating and activity in the caudate nucleus, a region previously implicated in reward-driven actions. The tendency to change one's evaluation of a song was positively correlated with activation in the anterior insula and anterior cingulate, two regions that are associated with physiological arousal and negative affective states. Sensitivity to popularity was linked to lower activation levels in the middle temporal gyrus, suggesting a lower depth of musical semantic processing. Our results suggest that a principal mechanism whereby popularity ratings affect consumer choice is through the anxiety generated by the mismatch between one's own preferences and others'. This mismatch anxiety motivates people to switch their choices in the direction of the consensus. Our data suggest that this is a major force behind the conformity observed in music tastes in some teenagers.
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Authors: Berns, G. S. - Capra, C. M. - Moore, S. - Noussair, C.
Journal: Neuroimage
It is well-known that social influences affect consumption decisions. We used functional magnetic resonance imaging (fMRI) to elucidate the neural mechanisms associated with social influence with regard to a common consumer good: music. Our study population was adolescents, age 12-17. Music is a common purchase in this age group, and it is widely believed that adolescent behavior is influenced by perceptions of popularity in their reference group. Using 15-second clips of songs from MySpace.com, we obtained behavioral measures of preferences and neurobiological responses to the songs. The data were gathered with, and without, the overall popularity of the song revealed. Song popularity had a significant effect on the participants' likability ratings of the songs. fMRI results showed a strong correlation between the participants' rating and activity in the caudate nucleus, a region previously implicated in reward-driven actions. The tendency to change one's evaluation of a song was positively correlated with activation in the anterior insula and anterior cingulate, two regions that are associated with physiological arousal and negative affective states. Sensitivity to popularity was linked to lower activation levels in the middle temporal gyrus, suggesting a lower depth of musical semantic processing. Our results suggest that a principal mechanism whereby popularity ratings affect consumer choice is through the anxiety generated by the mismatch between one's own preferences and others'. This mismatch anxiety motivates people to switch their choices in the direction of the consensus. Our data suggest that this is a major force behind the conformity observed in music tastes in some teenagers.
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Quantitative Prediction of Subjective Pain Intensity from Whole-Brain fMRI Data Using Gaussian Processes.
Publication Date: 2009 Oct 28 PMID: 19879364
Authors: Marquand, A. - Howard, M. - Brammer, M. - Chu, C. - Coen, S. - Mourao-Miranda, J.
Journal: Neuroimage
Supervised machine learning (ML) algorithms are increasingly popular tools for fMRI decoding due to their predictive capability and their ability to capture information encoded by spatially correlated voxels. In addition, an important secondary outcome is a multivariate representation of the pattern underlying the prediction. Despite an impressive array of applications, most fMRI applications are framed as classification problems and predictions are limited to categorical class decisions. For many applications, quantitative predictions are desirable that more accurately represent variability within subject groups and that can be correlated with behavioural variables. We evaluate the predictive capability of Gaussian process (GP) models for two types of quantitative prediction (multivariate regression and probabilistic classification) using whole-brain fMRI volumes. As a proof of concept, we apply GP models to an fMRI experiment investigating subjective responses to thermal pain and show GP models predict subjective pain ratings without requiring anatomical hypotheses about functional localisation of relevant brain processes. Even in the case of pain perception, where strong hypotheses do exist, GP predictions were more accurate than any region previously demonstrated to encode pain intensity. We demonstrate two brain mapping methods suitable for GP models and we show that GP regression models outperform state of the art support vector- and relevance vector regression. For classification, GP models perform categorical prediction as accurately as a support vector machine classifier and furnish probabilistic class predictions.
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Authors: Marquand, A. - Howard, M. - Brammer, M. - Chu, C. - Coen, S. - Mourao-Miranda, J.
Journal: Neuroimage
Supervised machine learning (ML) algorithms are increasingly popular tools for fMRI decoding due to their predictive capability and their ability to capture information encoded by spatially correlated voxels. In addition, an important secondary outcome is a multivariate representation of the pattern underlying the prediction. Despite an impressive array of applications, most fMRI applications are framed as classification problems and predictions are limited to categorical class decisions. For many applications, quantitative predictions are desirable that more accurately represent variability within subject groups and that can be correlated with behavioural variables. We evaluate the predictive capability of Gaussian process (GP) models for two types of quantitative prediction (multivariate regression and probabilistic classification) using whole-brain fMRI volumes. As a proof of concept, we apply GP models to an fMRI experiment investigating subjective responses to thermal pain and show GP models predict subjective pain ratings without requiring anatomical hypotheses about functional localisation of relevant brain processes. Even in the case of pain perception, where strong hypotheses do exist, GP predictions were more accurate than any region previously demonstrated to encode pain intensity. We demonstrate two brain mapping methods suitable for GP models and we show that GP regression models outperform state of the art support vector- and relevance vector regression. For classification, GP models perform categorical prediction as accurately as a support vector machine classifier and furnish probabilistic class predictions.
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Single-trial coupling of the gamma-band response and the corresponding BOLD signal.
Publication Date: 2009 Oct 27 PMID: 19878729
Authors: Mulert, C. - Leicht, G. - Hepp, P. - Kirsch, V. - Karch, S. - Pogarell, O. - Reiser, M. - Hegerl, U. - Jager, L. - Moller, H. J. - McCarley, R. W.
Journal: Neuroimage
Oscillations in the gamma-band frequency range have been described to be more closely connected to hemodynamic changes as assessed with functional magnetic resonance imaging (fMRI) than other aspects of neuronal activity. In addition, gamma-band oscillations have attracted much interest during the last few years since they are thought to play a crucial role in many aspects of brain function related to perception and cognition. It was the aim of the present simultaneous EEG-fMRI study to identify brain regions specifically involved in the generation of the auditory gamma-band response (GBR) using single-trial coupling of EEG and fMRI. Ten healthy subjects participated in this study. Three different runs of an auditory choice reaction task with increasing difficulty were performed. Brain activity was recorded simultaneously with high density EEG (61 channels) and fMRI (1.5 T). BOLD correlates of the GBR have been predicted using the single-trial amplitude of the GBR. Reaction times (p<0.001), error rates (p<0.05) and self-ratings of task difficulty and effort demands (p<0.001) were related to the level of difficulty in the task. In addition, we found a significant influence of task difficulty on the amplitude of the GBR at Cz (p<0.05). Using single-trial coupling of EEG and fMRI GBR-specific activations were found only in the auditory cortex, the thalamus and the anterior cingulate cortex (ACC) in the most difficult run. Single-trial coupling might be a useful method in order to increase our knowledge about the functional neuroanatomy of "neural ensembles" coupled by 40 Hz oscillations.
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Authors: Mulert, C. - Leicht, G. - Hepp, P. - Kirsch, V. - Karch, S. - Pogarell, O. - Reiser, M. - Hegerl, U. - Jager, L. - Moller, H. J. - McCarley, R. W.
Journal: Neuroimage
Oscillations in the gamma-band frequency range have been described to be more closely connected to hemodynamic changes as assessed with functional magnetic resonance imaging (fMRI) than other aspects of neuronal activity. In addition, gamma-band oscillations have attracted much interest during the last few years since they are thought to play a crucial role in many aspects of brain function related to perception and cognition. It was the aim of the present simultaneous EEG-fMRI study to identify brain regions specifically involved in the generation of the auditory gamma-band response (GBR) using single-trial coupling of EEG and fMRI. Ten healthy subjects participated in this study. Three different runs of an auditory choice reaction task with increasing difficulty were performed. Brain activity was recorded simultaneously with high density EEG (61 channels) and fMRI (1.5 T). BOLD correlates of the GBR have been predicted using the single-trial amplitude of the GBR. Reaction times (p<0.001), error rates (p<0.05) and self-ratings of task difficulty and effort demands (p<0.001) were related to the level of difficulty in the task. In addition, we found a significant influence of task difficulty on the amplitude of the GBR at Cz (p<0.05). Using single-trial coupling of EEG and fMRI GBR-specific activations were found only in the auditory cortex, the thalamus and the anterior cingulate cortex (ACC) in the most difficult run. Single-trial coupling might be a useful method in order to increase our knowledge about the functional neuroanatomy of "neural ensembles" coupled by 40 Hz oscillations.
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From Wikipedia,
Neuroimaging includes the use of various techniques to either directly or indirectly image the structure, function/pharmacology of the brain. It is a relatively new discipline within medicine and neuroscience/psychology. Neuroimaging falls into two broad categories, structural imaging, which deals with the structure of the brain and the diagnosis of gross (large scale) intracranial disease (such as tumor), and injury, and functional imaging, which is used to diagnose metabolic diseases and lesions on a finer scale (such as Alzheimer's disease) and also for neurological and cognitive psychology research and building brain-computer interfaces.
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