Recent Abstracts

By Darren Schreiber

In this set of abstracts, we get some interesting evidence on why high sensation seekers might be drawn to scary movies (1) and a series of methodological innovations that demonstrate how new advances are going to improve our ability to get useful insights from MRI data (2, 5, 7, 8, 9, 114). We also have some new work illuminating the role of stereotyped racial judgments (which rely on the amgydala) and individuate judgments which use a broad network of regions connected with mentalizing (3). Another article shows that there is variation in the deactivations of some regions of the default mode network in particular types tasks (4). We also learn that the default mode network contains the most heavily functionally connected brain regions, with the posterior cingulate being particular well connected to the rest of the brain (10).

Another article melds structural and functional connectivity data to provide an exciting methodological innovation (11). I have long hoped that brain imaging statistical analysis would start to do better at accounting for our priors about how the brain is organized, specifically that techniques would be developed to take advantage of our knowledge of structure while we try to understand function. This paper is a great step in this direction and I know that the developers of the FSL package are also making strides towards this goal.

On the topic of connectivity, we have a study that used a structural connectivity technique to demonstrate that the amgydala appears to have at least three distinct subregions (5). The amgydala is also shown to vary in size in non-medicated bi-polar patients, controls, and medicated bipolar patients (6).

Rounding out the remainder, we have a nice paper that provides a possible explanation for why the anterior cingulate appears to be active in reward activity in non-human primates, but seems to be mostly involved in error prediction in humans (12). Another paper demonstrates an important lesson for economists about the distinction between monetary and social rewards (13). While we may anticipate them using the same region (striatum), consumption of those rewards implicates distinct regions. We also have some insight into mental fatigue that confirms the importance of rest and perhaps provides a way of understanding why we feel so depleted after a hard day of academic brain busting (14). The next to last paper tries to synthesize two literatures suggesting alternative functions for the anterior temporal lobe, suggesting that perhaps it is our attempt to integrate conceptual understanding of our social tasks that is activating the region (15). And finally, we’ve got a paper looking at a potential genetic role for face recognition and a demonstration that it is independent of general intelligence (16).

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1) Miltner. Neural representation of anxiety and personality during exposure to anxiety-provoking and neutral scenes from scary movies. Human Brain Mapping (2010) vol. 31 (1) pp. 36-47
2) Lu et al. Improving fMRI sensitivity by normalization of basal physiologic state. Human Brain Mapping (2010) vol. 31 (1) pp. 80-7
3) Freeman et al. The neural origins of superficial and individuated judgments about ingroup and outgroup members. Human Brain Mapping (2010) vol. 31 (1) pp. 150-9
4) Mayer et al. Specialization in the default mode: Task-induced brain deactivations dissociate between visual working memory and attention. Human Brain Mapping (2010) vol. 31 (1) pp. 126-39
5) Solano-Castiella et al. Diffusion tensor imaging segments the human amygdala in vivo. NeuroImage (2009) pp.
6) Savitz et al. Amygdala volume in depressed patients with bipolar disorder assessed using high resolution 3T MRI: The impact of medication. Neuroimage (2009) pp.
7) Chumbley et al. Topological FDR for neuroimaging. NeuroImage (2009) pp.
8) Kasess et al. Multi-subject analyses with dynamic causal modeling. NeuroImage (2009) pp.
9) Stephan et al. Ten simple rules for dynamic causal modeling. NeuroImage (2009) pp.
10) Cole et al. Identifying the brain’s most globally connected regions. NeuroImage (2009) pp.
11) Saur et al. Combining functional and anatomical connectivity reveals brain networks for auditory language comprehension. NeuroImage (2009) pp.
12) Alexander and Brown. Competition between learned reward and error outcome predictions in anterior cingulate cortex. NeuroImage (2009) pp.
13) Rademacher et al. Dissociation of neural networks for anticipation and consumption of monetary and social rewards. NeuroImage (2009) pp.
14) Lim et al. Imaging brain fatigue from sustained mental workload: An ASL perfusion study of the time-on-task effect. NeuroImage (2009) pp.
15) Ross and Olson. Social cognition and the anterior temporal lobes. NeuroImage (2009) pp.
16) Zhu et al. Heritability of the Specific Cognitive Ability of Face Perception. Current biology : CB (2010) pp.

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1) Miltner. Neural representation of anxiety and personality during exposure to anxiety-provoking and neutral scenes from scary movies. Human Brain Mapping (2010) vol. 31 (1) pp. 36-47

Some people search for intense sensations such as being scared by frightening movies while others do not. The brain mechanisms underlying such inter-individual differences are not clear. Testing theoretical models, we investigated neural correlates of anxiety and the personality trait sensation seeking in 40 subjects who watched threatening and neutral scenes from scary movies during functional magnetic resonance imaging. Threat versus neutral scenes induced increased activation in anterior cingulate cortex, insula, thalamus, and visual areas. Movie-induced anxiety correlated positively with activation in dorsomedial prefrontal cortex, indicating a role for this area in the subjective experience of being scared. Sensation seeking-scores correlated positively with brain activation to threat versus neutral scenes in visual areas and in thalamus and anterior insula, i.e. regions involved in the induction and representation of arousal states. For the insula and thalamus, these outcomes were partly due to an inverse relation between sensation seeking scores and brain activation during neutral film clips. These results support models predicting cerebral hypoactivation in high sensation seekers during neutral stimulation, which may be compensated by more intense sensations such as watching scary movies.

2) Lu et al. Improving fMRI sensitivity by normalization of basal physiologic state. Human Brain Mapping (2010) vol. 31 (1) pp. 80-7

The power of fMRI in assessing neural activities is hampered by inter-subject variations in basal physiologic parameters, which may not be related to neural activation but has a modulatory effect on fMRI signals. Therefore, normalization of fMRI signals with these parameters is useful in reducing variations and improving sensitivity of this important technique. Recently, we have shown that basal venous oxygenation is a significant modulator of fMRI signals and individuals with higher venous oxygenation tend to have lower fMRI signals. In this study, we aim to test the utility of venous oxygenation normalization in distinguishing subject groups. A “model” condition was used in which two visual stimuli with different flashing frequencies were used to stimulate two subject groups, respectively, thereby simulating the situation of control and patient groups. It was found that visual-evoked BOLD signal is significantly correlated with baseline venous T2 (P = 0.0003) and inclusion of physiologic modulator in the regression analysis can substantially reduce P values of group-level statistical tests. When applied to voxel-wise analysis, the normalization process can allow the detection of more significant voxels. The utility of other basal parameters, including blood pressure, heart rate, arterial oxygenation, and end-tidal CO(2), in BOLD normalization was also assessed and it was found that the improvement was less significant. Time-to-peak of the BOLD responses was also studied and it was found that subjects with higher basal venous oxygenation tend to slower BOLD responses.

3) Freeman et al. The neural origins of superficial and individuated judgments about ingroup and outgroup members. Human Brain Mapping (2010) vol. 31 (1) pp. 150-9

We often form impressions of others based on superficial information, such as a mere glimpse of their face. Given the opportunity to get to know someone, however, our judgments are allowed to become more individuated. The neural origins of these two types of social judgment remain unknown. We used functional magnetic resonance imaging to dissociate the neural mechanisms underlying superficial and individuated judgments. Given behavioral evidence demonstrating impairments in individuating others outside one’s racial group, we additionally examined whether these neural mechanisms are race-selective. Superficial judgments recruited the amygdala. Individuated judgments engaged a cortical network implicated in mentalizing and theory of mind. One component of this mentalizing network showed selectivity to individuated judgments, but exclusively for targets of one’s own race. The findings reveal the distinct-and race-selective-neural bases of our everyday superficial and individuated judgments of others.

4) Mayer et al. Specialization in the default mode: Task-induced brain deactivations dissociate between visual working memory and attention. Human Brain Mapping (2010) vol. 31 (1) pp. 126-39

The idea of an organized mode of brain function that is present as default state and suspended during goal-directed behaviors has recently gained much interest in the study of human brain function. The default mode hypothesis is based on the repeated observation that certain brain areas show task-induced deactivations across a wide range of cognitive tasks. In this event-related functional resonance imaging study we tested the default mode hypothesis by comparing common and selective patterns of BOLD deactivation in response to the demands on visual attention and working memory (WM) that were independently modulated within one task. The results revealed task-induced deactivations within regions of the default mode network (DMN) with a segregation of areas that were additively deactivated by an increase in the demands on both attention and WM, and areas that were selectively deactivated by either high attentional demand or WM load. Attention-selective deactivations appeared in the left ventrolateral and medial prefrontal cortex and the left lateral temporal cortex. Conversely, WM-selective deactivations were found predominantly in the right hemisphere including the medial-parietal, the lateral temporo-parietal, and the medial prefrontal cortex. Moreover, during WM encoding deactivated regions showed task-specific functional connectivity. These findings demonstrate that task-induced deactivations within parts of the DMN depend on the specific characteristics of the attention and WM components of the task. The DMN can thus be subdivided into a set of brain regions that deactivate indiscriminately in response to cognitive demand (“the core DMN”) and a part whose deactivation depends on the specific task.

5) Solano-Castiella et al. Diffusion tensor imaging segments the human amygdala in vivo. NeuroImage (2009) pp.

The amygdala plays an important role in emotion, learning, and memory. It would be highly advantageous to understand more precisely its internal structure and connectivity for individual human subjects in vivo. Earlier cytoarchitectural research in post-mortem human and animal brains has revealed multiple subdivisions and connectivity patterns, probably related to different functions. With standard magnetic resonance imaging (MRI) techniques, however, the amygdala appears as an undifferentiated area of grey matter. Using high-quality diffusion tensor imaging (DTI) at 3 Tesla, we show diffusion anisotropy in this grey matter area. Such data allowed us to subdivide the amygdala for the first time in vivo. In 15 living subjects, we applied a spectral clustering algorithm to the principal diffusion direction in each amygdala voxel and found a consistent subdivision of the amygdala into a medial and a lateral region. The topography of these regions is in good agreement with the fibre architecture visible in myelin-stained sections through the amygdala of a human post-mortem brain. From these in vivo results we derived a probabilistic map of amygdalar fibre orientations. This segmentation technique has important implications for functional studies in the processing of emotions, cognitive function, and psychiatric disorders and in studying morphometry and volumetry of amygdala subdivisions.

6) Savitz et al. Amygdala volume in depressed patients with bipolar disorder assessed using high resolution 3T MRI: The impact of medication. Neuroimage (2009) pp.

MRI-based reports of both abnormally increased and decreased amygdala volume in bipolar disorder (BD) have surfaced in the literature. Two major methodological weaknesses characterizing extant studies are treatment with medication and inaccurate segmentation of the amygdala due to limitations in spatial and tissue contrast resolution. Here, we acquired high-resolution images (voxel size=0.55×0.55×0.60 mm) using a GE 3T MRI scanner, and a pulse sequence optimized for tissue contrast resolution. The amygdala was manually segmented by one rater blind to diagnosis, using coronal images. Eighteen unmedicated (mean medication-free period 11+/-10 months) BD subjects were age and gender matched with 18 healthy controls, and 17 medicated (lithium or divalproex) subjects were matched to 17 different controls. The unmedicated BD patients displayed smaller left and right amygdala volumes than their matched control group (p<0.01). Conversely, the BD subjects undergoing medication treatment showed a trend towards greater amygdala volumes than their matched HC sample (p=0.051). Right and left amygdala volumes were larger (p<0.05) or trended larger, respectively, in the medicated BD sample compared with the unmedicated BD sample. The two control groups did not differ from each other in either left or right amygdala volume. BD patients treated with lithium have displayed increased gray matter volume of the cortex and hippocampus relative to untreated BD subjects in previous studies. Here we extend these results to the amygdala. We raise the possibility that neuroplastic changes in the amygdala associated with BD are moderated by some mood stabilizing medications.

7) Chumbley et al. Topological FDR for neuroimaging. NeuroImage (2009) pp.

In this technical note, we describe and validate a topological false discovery rate (FDR) procedure for statistical parametric mapping. This procedure is designed to deal with signal that is continuous and has, in principle, unbounded spatial support. We therefore infer on topological features of the signal, such as the existence of local maxima or peaks above some threshold. Using results from random field theory, we assign a p-value to each maximum in an SPM and identify an adaptive threshold that controls false discovery rate, using the Benjamini and Hochberg (BH) procedure (1995). This provides a natural complement to conventional family wise error (FWE) control on local maxima. We use simulations to contrast these procedures; both in terms of their relative number of discoveries and their spatial accuracy (via the distribution of the Euclidian distance between true and discovered activations). We also assessed two other procedures: cluster-wise and voxel-wise FDR procedures. Our results suggest that (a) FDR control of maxima or peaks is more sensitive than FWE control of peaks with minimal cost in terms of false-positives, (b) voxel-wise FDR is substantially less accurate than topological FWE or FDR control. Finally, we present an illustrative application using an fMRI study of visual attention.

8) Kasess et al. Multi-subject analyses with dynamic causal modeling. NeuroImage (2009) pp.

Currently, most studies that employ dynamic causal modeling (DCM) use random-effects (RFX) analysis to make group inferences, applying a second-level frequentist test to subjects’ parameter estimates. In some instances, however, fixed-effects (FFX) analysis can be more appropriate. Such analyses can be implemented by combining the subjects’ posterior densities according to Bayes’ theorem either on a multivariate (Bayesian parameter averaging or BPA) or univariate basis (posterior variance weighted averaging or PVWA), or by applying DCM to time-series averaged across subjects beforehand (temporal averaging or TA). While all these FFX approaches have the advantage of allowing for Bayesian inferences on parameters a systematic comparison of their statistical properties has been lacking so far. Based on simulated data generated from a two-region network we examined the effects of signal-to-noise ratio (SNR) and population heterogeneity on group-level parameter estimates. Data sets were simulated assuming either a homogeneous large population (N=60) with constant connectivities across subjects or a heterogeneous population with varying parameters. TA showed advantages at lower SNR but is limited in its applicability. Because BPA and PVWA take into account posterior (co)variance structure, they can yield non-intuitive results when only considering posterior means. This problem is relevant for high SNR data, pronounced parameter interdependencies and when FFX assumptions are violated (i.e. inhomogeneous groups). It diminishes with decreasing SNR and is absent for models with independent parameters or when FFX assumptions are appropriate. Group results obtained with these FFX approaches should therefore be interpreted carefully by considering estimates of dependencies among model parameters.

9) Stephan et al. Ten simple rules for dynamic causal modeling. NeuroImage (2009) pp.

Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to conventional analysis techniques, a good knowledge of its theoretical foundations is needed to avoid pitfalls in its application and interpretation of results. By providing good practice recommendations for DCM, in the form of ten simple rules, we hope that this article serves as a helpful tutorial for the growing community of DCM users.

10) Cole et al. Identifying the brain’s most globally connected regions. NeuroImage (2009) pp.

Recent advances in brain connectivity methods have made it possible to identify hubs-the brain’s most globally connected regions. Such regions are essential for coordinating brain functions due to their connectivity with numerous regions with a variety of specializations. Current structural and functional connectivity methods generally agree that default mode network (DMN) regions have among the highest global brain connectivity (GBC). We developed two novel statistical approaches using resting state functional connectivity MRI-weighted and unweighted GBC (wGBC and uGBC)-to test the hypothesis that the highest global connectivity also occurs in the cognitive control network (CCN), a network anti-correlated with the DMN across a variety of tasks. High global connectivity was found in both CCN and DMN. The newly developed wGBC approach improves upon existing methods by quantifying inter-subject consistency, quantifying the highest GBC values by percentage, and avoiding arbitrarily connection strength thresholding. The uGBC approach is based on graph theory and includes many of these improvements, but still requires an arbitrary connection threshold. We found high GBC in several subcortical regions (e.g., hippocampus, basal ganglia) only with wGBC despite the regions’ extensive anatomical connectivity. These results demonstrate the complementary utility of wGBC and uGBC analyses for the characterization of the most highly connected, and thus most functionally important, regions of the brain. Additionally, the high connectivity of both the CCN and the DMN demonstrates that brain regions outside primary sensory-motor networks are highly involved in coordinating information throughout the brain.

11) Saur et al. Combining functional and anatomical connectivity reveals brain networks for auditory language comprehension. NeuroImage (2009) pp.

Cognitive functions are organized in distributed, overlapping, and interacting brain networks. Investigation of those large-scale brain networks is a major task in neuroimaging research. Here, we introduce a novel combination of functional and anatomical connectivity to study the network topology subserving a cognitive function of interest. (i) In a given network, direct interactions between network nodes are identified by analyzing functional MRI time series with the multivariate method of directed partial correlation (dPC). This method provides important improvements over shortcomings that are typical for ordinary (partial) correlation techniques. (ii) For directly interacting pairs of nodes, a region-to-region probabilistic fiber tracking on diffusion tensor imaging data is performed to identify the most probable anatomical white matter fiber tracts mediating the functional interactions. This combined approach is applied to the language domain to investigate the network topology of two levels of auditory comprehension: lower-level speech perception (i.e., phonological processing) and higher-level speech recognition (i.e., semantic processing). For both processing levels, dPC analyses revealed the functional network topology and identified central network nodes by the number of direct interactions with other nodes. Tractography showed that these interactions are mediated by distinct ventral (via the extreme capsule) and dorsal (via the arcuate/superior longitudinal fascicle fiber system) long- and short-distance association tracts as well as commissural fibers. Our findings demonstrate how both processing routines are segregated in the brain on a large-scale network level. Combining dPC with probabilistic tractography is a promising approach to unveil how cognitive functions emerge through interaction of functionally interacting and anatomically interconnected brain regions.

12) Alexander and Brown. Competition between learned reward and error outcome predictions in anterior cingulate cortex. NeuroImage (2009) pp.

The anterior cingulate cortex (ACC) is implicated in performance monitoring and cognitive control. Non-human primate studies of ACC show prominent reward signals, but these are elusive in human studies, which instead show mainly conflict and error effects. Here we demonstrate distinct appetitive and aversive activity in human ACC. The error likelihood hypothesis suggests that ACC activity increases in proportion to the likelihood of an error, and ACC is also sensitive to the consequence magnitude of the predicted error. Previous work further showed that error likelihood effects reach a ceiling as the potential consequences of an error increase, possibly due to reductions in the average reward. We explored this issue by independently manipulating reward magnitude of task responses and error likelihood while controlling for potential error consequences in an Incentive Change Signal Task. The fMRI results ruled out a modulatory effect of expected reward on error likelihood effects in favor of a competition effect between expected reward and error likelihood. Dynamic causal modeling showed that error likelihood and expected reward signals are intrinsic to the ACC rather than received from elsewhere. These findings agree with interpretations of ACC activity as signaling both perceptions of risk and predicted reward.

13) Rademacher et al. Dissociation of neural networks for anticipation and consumption of monetary and social rewards. NeuroImage (2009) pp.

Human behaviour is generally guided by the anticipation of potential outcomes that are considered to be rewarding. Reward processing can thus be dissected into a phase of reward anticipation and a phase of reward consumption. A number of brain structures have been suggested to be involved in reward processing. However, it is unclear whether anticipation and consumption are mediated by the same or different neural networks. We examined the neural basis of these processes using functional magnetic resonance imaging (fMRI) in an incentive delay task offering either money or social approval. In both conditions participants (N=28) were given a cue indicating potential reward. In order to receive reward a target button had to be pushed within a certain time window (adapted for individual reaction time). Cues triggering either monetary or social reward anticipation were presented sessionwise. Imaging was performed on a 1.5-Tesla Philips scanner in an event-related design. Anticipation of both reward types activated brain structures constituting the brain reward system including the ventral striatum. In contrast to the task independent activity in the anticipation phase, reward consumption evoked different patterns of activation for money and social approval, respectively. While social stimuli were mainly associated with amygdala activation, the thalamus was more strongly activated by the presentation of monetary rewards. Our results identify dissociable neural networks for the anticipation and consumption of reward. The findings implicate that the neural mechanisms underlying reward consumption are more modality-specific than those for reward anticipation, and that they are mediated by subjective reward value.

14) Lim et al. Imaging brain fatigue from sustained mental workload: An ASL perfusion study of the time-on-task effect. NeuroImage (2009) pp.

During sustained periods of a taxing cognitive workload, humans typically display time-on-task (TOT) effects, in which performance gets steadily worse over the period of task engagement. Arterial spin labeling (ASL) perfusion functional magnetic resonance imaging (fMRI) was used in this study to investigate the neural correlates of TOT effects in a group of 15 subjects as they performed a 20-min continuous psychomotor vigilance test (PVT). Subjects displayed significant TOT effects, as seen in progressively slower reaction times and significantly increased mental fatigue ratings after the task. Perfusion data showed that the PVT activates a right lateralized fronto-parietal attentional network in addition to the basal ganglia and sensorimotor cortices. The fronto-parietal network was less active during post-task rest compared to pre-task rest, and regional CBF decrease in this network correlated with performance decline. These results demonstrate the persistent effects of cognitive fatigue in the fronto-parietal network after a period of heavy mental work and indicate the critical role of this attentional network in mediating TOT effects. Furthermore, resting regional CBF in the thalamus and right middle frontal gyrus prior to task onset was predictive of subjects’ subsequent performance decline, suggesting that resting CBF quantified by ASL perfusion fMRI may be a useful indicator of performance potential and a marker of the level of fatigue in the neural attentional system.

15) Ross and Olson. Social cognition and the anterior temporal lobes. NeuroImage (2009) pp.

Two distinct literatures have emerged on the functionality of the anterior temporal lobes (ATL): in one field, the ATLs are conceived of as a repository for semantic or conceptual knowledge. In another field, the ATLs are thought to play some undetermined role in social-emotional functions such as Theory of Mind. Here we attempted to reconcile these distinct functions by assessing whether social semantic processing can explain ATL activation in other social cognitive tasks. Social semantic functions refer to knowledge about social concepts and rules. In a first experiment we tested the idea that social semantic representations can account for activations in the ATL to social attribution stimuli such as Heider and Simmel animations. Left ATL activations to Heider and Simmel stimuli overlapped with activations to social words. In a second experiment we assessed the putative roles of the ATLs in the processing of narratives and theory of mind content and found evidence for a role of the ATLs in the processing of theory of mind but not narrative per se. These findings indicate that the ATLs are part of a neuronal network supporting social cognition and that they are engaged when tasks demand access to social conceptual knowledge.

16) Zhu et al. Heritability of the Specific Cognitive Ability of Face Perception. Current biology : CB (2010) pp.

What makes one person socially insightful but mathematically challenged, and another musically gifted yet devoid of a sense of direction? Individual differences in general cognitive ability are thought to be mediated by “generalist genes” that affect many cognitive abilities similarly without specific genetic influences on particular cognitive abilities [1]. In contrast, we present here evidence for cognitive “specialist genes”: monozygotic twins are more similar than dizygotic twins in the specific cognitive ability of face perception. Each of three measures of face-specific processing was heritable, i.e., more correlated in monozygotic than dizygotic twins: face-specific recognition ability, the face-inversion effect [2], and the composite-face effect [3]. Crucially, this effect is due to the heritability of face processing in particular, not to a more general aspect of cognition such as IQ or global attention. Thus, individual differences in at least one specific mental talent are independently heritable. This finding raises the question of what other specific cognitive abilities are independently heritable and may elucidate the mechanisms by which heritable disorders like dyslexia and autism can have highly uneven cognitive profiles in which some mental processes can be selectively impaired while others remain unaffected or even selectively enhanced.

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One response to “Recent Abstracts

  1. Zhu et al. is imaginative. We might apply their framework to analyze political behaviors.

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