Theta frequency deep brain stimulation in the subthalamic nucleus improves working memory in Parkinson's disease.

Most research in Parkinson's disease focuses on improving motor symptoms. Yet, up to 80% of patients present with non-motor symptoms that often have a large impact on patients' quality of life. Impairment in working memory, a fundamental cognitive process, is common in Parkinson's disease. While deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms in Parkinson's disease, its impact on cognitive functions is less well studied. Here, we examine the effect of DBS in the theta, beta, low and high gamma frequency on working memory in 20 Parkinson's disease patients with bilateral STN-DBS. A linear mixed effects model demonstrates that STN-DBS in the theta frequency improves working memory performance. This effect is frequency-specific and was absent for beta and gamma frequency stimulation. Further, this effect is specific to cognitive performance, as theta frequency DBS did not affect motor function. A non-parametric cluster-based permutation analysis of whole-brain normative structural connectivity shows that working memory enhancement by theta frequency stimulation is associated with higher connectivity between the stimulated subthalamic area and the right middle frontal gyrus. Again, this association is frequency- and task-specific. These findings highlight the potential of theta frequency STN-DBS as a targeted intervention to improve working memory in patients with Parkinson's disease.

German normative data with naming latencies for 283 action pictures and 600 action verbs.

Timed picture naming is a common psycholinguistic paradigm. In this task, participants are asked to label visually depicted objects or actions. Naming performance can be influenced by several picture and verb characteristics which demands fully characterized normative data. In this study, we provide a first German normative data set of picture and verb characteristics associated with a compilation of 283 freely available action pictures and 600 action verbs including naming latencies from 55 participants. We report standard measures for pictures and verbs such as name agreement indices, visual complexity, word frequency, word length, imageability and age of acquisition. In addition, we include less common parameters, such as orthographic Levenshtein distance, transitivity, reflexivity, morphological complexity, and motor content of the pictures and their associated verbs. We use repeated measures correlations in order to investigate associations between picture and word characteristics and linear mixed effects modeling for the prediction of naming latency. Our analyses reveal comparable results to previous studies in other languages, indicating high construct validity. We found that naming latency varied as a function of entropy of responses, word frequency and motor content of pictures and words. In summary, we provide first German normative data for action pictures and their associated verbs and identify variables influencing naming latency.

Increased prefrontal top-down control in older adults predicts motor performance and age-group association.

Bimanual motor control declines during ageing, affecting the ability of older adults to maintain independence. An important underlying factor is cortical atrophy, particularly affecting frontal and parietal areas in older adults. As these regions and their interplay are highly involved in bimanual motor preparation, we investigated age-related connectivity changes between prefrontal and premotor areas of young and older adults during the preparatory phase of complex bimanual movements using high-density electroencephalography. Generative modelling showed that excitatory inter-hemispheric prefrontal to premotor coupling in older adults predicted age-group affiliation and was associated with poor motor-performance. In contrast, excitatory intra-hemispheric prefrontal to premotor coupling enabled older adults to maintain motor-performance at the cost of lower movement speed. Our results disentangle the complex interplay in the prefrontal-premotor network during movement preparation underlying reduced bimanual control and the well-known speed-accuracy trade-off seen in older adults.

Characterization of information processing in the subthalamic area of Parkinson's patients.

Despite advances in symptomatic treatment options the pathomechanism of idiopathic Parkinson's disease (PD) remains poorly understood. Animal studies from recent years suggest pathological information processing in the basal ganglia network to be responsible for major movement deficits observed in patients, which, according to the information lesion hypothesis, might also explain the mechanism of action of deep brain stimulation (DBS). Using novel measures from information theory we characterize the information content, storage and transfer of intraoperatively recorded local field potentials (LFP) from the subthalamic area of n â€‹= â€‹19 PD patients undergoing surgery for implantation of electrodes for deep brain stimulation. In agreement with recent animal studies we demonstrate a significant positive correlation of subthalamic information content and movement deficits (ρ â€‹> â€‹0.48). Analysis of information storage reveals a larger processing memory in the zona incerta (ZI) than in the subthalamic nucleus (STN). We discuss possible implications for the efficiency of high frequency DBS. Further, we estimate the information transfer between forearm muscles and ZI/STN. Here, we show that the bidirectional information flow with respect to the STN is larger compared to the ZI. In contrast to the STN, however, the bidirectional information flow in the ZI is modulated, namely increased, by movement. The results of our study may help to understand the mechanism of action of deep brain stimulation and further explain recent studies claiming efficiency of ZI stimulation for certain motor symptoms.

Dopamine substitution alters effective connectivity of cortical prefrontal, premotor, and motor regions during complex bimanual finger movements in Parkinson's disease.

Bimanual coordination is impaired in Parkinson's disease (PD), affecting patients' quality of life. Besides dysfunction of the basal ganglia network, alterations of cortical oscillatory coupling, particularly between prefrontal and (pre-)motoric areas, are thought to underlie this impairment. Here, we studied 16 PD patients OFF and ON medication and age-matched healthy controls recording high-resolution electroencephalography (EEG) during performance of spatially coupled and uncoupled bimanual finger movements. Dynamic causal modeling (DCM) for induced responses was used to infer task-induced effective connectivity within a network comprising bilateral prefrontal cortex (PFC), lateral premotor cortex (lPM), supplementary motor area (SMA), and primary motor cortex (M1). Performing spatially coupled movements, excitatory left-hemispheric PFC to lPM coupling was significantly stronger in controls compared to unmedicated PD patients. Levodopa-induced enhancement of this connection correlated with increased movement accuracy. During performance of spatially uncoupled movements, PD patients OFF medication exhibited inhibitory connectivity from left PFC to SMA. Levodopa intake diminished these inhibitory influences and restored excitatory PFC to lPM coupling. This restoration, however, did not improve motor function. Concluding, our results indicate that lateralization of prefrontal to premotor connectivity in PD can be augmented by levodopa substitution and is of compensatory nature up to a certain extent of complexity.

Ageing changes effective connectivity of motor networks during bimanual finger coordination.

Bimanual finger coordination declines with age. However, relatively little is known about the neurophysiological alterations in the motor-system causing this decline. In the present study, we used 128-channel electroencephalography (EEG) to evaluate causal interactions of cortical, motor-related brain areas. Right-handed young and elderly subjects performed complex temporally and spatially coupled as well as temporally coupled and spatially uncoupled finger tappings. Employing dynamic causal modelling (DCM) for induced responses, we inferred task-induced effective connectivity within a core motor network comprising bilateral primary motor cortex (M1), lateral premotor cortex (lPM), supplementary motor area (SMA), and prefrontal cortex (PFC). Behavioural analysis showed significantly increased error rates and performance times for elderly subjects, confirming that motor functions decrease with ageing. Additionally, DCM analysis revealed that this age-related decline can be associated with specific alterations of interhemispheric and prefrontal to premotor connectivity. Young and elderly subjects exhibited inhibitory left to right M1-M1 coupling during performance of temporally and spatially coupled movements. Effects of ageing on interhemispheric connectivity particularly emerged when movements became spatially uncoupled. Here, elderly participants still expressed inhibitory left to right M1-M1 coupling, whereas no such connection was present in the young. Furthermore, ageing affected prefrontal to premotor connectivity. In all conditions, elderly subjects showed significant couplings from left PFC to left lPM. In contrast, young participants exhibited left PFC to SMA connections. These results demonstrate that (i) in spatially uncoupled movements interhemispheric M1-connectivity increases with age and (ii) support the idea that ageing is associated with enhanced lateral prefrontal to premotor coupling (PFC to lPM) and hypoactivation of a medial pathway (PFC to SMA) within the dominant hemisphere.

Behavior of highly diluted electrolytes in strong electric fields-prevention of alumina deposition on grading electrodes in HVDC transmission modules by CO2-induced pH-control.

Alumina deposition on platinum grading electrodes in high voltage direct current (HVDC) transmission modules is an unsolved problem that has been around for more than three decades. This is due to the unavoidable corrosion of aluminum heat sinks that causes severe damage to electrical power plants and losses in the range of a million Euro range per day in power outage. Simple experiments in a representative HV test setup showed that aluminates at concentrations even below 10(-8) mol L(-1) can deposit on anodes through neutralization by protons produced in de-ionized water (κ≤0.15 µS cm(-1)) at 20-35 kV (8 mA) per electrode. In this otherwise electrolyte-poor aqueous environment, the depositions are formed three orders of magnitude below the critical precipitation concentration at pH 7! In the presence of an inert electrolyte such as TMAT (tetramethylammonium-p-toluenesulfonate), at a concentration level just above that of the total dissolved aluminum, no deposition was observed. Deposition can be also prevented by doping with CO2 gas at a concentration level that is magnitudes lower than that of the dissolved aluminum. From an overview of aqueous aluminum chemistry, the mystery of the alumina deposition process and its inhibition by CO2 is experimentally resolved and fully explained by field accumulation and repulsion models in synergism with acid-base equilibria. The extraordinary size of the alumina depositions is accounted for in terms of proton tunneling through "hydrated" alumina, which is supported by quantum chemical calculations. As a consequence, pulse-purging with pure CO2 gas is presented as a technical solution to prevent the deposition of alumina.

Binaural acoustic stimulation in patients with Parkinson's disease.

Acoustic stimulation can improve motor symptoms in Parkinson's disease (PD) and might therefore represent a potential non-invasive treatment option. Scalp electroencephalography studies in healthy subjects indicate that specifically binaural beat stimulation (BBS) in the gamma frequency range is associated with synchronized cortical oscillations at 40 Hertz (Hz). Several studies suggest that oscillations in the gamma-frequency range (>30 Hz) serve a prokinetic function in PD. In this double-blind, randomized study, 25 PD patients were recruited. The study was conducted with (ON) and without dopaminergic medication (OFF). Each drug condition consisted of two phases (no stimulation and acoustic stimulation). The acoustic stimulation phase was divided into two blocks including BBS and conventional acoustic stimulation (CAS) as a control condition. For BBS, a modulated frequency of 35 Hz was used (left: 320 Hz; right: 355 Hz) and for CAS 340 Hz on both sides. We assessed effects on motor performance using Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and two validated commercially available portable devices (Kinesia ONE™ and Kinesia 360™) measuring motor symptoms such as dyskinesia, bradykinesia, and tremor. Repeated measures ANOVA revealed that BBS improved resting tremor on the side of the more affected limb in the OFF condition, as measured by wearables (F(2,48) = 3.61, p = 0.035). However, BBS did not exert a general positive effect on motor symptoms as assessed via MDS-UPDRS (F(2,48) = 1.00, p = 0.327). For CAS, we did not observe an improvement in specific symptoms but rather an overall beneficial effect on motor performance (MDS-UPDRS total score OFF medication: F(2,48) = 4.17, p = 0.021; wearable scores: F(2,48) = 2.46, p = 0.097). In this study, we found an improvement of resting tremor when applying BBS in the gamma frequency band OFF medication. Moreover, the positive effects of CAS underline the general positive potential for improvement of motor function by acoustically supported therapeutic approaches. However, more studies are needed to fully characterize the clinical relevance of BBS and to further optimize its ameliorating effects.

NoLiTiA: An Open-Source Toolbox for Non-linear Time Series Analysis.

In many scientific fields including neuroscience, climatology or physics, complex relationships can be described most parsimoniously by non-linear mechanics. Despite their relevance, many neuroscientists still apply linear estimates in order to evaluate complex interactions. This is partially due to the lack of a comprehensive compilation of non-linear methods. Available packages mostly specialize in only one aspect of non-linear time-series analysis and most often require some coding proficiency to use. Here, we introduce NoLiTiA, a free open-source MATLAB toolbox for non-linear time series analysis. In comparison to other currently available non-linear packages, NoLiTiA offers (1) an implementation of a broad range of classic and recently developed methods, (2) an implementation of newly proposed spatially and time-resolved recurrence amplitude analysis and (3) an intuitive environment accessible even to users with little coding experience due to a graphical user interface and batch-editor. The core methodology derives from three distinct fields of complex systems theory, including dynamical systems theory, recurrence quantification analysis and information theory. Besides established methodology including estimation of dynamic invariants like Lyapunov exponents and entropy-based measures, such as active information storage, we include recent developments of quantifying time-resolved aperiodic oscillations. In general, the toolbox will make non-linear methods accessible to the broad neuroscientific community engaged in time series processing.

A Waveform-Independent Measure of Recurrent Neural Activity.

Rhythmic neural activity, so-called oscillations, plays a key role in neural information transmission, processing, and storage. Neural oscillations in distinct frequency bands are central to physiological brain function, and alterations thereof have been associated with several neurological and psychiatric disorders. The most common methods to analyze neural oscillations, e.g., short-time Fourier transform or wavelet analysis, assume that measured neural activity is composed of a series of symmetric prototypical waveforms, e.g., sinusoids. However, usually, the models generating the signal, including waveform shapes of experimentally measured neural activity are unknown. Decomposing asymmetric waveforms of nonlinear origin using these classic methods may result in spurious harmonics visible in the estimated frequency spectra. Here, we introduce a new method for capturing rhythmic brain activity based on recurrences of similar states in phase-space. This method allows for a time-resolved estimation of amplitude fluctuations of recurrent activity irrespective of or specific to waveform shapes. The algorithm is derived from the well-established field of recurrence analysis, which, in comparison to Fourier-based analysis, is still very uncommon in neuroscience. In this paper, we show its advantages and limitations in comparison to short-time Fourier transform and wavelet convolution using periodic signals of different waveform shapes. Furthermore, we demonstrate its application using experimental data, i.e., intracranial and noninvasive electrophysiological recordings from the human motor cortex of one epilepsy patient and one healthy adult, respectively.

Microstructural alterations predict impaired bimanual control in Parkinson's disease.

Bimanual coordination is impaired in Parkinson's disease affecting patients' ability to perform activities of daily living and to maintain independence. Conveyance of information between cortical and subcortical areas is essential for bimanual coordination and relies on the integrity of cerebral microstructure. As pathological deposition of alpha-synuclein compromises microstructure in Parkinson's disease, we investigated the relationship between microstructural integrity and bimanual coordination using diffusion-weighted MRI in 23 patients with Parkinson's disease (mean age ± standard deviation: 56.0 ± 6.45 years; 8 female) and 26 older adults (mean age ± standard deviation: 58.5 ± 5.52 years). Whole-brain analysis revealed specific microstructural alterations between patients and healthy controls matched for age, sex, handedness, and cognitive status congruent with the literature and known Parkinson's disease pathology. A general linear model revealed distinct microstructural alterations associated with poor bimanual coordination in Parkinson's disease, corrected for multiple comparisons using a permutation-based approach. Integrating known functional topography, we conclude that distinct changes in microstructure cause an impediment of structures involved in attention, working memory, executive function, motor planning, motor control, and visual processing contributing to impaired bimanual coordination in Parkinson's disease.

Non-invasive vagus nerve stimulation in epilepsy patients enhances cooperative behavior in the prisoner's dilemma task.

The vagus nerve constitutes a key link between the autonomic and the central nervous system. Previous studies provide evidence for the impact of vagal activity on distinct cognitive processes including functions related to social cognition. Recent studies in animals and humans show that vagus nerve stimulation is associated with enhanced reward-seeking and dopamine-release in the brain. Social interaction recruits similar brain circuits to reward processing. We hypothesize that vagus nerve stimulation (VNS) boosts rewarding aspects of social behavior and compare the impact of transcutaneous VNS (tVNS) and sham stimulation on social interaction in 19 epilepsy patients in a double-blind pseudo-randomized study with cross-over design. Using a well-established paradigm, i.e., the prisoner's dilemma, we investigate effects of stimulation on cooperative behavior, as well as interactions of stimulation effects with patient characteristics. A repeated-measures ANOVA and a linear mixed-effects model provide converging evidence that tVNS boosts cooperation. Post-hoc correlations reveal that this effect varies as a function of neuroticism, a personality trait linked to the dopaminergic system. Behavioral modeling indicates that tVNS induces a behavioral starting bias towards cooperation, which is independent of the decision process. This study provides evidence for the causal influence of vagus nerve activity on social interaction.

Schizotypy in Parkinson's disease predicts dopamine-associated psychosis.

Psychosis is the most common neuropsychiatric side-effect of dopaminergic therapy in Parkinson's disease (PD). It is still unknown which factors determine individual proneness to psychotic symptoms. Schizotypy is a multifaceted personality trait related to psychosis-proneness and dopaminergic neurotransmission in healthy subjects. We investigated whether (1) PD patients exhibit lower schizotypy than controls and (2) dopamine-related neuropsychiatric side-effects can be predicted by higher schizotypy. In this cross-sectional study, we used the Oxford-Liverpool Inventory of Feelings and Experiences in 56 PD patients (12 women, mean ± sd age: 61 ± 11 years) receiving their usual dopaminergic medication and 32 age-matched healthy controls (n = 32; 18 women, mean ± sd age: 57 ± 6 years). We further compared schizotypy scores of patients with (n = 18, 32.1%) and without previously experienced psychosis. We found that patients exhibited lower schizotypy than controls. Further, patients with a history of psychosis exhibited higher schizotypy than patients without these symptoms. Using an information theoretic measure and a machine learning approach, we show that schizotypy yields the greatest predictive value for dopamine-associated hallucinations compared to other patient characteristics and disease related factors. Our results indicate an overlap between neural networks associated with schizotypy and the pathophysiology of PD and a relationship between schizotypy and psychotic side-effects of dopaminergic medication.

Trust your gut: vagal nerve stimulation in humans improves reinforcement learning.

Whereas the effect of vagal nerve stimulation on emotional states is well established, its effect on cognitive functions is still unclear. Recent rodent studies show that vagal activation enhances reinforcement learning and neuronal dopamine release. The influence of vagal nerve stimulation on reinforcement learning in humans is still unknown. Here, we studied the effect of transcutaneous vagal nerve stimulation on reinforcement learning in eight long-standing seizure-free epilepsy patients, using a well-established forced-choice reward-based paradigm in a cross-sectional, within-subject study design. We investigated vagal nerve stimulation effects on overall accuracy using non-parametric cluster-based permutation tests. Furthermore, we modelled sub-components of the decision process using drift-diffusion modelling. We found higher accuracies in the vagal nerve stimulation condition compared to sham stimulation. Modelling suggests a stimulation-dependent increase in reward sensitivity and shift of accuracy-speed trade-offs towards maximizing rewards. Moreover, vagal nerve stimulation was associated with increased non-decision times suggesting enhanced sensory or attentional processes. No differences of starting bias were detected for both conditions. Accuracies in the extinction phase were higher in later trials of the vagal nerve stimulation condition, suggesting a perseverative effect compared to sham. Together, our results provide first evidence of causal vagal influence on human reinforcement learning and might have clinical implications for the usage of vagal stimulation in learning deficiency.

Evaluation of Spike Sorting Algorithms: Application to Human Subthalamic Nucleus Recordings and Simulations.

An important prerequisite for the analysis of spike synchrony in extracellular recordings is the extraction of single-unit activity from the multi-unit signal. To identify single units, potential spikes are separated with respect to their potential neuronal origins ('spike sorting'). However, different sorting algorithms yield inconsistent unit assignments, which seriously influences subsequent spike train analyses. We aim to identify the best sorting algorithm for subthalamic nucleus recordings of patients with Parkinson's disease (experimental data ED). Therefore, we apply various prevalent algorithms offered by the 'Plexon Offline Sorter' and evaluate the sorting results. Since this evaluation leaves us unsure about the best algorithm, we apply all methods again to artificial data (AD) with known ground truth. AD consists of pairs of single units with different shape similarity embedded in the background noise of the ED. The sorting evaluation depicts a significant influence of the respective methods on the single unit assignments. We find a high variability in the sortings obtained by different algorithms that increases with single units shape similarity. We also find significant differences in the resulting firing characteristics. We conclude that Valley-Seeking algorithms produce the most accurate result if the exclusion of artifacts as unsorted events is important. If the latter is less important ('clean' data) the K-Means algorithm is a better option. Our results strongly argue for the need of standardized validation procedures based on ground truth data. The recipe suggested here is simple enough to become a standard procedure.

The influence of filtering and downsampling on the estimation of transfer entropy.

Transfer entropy (TE) provides a generalized and model-free framework to study Wiener-Granger causality between brain regions. Because of its nonparametric character, TE can infer directed information flow also from nonlinear systems. Despite its increasing number of applications in neuroscience, not much is known regarding the influence of common electrophysiological preprocessing on its estimation. We test the influence of filtering and downsampling on a recently proposed nearest neighborhood based TE estimator. Different filter settings and downsampling factors were tested in a simulation framework using a model with a linear coupling function and two nonlinear models with sigmoid and logistic coupling functions. For nonlinear coupling and progressively lower low-pass filter cut-off frequencies up to 72% false negative direct connections and up to 26% false positive connections were identified. In contrast, for the linear model, a monotonic increase was only observed for missed indirect connections (up to 86%). High-pass filtering (1 Hz, 2 Hz) had no impact on TE estimation. After low-pass filtering interaction delays were significantly underestimated. Downsampling the data by a factor greater than the assumed interaction delay erased most of the transmitted information and thus led to a very high percentage (67-100%) of false negative direct connections. Low-pass filtering increases the number of missed connections depending on the filters cut-off frequency. Downsampling should only be done if the sampling factor is smaller than the smallest assumed interaction delay of the analyzed network.

Deep Brain Stimulation of Hemiparkinsonian Rats with Unipolar and Bipolar Electrodes for up to 6 Weeks: Behavioral Testing of Freely Moving Animals.

Although the clinical use of deep brain stimulation (DBS) is increasing, its basic mechanisms of action are still poorly understood. Platinum/iridium electrodes were inserted into the subthalamic nucleus of rats with unilateral 6-OHDA-induced lesions of the medial forebrain bundle. Six behavioral parameters were compared with respect to their potential to detect DBS effects. Locomotor function was quantified by (i) apomorphine-induced rotation, (ii) initiation time, (iii) the number of adjusting steps in the stepping test, and (iv) the total migration distance in the open field test. Sensorimotor neglect and anxiety were quantified by (v) the retrieval bias in the corridor test and (vi) the ratio of migration distance in the center versus in the periphery in the open field test, respectively. In our setup, unipolar stimulation was found to be more efficient than bipolar stimulation for achieving beneficial long-term DBS effects. Performance in the apomorphine-induced rotation test showed no improvement after 6 weeks. DBS reduced the initiation time of the contralateral paw in the stepping test after 3 weeks of DBS followed by 3 weeks without DBS. Similarly, sensorimotor neglect was improved. The latter two parameters were found to be most appropriate for judging therapeutic DBS effects.

Quantum chemical investigations of the water exchange mechanism on [Al(III)(H2O)5(L)]²âº as a function of the donor strength of the anionic L.

Water exchange reactions of the complexes Al(H2O)5(L)]²âº·H2O for L = →OCN⁻, F⁻, CF3⁻, →NC⁻, →CN⁻, Cl⁻, Br⁻, H⁻, SH⁻, OH⁻, →NCO⁻, →NCS⁻, →SCN⁻, CF3CH2⁻, CH3⁻, Et⁻, i-Pr⁻ and t-but⁻, were studied by DFT calculations (B3LYP/6-311+G**). The reactions follow a dissociative (D) pathway for Al(H2O)5(L)]²âº·H2O to form the five-coordinate intermediate [Al(H2O)4L]²âº·2H2O for the weaker donor ligands of the series. On increasing the donor strength of L, the five-coordinate intermediate becomes significantly more stable than the reactant state. At this point there is a mechanistic changeover to an associative (A) pathway for [Al(H2O)4L]²âº·2H2O as reactant to form a six-coordinate intermediate Al(H2O)5(L)]²âº·H2O. For some of the anionic ligands L = → NC⁻, →CN⁻, Cl⁻, OH⁻ and →SCN⁻) the energy gap between the reactant and intermediate states is small, such that the water exchange mechanism lies in the boarder of dissociative and associative pathways. The water exchange process involves cis- and trans-orientated transition states to form the product state that is similar to the reactant state.