Functional MRI applications for intra-axial brain tumours: uses and nuances in surgical practise.

PURPOSE: Functional MRI (fMRI) has well-established uses to inform risks and plan maximally safe approaches in neurosurgery. In the field of brain tumour surgery, however, fMRI is currently in a state of clinical equipoise due to debate around both its sensitivity and specificity. MATERIALS AND METHODS: In this review, we summarise the role and our experience of fMRI in neurosurgery for gliomas and metastases. We discuss nuances in the conduct and interpretation of fMRI that, based on our practise, most directly impact fMRI's usefulness in the neurosurgical setting. RESULTS: Illustrated examples in which fMRI in our hands directly influences the neurosurgical treatment of brain tumours include evaluating the probability and nature of functional risks, especially for language functions. These presurgical risk assessments, in turn, help to predict the resectability of tumours, select or deselect patients for awake surgery, indicate the need for neurophysiological monitoring and guide the optimal use of intra-operative stimulation mapping. A further emerging application of fMRI is in measuring functional adaptation of functional networks after (partial) surgery, of potential use in the timing of further surgery. CONCLUSIONS: In appropriately selected patients with a clearly defined surgical question, fMRI offers a valuable complementary tool in the pre-surgical evaluation of brain tumours. However, there is a great need for standards in the administration and analysis of fMRI as much as in the techniques that it is commonly evaluated against. Surprisingly little data exists that evaluates the accuracy of fMRI not just against complementary methods, but in terms of its ultimate clinical aim of minimising post-surgical morbidity.

Bayesian Inference for Brain Activity from Functional Magnetic Resonance Imaging Collected at Two Spatial Resolutions.

Neuroradiologists and neurosurgeons increasingly opt to use functional magnetic resonance imaging (fMRI) to map functionally relevant brain regions for noninvasive presurgical planning and intraoperative neuronavigation. This application requires a high degree of spatial accuracy, but the fMRI signal-to-noise ratio (SNR) decreases as spatial resolution increases. In practice, fMRI scans can be collected at multiple spatial resolutions, and it is of interest to make more accurate inference on brain activity by combining data with different resolutions. To this end, we develop a new Bayesian model to leverage both better anatomical precision in high resolution fMRI and higher SNR in standard resolution fMRI. We assign a Gaussian process prior to the mean intensity function and develop an efficient, scalable posterior computation algorithm to integrate both sources of data. We draw posterior samples using an algorithm analogous to Riemann manifold Hamiltonian Monte Carlo in an expanded parameter space. We illustrate our method in analysis of presurgical fMRI data, and show in simulation that it infers the mean intensity more accurately than alternatives that use either the high or standard resolution fMRI data alone.

Parakinesia: A Delphi consensus report.

Abnormal movements are intrinsic to some forms of endogenous psychoses. Spontaneous dyskinesias are observed in drug-naïve first-episode patients and at-risk subjects. However, recent descriptions of spontaneous dyskinesias may actually represent the rediscovery of a more complex phenomenon, 'parakinesia' which was described and documented in extensive cinematographic recordings and long-term observations by German and French neuropsychiatrists decades before the introduction of antipsychotics. With the emergence of drug induced movement disorders, the description of parakinesia has been refined to emphasize the features enabling differential diagnosis with tardive dyskinesia. Unfortunately, parakinesia was largely neglected by mainstream psychiatry to the point of being almost absent from the English-language literature. With the renewed interest in motor phenomena intrinsic to SSD, it was timely not only to raise awareness of parakinesia, but also to propose a scientifically usable definition for this phenomenon. Therefore, we conducted a Delphi consensus exercise with clinicians familiar with the concept of parakinesia. The original concept was separated into hyperkinetic parakinesia (HPk) as dyskinetic-like expressive movements and parakinetic psychomotricity (PPM), i.e., patient's departing from the patient's normal motion style. HPk prevails on the upper part of the face and body, resembling expressive and reactive gestures that not only occur inappropriately but also appear distorted. Abnormal movements vary in intensity depending on the level of psychomotor arousal and are thus abated by antipsychotics. HPk frequently co-occurs with PPM, in which gestures and mimics lose their naturalness and become awkward, disharmonious, stiff, mannered, and bizarre. Patients are never spontaneously aware of HPk or PPM, and the movements are never experienced as self-dystonic or self-alien. HPk and PPM are highly specific to endogenous psychoses, in which they are acquired and progressive, giving them prognostic value. Their differential diagnoses and correspondences with current international concepts are discussed.

Paratonia, Gegenhalten and psychomotor hypertonia Back to the roots.

In the first half of the 20th century, well before the antipsychotic era, paratonia, Gegenhalten and psychomotor hypertonia were described as new forms of hypertonia intrinsic to particular psychoses and catatonic disorders. A series of astute clinical observations and experiments supported their independence from rigidity seen in Parkinson's disease. After World War II, motor disorders went out of fashion in psychiatry, with drug-induced parkinsonism becoming the prevailing explanation for all involuntary resistance to passive motion. With the 'forgetting' of paratonia and Gegenhalten, parkinsonism became the prevailing reading grid, such that the rediscovery of hypertonia in antipsychotic-naive patients at the turn of the 21st century is currently referred to as "spontaneous parkinsonism", implicitly suggesting intrinsic and drug-induced forms to be the same. Classical descriptive psychopathology gives a more nuanced view in suggesting two non-parkinsonian hypertonias: (i) locomotor hypertonia corresponds to Ernest Dupré's paratonia and Karl Kleist's reactive Gegenhalten; it is a dys-relaxation phenomenon that often needs to be activated. (ii) Psychomotor hypertonia is experienced as an admixture of assistance and resistance that partially overlaps with Kleist's spontaneous Gegenhalten, but was convincingly isolated by Henri Claude and Henri Baruk thanks to electromyogram recordings; psychomotor hypertonia is underpinned by "anticipatory contractions" of cortical origin, occurrence of which in phase or antiphase with the movement accounted for facilitation or opposition to passive motions. This century-old knowledge is not only of historical interest. Some results have recently been replicated in dementia and as now known to involve specific premotor systems.

Simultaneous T1 and T2 measurements using inversion recovery TrueFISP with principle component-based reconstruction, off-resonance correction, and multicomponent analysis.

PURPOSE: To improve the reconstruction quality for quantitative T1 and T2 measurements using the inversion recovery (IR) TrueFISP sequence and to demonstrate the potential for multicomponent analysis. METHODS: The iterative reconstruction method takes advantage of the high redundancy in the smooth exponential signals using principle component analysis (PCA). Multicomponent information is preserved and allows voxel-by-voxel computation of relaxation time spectra with an inverse Laplace transform. Off-resonance effects are analytically and numerically investigated and a correction approach is presented. RESULTS: Single-shot IR TrueFISP in vivo measurements on healthy volunteers demonstrate the improved reconstruction performance compared to a view sharing (k-space weighted image contrast [KWIC]) reconstruction. Especially, tissue components with short apparent relaxation times T1 * are not filtered out and can be identified in the relaxation time spectra. These components include myelin in the human brain (T1 * ≈ 130 ms) and extra cranial subcutaneous fat. CONCLUSION: The PCA-based reconstruction method improves the temporal accuracy and preserves multicomponent information. Spatially resolved relaxation time spectra can be obtained and allow the identification of tissue types with short, apparent relaxation times.

A mixed-effects, spatially varying coefficients model with application to multi-resolution functional magnetic resonance imaging data.

Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensures a relatively high signal-to-noise ratio. However, for pre-surgical functional magnetic resonance imaging analysis, where spatial accuracy is paramount, high-resolution functional magnetic resonance imaging may play an important role with its greater spatial resolution. High spatial resolution comes at the cost of a smaller signal-to-noise ratio. This begs the question as to whether we can leverage the higher signal-to-noise ratio of a standard functional magnetic resonance imaging study with the greater spatial accuracy of a high-resolution functional magnetic resonance imaging study in a pre-operative patient. To answer this question, we propose to regress the statistic image from a high resolution scan onto the statistic image obtained from a standard resolution scan using a mixed-effects model with spatially varying coefficients. We evaluate our model via simulation studies and we compare its performance with a recently proposed model that operates at a single spatial resolution. We apply and compare the two models on data from a patient awaiting tumor resection. Both simulation study results and the real data analysis demonstrate that our newly proposed model indeed leverages the larger signal-to-noise ratio of the standard spatial resolution scan while maintaining the advantages of the high spatial resolution scan.

Oncolytic H-1 Parvovirus Shows Safety and Signs of Immunogenic Activity in a First Phase I/IIa Glioblastoma Trial.

Oncolytic virotherapy may be a means of improving the dismal prognosis of malignant brain tumors. The rat H-1 parvovirus (H-1PV) suppresses tumors in preclinical glioma models, through both direct oncolysis and stimulation of anticancer immune responses. This was the basis of ParvOryx01, the first phase I/IIa clinical trial of an oncolytic parvovirus in recurrent glioblastoma patients. H-1PV (escalating dose) was administered via intratumoral or intravenous injection. Tumors were resected 9 days after treatment, and virus was re-administered around the resection cavity. Primary endpoints were safety and tolerability, virus distribution, and maximum tolerated dose (MTD). Progression-free and overall survival and levels of viral and immunological markers in the tumor and peripheral blood were also investigated. H-1PV treatment was safe and well tolerated, and no MTD was reached. The virus could cross the blood-brain/tumor barrier and spread widely through the tumor. It showed favorable pharmacokinetics, induced antibody formation in a dose-dependent manner, and triggered specific T cell responses. Markers of virus replication, microglia/macrophage activation, and cytotoxic T cell infiltration were detected in infected tumors, suggesting that H-1PV may trigger an immunogenic stimulus. Median survival was extended in comparison with recent meta-analyses. Altogether, ParvOryx01 results provide an impetus for further H-1PV clinical development.

Voxelwise distribution of acute ischemic stroke lesions in patients with newly diagnosed atrial fibrillation: Trigger of arrhythmia or only target of embolism?

OBJECTIVE: Atrial fibrillation (AF) is frequently detected after ischemic stroke for the first time, and brain regions involved in autonomic control have been suspected to trigger AF. We examined whether specific brain regions are associated with newly detected AF after ischemic stroke. METHODS: Patients with acute cerebral infarctions on diffusion-weighted magnetic resonance imaging were included in this lesion mapping study. Lesions were mapped and modeled voxelwise using Bayesian Spatial Generalised Linear Mixed Modeling to determine differences in infarct locations between stroke patients with new AF, without AF and with AF already known before the stroke. RESULTS: 582 patients were included (median age 68 years; 63.2% male). AF was present in 109/582 patients [(18.7%); new AF: 39/109 (35.8%), known AF: 70/109 (64.2%)]. AF patients had larger infarct volumes than patients without AF (mean: 29.7 ± 45.8 ml vs. 15.2 ± 35.1 ml; p<0.001). Lesions in AF patients accumulated in the right central middle cerebral artery territory. Increasing stroke size predicted progressive cortical but not pontine and thalamic involvement. Patients with new AF had more frequently lesions in the right insula compared to patients without AF when stroke size was not accounted for, but no specific brain region was more frequently involved after adjustment for infarct volume. Controlled for stroke size, left parietal involvement was less likely for patients with new AF than for those without AF or with known AF. CONCLUSIONS: In the search for brain areas potentially triggering cardiac arrhythmias infarct size should be accounted for. After controlling for infarct size, there is currently no evidence that ischemic stroke lesions of specific brain areas are associated with new AF compared to patients without AF. This challenges the neurogenic hypothesis of AF according to which a relevant proportion of new AF is triggered by ischemic brain lesions of particular locations.

Multimodal population brain imaging in the UK Biobank prospective epidemiological study.

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank.

Reduced white matter integrity in amateur boxers.

INTRODUCTION: Professional boxing can lead to chronic traumatic encephalopathy, a variant of traumatic brain injury (TBI). Its occurrence in amateur boxers is a matter of debate since amateur boxing is considered to be less harmful due to more strict regulations. However, several studies using different methodological approaches have revealed subtle signs of TBI even in amateurs. Diffusion tensor imaging (DTI) is sensitive to microscopic white matter changes and has been proven useful in TBI when routine MR imaging often is unrevealing. METHODS: DTI, with tract-based spatial statistics (TBSS) together with neuropsychological examination of executive functions and memory, was used to investigate a collective of 31 male amateur boxers and 31 age-matched controls as well as a subgroup of 19 individuals, respectively, who were additionally matched for intellectual performance (IQ). RESULTS: All participants had normal findings in neurological examination and conventional MR. Amateur boxers did not show deficits in neuropsychological tests when their IQ was taken into account. Fractional anisotropy was significantly reduced, while diffusivity measures were increased along central white matter tracts in the boxers group. These changes were in part associated with the number of fights. CONCLUSIONS: TBSS revealed widespread white matter disturbance partially related to the individual fighting history in amateur boxers. These findings closely resemble those in patients with accidental TBI and indicate similar histological changes in amateur boxers.

Pre-Surgical fMRI Data Analysis Using a Spatially Adaptive Conditionally Autoregressive Model.

Spatial smoothing is an essential step in the analysis of functional magnetic resonance imaging (fMRI) data. One standard smoothing method is to convolve the image data with a three-dimensional Gaussian kernel that applies a fixed amount of smoothing to the entire image. In pre-surgical brain image analysis where spatial accuracy is paramount, this method, however, is not reasonable as it can blur the boundaries between activated and deactivated regions of the brain. Moreover, while in a standard fMRI analysis strict false positive control is desired, for pre-surgical planning false negatives are of greater concern. To this end, we propose a novel spatially adaptive conditionally autoregressive model with variances in the full conditional of the means that are proportional to error variances, allowing the degree of smoothing to vary across the brain. Additionally, we present a new loss function that allows for the asymmetric treatment of false positives and false negatives. We compare our proposed model with two existing spatially adaptive conditionally autoregressive models. Simulation studies show that our model outperforms these other models; as a real model application, we apply the proposed model to the pre-surgical fMRI data of two patients to assess peri- and intra-tumoral brain activity.

Feasibility of the Combined Application of Navigated Probabilistic Fiber Tracking and Navigated Ultrasonography in Brain Tumor Surgery.

BACKGROUND: Surgical resection of intra-axial tumors is a challenging procedure because of indistinct tumor margins, infiltration, and displacement of white matter tracts surrounding the lesion. Hence, gross total tumor resection without causing new neurologic deficits is demanding, especially in tumor sites adjoining eloquent structures. Feasibility of the combination of navigated probabilistic fiber tracking to identify eloquent fiber pathways and navigated ultrasonography to control brain shift was tested. METHODS: Eleven patients with lesions adjacent to eloquent white matter structures (pyramidal tract, optic radiation and arcuate fascicle) were preoperatively subjected to magnetic resonance imaging including diffusion-weighted imaging on a 3-T magnetic resonance system (Trio [Siemens, Erlangen, Germany]). Probabilistic fiber tracking was performed using the tools of the FMRIB Software Library (FSL). Results of probabilistic fiber tracking and high-resolution anatomic images were integrated into the neuronavigation system Stealth Station (Medtronic, Minneapolis, Minnesota, USA) together with the navigated ultrasonography (SonoNav [Medtronic]). RESULTS: FSL-based probabilistic fiber tracking depicted the pyramidal tract, the optic radiation, and arcuate fascicle anatomically plausibly. Integration of the probabilistic fiber tracking into neuronavigation was technically feasible and allowed visualization of the reconstructed fiber pathways. Navigated ultrasonography controlled brain shift. CONCLUSIONS: Integration of probabilistic fiber tracking and navigated ultrasonography into intraoperative neuronavigation facilitated anatomic orientation during glioma resection. FSL-based probabilistic fiber tracking integrated sophisticated fiber tracking algorithms, including modeling of crossing fibers. Combination with navigated ultrasonography provided a three-dimensional estimation of intraoperative brain shift and, therefore, improved the reliability of neuronavigation.

Excavating Meckel's cave: Cavum-trigeminale-cephaloceles (CTCs).

BACKGROUND AND PURPOSE: Cavum-trigeminale-cephaloceles (CTCs) are rare lesions of Meckel's cave and the petrous apex. Despite distinctive imaging features, they are frequently mistaken for other petrous apex lesions. In contrast to many of these entities, CTCs do--when asymptomatic--not require any invasive work-up or even surgical excision. Since correct diagnosis has profound impact on clinical decision-making, we report on a series of CTCs with distinct imaging features and their important differential diagnoses. MATERIAL AND METHODS: We report a retrospective series of 5 patients with CTCs and the associated imaging features including the absence of diffusion restriction and solid contrast enhancement as well as their size, anatomical location with regard to adjacent structures and the remodeling or erosion of surrounding bony structures. RESULTS: Our series contains the largest CTC that has, to the best of our knowledge, been reported so far. It revealed a deep cervical extension and was initially mistaken for a branchial cleft cyst. Furthermore, we show that CTCs can erode or remodel important structures such as canalis nervi hypoglossi, canalis Vidiani, foramen rotundum, ovale, lacerum and spinosum without causing clinical symptoms. CONCLUSION: In contrast to previous reports in which asymptomatic CTC did not include critical structures such as the foramina rotundum, ovale, lacerum or spinosum or the hypoglossal or Vidian canal, we show that CTCs can be asymptomatic even when eroding or remodeling such clinically important structures. When extending below the skull base, CTCs are a rare differential diagnosis to cystic cervical lesions such as type II branchial cleft cysts.

Generating multiple contrasts using single-shot radial T1 sensitive and insensitive steady-state imaging.

PURPOSE: Recently, the (Resolution Enhanced-) T1 insensitive steady-state imaging (TOSSI) approach has been proposed for the fast acquisition of T2 -weighted images. This has been achieved by balanced steady-state free precession (bSSFP) imaging between unequally spaced inversion pulses. The purpose of this work is to present an extension of this technique, considerably increasing both the efficiency and possibilities of TOSSI. THEORY AND METHODS: A radial trajectory in combination with an appropriate view-sharing reconstruction is used. Because each projection traverses the contrast defining k-space center, several different contrasts can be extracted from a single-shot measurement. These contrasts include various T2 -weightings and T2 /T1 -weighting if an even number of inversion pulses is used, while an odd number allow the generation of several images with predefined tissue types cancelled. RESULTS: The approach is validated for brain and abdominal imaging at 3.0 Tesla. Results are compared with RE-TOSSI, bSSFP, and turbo spin-echo images and are shown to provide similar contrasts in a fraction of scan time. Furthermore, the potential utility of the approach is illustrated by images obtained from a brain tumor patient. CONCLUSION: Radial T1 sensitive and insensitive steady-state imaging is able to generate multiple contrasts out of one single-shot measurement in a short scan time.

Combined acquisition technique (CAT) for neuroimaging of multiple sclerosis at low specific absorption rates (SAR).

PURPOSE: To compare a novel combined acquisition technique (CAT) of turbo-spin-echo (TSE) and echo-planar-imaging (EPI) with conventional TSE. CAT reduces the electromagnetic energy load transmitted for spin excitation. This radiofrequency (RF) burden is limited by the specific absorption rate (SAR) for patient safety. SAR limits restrict high-field MRI applications, in particular. MATERIAL AND METHODS: The study was approved by the local Medical Ethics Committee. Written informed consent was obtained from all participants. T2- and PD-weighted brain images of n = 40 Multiple Sclerosis (MS) patients were acquired by CAT and TSE at 3 Tesla. Lesions were recorded by two blinded, board-certificated neuroradiologists. Diagnostic equivalence of CAT and TSE to detect MS lesions was evaluated along with their SAR, sound pressure level (SPL) and sensations of acoustic noise, heating, vibration and peripheral nerve stimulation. RESULTS: Every MS lesion revealed on TSE was detected by CAT according to both raters (Cohen's kappa of within-rater/across-CAT/TSE lesion detection κCAT = 1.00, at an inter-rater lesion detection agreement of κLES = 0.82). CAT reduced the SAR burden significantly compared to TSE (p<0.001). Mean SAR differences between TSE and CAT were 29.0 (± 5.7) % for the T2-contrast and 32.7 (± 21.9) % for the PD-contrast (expressed as percentages of the effective SAR limit of 3.2 W/kg for head examinations). Average SPL of CAT was no louder than during TSE. Sensations of CAT- vs. TSE-induced heating, noise and scanning vibrations did not differ. CONCLUSION: T2-/PD-CAT is diagnostically equivalent to TSE for MS lesion detection yet substantially reduces the RF exposure. Such SAR reduction facilitates high-field MRI applications at 3 Tesla or above and corresponding protocol standardizations but CAT can also be used to scan faster, at higher resolution or with more slices. According to our data, CAT is no more uncomfortable than TSE scanning.

Limbic hyperconnectivity in the vegetative state.

OBJECTIVE: To investigate functional connectivity between the default mode network (DMN) and other networks in disorders of consciousness. METHODS: We analyzed MRI data from 11 patients in a vegetative state and 7 patients in a minimally conscious state along with age- and sex-matched healthy control subjects. MRI data analysis included nonlinear spatial normalization to compensate for disease-related anatomical distortions. We studied brain connectivity data from resting-state MRI temporal series, combining noninferential (independent component analysis) and inferential (seed-based general linear model) methods. RESULTS: In DMN hypoconnectivity conditions, a patient's DMN functional connectivity shifts and paradoxically increases in limbic structures, including the orbitofrontal cortex, insula, hypothalamus, and the ventral tegmental area. CONCLUSIONS: Concurrently with DMN hypoconnectivity, we report limbic hyperconnectivity in patients in vegetative and minimally conscious states. This hyperconnectivity may reflect the persistent engagement of residual neural activity in self-reinforcing neural loops, which, in turn, could disrupt normal patterns of connectivity.

Boosting BOLD fMRI by K-space density weighted echo planar imaging.

Functional magnetic resonance imaging (fMRI) has become a powerful and influential method to non-invasively study neuronal brain activity. For this purpose, the blood oxygenation level-dependent (BOLD) effect is most widely used. T2* weighted echo planar imaging (EPI) is BOLD sensitive and the prevailing fMRI acquisition technique. Here, we present an alternative to its standard Cartesian recordings, i.e. k-space density weighted EPI, which is expected to increase the signal-to-noise ratio in fMRI data. Based on in vitro and in vivo pilot measurements, we show that fMRI by k-space density weighted EPI is feasible and that this new acquisition technique in fact boosted spatial and temporal SNR as well as the detection of local fMRI activations. Spatial resolution, spatial response function and echo time were identical for density weighted and conventional Cartesian EPI. The signal-to-noise ratio gain of density weighting can improve activation detection and has the potential to further increase the sensitivity of fMRI investigations.

Combined acquisition technique (CAT) for high-field neuroimaging with reduced RF power.

OBJECT: Clinical 3 T MRI systems are rapidly increasing and MRI systems with a static field of 7 T or even more have been installed. The RF power deposition is proportional to the square of the static magnetic field strength and is characterized by the specific absorption rate (SAR). Therefore, there exist defined safety limits to avoid heating of the patient. Here, we describe a hybrid method to significantly reduce the SAR compared to a turbo-spin-echo (TSE) sequence. MATERIALS AND METHODS: We investigate the potential benefits of a combined acquisition technique (CAT) for high-field neuroimaging at 3 and 7 T. The TSE/EPI CAT experiments were performed on volunteers and patients and compared with standard TSE and GRASE protocols. Problems and solutions regarding T2 weighted CAT imaging are discussed. RESULTS: We present in vivo images with T2 and proton density contrast obtained on 3 and 7 T with significant SAR reduction (up to 60%) compared with standard TSE. Image quality is comparable to TSE but CAT shows fewer artifacts than a GRASE sequence. CONCLUSION: CAT is a promising candidate for neuroimaging at high fields up to 7 T. The SAR reduction allows one to shorten the waiting time between two excitations or to image more slices thereby reducing the overall measurement time.

A Bayesian non-parametric Potts model with application to pre-surgical FMRI data.

The Potts model has enjoyed much success as a prior model for image segmentation. Given the individual classes in the model, the data are typically modeled as Gaussian random variates or as random variates from some other parametric distribution. In this article, we present a non-parametric Potts model and apply it to a functional magnetic resonance imaging study for the pre-surgical assessment of peritumoral brain activation. In our model, we assume that the Z-score image from a patient can be segmented into activated, deactivated, and null classes, or states. Conditional on the class, or state, the Z-scores are assumed to come from some generic distribution which we model non-parametrically using a mixture of Dirichlet process priors within the Bayesian framework. The posterior distribution of the model parameters is estimated with a Markov chain Monte Carlo algorithm, and Bayesian decision theory is used to make the final classifications. Our Potts prior model includes two parameters, the standard spatial regularization parameter and a parameter that can be interpreted as the a priori probability that each voxel belongs to the null, or background state, conditional on the lack of spatial regularization. We assume that both of these parameters are unknown, and jointly estimate them along with other model parameters. We show through simulation studies that our model performs on par, in terms of posterior expected loss, with parametric Potts models when the parametric model is correctly specified and outperforms parametric models when the parametric model in misspecified.

A brain network processing the age of faces.

Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke's understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships.