Metal-insulator transition of spinless fermions coupled to dispersive optical bosons.

Including the previously ignored dispersion of phonons we revisit the metal-insulator transition problem in one-dimensional electron-phonon systems on the basis of a modified spinless fermion Holstein model. Using matrix-product-state techniques we determine the global ground-state phase diagram in the thermodynamic limit for the half-filled band case, and show that in particular the curvature of the bare phonon band has a significant effect, not only on the transport properties characterized by the conductance and the Luttinger liquid parameter, but also on the phase space structure of the model as a whole. While a downward curved (convex) dispersion of the phonons only shifts the Tomonaga-Luttinger-liquid to charge-density-wave quantum phase transition towards stronger EP coupling, an upward curved (concave) phonon band leads to a new phase-separated state which, in the case of strong dispersion, can even completely cover the charge-density wave. Such phase separation does not occur in the related Edwards fermion-boson model.

Deep brain stimulation of symptom-specific networks in Parkinson's disease.

Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson's disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient's symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.

Watching (natural) beauty boosts task performance: testing the nature-as-reward hypothesis.

In two online studies, we tested the "nature-as-reward hypothesis", which suggests that superior cognitive task performance following nature exposure reflects a general performance improvement, driven by the reward value of beautiful things. In both between-subjects experiments, participants viewed either beautiful or less beautiful images for 10 s, comprising beautiful mountain photos (vs. less beautiful mountain drawings) in Study 1 and beautiful fractals (vs. less beautiful pixelated images) in Study 2. Following image exposure, participants engaged in a ticking task requiring them to freely tick up to 200 boxes. Participants had to complete four (Study 1) or five (Study 2) of such ticking tasks, with each task being preceded by either a beautiful or less beautiful image. In Study 1, for a subset of participants the ticking task was framed as a game. We found that in Study 1, ticking declined over the ticking rounds when participants had viewed less beautiful line drawings of mountains, while ticking performance remained unchanged over the rounds after seeing beautiful mountain images. However, when the ticking task was framed as a game, there was no significant difference in ticking performance between the two beauty conditions over the four ticking rounds. In Study 2, participants ticked more boxes over all ticking rounds after viewing images of beautiful fractals compared to less beautiful pixelated images. In line with the nature-as-reward hypothesis, these findings show that brief exposures to beautiful (nature) images can motivate to work and that framing tasks as a game can attenuate this beauty advantage.

The effects of virtual nature exposure on pro-environmental behaviour.

Exposure to (virtual) natural environments may encourage people to care about environmental protection and to engage in pro-environmental behaviour. Previous research on this effect produced inconsistent results, suggesting that it may depend on the type of nature and behaviour under study. In the present study (N = 266), we investigated nature exposure effects on effortful pro-environmental behaviour in an online experiment. After watching pictures of either intact or destroyed natural environments, participants could exert voluntary extra efforts to generate real donations to an environmental organisation. In comparison to the intact nature condition, participants exerted significantly more effort for environmental protection after being exposed to pictures of destroyed nature. No clear differences were observed between the nature exposure conditions and a no-picture control condition. These findings illustrate the complexity of nature exposure effects and suggest that different types of nature exposure may differentially affect people's pro-environmental behaviour.

Feasibility of local field potential-guided programming for deep brain stimulation in Parkinson's disease: A comparison with clinical and neuro-imaging guided approaches in a randomized, controlled pilot trial.

BACKGROUND: Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for advanced Parkinson's disease (PD). Clinical outcomes after DBS can be limited by poor programming, which remains a clinically driven, lengthy and iterative process. Electrophysiological recordings in PD patients undergoing STN-DBS have shown an association between STN spectral power in the beta frequency band (beta power) and the severity of clinical symptoms. New commercially-available DBS devices now enable the recording of STN beta oscillations in chronically-implanted PD patients, thereby allowing investigation into the use of beta power as a biomarker for DBS programming. OBJECTIVE: To determine the potential advantages of beta-guided DBS programming over clinically and image-guided programming in terms of clinical efficacy and programming time. METHODS: We conducted a randomized, blinded, three-arm, crossover clinical trial in eight Parkinson's patients with STN-DBS who were evaluated three months after DBS surgery. We compared clinical efficacy and time required for each DBS programming paradigm, as well as DBS parameters and total energy delivered between the three strategies (beta-, clinically- and image-guided). RESULTS: All three programming methods showed similar clinical efficacy, but the time needed for programming was significantly shorter for beta- and image-guided programming compared to clinically-guided programming (p < 0.001). CONCLUSION: Beta-guided programming may be a useful and more efficient approach to DBS programming in Parkinson's patients with STN-DBS. It takes significantly less time to program than traditional clinically-based programming, while providing similar symptom control. In addition, it is readily available within the clinical DBS programmer, making it a valuable tool for improving current clinical practice.

Machine versus physician-based programming of deep brain stimulation in isolated dystonia: A feasibility study.

BACKGROUND: Deep brain stimulation of the internal globus pallidus effectively alleviates dystonia motor symptoms. However, delayed symptom control and a lack of therapeutic biomarkers and a single pallidal sweetspot region complicates optimal programming. Postoperative management is complex, typically requiring multiple, lengthy follow-ups with an experienced physician - an important barrier to widespread adoption in medication-refractory dystonia patients. OBJECTIVE: Here we prospectively tested the best machine-predicted programming settings in a dystonia cohort treated with GPi-DBS against the settings derived from clinical long-term care in a specialised DBS centre. METHODS: Previously, we reconstructed an anatomical map of motor improvement probability across the pallidal region using individual stimulation volumes and clinical outcomes in dystonia patients. We used this to develop an algorithm that tests in silico thousands of putative stimulation settings in de novo patients after reconstructing an individual, image-based anatomical model of electrode positions, and suggests stimulation parameters with the highest likelihood of optimal symptom control. To test real-life application, our prospective study compared results in 10 patients against programming settings derived from long-term care. RESULTS: In this cohort, dystonia symptom reduction was observed at 74.9 ± 15.3% with C-SURF programming as compared to 66.3 ± 16.3% with clinical programming (p < 0.012). The average total electrical energy delivered (TEED) was similar for both the clinical and C-SURF programming (262.0 µJ/s vs. 306.1 µJ/s respectively). CONCLUSION: Our findings highlight the clinical potential of machine-based programming in dystonia, which could markedly reduce the programming burden in postoperative management.

Distinct phenotypes of stimulation-induced dysarthria represent different cortical networks in STN-DBS.

BACKGROUND: Deep brain stimulation of the subthalamic nucleus is an effective treatment of Parkinson's disease, yet it is often associated with a general deterioration of speech intelligibility. Clustering the phenotypes of dysarthria has been proposed as a strategy to tackle these stimulation-induced speech problems. METHODS: In this study, we examine a cohort of 24 patients to test the real-life application of the proposed clustering and attempt to attribute the clusters to specific brain networks with two different approaches of connectivity analysis. RESULTS: Both our data-driven and hypothesis-driven approaches revealed strong connections of variants of stimulation-induced dysarthria to brain regions that are known actors of motor speech control. We showed a strong connection between the spastic dysarthria type and the precentral gyrus and supplementary motor area, prompting a possible disruption of corticobulbar fibers. The connection between the strained voice dysarthria and more frontal areas hints toward a deeper disruption of the motor programming of speech production. CONCLUSIONS: These results provide insights into the mechanism of stimulation-induced dysarthria in deep brain stimulation of the subthalamic nucleus and may guide reprogramming attempts for individual Parkinson's patients based on pathophysiological understanding of the affected networks.

The laboratory journey to become a decision engine: a roadmap for diagnostic transformation.

Laboratories and diagnostic departments are presiding over a massive amount of data they are failing to fully leverage it. Data is the new black gold of healthcare organizations and by extracting insights from it, laboratories could become true decision engines, able to drive action across healthcare. This opinion paper responds three fundamental questions: (1) Where are we (diagnostic parties)? Taking a look at the most significant trends and challenges in healthcare and shedding some light upon the status of diagnostics. (2) Where do we want to be? Reviewing the opportunities for digital health, its role in the healthcare of the future and providing inspiration about what success looks like. (3) What do we need to do? Explaining what Digital Health Solutions (DHS) from Abbott is doing in this regard. This will include information about how DHS can impact the Diagnosis Cycle and how to set a roadmap for laboratories and diagnostic organizations. Diagnosis Cycle means the different steps in the diagnosis process, from the beginning when a patient is seen by a clinician and some tests are ordered, until the results are reviewed by the clinician and the treatment, follow up or discharge is decided.

Behavioral paradigms for studying pro-environmental behavior: A systematic review.

In view of global environmental deterioration and climate change, researchers from multiple fields of the behavioral sciences examine the determinants of pro-environmental behavior. Research on pro-environmental behavior is dominated by the use of self-report measures, which relates to critical validity problems. Some of these problems can be addressed by studying consequential behavior in behavioral paradigms (i.e., systematically arranged situations of actual environmental relevance). However, pro-environmental behavior paradigms have been scattered across disciplines, and many researchers may not be aware of the wealth of available paradigms. The present review aims to acquaint researchers across disciplinary borders with the behavioral paradigms developed to study pro-environmental behavior in different domains. A systematic literature search revealed 99 ad hoc paradigms and five validated paradigms of pro-environmental behavior. I review how different authors have succeeded in implementing the consequences of pro-environmental behavior in standardized field, laboratory, or online situations, point to caveats in the use of behavioral paradigms, and illustrate how researchers can select a paradigm for their own research.

Potential Contributions of Behavior Analysis to Research on Pro-environmental Behavior.

Large parts of contemporary research on pro-environmental behavior focus on mechanistic explanations and mental constructs. Exclusive reliance on this approach may hinder the search for novel solutions to conceptual problems, more powerful methods, and innovative behavior change interventions. Theoretical diversity, on the other hand, can render a field adaptive in its responses to crises and impasses. Against this background, we describe the complementary approach of behavior analysis and its potential contributions to problems of contemporary research on pro-environmental behavior. Behavior analysis (1) provides a consistent account of phenomena that are difficult to reconcile with the mechanistic perspective, (2) redirects the spotlight to context, (3) provides a framework and methodology for assessing behavior with actual environmental impact, and (4) could inspire the development of new intervention techniques. Based on these contributions, we conclude that behavior analysis could substantially enrich research on pro-environmental behavior.

Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia.

Dystonia is a debilitating disease with few treatment options. One effective option is deep brain stimulation (DBS) to the internal pallidum. While cervical and generalized forms of isolated dystonia have been targeted with a common approach to the posterior third of the nucleus, large-scale investigations regarding optimal stimulation sites and potential network effects have not been carried out. Here, we retrospectively studied clinical results following DBS for cervical and generalized dystonia in a multicenter cohort of 80 patients. We model DBS electrode placement based on pre- and postoperative imaging and introduce an approach to map optimal stimulation sites to anatomical space. Second, we investigate which tracts account for optimal clinical improvements, when modulated. Third, we investigate distributed stimulation effects on a whole-brain functional connectome level. Our results show marked differences of optimal stimulation sites that map to the somatotopic structure of the internal pallidum. While modulation of the striatopallidofugal axis of the basal ganglia accounted for optimal treatment of cervical dystonia, modulation of pallidothalamic bundles did so in generalized dystonia. Finally, we show a common multisynaptic network substrate for both phenotypes in the form of connectivity to the cerebellum and somatomotor cortex. Our results suggest a brief divergence of optimal stimulation networks for cervical vs. generalized dystonia within the pallidothalamic loop that merge again on a thalamo-cortical level and share a common whole-brain network.

The Work for Environmental Protection Task: A consequential web-based procedure for studying pro-environmental behavior.

Some human behaviors have serious societal consequences, but these consequences tend to be neglected in online research on societally relevant behaviors. For example, human activities contribute to climate change and biodiversity loss, but pro-environmental behavior is often studied using inconsequential self-reports and hypothetical scenarios. Such measures can easily be administered online, but suffer from severe validity problems. To address these problems, we developed a multi-trial web-based procedure for the study of consequential pro-environmental behavior. On the Work for Environmental Protection Task (WEPT), participants can choose to exert voluntary extra efforts screening numerical stimuli in exchange for donations to an environmental organization. They thus have the opportunity to produce actual environmental benefits at actual behavioral costs (i.e., to show actual pro-environmental behavior). In a preregistered validation study (N = 209), we found WEPT performance to systematically vary with these consequences, that is, the implemented costs and benefits were large enough for participants to effectively take them into account. In addition, aggregated WEPT performance was found to be highly reliable and to be correlated to self-reports and objective observations of other pro-environmental behaviors and conceptually related measures. These findings support the validity of the WEPT as an online procedure for the study of actual pro-environmental behavior. We discuss how the WEPT can advance the experimental analysis of pro-environmental behavior, help to address problems of common-method variance in individual difference research, and be adapted for the consequential study of other societally relevant behaviors.

DIPS (Dystonia Image-based Programming of Stimulation: a prospective, randomized, double-blind crossover trial).

INTRODUCTION: Deep brain stimulation of the internal globus pallidus is an effective treatment for dystonia. However, there is a large variability in clinical outcome with up to 25% non-responders even in highly selected primary dystonia patients. In a large cohort of patients we recently demonstrated that the variable clinical outcomes of pallidal DBS for dystonia may result to a large degree by the exact location and stimulation volume within the pallidal region. Here we test a novel approach of programing based on these insights: we first defined probabilistic maps of anti-dystonic effects by aggregating individual electrode locations and volumes of tissue activated of > 80 patients collected in a multicentre effort. We subsequently modified the algorithms to be able to test all possible stimulation settings of de novo patients in silico based on the expected clinical outcome and thus potentially predict the best possible stimulation parameters for the individual patients. METHODS: Within the framework of a BMBF-funded study, this concept of a computer-based prediction of optimal stimulation parameters for patients with dystonia will be tested in a randomized, controlled crossover study. The main parameter for clinical efficacy and primary endpoint is based on the blinded physician rating of dystonia severity reflected by Clinical Dystonia Rating Scales for both interventions (best clinical settings and model predicted settings) after 4 weeks of continuous stimulation. The primary endpoint is defined as "successful treatment with model predicted settings" (yes or no). The value is "yes" if the motor symptoms with model predicted settings are equal or better (tolerance 5% of absolute difference in percentages) to clinical settings. Secondary endpoints will include measures of quality of life, calculated energy consumption of the neurostimulation system and physician time for programming. PERSPECTIVE: We envision, that computer-guided deep brain stimulation programming in silico might provide optimal stimulation settings for patients with dystonia without the burden of months of programming sessions. The study protocol is designed to evaluate which programming method is more effective in controlling motor symptom severity and improving quality of life in dystonia (best clinical settings and model predicted settings). Trial registration Registered with ClinicalTrials.gov on Oct 27, 2021 (NCT05097001).

Predicting Outcome in a Cohort of Isolated and Combined Dystonia within Probabilistic Brain Mapping.

BACKGROUND: Probabilistic brain mapping is a promising tool to estimate the expected benefit of pallidal deep brain stimulation (GPi-DBS) in patients with isolated dystonia (IsoD). OBJECTIVES: To investigate the role of probabilistic mapping in combined dystonia (ComD). METHODS: We rendered the pallidal atlas and the volume of tissue activated (VTA) for a cohort of patients with IsoD (n = 20) and ComD (n = 10) that underwent GPi-DBS. The VTA was correlated with clinical improvement. Afterwards, each VTA was applied on the previously published probabilistic model (Reich et al., 2019). The correlation between predicted and observed clinical benefit was studied in a linear regression model. RESULTS: A good correlation between observed and predicted outcome was found for both patients with IsoD (n = 14) and ComD (n = 7) (r2 = 0.32; P < 0.05). In ComD, 42% of the variance in DBS response is explained by VTA-based outcome map. CONCLUSION: A probabilistic model would be helpful in clinical practice to circumvent unpredictable and less impressive motor results often found in ComD.

Reduced Programming Time and Strong Symptom Control Even in Chronic Course Through Imaging-Based DBS Programming.

Objectives: Deep brain stimulation (DBS) programming is based on clinical response testing. Our clinical pilot trial assessed the feasibility of image-guided programing using software depicting the lead location in a patient-specific anatomical model. Methods: Parkinson's disease patients with subthalamic nucleus-DBS were randomly assigned to standard clinical-based programming (CBP) or anatomical-based (imaging-guided) programming (ABP) in an 8-week crossover trial. Programming characteristics and clinical outcomes were evaluated. Results: In 10 patients, both programs led to similar motor symptom control (MDS-UPDRS III) after 4 weeks (medicationOFF/stimulationON; CPB: 18.27 ± 9.23; ABP: 18.37 ± 6.66). Stimulation settings were not significantly different, apart from higher frequency in the baseline program than CBP (p = 0.01) or ABP (p = 0.003). Time spent in a program was not significantly different (CBP: 86.1 ± 29.82%, ABP: 88.6 ± 29.0%). Programing time was significantly shorter (p = 0.039) with ABP (19.78 ± 5.86 min) than CBP (45.22 ± 18.32). Conclusion: Image-guided DBS programming in PD patients drastically reduces programming time without compromising symptom control and patient satisfaction in this small feasibility trial.

Deep Brain Stimulation for Tremor: Update on Long-Term Outcomes, Target Considerations and Future Directions.

Deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus is one of the main advanced neurosurgical treatments for drug-resistant tremor. However, not every patient may be eligible for this procedure. Nowadays, various other functional neurosurgical procedures are available. In particular cases, radiofrequency thalamotomy, focused ultrasound and radiosurgery are proven alternatives to DBS. Besides, other DBS targets, such as the posterior subthalamic area (PSA) or the dentato-rubro-thalamic tract (DRT), may be appraised as well. In this review, the clinical characteristics and pathophysiology of tremor syndromes, as well as long-term outcomes of DBS in different targets, will be summarized. The effectiveness and safety of lesioning procedures will be discussed, and an evidence-based clinical treatment approach for patients with drug-resistant tremor will be presented. Lastly, the future directions in the treatment of severe tremor syndromes will be elaborated.

Cognition and action: a latent variable approach to study contributions of executive functions to motor control in older adults.

Aging is associated with profound alterations in motor control that may be exacerbated by age-related executive functioning decline. Executive functions span multiple facets including inhibition (suppressing unwanted response tendencies), shifting (switching between cognitive operations), and updating (managing working memory content). However, comprehensive studies regarding the contributions of single facets of executive functioning to movement control in older adults are still lacking. A battery of nine neuropsychological tasks was administered to n = 92 older adults in order to derive latent factors for inhibition, shifting, and updating by structural equation modeling. A bimanual task was used to assess complex motor control. A sample of n = 26 young adults served as a control group to verify age-related performance differences. In older adults, structural equation models revealed that performance on the most challenging condition of the complex motor task was best predicted by the updating factor and by general executive functioning performance. These data suggest a central role for working memory updating in complex motor performance and contribute to our understanding of how individual differences in executive functioning relate to movement control in older adults.

A Multilab Replication of the Ego Depletion Effect.

There is an active debate regarding whether the ego depletion effect is real. A recent preregistered experiment with the Stroop task as the depleting task and the antisaccade task as the outcome task found a medium-level effect size. In the current research, we conducted a preregistered multilab replication of that experiment. Data from 12 labs across the globe (N = 1,775) revealed a small and significant ego depletion effect, d = 0.10. After excluding participants who might have responded randomly during the outcome task, the effect size increased to d = 0.16. By adding an informative, unbiased data point to the literature, our findings contribute to clarifying the existence, size, and generality of ego depletion.

Generation of Current Vortex by Spin Current in Rashba Systems.

Employing unbiased large-scale time-dependent density-matrix renormalization-group simulations, we demonstrate the generation of a charge-current vortex via spin injection in the Rashba system. The spin current is polarized perpendicular to the system plane and injected from an attached antiferromagnetic spin chain. We discuss the conversion between spin and orbital angular momentum in the current vortex that occurs because of the conservation of the total angular momentum and the spin-orbit interaction. This is in contrast to the spin Hall effect, in which the angular-momentum conservation is violated. Finally, we predict the electromagnetic field that accompanies the vortex with regard to possible future experiments.