Rivalry of homeostatic and sensory-evoked emotions: dehydration attenuates olfactory disgust and its neural correlates

Neural correlates have been described for emotions evoked by states of homeostatic imbalance (e.g. thirst, hunger, and breathlessness) and for emotions induced by external sensory stimulation (such as fear and disgust). However, the neurobiological mechanisms of their interaction, when they are experienced simultaneously, are still unknown. We investigated the interaction on the neurobiological and the perceptional level using subjective ratings, serum parameters, and functional magnetic resonance imaging (fMRI) in a situation of emotional rivalry, when both a homeostatic and a sensory-evoked emotion were experienced at the same time. Twenty highly dehydrated male subjects rated a disgusting odor as significantly less repulsive when they were thirsty. On the neurobiological level, we found that this reduction in subjective disgust during thirst was accompanied by a significantly reduced neural activity in the insular cortex, a brain area known to be considerably involved in processing of disgust. Furthermore, during the experience of disgust in the satiated condition, we observed a significant functional connectivity between brain areas responding to the disgusting odor, which was absent during the stimulation in the thirsty condition. These results suggest interference of conflicting emotions: An acute homeostatic imbalance can attenuate the experience of another emotion evoked by the sensory perception of a potentially harmful external agent. This finding offers novel insights with regard to the behavioral relevance of biologically different types of emotions, indicating that some types of emotions are more imperative for behavior than others. As a general principle, this modulatory effect during the conflict of homeostatic and sensory-evoked emotions may function to safeguard survival.

The functional significance of EEG microstates-Associations with modalities of thinking

The momentary, global functional state of the brain is reflected by its electric field configuration. Cluster analytical approaches consistently extracted four head-surface brain electric field configurations that optimally explain the variance of their changes across time in spontaneous EEG recordings. These four configurations are referred to as EEG microstate classes A, B, C, and D and have been associated with verbal/phonological, visual, attention reorientation, and subjective interoceptive-autonomic processing, respectively. The present study tested these associations via an intra-individual and inter-individual analysis approach. The intra-individual approach tested the effect of task-induced increased modality-specific processing on EEG microstate parameters. The inter-individual approach tested the effect of personal modality-specific parameters on EEG microstate parameters. We obtained multichannel EEG from 61 healthy, right-handed, male students during four eyes-closed conditions: object-visualization, spatial-visualization, verbalization (6 runs each), and resting (7 runs). After each run, we assessed participants' degrees of object-visual, spatial-visual, and verbal thinking using subjective reports. Before and after the recording, we assessed modality-specific cognitive abilities and styles using nine cognitive tests and two questionnaires. The EEG of all participants, conditions, and runs was clustered into four classes of EEG microstates (A, B, C, and D). RMANOVAs, ANOVAs and post-hoc paired t-tests compared microstate parameters between conditions. TANOVAs compared microstate class topographies between conditions. Differences were localized using eLORETA. Pearson correlations assessed interrelationships between personal modality-specific parameters and EEG microstate parameters during no-task resting. As hypothesized, verbal as opposed to visual conditions consistently affected the duration, occurrence, and coverage of microstate classes A and B. Contrary to associations suggested by previous reports, parameters were increased for class A during visualization, and class B during verbalization. In line with previous reports, microstate D parameters were increased during no-task resting compared to the three internal, goal-directed tasks. Topographic differences between conditions concerned particular sub-regions of components of the metabolic default mode network. Modality-specific personal parameters did not consistently correlate with microstate parameters except verbal cognitive style which correlated negatively with microstate class A duration and positively with class C occurrence. This is the first study that aimed to induce EEG microstate class parameter changes based on their hypothesized functional significance. Beyond, the associations of microstate classes A and B with visual and verbal processing, respectively and microstate class D with interoceptive-autonomic processing, our results suggest that a finely-tuned interplay between all four EEG microstate classes is necessary for the continuous formation of visual and verbal thoughts, as well as interoceptive-autonomic processing. Our results point to the possibility that the EEG microstate classes may represent the head-surface measured activity of intra-cortical sources primarily exhibiting inhibitory functions. However, additional studies are needed to verify and elaborate on this hypothesis.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Neuroanatomy of intergroup bias: A white matter microstructure study of individual differences

Intergroup bias - the tendency to behave more positively towards an ingroup member than an outgroup member - is a powerful social force, for good and ill. And though it is widely demonstrated, intergroup bias is not universal, as it is characterized by significant individual differences. Recently, attention has begun to turn to whether neuroanatomy might explain these individual differences in intergroup bias. However, no research to date has examined whether white matter microstructure could help determine differences in behavior towards ingroup and outgroup members. In the current research, we examine intergroup bias with the third-party punishment paradigm and white matter integrity and connectivity strength as determined by diffusion tensor imaging (DTI). We found that both increased white matter integrity at the right temporal-parietal junction (TPJ) and connectivity strength between the right TPJ and the dorsomedial prefrontal cortex (DMPFC) were associated with increased impartiality in the third-party punishment paradigm, i.e., reduced intergroup bias. Further, consistent with the role that these brain regions play in the mentalizing network, we found that these effects were mediated by mentalizing processes. Participants with greater white matter integrity at the right TPJ and connectivity strength between the right TPJ and the DMPFC employed mentalizing processes more equally for ingroup and outgroup members, and this non-biased use of mentalizing was associated with increased impartiality. The current results help shed light on the mechanisms of bias and, potentially, on interventions that promote impartiality over intergroup bias.

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel–Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although acorrelation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo. Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analyzed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, intervals 58–82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillations

Dynamic gamma frequency feedback coupling between higher and lower order visual cortices underlies perceptual completion in humans

To perceive a coherent environment, incomplete or overlapping visual forms must be integrated into meaningful coherent percepts, a process referred to as ?Gestalt? formation or perceptual completion. Increasing evidence suggests that this process engages oscillatory neuronal activity in a distributed neuronal assembly. A separate line of evidence suggests that Gestalt formation requires top-down feedback from higher order brain regions to early visual cortex. Here we combine magnetoencephalography (MEG) and effective connectivity analysis in the frequency domain to specifically address the effective coupling between sources of oscillatory brain activity during Gestalt formation. We demonstrate that perceptual completion of two-tone ?Mooney? faces induces increased gamma frequency band power (55?71 Hz) in human early visual, fusiform and parietal cortices. Within this distributed neuronal assembly fusiform and parietal gamma oscillators are coupled by forward and backward connectivity during Mooney face perception, indicating reciprocal influences of gamma activity between these higher order visual brain regions. Critically, gamma band oscillations in early visual cortex are modulated by top-down feedback connectivity from both fusiform and parietal cortices. Thus, we provide a mechanistic account of Gestalt perception in which gamma oscillations in feature sensitive and spatial attention-relevant brain regions reciprocally drive one another and convey global stimulus aspects to local processing units at low levels of the sensory hierarchy by top-down feedback. Our data therefore support the notion of inverse hierarchical processing within the visual system underlying awareness of coherent percepts.

Dopamine receptor 4 promoter polymorphism modulates memory and neuronal responses to salience

Animal models and human functional imaging data implicate the dopamine system in mediating enhanced encoding of novel stimuli into human memory. A separate line of investigation suggests an association between a functional polymorphism in the promoter region for the human dopamine 4 receptor gene (DRD4) and sensitivity to novelty. We demonstrate, in two independent samples, that the -521Cmayor queT DRD4 promoter polymorphism determines the magnitude of human memory enhancement for contextually novel, perceptual oddball stimuli in an allele dose-dependent manner. The genotype-dependent memory enhancement conferred by the C allele is associated with increased neuronal responses during successful encoding of perceptual oddballs in the ventral striatum, an effect which is again allele dose-dependent. Furthermore, with repeated presentations of oddball stimuli, this memory advantage decreases, an effect mirrored by adaptation of activation in the hippocampus and substantia nigra/ventral tegmental area in C carriers only. Thus, a dynamic modulation of human memory enhancement for perceptually salient stimuli is associated with activation of a dopaminergic-hippocampal system, which is critically dependent on a functional polymorphism in the DRD4 promoter region.

Dynamics of brain networks in aesthetic appreciation

Neuroimage experiments have been essential for identifying active brain networks. During cognitive tasks as in, e.g., aesthetic appreciation, such networks include regions that belong to the default mode network (DMN). Theoretically, DMN activity should be interrupted during cognitive tasks demanding attention, as is the case for aesthetic appreciation. Analyzing the functional connectivity dynamics along three temporal windows and two conditions, beautiful and not beautiful stimuli, here we report experimental support for the hypothesis that aesthetic appreciation relies on the activation of two different networks, an initial aesthetic network and a delayed aesthetic network, engaged within distinct time frames. Activation of the DMN might correspond mainly to the delayed aesthetic network. We discuss adaptive and evolutionary explanations for the relationships existing between the DMN and aesthetic networks and offer unique inputs to debates on the mind/brain interaction.

White matter damage disorganizes brain functional networks in amnestic mild cognitive impairment

Although progressive functional brain network disruption has been one of the hallmarks of Alzheimer?s Dis- ease, little is known about the origin of this functional impairment that underlies cognitive symptoms. We in- vestigated how the loss of white matter (WM) integrity disrupts the organization of the functional networks at different frequency bands. The analyses were performed in a sample of healthy elders and mild cognitive im- pairment (MCI) subjects. Spontaneous brain magnetic activity (measured with magnetoencephalography) was characterized with phase synchronization analysis, and graph theory was applied to the functional networks. We identified WM areas (using diffusion weighted magnetic resonance imaging) that showed a statistical de- pendence between the fractional anisotropy and the graph metrics. These regions are part of an episodic mem- ory network and were also related to cognitive functions. Our data support the hypothesis that disruption of the anatomical networks influences the organization at the functional level resulting in the prodromal dementia syndrome of MCI.

The default mode network is functionally and structurally disrupted in amnestic mild cognitive impairment — a bimodal MEG–DTI study

Over the past years, several studies on Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) have reported Default Mode Network (DMN) deficits. This network is attracting increasing interest in the AD community, as it seems to play an important role in cognitive functioning and in beta amyloid deposition. Attention has been particularly drawn to how different DMN regions are connected using functional or structural connectivity. To this end, most studies have used functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET) or Diffusion Tensor Imaging (DTI). In this study we evaluated (1) functional connectivity from resting state magnetoencephalography (MEG) and (2) structural connectivity from DTI in 26 MCI patients and 31 age-matched controls. Compared to controls, the DMN in the MCI group was functionally disrupted in the alpha band, while no differences were found for delta, theta, beta and gamma frequency bands. In addition, structural disconnection could be assessed through a decreased fractional anisotropy along tracts connecting different DMN regions. This suggests that the DMN functional and anatomical disconnection could represent a core feature of MCI.

Guiding functional connectivity estimation by structural connectivity in MEG: an application to discrimination of mild cognitive impaired conditions

Whole brain resting state connectivity is a promising biomarker that might help to obtain an early diagnosis in many neurological diseases, such as dementia. Inferring resting-state connectivity is often based on correlations, which are sensitive to indirect connections, leading to an inaccurate representation of the real backbone of the network. The precision matrix is a better representation for whole brain connectivity, as it considers only direct connections. The network structure can be estimated using the graphical lasso (GL), which achieves sparsity through l1-regularization on the precision matrix. In this paper, we propose a structural connectivity adaptive version of the GL, where weaker anatomical connections are represented as stronger penalties on the corre- sponding functional connections. We applied beamformer source reconstruction to the resting state MEG record- ings of 81 subjects, where 29 were healthy controls, 22 were single-domain amnestic Mild Cognitive Impaired (MCI), and 30 were multiple-domain amnestic MCI. An atlas-based anatomical parcellation of 66 regions was ob- tained for each subject, and time series were assigned to each of the regions. The fiber densities between the re- gions, obtained with deterministic tractography from diffusion-weighted MRI, were used to define the anatomical connectivity. Precision matrices were obtained with the region specific time series in five different frequency bands. We compared our method with the traditional GL and a functional adaptive version of the GL, in terms of log-likelihood and classification accuracies between the three groups. We conclude that introduc- ing an anatomical prior improves the expressivity of the model and, in most cases, leads to a better classification between groups.

Avaliação de linguagem por ressonância magnética funcional em pacientes com epilepsia associada à esclerose mesial temporal unilateral: correlação com avaliação clínica de linguagem

Introdução: A esclerose mesial temporal (EMT) é a principal causa de epilepsia resistente ao tratamento medicamentoso. Pacientes com EMT apresentam dificuldades no processamento semântico e fonológico de linguagem e maior incidência de reorganização cerebral da linguagem (bilateral ou à direita) em relação à população geral. A ressonância magnética funcional (RMf) permite avaliar a reorganização cerebral das redes de linguagem, comparando padrões de ativação cerebral entre diversas regiões cerebrais. Objetivo: Investigar o desempenho linguístico de pacientes com EMT unilateral esquerda e direita e a ocorrência de reorganização das redes de linguagem com RMf para avaliar se a reorganização foi benéfica para a linguagem nestes pacientes. Métodos: Utilizamos provas clínicas de linguagem e paradigmas de nomeação visual e responsiva para RMf, desenvolvidos para este estudo. Foram avaliados 24 pacientes com EMTe, 22 pacientes com EMTd e 24 controles saudáveis, submetidos a provas de linguagem (fluência semântica e fonológica, nomeação de objetos, verbos, nomes próprios e responsiva, e compreensão de palavras) e a três paradigmas de linguagem por RMf [nomeação por confrontação visual (NCV), nomeação responsiva à leitura (NRL) e geração de palavras (GP)]. Seis regiões cerebrais de interesse (ROI) foram selecionadas (giro frontal inferior, giro frontal médio, giro frontal superior, giro temporal inferior, giro temporal médio e giro temporal superior). Índices de Lateralidade (ILs) foram calculados com dois métodos: bootstrap, do programa LI-Toolbox, independe de limiar, e PSC, que indica a intensidade da ativação cerebral de cada voxel. Cada grupo de pacientes (EMTe e EMTd) foi dividido em dois subgrupos, de acordo com o desempenho em relação aos controles na avaliação clinica de linguagem. O <= -1,5 foi utilizado como nota de corte para dividir os grupos em pacientes com bom e com mau desempenho de linguagem. Em seguida, comparou-se o desempenho linguístico dos subgrupos ao índices IL-boot. Resultados: Pacientes com EMT esquerda e direita mostraram pior desempenho que controles nas provas clínicas de nomeação de verbos, nomeação de nomes próprios, nomeação responsiva e fluência verbal. Os mapas de ativação cerebral por RMf mostraram efeito BOLD em regiões frontais e temporoparietais de linguagem. Os mapas de comparação de ativação cerebral entre os grupos revelaram que pacientes com EMT esquerda e direita apresentam maior ativação em regiões homólogas do hemisfério direito em relação aos controles. Os ILs corroboraram estes resultados, mostrando valores médios menores para os pacientes em relação aos controles e, portanto, maior simetria na representação da linguagem. A comparação entre o IL-boot e o desempenho nas provas clínicas de linguagem indicou que, no paradigma de nomeação responsiva à leitura, a reorganização funcional no giro temporal médio, e possivelmente, nos giros temporal inferior e superior associou-se a desempenho preservado em provas de nomeação. Conclusão: Pacientes com EMT direita e esquerda apresentam comprometimento de nomeação e fluência verbal e reorganização da rede cerebral de linguagem. A reorganização funcional de linguagem em regiões temporais, especialmente o giro temporal médio associou-se a desempenho preservado em provas de nomeação em pacientes com EMT esquerda no paradigma de RMf de nomeação responsiva à leitura

Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex

Gamma activity to stationary grating stimuli was studied non-invasively using MEG recordings in humans. Using a spatial filtering technique, we localized gamma activity to primary visual cortex. We tested the hypothesis that spatial frequency properties of visual stimuli may be related to the temporal frequency characteristics of the associated cortical responses. We devised a method to assess temporal frequency differences between stimulus-related responses that typically exhibit complex spectral shapes. We applied this methodology to either single-trial (induced) or time-averaged (evoked) responses in four frequency ranges (0-40, 20-60, 40-80 and 60-100 Hz) and two time windows (either the entire duration of stimulus presentation or the first second following stimulus onset). Our results suggest that stimuli of varying spatial frequency induce responses that exhibit significantly different temporal frequency characteristics. These effects were particularly accentuated for induced responses in the classical gamma frequency band (20-60 Hz) analyzed over the entire duration of stimulus presentation. Strikingly, examining the first second of the responses following stimulus onset resulted in significant loss in stimulus specificity, suggesting that late signal components contain functionally relevant information. These findings advocate a functional role of gamma activity in sensory representation. We suggest that stimulus specific frequency characteristics of MEG signals can be mapped to processes of neuronal synchronization within the framework of coupled dynamical systems.