Sound-Evoked Neural Activity in Normal-Hearing Tinnitus: Effects of Frequency and Stimulated Ear Side.

Tinnitus is a common phantom auditory percept believed to be related to plastic changes in the brain due to hearing loss. However, tinnitus can also occur in the absence of any clinical hearing loss. In this case, since there is no hearing loss, the mechanisms that drive plastic changes remain largely enigmatic. Previous studies showed subtle differences in sound-evoked brain activity associated with tinnitus in subjects with tinnitus and otherwise normal hearing, but the results are not consistent across studies. Here, we aimed to investigate these differences using monaural rather than binaural stimuli. Sound-evoked responses were measured using functional magnetic resonance imaging (MRI) in participants with and without tinnitus. All participants had clinically normal audiograms. The stimuli were pure tones with frequencies between 353 and 8000 Hz, presented monaurally. A Principal Component Analysis (PCA) of the response in the auditory cortex revealed no difference in tonotopic organization, which confirmed earlier studies. A GLM analysis showed hyperactivity in the lateral areas of the bilateral auditory cortex. Consistent with the tonotopic map, this hyperactivity mainly occurred in response to low stimulus frequencies. This may be related to hyperacusis. Furthermore, there was an interaction between stimulation side and tinnitus in the parahippocampus. This may reflect an interference between tinnitus and spatial orientation.

Subspace corrected relevance learning with application in neuroimaging.

In machine learning, data often comes from different sources, but combining them can introduce extraneous variation that affects both generalization and interpretability. For example, we investigate the classification of neurodegenerative diseases using FDG-PET data collected from multiple neuroimaging centers. However, data collected at different centers introduces unwanted variation due to differences in scanners, scanning protocols, and processing methods. To address this issue, we propose a two-step approach to limit the influence of center-dependent variation on the classification of healthy controls and early vs. late-stage Parkinson's disease patients. First, we train a Generalized Matrix Learning Vector Quantization (GMLVQ) model on healthy control data to identify a "relevance space" that distinguishes between centers. Second, we use this space to construct a correction matrix that restricts a second GMLVQ system's training on the diagnostic problem. We evaluate the effectiveness of this approach on the real-world multi-center datasets and simulated artificial dataset. Our results demonstrate that the approach produces machine learning systems with reduced bias - being more specific due to eliminating information related to center differences during the training process - and more informative relevance profiles that can be interpreted by medical experts. This method can be adapted to similar problems outside the neuroimaging domain, as long as an appropriate "relevance space" can be identified to construct the correction matrix.

Dynamic phase-locking states and personality in sub-acute mild traumatic brain injury: An exploratory study.

Research has shown that maladaptive personality characteristics, such as Neuroticism, are associated with poor outcome after mild traumatic brain injury (mTBI). The current exploratory study investigated the neural underpinnings of this process using dynamic functional network connectivity (dFNC) analyses of resting-state (rs) fMRI, and diffusion MRI (dMRI). Twenty-seven mTBI patients and 21 healthy controls (HC) were included. After measuring the Big Five personality dimensions, principal component analysis (PCA) was used to obtain a superordinate factor representing emotional instability, consisting of high Neuroticism, moderate Openness, and low Extraversion, Agreeableness, and Conscientiousness. Persistent symptoms were measured using the head injury symptom checklist at six months post-injury; symptom severity (i.e., sum of all items) was used for further analyses. For patients, brain MRI was performed in the sub-acute phase (~1 month) post-injury. Following parcellation of rs-fMRI using independent component analysis, leading eigenvector dynamic analysis (LEiDA) was performed to compute dynamic phase-locking brain states. Main patterns of brain diffusion were computed using tract-based spatial statistics followed by PCA. No differences in phase-locking state measures were found between patients and HC. Regarding dMRI, a trend significant decrease in fractional anisotropy was found in patients relative to HC, particularly in the fornix, genu of the corpus callosum, anterior and posterior corona radiata. Visiting one specific phase-locking state was associated with lower symptom severity after mTBI. This state was characterized by two clearly delineated communities (each community consisting of areas with synchronized phases): one representing an executive/saliency system, with a strong contribution of the insulae and basal ganglia; the other representing the canonical default mode network. In patients who scored high on emotional instability, this relationship was even more pronounced. Dynamic phase-locking states were not related to findings on dMRI. Altogether, our results provide preliminary evidence for the coupling between personality and dFNC in the development of long-term symptoms after mTBI.

A Framework for the Continuous Evaluation of 3D Motion Perception in Virtual Reality.

OBJECTIVE: We present a novel framework for the detection and continuous evaluation of 3D motion perception by deploying a virtual reality environment with built-in eye tracking. METHODS: We created a biologically-motivated virtual scene that involved a ball moving in a restricted Gaussian random walk against a background of 1/f noise. Sixteen visually healthy participants were asked to follow the moving ball while their eye movements were monitored binocularly using the eye tracker. We calculated the convergence positions of their gaze in 3D using their fronto-parallel coordinates and linear least-squares optimization. Subsequently, to quantify 3D pursuit performance, we employed a first-order linear kernel analysis known as the Eye Movement Correlogram technique to separately analyze the horizontal, vertical and depth components of the eye movements. Finally, we checked the robustness of our method by adding systematic and variable noise to the gaze directions and re-evaluating 3D pursuit performance. RESULTS: We found that the pursuit performance in the motion-through depth component was reduced significantly compared to that for fronto-parallel motion components. We found that our technique was robust in evaluating 3D motion perception, even when systematic and variable noise was added to the gaze directions. CONCLUSION: The proposed framework enables the assessment of 3D Motion perception by evaluating continuous pursuit performance through eye-tracking. SIGNIFICANCE: Our framework paves the way for a rapid, standardized and intuitive assessment of 3D motion perception in patients with various eye disorders.

Paracingulate Sulcus Length and Cortical Thickness in Schizophrenia Patients With and Without a Lifetime History of Auditory Hallucinations.

BACKGROUND: It has been theorized that hallucinations, a common symptom of schizophrenia, are caused by failures in reality monitoring. The paracingulate sulcus (PCS) has been implicated as a brain structure supporting reality monitoring with the absence or shorter length of PCS associated with an occurrence of hallucinations in schizophrenia. The absence or shorter length of PCS has been associated with an occurrence of hallucinations. There are inconsistent findings in the literature regarding the role of the asymmetry of this structure for hallucinations. Here, we investigated the length of the PCS and cortical thickness of surrounding structures in patients with a lifetime history of auditory verbal hallucinations (AVH). DESIGN: Seventy-seven patients and twenty-eight healthy controls (HC) underwent an anatomical MRI scan. PCS length and cortical thickness were estimated using Mango brain visualization and FreeSurfer, respectively. Patients with AVH (n = 45) and patients without AVH were compared (n = 32) to the controls. RESULTS: PCS length significantly differed between HC and patient groups (F(2,102) = 3.57, P = .032) in the left but not in the right sulcus. We found significantly longer PCS between HC and AVH group but no difference between patient groups. Similarly, we found significant thinning of cortical structures including structures surrounding anterior parts of PCS between HC and patients either in general or per group, but no significant differences were observed between patient groups. CONCLUSIONS: PCS length in the left hemisphere is shorter in schizophrenia patients with hallucinations as compared to HC subjects. The patient group without hallucinations was in between those 2 groups. Cortical thickness of neighboring areas of PCS is diminished in patient groups relative to the healthy comparison subjects. The role of lateralization and functional involvement of the PCS region in processes underlying hallucinations, such as reality monitoring, needs further clarification.

The C4EB study-Transvamix (10% THC / 5% CBD) to treat chronic pain in epidermolysis bullosa: A protocol for an explorative randomized, placebo controlled, and double blind intervention crossover study.

Patients with the genetic blistering skin condition epidermolysis bullosa (EB) report severe pain as a consequence of skin and mucous membrane lesions including blisters, wounds, and scars. Adequate symptom alleviation is not often achieved using conventional pharmacologic interventions. Finding novel approaches to pain care in EB is imperative to improve the quality of life of patients living with EB. There are several anecdotal reports on the use of cannabinoid-based medicines (CBMs) by EB patients to reduce the burden of symptoms. However, controlled clinical investigations assessing these reported effects are lacking. As the pain quality "unpleasantness" delineates EB pain, we hypothesize the modulation of affective pain processing in the brain by way of intervention with CBMs comprising the cannabinoids Δ-9-tetrahydrocannabinol and cannabidiol-objectified by functional magnetic resonance imaging (fMRI). The C4EB study is an investigator-initiated, single-centre, randomized, double-blind, placebo-controlled and crossover trial. Adult patients with the diagnosis epidermolysis bullosa, reporting chronic pain will be eligible to participate. Following baseline measurements, participants will be randomized to receive the sublingually administered interventions placebo and Transvamix® in forward or reversed orders, each for two weeks and separated by a washout. The primary outcome is the difference in numeric rating scale pain scores between grouped interventions, using affective descriptors within the Short-form McGill Pain Questionnaire-2. Secondary outcomes include pain self-efficacy, concomitant analgesic medication-use and adverse events. Additionally, fMRI will be employed to assess brain connectivity related to neuroanatomic pain circuits at baseline, placebo and Transvamix® interventions. The study was approved by the ethical committee at the University Medical Center of Groningen in the Netherlands. Results will be submitted for publication in a peer-reviewed journal. Trial registration number: Netherlands Trial Register: NL9347 (Acronym: C4EB).

Local neuroplasticity in adult glaucomatous visual cortex.

The degree to which the adult human visual cortex retains the ability to functionally adapt to damage at the level of the eye remains ill-understood. Previous studies on cortical neuroplasticity primarily focused on the consequences of foveal visual field defects (VFD), yet these findings may not generalize to peripheral defects such as occur in glaucoma. Moreover, recent findings on neuroplasticity are often based on population receptive field (pRF) mapping, but interpreting these results is complicated in the absence of appropriate control conditions. Here, we used fMRI-based neural modeling to assess putative changes in pRFs associated with glaucomatous VFD. We compared the fMRI-signals and pRF in glaucoma participants to those of controls with case-matched simulated VFD. We found that the amplitude of the fMRI-signal is reduced in glaucoma compared to control participants and correlated with disease severity. Furthermore, while coarse retinotopic structure is maintained in all participants with glaucoma, we observed local pRF shifts and enlargements in early visual areas, relative to control participants. These differences suggest that the adult brain retains some degree of local neuroplasticity. This finding has translational relevance, as it is consistent with VFD masking, which prevents glaucoma patients from noticing their VFD and seeking timely treatment.

Bayesian connective field modeling using a Markov Chain Monte Carlo approach.

The majority of neurons in the human brain process signals from neurons elsewhere in the brain. Connective Field (CF) modelling is a biologically-grounded method to describe this essential aspect of the brain's circuitry. It allows characterizing the response of a population of neurons in terms of the activity in another part of the brain. CF modelling translates the concept of the receptive field (RF) into the domain of connectivity by assessing, at the voxel level, the spatial dependency between signals in distinct cortical visual field areas. Thus, the approach enables to characterize the functional cortical circuitry of the human cortex. While already very useful, the present CF modelling approach has some intrinsic limitations due to the fact that it only estimates the model's explained variance and not the probability distribution associated with the estimated parameters. If we could resolve this, CF modelling would lend itself much better for statistical comparisons at the level of single voxels and individuals. This is important when trying to gain a detailed understanding of the neurobiology and pathophysiology of the visual cortex, notably in rare cases. To enable this, we present a Bayesian approach to CF modeling (bCF). Using a Markov Chain Monte Carlo (MCMC) procedure, it estimates the posterior probability distribution underlying the CF parameters. Based on this, bCF quantifies, at the voxel level, the uncertainty associated with each parameter estimate. This information can be used in various ways to increase confidence in the CF model predictions. We applied bCF to BOLD responses recorded in the early human visual cortex using 3T fMRI. We estimated both the CF parameters and their associated uncertainties and show they are only weakly correlated. Moreover, we show how bCF facilitates the use of effect size (beta) as a data-driven parameter that can be used to select the most reliable voxels for further analysis. Finally, to further illustrate the functionality gained by bCF, we apply it to perform a voxel-level comparison of a single, circular symmetric, Gaussian versus a Difference-of-Gaussian model. We conclude that our bCF framework provides a comprehensive tool to study human functional cortical circuitry in health and disease.

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder.

BACKGROUND AND OBJECTIVES: 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson's disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer's disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory. METHODS: We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories. RESULTS: The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman's rho =0.62, P=0.004). CONCLUSION: In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages.

Alzheimer's disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA.

BACKGROUND: 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer's disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. RESULTS: In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. CONCLUSION: rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.

Diffusion-derived parameters in lesions, peri-lesion and normal-appearing white matter in multiple sclerosis using tensor, kurtosis and fixel-based analysis.

Neuronal damage is the primary cause of long-term disability of multiple sclerosis (MS) patients. Assessment of axonal integrity from diffusion MRI parameters might enable better disease characterisation. 16 diffusion derived measurements from diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and fixel-based analysis (FBA) in lesions, peri-lesion and normal appearing white matter were investigated. Diffusion MRI scans of 11 MS patients were processed to generate DTI, DKI, and FBA images. Fractional anisotropy (FA) and fibre density (FD) were used to assess axonal integrity across brain regions. Subsequently, 359 lesions were identified, and lesion and peri-lesion segmentation was performed using structural T1w, T2w, T2w-FLAIR, and T1w post-contrast MRI. The segmentations were then used to extract 16 diffusion MRI parameters from lesion, peri-lesion, and contralateral normal appearing white matter (NAWM). The measurements for axonal integrity, DTI-FA, DKI-FA, FBA-FD, produced similar results. All diffusion MRI parameters were affected in lesions as compared to NAWM (p < 0.001), confirming loss of axonal integrity in lesions. In peri-lesions, most parameters, except FBA-FD, were also significantly different from NAWM, although the effect size was smaller than in lesions. The reduction in axonal integrity in peri-lesions, despite unaffected fibre density estimates, suggests an effect of Wallerian degeneration.

A psychophysical and neuroimaging analysis of genital hedonic sensation in men.

Current understanding of human genital-brain interactions relates primarily to neuroendocrine and autonomic control, whereas interactions during sexual stimulation remain largely unexplored. Here we present a systematic approach towards identifying how the human brain encodes sensory genital information. Using a validated affective touch paradigm and functional magnetic resonance imaging, we found that hedonic responses to discriminatory versus affective tactile stimulation were distinctly different for both penile shaft and forearm. This suggests that, as with other body sites, genital skin contains small diameter mechanoreceptive nerve fibres that signal pleasant touch. In the brain, secondary somatosensory cortex (S2) distinguished between affective and discriminative touch for the penile shaft, but not for the forearm. Frenulum stimulation induced the greatest reports of subjective pleasure and led to the greatest deactivation of the default-mode network. This study represents a first pass at investigating, in humans, the relationship between innervation of genital surfaces, hedonic feelings, and brain mechanisms, in a systematic way.

A resting-state fMRI pattern of spinocerebellar ataxia type 3 and comparison with 18F-FDG PET.

Spinocerebellar ataxia type 3 (SCA3) is a rare genetic neurodegenerative disease. The neurobiological basis of SCA3 is still poorly understood, and up until now resting-state fMRI (rs-fMRI) has not been used to study this disease. In the current study we investigated (multi-echo) rs-fMRI data from patients with genetically confirmed SCA3 (n = 17) and matched healthy subjects (n = 16). Using independent component analysis (ICA) and subsequent regression with bootstrap resampling, we identified a pattern of differences between patients and healthy subjects, which we coined the fMRI SCA3 related pattern (fSCA3-RP) comprising cerebellum, anterior striatum and various cortical regions. Individual fSCA3-RP scores were highly correlated with a previously published 18F-FDG PET pattern found in the same sample (rho = 0.78, P = 0.0003). Also, a high correlation was found with the Scale for Assessment and Rating of Ataxia scores (r = 0.63, P = 0.007). No correlations were found with neuropsychological test scores, nor with levels of grey matter atrophy. Compared with the 18F-FDG PET pattern, the fSCA3-RP included a more extensive contribution of the mediofrontal cortex, putatively representing changes in default network activity. This rs-fMRI identification of additional regions is proposed to reflect a consequence of the nature of the BOLD technique, enabling measurement of dynamic network activity, compared to the more static 18F-FDG PET methodology. Altogether, our findings shed new light on the neural substrate of SCA3, and encourage further validation of the fSCA3-RP to assess its potential contribution as imaging biomarker for future research and clinical use.

The effect of lesion filling on brain network analysis in multiple sclerosis using structural magnetic resonance imaging.

BACKGROUND: Graph theoretical network analysis with structural magnetic resonance imaging (MRI) of multiple sclerosis (MS) patients can be used to assess subtle changes in brain networks. However, the presence of multiple focal brain lesions might impair the accuracy of automatic tissue segmentation methods, and hamper the performance of graph theoretical network analysis. Applying "lesion filling" by substituting the voxel intensities of a lesion with the voxel intensities of nearby voxels, thus creating an image devoid of lesions, might improve segmentation and graph theoretical network analysis. This study aims to determine if brain networks are different between MS subtypes and healthy controls (HC) and if the assessment of these differences is affected by lesion filling. METHODS: The study included 49 MS patients and 19 HC that underwent a T1w, and T2w-FLAIR MRI scan. Graph theoretical network analysis was performed from grey matter fractions extracted from the original T1w-images and T1w-images after lesion filling. RESULTS: Artefacts in lesion-filled T1w images correlated positively with total lesion volume (r = 0.84, p < 0.001) and had a major impact on grey matter segmentation accuracy. Differences in sensitivity for network alterations were observed between original T1w data and after application of lesion filling: graph theoretical network analysis obtained from lesion-filled T1w images produced more differences in network organization in MS patients. CONCLUSION: Lesion filling might reduce variability across subjects resulting in an increased detection rate of network alterations in MS, but also induces significant artefacts, and therefore should be applied cautiously especially in individuals with higher lesions loads.

Imaging of neuroinflammation due to repetitive head injury in currently active kickboxers.

PURPOSE: Chronic traumatic encephalopathy refers to a neurodegenerative disease resulting from repetitive head injury of participants in contact sports. Similar to other neurodegenerative diseases, neuroinflammation is thought to play a role in the onset and progression of the disease. Limited knowledge is available regarding the neuroinflammatory consequences of repetitive head injury in currently active contact sports athletes. PET imaging of the 18-kDa translocator protein (TSPO) allows quantification of microglial activation in vivo, a marker of neuroinflammation. METHODS: Eleven rank A kickboxers and 11 age-matched controls underwent TSPO PET using [11C]-PK11195, anatomical MRI, diffusion tensor imaging, and neuropsychological testing. Relevant imaging parameters were derived and correlated with the outcomes of the neuropsychological testing. RESULTS: On a group level, no statistically significant differences were detected in non-displaceable binding potential (BPND) using PET. Individually, 3 kickboxers showed increased BPNDs in widespread regions of the brain without a correlation with other modalities. Increased FA was observed in the superior corona radiata bilaterally. DTI parameters in other regions did not differ between groups. CONCLUSION: Despite negative results on a group level, individual results suggest that neuroinflammation may be present as a consequence of repetitive head injury in active kickboxers. Future studies using a longitudinal design may determine whether the observed TSPO upregulation is related to the future development of neuropsychiatric symptoms.

Rapid Eye Movement Sleep Behavior Disorder: Abnormal Cardiac Image and Progressive Abnormal Metabolic Brain Pattern.

BACKGROUND: Isolated rapid eye movement sleep behavior disorder (iRBD) is prodromal for α-synucleinopathies. OBJECTIVE: The aim of this study was to determine whether pathological cardiac [123 I]meta-iodobenzylguanidine scintigraphy ([123 I]MIBG) is associated with progression of [18 F]fluorodeoxyglucose-positron emission tomography-based Parkinson's disease (PD)-related brain pattern (PDRP) expression in iRBD. METHODS: Seventeen subjects with iRBD underwent [18 F]fluorodeoxyglucose-positron emission tomography brain imaging twice ~3.6 years apart. In addition, [123 I]MIBG and [123 I]N-ω-fluoropropyl-2ß-carbomethoxy-3ß-(4-iodophenyl)nortropane single-photon emission computed tomography ([123 I]FP-CIT-SPECT) at baseline were performed. Olfactory, cognitive, and motor functions were tested annually. RESULTS: Twelve of 17 subjects had pathological [123 I]MIBG. At baseline, 6 of 12 of these expressed the PDRP (suprathreshold PDRP z score). At follow-up, 12 of 17 subjects had suprathreshold PDRP z scores, associated with pathological [123 I]MIBG in 92% and with pathological [123 I]FP-CIT-SPECT in 75%. Subjects with pathological [123 I]MIBG had higher PDRP z score change per year (P = 0.027). Three subjects phenoconverted to PD; all had pathological [123 I]MIBG and [123 I]FP-CIT-SPECT, suprathreshold baseline PDRP z scores, and hyposmia. CONCLUSIONS: Pathological [123 I]MIBG was associated with progressive and suprathreshold PDRP z scores at follow-up. Abnormal [123 I]MIBG likely identifies iRBD as prodromal PD earlier than pathological [123 I]FP-CIT-SPECT. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Depressive symptom trajectory following romantic relationship breakup and effects of rumination, neuroticism and cognitive control.

Studying individuals who recently experienced a romantic reltionship breakup allows us to investigate mood disturbances in otherwise healthy individuals. In our study, we aimed to identify distinct depressive symptom trajectories following breakup and investigate whether these trajectories relate to personality traits and cognitive control. Subjects (n = 87) filled out questionnaires (RRS-NL-EXT trait rumination and NEO-FFI neuroticism) and performed cognitive tasks (trail making test, Stroop task) during a period of 30 weeks. To identify distinct depressive symptom trajectories ('trajectory groups'), we performed K-means clustering on the consecutive (assessed every 2 weeks) Major Depression Inventory scores. This resulted in four trajectory groups; 'resilience', 'fast recovery', 'slow recovery' and 'chronic distress'. The 'slow recovery group' and the 'chronic distress group' were found to have higher neuroticism and trait rumination levels compared to the 'resilience group', and the 'chronic distress group' also had higher neuroticism levels than the 'fast recovery group'. Moreover, the 'chronic distress group' showed worse overall trail making test performance than the 'resilience group'. Taken together, our findings show that distinct patterns of depressive symptom severity can be observed following breakup and that personality traits and cognitive flexibility seem to play a role in these depressive symptom patterns.

Predictive masking of an artificial scotoma is associated with a system-wide reconfiguration of neural populations in the human visual cortex.

The visual brain has the remarkable capacity to complete our percept of the world even when the information extracted from the visual scene is incomplete. This ability to predict missing information based on information from spatially adjacent regions is an intriguing attribute of healthy vision. Yet, it gains particular significance when it masks the perceptual consequences of a retinal lesion, leaving patients unaware of their partial loss of vision and ultimately delaying diagnosis and treatment. At present, our understanding of the neural basis of this masking process is limited which hinders both quantitative modeling as well as translational application. To overcome this, we asked the participants to view visual stimuli with and without superimposed artificial scotoma (AS). We used fMRI to record the associated cortical activity and applied model-based analyzes to track changes in cortical population receptive fields and connectivity in response to the introduction of the AS. We found that throughout the visual field and cortical hierarchy, pRFs shifted their preferred position towards the AS border. Moreover, extrastriate areas biased their sampling of V1 towards sections outside the AS projection zone, thereby effectively masking the AS with signals from spared portions of the visual field. We speculate that the signals that drive these system-wide population modifications originate in extrastriate visual areas and, through feedback, also reconfigure the neural populations in the earlier visual areas.

Anosognosia in Amnestic Mild Cognitive Impairment Is Related to Diminished Hippocampal Volume Comparable to Alzheimer's Disease Dementia: Preliminary MRI Findings.

Although the presence of anosognosia in amnestic mild cognitive impairment (aMCI) may be predictive of conversion to Alzheimer's disease (AD), little is known about its neural correlates in AD and aMCI. Four different groups were compared using volumetric and diffusion magnetic resonance imaging metrics in regions of interest (hippocampus and cingulum cortex gray matter, cingulum bundle white matter): aMCI subjects with anosognosia (n = 6), aMCI subjects without anosognosia (n = 12), AD subjects with anosognosia (n = 6), and AD subjects without anosognosia (n = 9). aMCI subjects with anosognosia displayed a significantly lower gray matter density (GMD) in the bilateral hippocampus than aMCI subjects without anosognosia, which was accounted for by bilateral hippocampal differences. Furthermore, we identified that the mean hippocampal gray matter density of aMCI subjects with anosognosia was not statistically different than that of AD subjects. The groups of aMCI and AD subjects with anosognosia also displayed a lower GMD in the bilateral cingulum cortex compared to subjects without anosognosia, but these differences were not statistically significant. No statistically significant differences were found in the fractional anisotropy or mean diffusivity of the hippocampus or cingulum between subjects with and without anosognosia in aMCI or AD groups. While these findings are derived from a small population of subjects and are in need of replication, they suggest that anosognosia in aMCI might be a useful clinical marker to suspect brain changes associated with AD neuropathology.