Brain responses to self- and other- unfairness under resource distribution context: Meta-analysis of fMRI studies.

Under resource distribution context, individuals have a strong aversion to unfair treatment not only toward themselves but also toward others. However, there is no clear consensus regarding the commonality and distinction between these two types of unfairness. Moreover, many neuroimaging studies have investigated how people evaluate and respond to unfairness in the abovementioned two contexts, but the consistency of the results remains to be investigated. To resolve these two issues, we sought to summarize existing findings regarding unfairness to self and others and to further elucidate the neural underpinnings related to distinguishing evaluation and response processes through meta-analyses of previous neuroimaging studies. Our results indicated that both types of unfairness consistently activate the affective and conflict-related anterior insula (AI) and dorsal anterior cingulate cortex/supplementary motor area (dACC/SMA), but the activations related to unfairness to self appeared stronger than those related to others, suggesting that individuals had negative reactions to both unfairness and a greater aversive response toward unfairness to self. During the evaluation process, unfairness to self activated the bilateral AI, dACC, and right dorsolateral prefrontal cortex (DLPFC), regions associated with unfairness aversion, conflict, and cognitive control, indicating reactive, emotional and automatic responses. In contrast, unfairness to others activated areas associated with theory of mind, the inferior parietal lobule and temporoparietal junction (IPL-TPJ), suggesting that making rational judgments from the perspective of others was needed. During the response, unfairness to self activated the affective-related left AI and striatum, whereas unfairness to others activated cognitive control areas, the left DLPFC and the thalamus. This indicated that the former maintained the traits of automaticity and emotionality, whereas the latter necessitated cognitive control. These findings provide a fine-grained description of the common and distinct neurocognitive mechanisms underlying unfairness to self and unfairness to others. Overall, this study not only validates the inequity aversion model but also provides direct evidence of neural mechanisms for neurobiological models of fairness.

Prior-guided individualized thalamic parcellation based on local diffusion characteristics.

Comprising numerous subnuclei, the thalamus intricately interconnects the cortex and subcortex, orchestrating various facets of brain functions. Extracting personalized parcellation patterns for these subnuclei is crucial, as different thalamic nuclei play varying roles in cognition and serve as therapeutic targets for neuromodulation. However, accurately delineating the thalamic nuclei boundary at the individual level is challenging due to intersubject variability. In this study, we proposed a prior-guided parcellation (PG-par) method to achieve robust individualized thalamic parcellation based on a central-boundary prior. We first constructed probabilistic atlas of thalamic nuclei using high-quality diffusion MRI datasets based on the local diffusion characteristics. Subsequently, high-probability voxels in the probabilistic atlas were utilized as prior guidance to train unique multiple classification models for each subject based on a multilayer perceptron. Finally, we employed the trained model to predict the parcellation labels for thalamic voxels and construct individualized thalamic parcellation. Through a test-retest assessment, the proposed prior-guided individualized thalamic parcellation exhibited excellent reproducibility and the capacity to detect individual variability. Compared with group atlas registration and individual clustering parcellation, the proposed PG-par demonstrated superior parcellation performance under different scanning protocols and clinic settings. Furthermore, the prior-guided individualized parcellation exhibited better correspondence with the histological staining atlas. The proposed prior-guided individualized thalamic parcellation method contributes to the personalized modeling of brain parcellation.

On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites.

For decades, fMRI data have been used to search for biomarkers for patients with schizophrenia. Still, firm conclusions are yet to be made, which is often attributed to the high internal heterogeneity of the disorder. A promising way to disentangle the heterogeneity is to search for subgroups of patients with more homogeneous biological profiles. We applied an unsupervised multiple co-clustering (MCC) method to identify subtypes using functional connectivity data from a multisite resting-state data set. We merged data from two publicly available databases and split the data into a discovery data set (143 patients and 143 healthy controls (HC)) and an external test data set (63 patients and 63 HC) from independent sites. On the discovery data, we investigated the stability of the clustering toward data splits and initializations. Subsequently we searched for cluster solutions, also called "views," with a significant diagnosis association and evaluated these based on their subject and feature cluster separability, and correlation to clinical manifestations as measured with the positive and negative syndrome scale (PANSS). Finally, we validated our findings by testing the diagnosis association on the external test data. A major finding of our study was that the stability of the clustering was highly dependent on variations in the data set, and even across initializations, we found only a moderate subject clustering stability. Nevertheless, we still discovered one view with a significant diagnosis association. This view reproducibly showed an overrepresentation of schizophrenia patients in three subject clusters, and one feature cluster showed a continuous trend, ranging from positive to negative connectivity values, when sorted according to the proportions of patients with schizophrenia. When investigating all patients, none of the feature clusters in the view were associated with severity of positive, negative, and generalized symptoms, indicating that the cluster solutions reflect other disease related mechanisms.

Do time preferences predict diabetes outcomes? A combined survey and register-based study.

Identifying determinants of heterogeneity in health outcomes continues to be a focus in the health economic literature. In this study, we analyze whether time preferences predict health outcomes in individuals with type 1 diabetes (T1D) who use insulin pump therapy to manage their condition. We collect data on time preferences using a hypothetical matching task and estimate aggregate as well as individual-level discounting parameters using the exponential, hyperbolic, and quasi-hyperbolic discounting models. These parameters are then regressed against essential diabetes-related health outcomes obtained from registries and medical records, including glycemic control, kidney function, BMI, and number of hospital contacts. Our analyses indicate that all three discounting models fit the data equally well. Except for hospital contacts, we find robust evidence that impatience, as reflected by higher discounting, predicts worse health outcomes. Additionally, present bias is associated with worse kidney function. Our findings suggest that time preferences can explain some of the heterogeneity in health among individuals with T1D and call for increased attention on the role of time preferences in the design of disease management programs for individuals with chronic conditions.

Probabilistic PARAFAC2.

The Parallel Factor Analysis 2 (PARAFAC2) is a multimodal factor analysis model suitable for analyzing multi-way data when one of the modes has incomparable observation units, for example, because of differences in signal sampling or batch sizes. A fully probabilistic treatment of the PARAFAC2 is desirable to improve robustness to noise and provide a principled approach for determining the number of factors, but challenging because direct model fitting requires that factor loadings be decomposed into a shared matrix specifying how the components are consistently co-expressed across samples and sample-specific orthogonality-constrained component profiles. We develop two probabilistic formulations of the PARAFAC2 model along with variational Bayesian procedures for inference: In the first approach, the mean values of the factor loadings are orthogonal leading to closed form variational updates, and in the second, the factor loadings themselves are orthogonal using a matrix Von Mises-Fisher distribution. We contrast our probabilistic formulations to the conventional direct fitting algorithm based on maximum likelihood on synthetic data and real fluorescence spectroscopy and gas chromatography-mass spectrometry data showing that the probabilistic formulations are more robust to noise and model order misspecification. The probabilistic PARAFAC2, thus, forms a promising framework for modeling multi-way data accounting for uncertainty.

Evaluating the influence of anatomical accuracy and electrode positions on EEG forward solutions.

Generating realistic volume conductor models for forward calculations in electroencephalography (EEG) is not trivial and several factors contribute to the accuracy of such models, two of which are its anatomical accuracy and the accuracy with which electrode positions are known. Here, we investigate effects of anatomical accuracy by comparing forward solutions from SimNIBS, a tool which allows state-of-the-art anatomical modeling, with well-established pipelines in MNE-Python and FieldTrip. We also compare different ways of specifying electrode locations when digitized positions are not available such as transformation of measured positions from standard space and transformation of a manufacturer layout. Substantial effects of anatomical accuracy were seen throughout the entire brain both in terms of field topography and magnitude with SimNIBS generally being more accurate than the pipelines in MNE-Python and FieldTrip. Topographic and magnitude effects were particularly pronounced for MNE-Python which uses a three-layer boundary element method (BEM) model. We attribute these mainly to the coarse representation of the anatomy used in this model, in particular differences in skull and cerebrospinal fluid (CSF). Effects of electrode specification method were evident in occipital and posterior areas when using a transformed manufacturer layout whereas transforming measured positions from standard space generally resulted in smaller errors. We suggest modeling the anatomy of the volume conductor as accurately possible and we hope to facilitate this by making it easy to export simulations from SimNIBS to MNE-Python and FieldTrip for further analysis. Likewise, if digitized electrode positions are not available, a set of measured positions on a standard head template may be preferable to those specified by the manufacturer.

Dynamic involvement of premotor and supplementary motor areas in bimanual pinch force control.

Many activities of daily living require quick shifts between symmetric and asymmetric bimanual actions. Bimanual motor control has been mostly studied during continuous repetitive tasks, while little research has been carried out in experimental settings requiring dynamic changes in motor output generated by both hands. Here, we performed functional magnetic resonance imaging (MRI) while healthy volunteers performed a visually guided, bimanual pinch force task. This enabled us to map functional activity and connectivity of premotor and motor areas during bimanual pinch force control in different task contexts, requiring mirror-symmetric or inverse-asymmetric changes in discrete pinch force exerted with the right and left hand. The bilateral dorsal premotor cortex showed increased activity and effective coupling to the ipsilateral supplementary motor area (SMA) in the inverse-asymmetric context compared to the mirror-symmetric context of bimanual pinch force control while the SMA showed increased negative coupling to visual areas. Task-related activity of a cluster in the left caudal SMA also scaled positively with the degree of synchronous initiation of bilateral pinch force adjustments, irrespectively of the task context. The results suggest that the dorsal premotor cortex mediates increasing complexity of bimanual coordination by increasing coupling to the SMA while SMA provides feedback about motor actions to the sensory system.

Optimized flip angle schemes for the split acquisition of fast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging.

PURPOSE: The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T 2 $$ {}_2 $$ -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. METHODS: An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. RESULTS: Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. CONCLUSION: The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

Anterior cingulate glutamate levels associate with functional activation and connectivity during sensory integration in schizophrenia: a multimodal 1H-MRS and fMRI study.

BACKGROUND: Glutamatergic dysfunction has been implicated in sensory integration deficits in schizophrenia, yet how glutamatergic function contributes to behavioural impairments and neural activities of sensory integration remains unknown. METHODS: Fifty schizophrenia patients and 43 healthy controls completed behavioural assessments for sensory integration and underwent magnetic resonance spectroscopy (MRS) for measuring the anterior cingulate cortex (ACC) glutamate levels. The correlation between glutamate levels and behavioural sensory integration deficits was examined in each group. A subsample of 20 pairs of patients and controls further completed an audiovisual sensory integration functional magnetic resonance imaging (fMRI) task. Blood Oxygenation Level Dependent (BOLD) activation and task-dependent functional connectivity (FC) were assessed based on fMRI data. Full factorial analyses were performed to examine the Group-by-Glutamate Level interaction effects on fMRI measurements (group differences in correlation between glutamate levels and fMRI measurements) and the correlation between glutamate levels and fMRI measurements within each group. RESULTS: We found that schizophrenia patients exhibited impaired sensory integration which was positively correlated with ACC glutamate levels. Multimodal analyses showed significantly Group-by-Glutamate Level interaction effects on BOLD activation as well as task-dependent FC in a 'cortico-subcortical-cortical' network (including medial frontal gyrus, precuneus, ACC, middle cingulate gyrus, thalamus and caudate) with positive correlations in patients and negative in controls. CONCLUSIONS: Our findings indicate that ACC glutamate influences neural activities in a large-scale network during sensory integration, but the effects have opposite directionality between schizophrenia patients and healthy people. This implicates the crucial role of glutamatergic system in sensory integration processing in schizophrenia.

Associations between insulin pump self-management and HbA1c in type 1 diabetes.

AIMS: Insulin pump self-management is important for glycaemic outcomes. We aimed to investigate associations between self-management factors and HbA1c. METHODS: Adult insulin pump users with type 1 diabetes (n = 770) completed an online questionnaire. The latest HbA1c and demographics were extracted from national registries. Associations between HbA1c and self-management (use of advanced features, timing of infusion set change, timing of meal bolus, data-upload and pump settings adjustments) were investigated using backward selected linear regression models. RESULTS: Of the 699 responders eligible for this study, 60% were women; the median age and diabetes duration were 49 and 25 years, respectively. Significant associations with HbA1c were found for changing infusion set every 0-4 days relative to 5-10 days (-5 mmol/mol (-0.4%), p = 0.003), and for never/rarely missing a bolus (-6 mmol/mol (-0.5%), p < 0.001) relative to often missing a bolus. Timing insulin 10-15 min before meal relative to after meal start was also associated with lower HbA1c (-3 mmol/mol (-0.3%), p = 0.023). Self-adjusting pump settings showed the strongest association with lower HbA1c (-6 mmol/mol (-0.6%), p < 0.001) relative to health care professionals doing all adjustments. CONCLUSION: Self-adjusting insulin pump settings, optimal timing and few omissions of meal boluses, and timely change of infusion set are associated with lower HbA1c.

Uncovering the genetic profiles underlying the intrinsic organization of the human cerebellum.

The functional diversity of the human cerebellum is largely believed to be derived more from its extensive connections rather than being limited to its mostly invariant architecture. However, whether and how the determination of cerebellar connections in its intrinsic organization interact with microscale gene expression is still unknown. Here we decode the genetic profiles of the cerebellar functional organization by investigating the genetic substrates simultaneously linking cerebellar functional heterogeneity and its drivers, i.e., the connections. We not only identified 443 network-specific genes but also discovered that their co-expression pattern correlated strongly with intra-cerebellar functional connectivity (FC). Ninety of these genes were also linked to the FC of cortico-cerebellar cognitive-limbic networks. To further discover the biological functions of these genes, we performed a "virtual gene knock-out" by observing the change in the coupling between gene co-expression and FC and divided the genes into two subsets, i.e., a positive gene contribution indicator (GCI+) involved in cerebellar neurodevelopment and a negative gene set (GCI-) related to neurotransmission. A more interesting finding is that GCI- is significantly linked with the cerebellar connectivity-behavior association and many recognized brain diseases that are closely linked with the cerebellar functional abnormalities. Our results could collectively help to rethink the genetic substrates underlying the cerebellar functional organization and offer possible micro-macro interacted mechanistic interpretations of the cerebellum-involved high order functions and dysfunctions in neuropsychiatric disorders.

Lack of reproducibility of resting-state functional MRI findings in migraine with aura.

BACKGROUND: Several studies have applied resting-state functional MRI to examine whether functional brain connectivity is altered in migraine with aura patients. These studies had multiple limitations, including small sample sizes, and reported conflicting results. Here, we performed a large, cross-sectional brain imaging study to reproduce previous findings. METHODS: We recruited women aged 30-60 years from the nationwide Danish Twin Registry. Resting-state functional MRI of women with migraine with aura, their co-twins, and unrelated migraine-free twins was performed at a single centre. We carried out an extensive series of brain connectivity data analyses. Patients were compared to migraine-free controls and to co-twins. RESULTS: Comparisons were based on data from 160 patients, 30 co-twins, and 136 controls. Patients were similar to controls with regard to age, and several lifestyle characteristics. We replicated clear effects of age on resting-state networks. In contrast, we failed to detect any differences, and to replicate previously reported differences, in functional connectivity between migraine patients with aura and non-migraine controls or their co-twins in any of the analyses. CONCLUSION: Given the large sample size and the unbiased population-based design of our study, we conclude that women with migraine with aura have normal resting-state brain connectivity outside of migraine attacks.

Investigations of the subarachnoid space as a potential link between aura and headache in migraine: A case-control MRI study.

BACKGROUND: The connection between migraine aura and headache is poorly understood. Some patients experience migraine aura without headache, and patients with migraine aura with headache commonly experience milder headaches with age. The distance between the cerebral cortex and the overlying dura mater has been hypothesized to influence development of headache following aura. We tested this hypothesis by comparing approximated distances between visual cortical areas and overlying dura mater between female patients with migraine aura without headache and female patients with migraine aura with headache. METHODS: Twelve cases with migraine aura without headache and 45 age-matched controls with migraine aura with headache underwent 3.0 T MRI. We calculated average distances between the occipital lobes, between the calcarine sulci, and between the skull and visual areas V1, V2 and V3a. We also measured volumes of corticospinal fluid between the occipital lobes, between the calcarine sulci, and overlying visual areas V2 and V3a. We investigated the relationship between headache status, distances and corticospinal fluid volumes using conditional logistic regression. RESULTS: Distances between the occipital lobes, calcarine sulci and between the skull and V1, V2 and V3a did not differ between patients with migraine aura with headache and patients with migraine aura without headache. We found no differences in corticospinal fluid volumes between groups. CONCLUSION: We found no indication for a connection between visual migraine aura and headache based on cortico-cortical, cortex-to-skull distances, or corticospinal fluid volumes overlying visual cortical areas. Longitudinal studies with imaging sequences optimized for measuring the cortico-dural distance and a larger sample of patients are needed to further investigate the hypothesis.

The Myelin Content of the Human Precentral Hand Knob Reflects Interindividual Differences in Manual Motor Control at the Physiological and Behavioral Level.

The primary motor cortex hand area (M1HAND) and adjacent dorsal premotor cortex (PMd) form the so-called motor hand knob in the precentral gyrus. M1HAND and PMd are critical for dexterous hand use and are densely interconnected via corticocortical axons, lacking a sharp demarcating border. In 24 young right-handed volunteers, we performed multimodal mapping to delineate the relationship between structure and function in the right motor hand knob. Quantitative structural magnetic resonance imaging (MRI) at 3 tesla yielded regional R1 maps as a proxy of cortical myelin content. Participants also underwent functional MRI (fMRI). We mapped task-related activation and temporal precision, while they performed a visuomotor synchronization task requiring visually cued abduction movements with the left index or little finger. We also performed sulcus-aligned transcranial magnetic stimulation of the motor hand knob to localize the optimal site (hotspot) for evoking a motor evoked potential (MEP) in two intrinsic hand muscles. Individual motor hotspot locations varied along the rostrocaudal axis. The more rostral the motor hotspot location in the precentral crown, the longer were corticomotor MEP latencies. "Hotspot rostrality" was associated with the regional myelin content in the precentral hand knob. Cortical myelin content also correlated positively with task-related activation of the precentral crown and temporal precision during the visuomotor synchronization task. Together, our results suggest a link among cortical myelination, the spatial cortical representation, and temporal precision of finger movements. We hypothesize that the myelination of cortical axons facilitates neuronal integration in PMd and M1HAND and, hereby, promotes the precise timing of movements.SIGNIFICANCE STATEMENT Here we used magnetic resonance imaging and transcranial magnetic stimulation of the precentral motor hand knob to test for a link among cortical myelin content, functional corticomotor representations, and manual motor control. A higher myelin content of the precentral motor hand knob was associated with more rostral corticomotor presentations, with stronger task-related activation and a higher precision of movement timing during a visuomotor synchronization task. We propose that a high precentral myelin content enables fast and precise neuronal integration in M1 (primary motor cortex) and dorsal premotor cortex, resulting in higher temporal precision during dexterous hand use. Our results identify the degree of myelination as an important structural feature of the neocortex that is tightly linked to the function and behavior supported by the cortical area.

Mapping cortico-subcortical sensitivity to 4 Hz amplitude modulation depth in human auditory system with functional MRI.

Temporal modulations in the envelope of acoustic waveforms at rates around 4 Hz constitute a strong acoustic cue in speech and other natural sounds. It is often assumed that the ascending auditory pathway is increasingly sensitive to slow amplitude modulation (AM), but sensitivity to AM is typically considered separately for individual stages of the auditory system. Here, we used blood oxygen level dependent (BOLD) fMRI in twenty human subjects (10 male) to measure sensitivity of regional neural activity in the auditory system to 4 Hz temporal modulations. Participants were exposed to AM noise stimuli varying parametrically in modulation depth to characterize modulation-depth effects on BOLD responses. A Bayesian hierarchical modeling approach was used to model potentially nonlinear relations between AM depth and group-level BOLD responses in auditory regions of interest (ROIs). Sound stimulation activated the auditory brainstem and cortex structures in single subjects. BOLD responses to noise exposure in core and belt auditory cortices scaled positively with modulation depth. This finding was corroborated by whole-brain cluster-level inference. Sensitivity to AM depth variations was particularly pronounced in the Heschl's gyrus but also found in higher-order auditory cortical regions. None of the sound-responsive subcortical auditory structures showed a BOLD response profile that reflected the parametric variation in AM depth. The results are compatible with the notion that early auditory cortical regions play a key role in processing low-rate modulation content of sounds in the human auditory system.

Tracking of rigid head motion during MRI using an EEG system.

PURPOSE: To demonstrate a novel method for tracking of head movements during MRI using electroencephalography (EEG) hardware for recording signals induced by native imaging gradients. THEORY AND METHODS: Gradient switching during simultaneous EEG-fMRI induces distortions in EEG signals, which depend on subject head position and orientation. When EEG electrodes are interconnected with high-impedance carbon wire loops, the induced voltages are linear combinations of the temporal gradient waveform derivatives. We introduce head tracking based on these signals (CapTrack) involving 3 steps: (1) phantom scanning is used to characterize the target sequence and a fast calibration sequence; (2) a linear relation between changes of induced signals and head pose is established using the calibration sequence; and (3) induced signals recorded during target sequence scanning are used for tracking and retrospective correction of head movement without prolonging the scan time of the target sequence. Performance of CapTrack is compared directly to interleaved navigators. RESULTS: Head-pose tracking at 27.5 Hz during echo planar imaging (EPI) was demonstrated with close resemblance to rigid body alignment (mean absolute difference: [0.14 0.38 0.15]-mm translation, [0.30 0.27 0.22]-degree rotation). Retrospective correction of 3D gradient-echo imaging shows an increase of average edge strength of 12%/-0.39% for instructed/uninstructed motion with CapTrack pose estimates, with a tracking interval of 1561 ms and high similarity to interleaved navigator estimates (mean absolute difference: [0.13 0.33 0.12] mm, [0.28 0.15 0.22] degrees). CONCLUSION: Motion can be estimated from recordings of gradient switching with little or no sequence modification, optionally in real time at low computational burden and synchronized to image acquisition, using EEG equipment already found at many research institutions.

Locus Coeruleus Shows a Spatial Pattern of Structural Disintegration in Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) causes a loss of neuromelanin-positive, noradrenergic neurons in the locus coeruleus (LC), which has been implicated in nonmotor dysfunction. OBJECTIVES: We used "neuromelanin sensitive" magnetic resonance imaging (MRI) to localize structural disintegration in the LC and its association with nonmotor dysfunction in PD. METHODS: A total of 42 patients with PD and 24 age-matched healthy volunteers underwent magnetization transfer weighted (MTw) MRI of the LC. The contrast-to-noise ratio of the MTw signal (CNRMTw ) was used as an index of structural LC integrity. We performed slicewise and voxelwise analyses to map spatial patterns of structural disintegration, complemented by principal component analysis (PCA). We also tested for correlations between regional CNRMTw and severity of nonmotor symptoms. RESULTS: Mean CNRMTw of the right LC was reduced in patients relative to controls. Voxelwise and slicewise analyses showed that the attenuation of CNRMTw was confined to the right mid-caudal LC and linked regional CNRMTw to nonmotor symptoms. CNRMTw attenuation in the left mid-caudal LC was associated with the orthostatic drop in systolic blood pressure, whereas CNRMTw attenuation in the caudal most portion of right LC correlated with apathy ratings. PCA identified a bilateral component that was more weakly expressed in patients. This component was characterized by a gradient in CNRMTw along the rostro-caudal and dorso-ventral axes of the nucleus. The individual expression score of this component reflected the overall severity of nonmotor symptoms. CONCLUSION: A spatially heterogeneous disintegration of LC in PD may determine the individual expression of specific nonmotor symptoms such as orthostatic dysregulation or apathy. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.

Flexible inclusion of dialogue about psychosocial aspects of life with type 1 diabetes in routine consultations: A study of a questionnaire-based dialogue tool to promote person-centred support.

AIMS: To explore (1) experiences among people with type 1 diabetes and diabetologists of using a questionnaire-based dialogue tool in routine consultations to identify and address psychosocial challenges and (2) experiences of person-centredness in this group compared with a group who did not use the tool. METHODS: In all, 42 people with type 1 diabetes (mean age 54 years, mean diabetes duration 31 years and 60% women) were interviewed and completed an evaluation questionnaire following a routine consultation with the use of a dialogue tool including PAID-5, WHO-5 and open-ended questions. A comparison group of 42 people with type 1 diabetes attending routine consultations without the use of dialogue tools completed evaluation questionnaires. All consultations were audio recorded. Diabetologists were interviewed after completing all test consultations. Interviews were analysed using thematic text condensation. Evaluation questionnaires were analysed using descriptive statistics, chi square tests and Student's two-sided t-tests. RESULTS: Most participants found questions in the dialogue tool relevant to discuss with the diabetologist, and two-thirds were satisfied with the time spent on that. Experiences of people with type 1 diabetes and diabetologists were related to three pathways: (1) the tool supported valuable conversations with the diabetologist, (2) conversations with the diabetologist were unchanged and (3) the tool derailed conversations. All participants reported high levels of person centredness; however, significantly more in the comparison group reported that the diabetologist made them feel at ease (80 vs. 55%) and discussed and planned specific changes with them (93 vs. 67%). CONCLUSION: A questionnaire-based dialogue tool in consultations can support the discussion of psychosocial issues of people with type 1 diabetes. However, flexible and tailored use of the dialogue tool is crucial as consultations may otherwise be derailed.

Ergodicity-breaking reveals time optimal decision making in humans.

Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To optimize wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing decision theories. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximize the time average growth of in-game wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations.

Altered empathy-related resting-state functional connectivity in patients with bipolar disorder.

Empathy is the ability to generate emotional responses (i.e., cognitive empathy) and to make cognitive inferences (i.e., affective empathy) to other people's emotions. Empirical evidence suggests that patients with bipolar disorder (BD) exhibit impairment in cognitive empathy, but findings on affective empathy are inconsistent. Few studies have examined the neural mechanisms of cognitive and affective empathy in patients with BD. In this study, we examined the empathy-related resting-state functional connectivity (rsFC) in BD patients. Thirty-seven patients with BD and 42 healthy controls completed the self-report Questionnaires of Cognitive and Affective Empathy (QCAE), the Yoni behavioural task, and resting-sate fMRI brain scans. Group comparison of empathic ability was conducted. The interactions between group and empathic ability on seed-based whole brain rsFC were examined. BD patients scored lower on the Online Simulation subscale of the QCAE and showed positive correlations between cognitive empathy and the rsFC of the dorsal Medial Prefrontal Cortex (dmPFC) with the lingual gyrus. The correlations between cognitive empathy and the rsFC of the temporal-parietal junction (TPJ) with the fusiform gyrus, the cerebellum and the parahippocampus were weaker in BD patients than that in healthy controls. These findings highlight the underlying neural mechanisms of empathy impairments in BD patients.