Characterising group-level brain connectivity: A framework using Bayesian exponential random graph models.

The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical phenotype such as age-group, disease condition or mental state. To do so reliably, it is necessary to determine the features of the connectivity structure that are common across a group of brain scans. Given the complex interdependencies inherent in network data, this is not a straightforward task. Some studies construct a group-representative network (GRN), ignoring individual differences, while other studies analyse networks for each individual independently, ignoring information that is shared across individuals. We propose a Bayesian framework based on exponential random graph models (ERGM) extended to multiple networks to characterise the distribution of an entire population of networks. Using resting-state fMRI data from the Cam-CAN project, a study on healthy ageing, we demonstrate how our method can be used to characterise and compare the brain's functional connectivity structure across a group of young individuals and a group of old individuals.

Healthy minds from 0-100 years: Optimising the use of European brain imaging cohorts ("Lifebrain").

The main objective of "Lifebrain" is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5,000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.

Symptoms of depression in a large healthy population cohort are related to subjective memory complaints and memory performance in negative contexts.

BACKGROUND: Decades of research have investigated the impact of clinical depression on memory, which has revealed biases and in some cases impairments. However, little is understood about the effects of subclinical symptoms of depression on memory performance in the general population. METHODS: Here we report the effects of symptoms of depression on memory problems in a large population-derived cohort (N = 2544), 87% of whom reported at least one symptom of depression. Specifically, we investigate the impact of depressive symptoms on subjective memory complaints, objective memory performance on a standard neuropsychological task and, in a subsample (n = 288), objective memory in affective contexts. RESULTS: There was a dissociation between subjective and objective memory performance, with depressive symptoms showing a robust relationship with self-reports of memory complaints, even after adjusting for age, sex, general cognitive ability and symptoms of anxiety, but not with performance on the standardised measure of verbal memory. Contrary to our expectations, hippocampal volume (assessed in a subsample, n = 592) did not account for significant variance in subjective memory, objective memory or depressive symptoms. Nonetheless, depressive symptoms were related to poorer memory for pictures presented in negative contexts, even after adjusting for memory for pictures in neutral contexts. CONCLUSIONS: Thus the symptoms of depression, associated with subjective memory complaints, appear better assessed by memory performance in affective contexts, rather than standardised memory measures. We discuss the implications of these findings for understanding the impact of depressive symptoms on memory functioning in the general population.

Age-related delay in visual and auditory evoked responses is mediated by white- and grey-matter differences.

Slowing is a common feature of ageing, yet a direct relationship between neural slowing and brain atrophy is yet to be established in healthy humans. We combine magnetoencephalographic (MEG) measures of neural processing speed with magnetic resonance imaging (MRI) measures of white and grey matter in a large population-derived cohort to investigate the relationship between age-related structural differences and visual evoked field (VEF) and auditory evoked field (AEF) delay across two different tasks. Here we use a novel technique to show that VEFs exhibit a constant delay, whereas AEFs exhibit delay that accumulates over time. White-matter (WM) microstructure in the optic radiation partially mediates visual delay, suggesting increased transmission time, whereas grey matter (GM) in auditory cortex partially mediates auditory delay, suggesting less efficient local processing. Our results demonstrate that age has dissociable effects on neural processing speed, and that these effects relate to different types of brain atrophy.

Assessing dynamic functional connectivity in heterogeneous samples.

Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brain's functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured dFC may be caused by other sources of heterogeneity between people. For example, the shape of the haemodynamic response function (HRF) and levels of measurement noise have been found to vary with age. We use a generic simulation framework for fMRI data to investigate the effect of such heterogeneity on estimates of dFC. Our findings show that, despite no differences in true dFC, individual differences in measured dFC can result from other (non-dynamic) features of the data, such as differences in neural autocorrelation, HRF shape, connectivity strength and measurement noise. We also find that common dFC methods such as k-means and multilayer modularity approaches can detect spurious group differences in dynamic connectivity due to inappropriate setting of their hyperparameters. fMRI studies therefore need to consider alternative sources of heterogeneity across individuals before concluding differences in dFC.

How to discover modules in mind and brain: the curse of nonlinearity, and blessing of neuroimaging. A comment on Sternberg (2011).

Sternberg (2011) elegantly formalizes how certain sets of hypotheses, specifically modularity and pure or composite measures, imply certain patterns of behavioural and neuroimaging data. Experimentalists are often interested in the converse, however: whether certain patterns of data distinguish certain hypotheses, specifically whether more than one module is involved. In this case, there is a striking reversal of the relative value of the data patterns that Sternberg considers. Foremost, the example of additive effects of two factors on one composite measure becomes noninformative for this converse question. Indeed, as soon as one allows for nonlinear measurement functions and nonlinear module processes, even a cross-over interaction between two factors is noninformative in this respect. Rather, one requires more than one measure, from which certain data patterns do provide strong evidence for multiple modules, assuming only that the measurement functions are monotonic. If two measures are not monotonically related to each other across the levels of one or more experimental factors, then one has evidence for more than one module (i.e., more than one nonmonotonic transform). Two special cases of this are illustrated here: a "reversed association" between two measures across three levels of a single factor, and Sternberg's example of selective effects of two factors on two measures. Fortunately, functional neuroimaging methods normally do provide multiple measures over space (e.g., functional magnetic resonance imaging, fMRI) and/or time (e.g., electroencephalography, EEG). Thus to the extent that brain modules imply mind modules (i.e., separate processors imply separate processes), the performance data offered by functional neuroimaging are likely to be more powerful in revealing modules than are the single behavioural measures (such as accuracy or reaction time, RT) traditionally considered in psychology.

Stimulus-response bindings code both abstract and specific representations of stimuli: evidence from a classification priming design that reverses multiple levels of response representation.

Repetition priming can be caused by the rapid retrieval of previously encoded stimulus-response (S-R) bindings. S-R bindings have recently been shown to simultaneously code multiple levels of response representation, from specific Motor-actions to more abstract Decisions ("yes"/"no") and Classifications (e.g., "man-made"/"natural"). Using an experimental design that reverses responses at all of these levels, we assessed whether S-R bindings also code multiple levels of stimulus representation. Across two experiments, we found effects of response reversal on priming when switching between object pictures and object names, consistent with S-R bindings that code stimuli at an abstract level. Nonetheless, the size of this reversal effect was smaller for such across-format (e.g., word-picture) repetition than for within-format (e.g., picture-picture) repetition, suggesting additional coding of format-specific stimulus representations. We conclude that S-R bindings simultaneously represent both stimuli and responses at multiple levels of abstraction.

Variants in several genomic regions associated with asperger disorder.

Asperger disorder (ASP) is one of the autism spectrum disorders (ASD) and is differentiated from autism largely on the absence of clinically significant cognitive and language delays. Analysis of a homogenous subset of families with ASP may help to address the corresponding effect of genetic heterogeneity on identifying ASD genetic risk factors. To examine the hypothesis that common variation is important in ASD, we performed a genome-wide association study (GWAS) in 124 ASP families in a discovery data set and 110 ASP families in a validation data set. We prioritized the top 100 association results from both cohorts by employing a ranking strategy. Novel regions on 5q21.1 (P = 9.7 × 10(-7) ) and 15q22.1-q22.2 (P = 7.3 × 10(-6) ) were our most significant findings in the combined data set. Three chromosomal regions showing association, 3p14.2 (P = 3.6 × 10(-6) ), 3q25-26 (P = 6.0 × 10(-5) ) and 3p23 (P = 3.3 × 10(-4) ) overlapped linkage regions reported in Finnish ASP families, and eight association regions overlapped ASD linkage areas. Our findings suggest that ASP shares both ASD-related genetic risk factors, as well as has genetic risk factors unique to the ASP phenotype.

Selecting forward models for MEG source-reconstruction using model-evidence.

We investigated four key aspects of forward models for distributed solutions to the MEG inverse problem: 1) the nature of the cortical mesh constraining sources (derived from an individual's MRI, or inverse-normalised from a template mesh); 2) the use of single-sphere, overlapping spheres, or Boundary Element Model (BEM) head-models; 3) the density of the cortical mesh (3000 vs. 7000 vertices); and 4) whether source orientations were constrained to be normal to that mesh. These were compared within the context of two types of spatial prior on the sources: a single prior corresponding to a standard L2-minimum-norm (MNM) inversion, or multiple sparse priors (MSP). The resulting generative models were compared using a free-energy approximation to the Bayesian model-evidence after fitting multiple epochs of responses to faces or scrambled faces. Statistical tests of the free-energy, across nine participants, showed clear superiority of MSP over MNM models; with the former reconstructing deeper sources. Furthermore, there was 1) no evidence that an individually-defined cortical mesh was superior to an inverse-normalised canonical mesh, but 2) clear evidence that a BEM was superior to spherical head-models, provided individually-defined inner skull and scalp meshes were used. Finally, for MSP models, there was evidence that the combination of 3) higher density cortical meshes and 4) dipoles constrained to be normal to the mesh was superior to lower-density or freely-oriented sources (in contrast to the MNM models, in which free-orientation was optimal). These results have practical implications for MEG source reconstruction, particularly in the context of group studies.

Forward and backward connections in the brain: a DCM study of functional asymmetries.

In this paper, we provide evidence for functional asymmetries in forward and backward connections that define hierarchical architectures in the brain. We exploit the fact that modulatory or nonlinear influences of one neuronal system on another (i.e., effective connectivity) entail coupling between different frequencies. Functional asymmetry in forward and backward connections was addressed by comparing dynamic causal models of MEG responses induced by visual processing of normal and scrambled faces. We compared models with and without nonlinear (between-frequency) coupling in both forward and backward connections. Bayesian model comparison indicated that the best model had nonlinear forward and backward connections. Using the best model we then quantified frequency-specific causal influences mediating observed spectral responses. We found a striking asymmetry between forward and backward connections; in which high (gamma) frequencies in higher cortical areas suppressed low (alpha) frequencies in lower areas. This suppression was significantly greater than the homologous coupling in the forward connections. Furthermore, exactly the asymmetry was observed when we examined face-selective coupling (i.e., coupling under faces minus scrambled faces). These results highlight the importance of nonlinear coupling among brain regions and point to a functional asymmetry between forward and backward connections in the human brain that is consistent with anatomical and physiological evidence from animal studies. This asymmetry is also consistent with functional architectures implied by theories of perceptual inference in the brain, based on hierarchical generative models.

Priming, response learning and repetition suppression.

Prior exposure to a stimulus can facilitate its subsequent identification and classification, a phenomenon called priming. This behavioural facilitation is usually accompanied by a reduction in neural response within specific cortical regions (repetition suppression, RS). Recent research has suggested that both behavioural priming and RS can be largely determined by previously learned stimulus-response associations. According to this view, a direct association forms between the stimulus presented and the response made to it. On a subsequent encounter with the stimulus, this association automatically cues the response, bypassing the various processing stages that were required to select that response during its first presentation. Here we reproduce behavioural evidence for such stimulus-response associations, and show the PFC to be sensitive to such changes. In contrast, RS within ventral temporal regions (such as the fusiform cortex), which are usually associated with perceptual processing, is shown to be robust to response changes. The present study therefore suggests a dissociation between RS within the PFC, which may be sensitive to retrieval of stimulus-response associations, and RS within posterior perceptual regions, which may reflect facilitation of perceptual processing independent of stimulus-response associations.

Electrophysiological correlates of masked face priming.

Using a sandwich-masked priming paradigm with faces, we report two ERP effects that appear to reflect different levels of subliminal face processing. These two ERP repetition effects dissociate in their onset, scalp topography, and sensitivity to face familiarity. The "early" effect occurred between 100 and 150 ms, was maximally negative-going over lateral temporoparietal channels, and was found for both familiar and unfamiliar faces. The "late" effect occurred between 300 and 500 ms, was maximally positive-going over centroparietal channels, and was found only for familiar faces. The early effect resembled our previous fMRI data from the same paradigm; the late effect resembled the behavioural priming found, in the form of faster reaction times to make fame judgments about primed relative to unprimed familiar faces. None of the ERP or behavioural effects appeared explicable by a measure of participants' ability to see the primes. The ERP and behavioural effects showed some sensitivity to whether the same or a different photograph of a face was repeated, but could remain reliable across different photographs, and did not appear attributable to a low-level measure of pixelwise overlap between prime and probe photograph. The functional significance of these ERP effects is discussed in relation to unconscious perception and face processing.

Epigenetic regulation of microRNA-370 by interleukin-6 in malignant human cholangiocytes.

Interleukin-6 (IL-6) is overexpressed and contributes to tumor cell growth in cholangiocarcinoma. Enforced IL-6 production can alter the expression of specific microRNAs (miRNAs) involved in tumor growth, and moreover can modulate expression of methylation-dependent genes. Thus, we assessed the methylation-dependent regulation of miRNA expression in human malignant cholangiocytes stably transfected to overexpress IL-6. The expression of the methyltransferases DNA methyltransferase enzyme-1 and HASJ4442 was increased by IL-6 overexpression, but was decreased by the methylation inhibitor 5-aza-2'-deoxycytidine (5-aza-CdR). Expression profiling identified seven miRNAs that were significantly downregulated by IL-6 overexpression (<0.4-fold) and upregulated (>2-fold) by 5-aza-CdR. One of these, miR-370, is embedded in a CpG island. Although 5-aza-CdR increased miR-370 expression by 2.1-fold in malignant cells, the expression in nonmalignant cells was unchanged. The oncogene mitogen-activated protein kinase kinase kinase 8 (MAP3K8) was identified as a target of miR-370, and its expression was decreased by 5-aza-CdR in cholangiocarcinoma cells. Overexpression of IL-6 reduced miR-370 expression and reinstated MAP3K8 expression in vitro as well as in tumor cell xenografts in vivo. Thus, IL-6 may contribute to tumor growth by modulation of expression of selected miRNAs, such as miR-370. These studies define a mechanism by which inflammation-associated cytokines can epigenetically modulate gene expression and directly contribute to tumor biology.

Population-level inferences for distributed MEG source localization under multiple constraints: application to face-evoked fields.

We address some key issues entailed by population inference about responses evoked in distributed brain systems using magnetoencephalography (MEG). In particular, we look at model selection issues at the within-subject level and feature selection issues at the between-subject level, using responses evoked by intact and scrambled faces around 170 ms (M170). We compared the face validity of subject-specific forward models and their summary statistics in terms of how estimated responses reproduced over subjects. At the within-subject level, we focused on the use of multiple constraints, or priors, for inverting distributed source models. We used restricted maximum likelihood (ReML) estimates of prior covariance components (in both sensor and source space) and show that their relative importance is conserved over subjects. At the between-subject level, we used standard anatomical normalization methods to create posterior probability maps that furnish inference about regionally specific population responses. We used these to compare different summary statistics, namely; (i) whether to test for differences between condition-specific source estimates, or whether to test the source estimate of differences between conditions, and (ii) whether to accommodate differences in source orientation by using signed or unsigned (absolute) estimates of source activity.

Effect of spatial attention on stimulus-specific haemodynamic repetition effects.

The aim of this fMRI study was to investigate whether spatial attention to the initial and/or repeated presentation of a stimulus is necessary to observe repetition-related modulations of the neural responses evoked by that stimulus. During each trial, two stimuli were presented simultaneously, one left and one right of fixation. During each block, participants were instructed to attend covertly to stimuli in one of the two hemifields and respond whether each was a face or house, ignoring the contralateral stimulus. Regions that preferred one stimulus category over the other, such as the fusiform face area and parahippocampal place area, showed evidence of some processing of the ignored stimuli. However, a reduced response to repeated stimuli (repetition suppression) was only reliable for preferred stimuli when both their initial and repeated presentations were attended. This suggests that attention is necessary for both the acquisition and expression of the neural mechanisms that underlie repetition suppression, at least over the lags of 2-16 intervening trials used here.

Mechanisms of top-down facilitation in perception of visual objects studied by FMRI.

Prior knowledge regarding the possible identity of an object facilitates its recognition from a degraded visual input, though the underlying mechanisms are unclear. Previous work implicated ventral visual cortex but did not disambiguate whether activity-changes in these regions are causal to or merely reflect an effect of facilitated recognition. We used functional magnetic resonance imaging to study top-down influences on processing of gradually revealed objects, by preceding each object with a name that was congruent or incongruent with the object. Congruently primed objects were recognized earlier than incongruently primed, and this was paralleled by shifts in activation profiles for ventral visual, parietal, and prefrontal cortices. Prior to recognition, defined on a trial-by-trial basis, activity in ventral visual cortex rose gradually but equivalently for congruently and incongruently primed objects. In contrast, prerecognition activity was greater with congruent priming in lateral parietal, retrosplenial, and lateral prefrontal cortices, whereas functional coupling between parietal and ventral visual (and also left lateral prefrontal and parietal) cortices was enhanced in the same context. Thus, when controlling for recognition point and stimulus information, activity in ventral visual cortex mirrors recognition success, independent of condition. Facilitation by top-down cues involves lateral parietal cortex interacting with ventral visual areas, potentially explaining why parietal lesions can lead to deficits in recognizing degraded objects even in the context of top-down knowledge.

Impact of Sclerotinia Stem Rot on Yield of Canola.

Sclerotinia sclerotiorum is the causal agent of Sclerotinia stem rot (SSR) of canola (Brassica napus). In North Dakota, the leading canola producer in the United States, SSR is an endemic disease. In order to estimate the impact of this disease on canola yield, field experiments were conducted from 2000 to 2004 at several locations in North Dakota and Minnesota. Experimental plots were either inoculated with laboratory-produced ascospores or infected by naturally occurring inoculum in commercial fields. Applying fungicides at different concentrations and timings during the flowering period created epiphytotics of diverse intensities. Disease incidence was measured once prior to harvesting the crop on 50 to 100 plants per plot. Results of the study indicated that 0.5% of the potential yield (equivalent to 12.75 kg/ha) was lost for every unit percentage of SSR incidence (range of 0.18 to 0.96%). Considering the current cost of fungicide applications and the market value of this commodity, a 17% SSR incidence could cause losses similar to the cost of a fungicide application. Additional efforts are required to improve current levels of tolerance of canola plants to this pathogen.

A critique of functional localisers.

In this critique, we review the usefulness of functional localising scans in functional MRI studies. We consider their conceptual motivations and the implications for experimental design and inference. Functional localisers can often be viewed as acquiring data from cells that have been removed from an implicit factorial design. This perspective reveals their potentially restrictive nature. We deconstruct two examples from the recent literature to highlight the key issues. We conclude that localiser scans can be unnecessary and, in some instances, lead to a biased and inappropriately constrained characterisation of functional anatomy.

Efficacy of Fungicides for Control of Sclerotinia Stem Rot of Canola.

Sclerotinia stem rot (SSR), incited by Sclerotinia sclerotiorum, causes yield reductions to canola (Brassica napus) grown in North Dakota and Minnesota. Field trials were conducted in North Dakota and Minnesota from 2000 to 2004 to evaluate the effect of foliar fungicides on SSR and canola yield. Levels of SSR varied among years and location. In general, fungicides that consistently reduced SSR incidence compared with an untreated control were azoxystrobin, benomyl, boscalid, iprodione, prothioconazole, tebuconazole, thiophanate-methyl, trifloxystrobin, and vinclozolin. Significant reductions in SSR incidence with fungicides did not always translate into differences in canola yield, however. Inconsistent results were observed with different timings of applications based on percent bloom. This indicates that application timing should be based on factors in addition to percent bloom.

Response of Canola Cultivars to Sclerotinia sclerotiorum in Controlled and Field Environments.

Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum, can be a devastating disease of canola (Brassica napus) in the northern United States. No canola cultivars are marketed as having resistance to SSR. Field trials were established in Red Lake Falls, MN (2001, 2003, and 2004) and Carrington, ND (2001, 2002, 2003, and 2004) to evaluate canola cultivars for resistance to SSR. These cultivars also were evaluated for resistance to SSR under controlled conditions using the following methods: petiole inoculation technique (PIT), detached leaf assay (DLA), and oxalic acid assay (OAA). Significant (P ≤ 0.05) differences were detected among cultivars for SSR and yield in the field trials, with SSR levels varying from low to high among years and locations. Cultivars with consistent high levels and low levels of SSR in the field trials were identified. Significant (P ≤ 0.05) differences were detected among cultivars for SSR using the PIT and OAA methods, but not the DLA method. No significant (P ≤ 0.05) correlations between SSR levels in the controlled studies with SSR levels in the field trials were detected; however, significant negative correlations were detected between SSR area under the disease process curve values from the PIT method and yield from Carrington, ND in 2001 and 2002. Although the PIT and OAA methods differentiated cultivars, neither method was able to predict the reaction of cultivars to SSR in the field, indicating that field screening for SSR resistance is still critical for the development of resistant cultivars.