Task-free MRI predicts individual differences in brain activity during task performance.

When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

Unmasking Latent Inhibitory Connections in Human Cortex to Reveal Dormant Cortical Memories.

Balance of cortical excitation and inhibition (EI) is thought to be disrupted in several neuropsychiatric conditions, yet it is not clear how it is maintained in the healthy human brain. When EI balance is disturbed during learning and memory in animal models, it can be restabilized via formation of inhibitory replicas of newly formed excitatory connections. Here we assess evidence for such selective inhibitory rebalancing in humans. Using fMRI repetition suppression we measure newly formed cortical associations in the human brain. We show that expression of these associations reduces over time despite persistence in behavior, consistent with inhibitory rebalancing. To test this, we modulated excitation/inhibition balance with transcranial direct current stimulation (tDCS). Using ultra-high-field (7T) MRI and spectroscopy, we show that reducing GABA allows cortical associations to be re-expressed. This suggests that in humans associative memories are stored in balanced excitatory-inhibitory ensembles that lie dormant unless latent inhibitory connections are unmasked.

Effects of image reconstruction on fiber orientation mapping from multichannel diffusion MRI: reducing the noise floor using SENSE.

PURPOSE: To examine the effects of the reconstruction algorithm of magnitude images from multichannel diffusion MRI on fiber orientation estimation. THEORY AND METHODS: It is well established that the method used to combine signals from different coil elements in multichannel MRI can have an impact on the properties of the reconstructed magnitude image. Using a root-sum-of-squares approach results in a magnitude signal that follows an effective noncentral-χ distribution. As a result, the noise floor, the minimum measurable in the absence of any true signal, is elevated. This is particularly relevant for diffusion-weighted MRI, where the signal attenuation is of interest. RESULTS: In this study, we illustrate problems that such image reconstruction characteristics may cause in the estimation of fiber orientations, both for model-based and model-free approaches, when modern 32-channel coils are used. We further propose an alternative image reconstruction method that is based on sensitivity encoding (SENSE) and preserves the Rician nature of the single-channel, magnitude MR signal. We show that for the same k-space data, root-sum-of-squares can cause excessive overfitting and reduced precision in orientation estimation compared with the SENSE-based approach. CONCLUSION: These results highlight the importance of choosing the appropriate image reconstruction method for tractography studies that use multichannel receiver coils for diffusion MRI acquisition.

Shifts in reinforcement signalling while playing slot-machines as a function of prior experience and impulsivity.

Electronic gaming machines (EGMs) offer significant revenue streams for mercantile gambling. However, limited clinical and experimental evidence suggests that EGMs are associated with heightened risks of clinically problematic patterns of play. Little is known about the neural structures that might mediate the transition from exploratory EGM play to the 'addictive' play seen in problem gamblers; neither is it known how personality traits associated with gambling activity (and gambling problems) influence reinforcement processing while playing EGMs. Using functional magnetic resonance imaging in healthy participants, we show that a single episode of slot-machine play is subsequently associated with reduced amplitudes of blood-oxygenation level-dependent signals within reinforcement-related structures, such as the ventral striatum and caudate nucleus, following winning game outcomes; but increased amplitudes of anticipatory signals within the ventral striatum and amygdala while watching the game reels spin. Trait impulsivity enhanced positive signals within the ventral striatum and amygdala following the delivery of winning outcomes but diminished positive signals following the experience of almost-winning ('near-misses'). These results indicate that a single episode of slot-machine play engages the well-characterised reinforcement-learning mechanisms mediated by ascending dopamine mesolimbic and mesostriatal pathways, to shift reward value of EGMs away from game outcomes towards anticipatory states. Impulsivity, itself linked to problem gambling and heightened vulnerability to other addictive disorders, is associated with divergent coding of winning outcomes and almost-winning experiences within the ventral striatum and amygdala, potentially enhancing the reward value of successful slot-machine game outcomes but, at the same time,modulating the aversive motivational consequences of near-miss outcomes.

Shifts in reinforcement signalling while playing slot-machines as a function of prior experience and impulsivity.

Electronic gaming machines (EGMs) offer significant revenue streams for mercantile gambling. However, limited clinical and experimental evidence suggests that EGMs are associated with heightened risks of clinically problematic patterns of play. Little is known about the neural structures that might mediate the transition from exploratory EGM play to the 'addictive' play seen in problem gamblers; neither is it known how personality traits associated with gambling activity (and gambling problems) influence reinforcement processing while playing EGMs. Using functional magnetic resonance imaging in healthy participants, we show that a single episode of slot-machine play is subsequently associated with reduced amplitudes of blood-oxygenation-level-dependent signals within reinforcement-related structures, such as the ventral striatum and caudate nucleus, following winning game outcomes; but increased amplitudes of anticipatory signals within the ventral striatum and amygdala while watching the game reels spin. Trait impulsivity enhanced positive signals within the ventral striatum and amygdala following the delivery of winning outcomes but diminished positive signals following the experience of almost-winning ('near-misses'). These results indicate that a single episode of slot-machine play engages the well-characterised reinforcement-learning mechanisms mediated by ascending dopamine mesolimbic and mesostriatal pathways, to shift reward value of EGMs away from game outcomes towards anticipatory states. Impulsivity, itself linked to problem gambling and heightened vulnerability to other addictive disorders, is associated with divergent coding of winning outcomes and almost-winning experiences within the ventral striatum and amygdala, potentially enhancing the reward value of successful slot-machine game outcomes but, at the same time, modulating the aversive motivational consequences of near-miss outcomes.

The Human Connectome Project: a data acquisition perspective.

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences.

The danger of systematic bias in group-level FMRI-lag-based causality estimation.

Schippers, Renken and Keysers (NeuroImage, 2011) present a simulation of multi-subject lag-based causality estimation. We fully agree that single-subject evaluations (e.g., Smith et al., 2011) need to be revisited in the context of multi-subject studies, and Schippers' paper is a good example, including detailed multi-level simulation and cross-subject statistical modelling. The authors conclude that "the average chance to find a significant Granger causality effect when no actual influence is present in the data stays well below the p-level imposed on the second level statistics" and that "when the analyses reveal a significant directed influence, this direction was accurate in the vast majority of the cases". Unfortunately, we believe that the general meaning that may be taken from these statements is not supported by the paper's results, as there may in reality be a systematic (group-average) difference in haemodynamic delay between two brain areas. While many statements in the paper (e.g., the final two sentences) do refer to this problem, we fear that the overriding message that many readers may take from the paper could cause misunderstanding.

Network analysis detects changes in the contralesional hemisphere following stroke.

Changes in brain structure occur in remote regions following focal damage such as stroke. Such changes could disrupt processing of information across widely distributed brain networks. We used diffusion MRI tractography to assess connectivity between brain regions in 9 chronic stroke patients and 18 age-matched controls. We applied complex network analysis to calculate 'communicability', a measure of the ease with which information can travel across a network. Clustering individuals based on communicability separated patient and control groups, not only in the lesioned hemisphere but also in the contralesional hemisphere, despite the absence of gross structural pathology in the latter. In our highly selected patient group, lesions were localised to the left basal ganglia/internal capsule. We found reduced communicability in patients in regions surrounding the lesions in the affected hemisphere. In addition, communicability was reduced in homologous locations in the contralesional hemisphere for a subset of these regions. We interpret this as evidence for secondary degeneration of fibre pathways which occurs in remote regions interconnected, directly or indirectly, with the area of primary damage. We also identified regions with increased communicability in patients that could represent adaptive, plastic changes post-stroke. Network analysis provides new and powerful tools for understanding subtle changes in interactions across widely distributed brain networks following stroke.

Separate value comparison and learning mechanisms in macaque medial and lateral orbitofrontal cortex.

Uncertainty about the function of orbitofrontal cortex (OFC) in guiding decision-making may be a result of its medial (mOFC) and lateral (lOFC) divisions having distinct functions. Here we test the hypothesis that the mOFC is more concerned with reward-guided decision making, in contrast with the lOFC's role in reward-guided learning. Macaques performed three-armed bandit tasks and the effects of selective mOFC lesions were contrasted against lOFC lesions. First, we present analyses that make it possible to measure reward-credit assignment--a crucial component of reward-value learning--independently of the decisions animals make. The mOFC lesions do not lead to impairments in reward-credit assignment that are seen after lOFC lesions. Second, we examined how the reward values of choice options were compared. We present three analyses, one of which examines reward-guided decision making independently of reward-value learning. Lesions of the mOFC, but not the lOFC, disrupted reward-guided decision making. Impairments after mOFC lesions were a function of the multiple option contexts in which decisions were made. Contrary to axiomatic assumptions of decision theory, the mOFC-lesioned animals' value comparisons were no longer independent of irrelevant alternatives.

Multiple-subjects connectivity-based parcellation using hierarchical Dirichlet process mixture models.

We propose a hierarchical infinite mixture model approach to address two issues in connectivity-based parcellations: (i) choosing the number of clusters, and (ii) combining data from different subjects. In a Bayesian setting, we model voxel-wise anatomical connectivity profiles as an infinite mixture of multivariate Gaussian distributions, with a Dirichlet process prior on the cluster parameters. This type of prior allows us to conveniently model the number of clusters and estimate its posterior distribution directly from the data. An important benefit of using Bayesian modelling is the extension to multiple subjects clustering via a hierarchical mixture of Dirichlet processes. Data from different subjects are used to infer on class parameters and the number of classes at individual and group level. Such a method accounts for inter-subject variability, while still benefiting from combining different subjects data to yield more robust estimates of the individual clusterings.

Anatomical connectivity of the subgenual cingulate region targeted with deep brain stimulation for treatment-resistant depression.

Chronic deep brain stimulation (DBS) of subgenual cingulate white matter results in dramatic remission of symptoms in some previously treatment-resistant depression patients. The effects of stimulation may be mediated locally or via corticocortical or corticosubcortical connections. We use tractography to define the likely connectivity of cingulate regions stimulated in DBS-responsive patients using diffusion imaging data acquired in healthy control subjects. We defined 2 distinct regions within anterior cingulate cortex based on anatomical connectivity: a pregenual region strongly connected to medial prefrontal and anterior midcingulate cortex and a subgenual region with strongest connections to nucleus accumbens, amygdala, hypothalamus, and orbitofrontal cortex. The location of electrode contact points from 9 patients successfully treated with DBS lies within this subgenual region. The anatomical connectivity of the subgenual cingulate region targeted with DBS for depression supports the hypothesis that treatment efficacy is mediated via effects on a distributed network of frontal, limbic, and visceromotor brain regions. At present, targeting of DBS for depression is based on landmarks visible in conventional magnetic resonance imaging. Preoperatively acquired diffusion imaging for connectivity-based cortical mapping could improve neurosurgical targeting. We hypothesize that the subgenual region with greatest connectivity across the distributed network described here may prove most effective.

A Bayesian framework for global tractography.

We readdress the diffusion tractography problem in a global and probabilistic manner. Instead of tracking through local orientations, we parameterise the connexions between brain regions at a global level, and then infer on global and local parameters simultaneously in a Bayesian framework. This approach offers a number of important benefits. The global nature of the tractography reduces sensitivity to local noise and modelling errors. By constraining tractography to ensure a connexion is found, and then inferring on the exact location of the connexion, we increase the robustness of connectivity-based parcellations, allowing parcellations of connexions that were previously invisible to tractography. The Bayesian framework allows a direct comparison of the evidence for connecting and non-connecting models, to test whether the connexion is supported by the data. Crucially, by explicit parameterisation of the connexion between brain regions, we infer on a parameter that is shared with models of functional connectivity. This model is a first step toward the joint inference on functional and anatomical connectivity.

Discordant white matter N-acetylasparate and diffusion MRI measures suggest that chronic metabolic dysfunction contributes to axonal pathology in multiple sclerosis.

Diffusion MRI and magnetic resonance spectroscopic measurements of selectively neuronally localised N-acetylaspartate (NAA) both have been used widely to assess white matter integrity and axonal loss. We have tested directly the relationship between changes in diffusion MRI parameters and NAA concentrations in the corpus callosum (CC) in an in vivo study of patients with MS. Fifteen MS patients (median EDSS 2.5, range 1-4) were studied with T(1) anatomical, T(2)-weighted, and diffusion-sensitised MRI and PRESS single-voxel MRS. A recently described method, tract-based spatial statistics (TBSS) [Smith, S.M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T.E., Mackay, C.E. et al., 2006. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31, 1487-1505] also was used to perform exploratory voxelwise whole-brain analysis of white matter diffusion fractional anisotropy (FA). We found a strong correlation between callosal size and both mean FA (r=0.68, p<0.005) (related specifically to changes in the radial tensor component) and mean inter-hemispheric motor tract connectivity probability (r=0.74, p<0.001). TBSS confirmed that the diffusion anisotropies of white matter voxels specifically within the callosum were correlated with the callosal size. Individual patient global T(2) lesion volumes were correlated with both the probability of callosal connectivity (r=-0.69, p<0.005) and fractional anisotropy across the callosum (r=-0.76, p<0.001). However, absolute concentrations of NAA from the voxel showed no correlation with callosal cross-sectional area, mean connectivity or fractional anisotropy within the callosal pathway. We conclude that diffusion MRI shows changes consistent with sensitivity to axonal loss, but that relative NAA changes are not necessarily related directly to this. Axonal metabolic function, independent of structural integrity, may be a major determinant of NAA measures in MS.

Contrasting roles for cingulate and orbitofrontal cortex in decisions and social behaviour.

There is general acknowledgement that both the anterior cingulate and orbitofrontal cortex are implicated in reinforcement-guided decision making, and emotion and social behaviour. Despite the interest that these areas generate in both the cognitive neuroscience laboratory and the psychiatric clinic, ideas about the distinctive contributions made by each have only recently begun to emerge. This reflects an increasing understanding of the component processes that underlie reinforcement-guided decision making, such as the representation of reinforcement expectations, the exploration, updating and representation of action values, and the appreciation that choices are guided not just by the prospect of reward but also by the costs that action entails. Evidence is emerging to suggest that the anterior cingulate and orbitofrontal cortex make distinct contributions to each of these aspects of decision making.

Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?

We present a direct extension of probabilistic diffusion tractography to the case of multiple fibre orientations. Using automatic relevance determination, we are able to perform online selection of the number of fibre orientations supported by the data at each voxel, simplifying the problem of tracking in a multi-orientation field. We then apply the identical probabilistic algorithm to tractography in the multi- and single-fibre cases in a number of example systems which have previously been tracked successfully or unsuccessfully with single-fibre tractography. We show that multi-fibre tractography offers significant advantages in sensitivity when tracking non-dominant fibre populations, but does not dramatically change tractography results for the dominant pathways.

Between session reproducibility and between subject variability of diffusion MR and tractography measures.

As diffusion tractography is increasingly used to generate quantitative measures to address clinical questions, it is important to characterise the inter-session reproducibility and inter-subject variability of these measures. Here, we assess the reproducibility and variability of diffusion tractography measures using diffusion data from 8 subjects scanned 3 times. We used probabilistic tractography to define the cingulum bundle, pyramidal tracts, optic radiations and genu of the corpus callosum in each individual data set using three different methods of seed definition. Measures of mean fractional anisotropy (FA) and mean diffusivity (MD) along the tracts were more reproducible than measures of tract volume. Further, tracts defined using a two region of interest (ROI) approach were more reproducible than those defined using manually placed seed masks alone. For mean FA taken from tracts defined using the two ROI approach, inter-session coefficients of variation (CV) were all below 5% and inter-subject CVs were below 10%; for mean MD inter-session, CVs were all below 3% and inter-subject CVs were below 8%. We use the variability measures found here to calculate the sample sizes required to detect changes in FA, MD or tract volume of a given size, either between groups of subjects or within subjects over time. Finally, we compare tractography results using 60 diffusion encoding directions to those found using a subset of 12 directions; the number of diffusion directions did not have a significant effect on reproducibility, but tracts derived using fewer directions were consistently smaller than those derived using 60 direction data. We suggest that 12 direction data are sufficient for reproducibly defining the core of large bundles but may be less sensitive to smaller pathways.

Probabilistic diffusion tractography: a potential tool to assess the rate of disease progression in amyotrophic lateral sclerosis.

The goal of probabilistic tractography is to obtain a connectivity index along a white matter pathway that reflects fibre organization and is sensitive to pathological abnormalities contributing to disability. Here, we present the development of voxel-based connectivity measures along the tractography-derived corticospinal tract (CST). We investigated whether these connectivity measures are different in patients with amyotrophic lateral sclerosis (ALS) and correlate with the rate of disease progression. We also investigated whether fractional anisotropy (FA), which reflects directional coherence of fibre tracts, is reduced in the CST of ALS patients and relates to disease progression rate. Thirteen patients with probable or definite ALS and 19 healthy subjects were studied. The probabilistic tractography algorithm segmented the bilateral CST, along which FA and connectivity values were obtained. To take into account the asymmetric distribution of connectivity values, two summary statistic measures that focused on voxels with higher connectivity values were selected and then used in the analysis, together with the mean connectivity and the mean FA. To complete the analysis, the same summary measures for FA were included. Differences in all these indices between patients with moderate or rapid disease progression rate and controls were investigated using linear regression, adjusted for age and white matter fraction. The association between FA or connectivity in the CST and the disease progression rate was assessed using linear regression. Patients with a rapid disease progression rate had significantly lower summary connectivity measures than controls in the left CST, but there was only a borderline statistical difference in mean connectivity. Patients with rapid progression had a significantly lower mean FA, and any other FA measure, in both CSTs than controls. When only patients were considered, strong associations between the rate of disease progression and all the connectivity measures in the left CST were found (P-values between P < 0.001 and P = 0.002, partial correlation coefficients between -0.90 and -0.82). However, there was no evidence of an association between disease progression rate and any of the FA measures in the bilateral CST. Our findings suggest that FA and connectivity provide complementary information, since FA is sensitive to the detection of all the group differences, whereas the summary connectivity measures correlate with disease progression rate. The development of such connectivity measures raises their potential as markers of disease progression in ALS, and provides guidance for their use in other neurological diseases.

Reliable identification of the auditory thalamus using multi-modal structural analyses.

The medial geniculate body (MGB) of the thalamus is a key component of the auditory system. It is involved in relaying and transforming auditory information to the cortex and in top-down modulation of processing in the midbrain, brainstem, and ear. Functional imaging investigations of this region in humans, however, have been limited by the difficulty of distinguishing MGB from other thalamic nuclei. Here, we introduce two methods for reliably delineating MGB anatomically in individuals based on conventional and diffusion MRI data. The first uses high-resolution proton density weighted scanning optimized for subcortical grey-white contrast. The second uses diffusion-weighted imaging and probabilistic tractography to automatically segment the medial and lateral geniculate nuclei from surrounding structures based on their distinctive patterns of connectivity to the rest of the brain. Both methods produce highly replicable results that are consistent with published atlases. Importantly, both methods rely on commonly available imaging sequences and standard hardware, a significant advantage over previously described approaches. In addition to providing useful approaches for identifying the MGB and LGN in vivo, our study offers further validation of diffusion tractography for the parcellation of grey matter regions on the basis of their connectivity patterns.

A consistent relationship between local white matter architecture and functional specialisation in medial frontal cortex.

Functionally significant landmarks in the brain do not necessarily align with local sulcal and gyral architecture in a manner that is consistent across individuals. However, the functional specialisation underlying these landmarks is strongly constrained by the connectional architecture of the region. Here, we explore this relationship in the supplementary motor area (SMA) and pre-SMA in the medial frontal cortex of the human brain. Using diffusion tensor, conventional and functional MR imaging, we find that the location of the functional boundary between SMA and preSMA is more consistent with respect to specific features of the local white matter as it approaches neocortex than with respect to the local gyral and sulcal anatomy in the region.

Distinct right frontal lobe activation in language processing following left hemisphere injury.

Right hemisphere activation during functional imaging studies of language has frequently been reported following left hemisphere injury. Few studies have anatomically characterized the specific right hemisphere structures engaged. We used functional MRI (fMRI) with verbal fluency tasks in 12 right-handed patients with left temporal lobe epilepsy (LTLE) and 12 right-handed healthy controls to localize language-related activity in the right inferior frontal gyrus (RIFG). During the phonemic task, LTLE patients activated a significantly more posterior region of the right anterior insula/frontal operculum than healthy controls (P = 0.02). Activation of the left inferior frontal gyrus (LIFG) did not differ significantly between the two groups. This suggests that, following left hemisphere injury, language-related processing in the right hemisphere differs from that with a functionally normal left hemisphere. The localization of activation in the left and right inferior frontal gyri was determined with respect to the anatomical sub-regions pars opercularis (Pop), pars triangularis (Ptr) and pars orbitalis (Por). In the LIFG, both healthy controls (8 out of 12) and LTLE patients (9 out of 12) engaged primarily Pop during phonemic fluency. Activations in the RIFG, however, were located mostly in the anterior insula/frontal operculum in both healthy controls (8 out of 12) and LTLE patients (8 out of 12), albeit in distinct regions. Mapping the locations of peak voxels in relation to previously obtained cytoarchitectonic maps of Broca's area confirmed lack of homology between activation regions in the left and right IFG. Verbal fluency-related activation in the RIFG was not anatomically homologous to LIFG activation in either patients or controls. To test more directly whether RIFG activation shifts in a potentially adaptive manner after left hemisphere injury, fMRI studies were performed in a patient prior to and following anatomical left hemispherectomy for the treatment of Rasmussen's encephalitis. An increase in activation magnitude and posterior shift in location were found in the RIFG after hemispherectomy for both phonemic and semantic tasks. Together, these results suggest that left temporal lobe injury is associated with potentially adaptive changes in right inferior frontal lobe functions in processing related to expressive language.