Occlusion-related lateral connections stabilize kinetic depth stimuli through perceptual coupling

Local sensory information is often ambiguous forcing the brain to integrate spatiotemporally separated information for stable conscious perception. Lateral connections between clusters of similarly tuned neurons in the visual cortex are a potential neural substrate for the coupling of spatially separated visual information. Ecological optics suggests that perceptual coupling of visual information is particularly beneficial in occlusion situations. Here we present a novel neural network model and a series of human psychophysical experiments that can together explain the perceptual coupling of kinetic depth stimuli with activity-driven lateral information sharing in the far depth plane. Our most striking finding is the perceptual coupling of an ambiguous kinetic depth cylinder with a coaxially presented and disparity defined cylinder backside, while a similar frontside fails to evoke coupling. Altogether, our findings are consistent with the idea that clusters of similarly tuned far depth neurons share spatially separated motion information in order to resolve local perceptual ambiguities. The classification of far depth in the facilitation mechanism results from a combination of absolute and relative depth that suggests a functional role of these lateral connections in the perception of partially occluded objects

Validation of soft multipin dry EEG electrodes

Current developments towards multipin, dry electrodes in electroencephalography (EEG) are promising for applications in non-laboratory environments. Dry electrodes do not require the application of conductive gel, which mostly confines the use of gel EEG systems to the laboratory environment. The aim of this study is to validate soft, multipin, dry EEG electrodes by comparing their performance to conventional gel EEG electrodes. Fifteen healthy volunteers performed three tasks, with a 32-channel gel EEG system and a 32-channel dry EEG system: the 40 Hz Auditory Steady-State Response (ASSR), the checkerboard paradigm, and an eyes open/closed task. Within-subject analyses were performed to compare the signal quality in the time, frequency, and spatial domains. The results showed strong similarities between the two systems in the time and frequency domains, with strong correlations of the visual (ρ = 0.89) and auditory evoked potential (ρ = 0.81), and moderate to strong correlations for the alpha band during eye closure (ρ = 0.81–0.86) and the 40 Hz-ASSR power (ρ = 0.66–0.72), respectively. However, delta and theta band power was significantly increased, and the signal-to-noise ratio was significantly decreased for the dry EEG system. Topographical distributions were comparable for both systems. Moreover, the application time of the dry EEG system was significantly shorter (8 min). It can be concluded that the soft, multipin dry EEG system can be used in brain activity research with similar accuracy as conventional gel electrodes

Synchronization of the parkinsonian globus pallidus by gap junctions

We introduce pallidal gap junctional coupling as a possible mechanism for synchronization of the GPe after dopamine depletion. In a confocal imaging study, we show the presence of the neural gap junction protein Cx36 in the human GPe, including a possible remodeling process in PD patients. Dopamine has been shown to down-regulate the conductance of gap junctions in different regions of the brain [2,3], making dopamine depletion a possible candidate for increased influence of gap junctional coupling in PD

The effect of doorway characteristics on freezing of gait in Parkinson’s disease

Background: Freezing of gait is a debilitating symptom in Parkinson’s disease, during which a sudden motor block prevents someone from moving forward. Remarkably, doorways can provoke freezing. Most research has focused on the influence of doorway width, and little is known about other doorway characteristics influencing doorway freezing. Objective: Firstly, to provide guidelines on how to design doorways for people with freezing. Secondly, to compare people with doorway freezing to people without doorway freezing, and to explore the underlying mechanisms of doorway freezing. Methods: We designed a web-based, structured survey consisting of two parts. Part I (n = 171 responders), open to people with Parkinson’s disease with freezing in general, aimed to compare people with doorway freezing to people without doorway freezing. We explored underlying processes related to doorway freezing with the Gait-Specific Attention Profile (G-SAP), inquiring about conscious movement processes occurring during doorway passing. Part II (n = 60), open for people experiencing weekly doorway freezing episodes, inquired about the influence of specific doorway characteristics on freezing. Results: People with doorway freezing (69% of Part I) had higher freezing severity, longer disease duration, and scored higher on all sub scores of the G-SAP (indicating heightened motor, attentional, and emotional thoughts when passing through doorways) than people without doorway freezing. The main categories provoking doorway freezing were: dimensions of the door and surroundings, clutter around the door, lighting conditions, and automatic doors. Conclusion: We provide recommendations on how to maximally avoid freezing in a practical setting. Furthermore, we suggest that doorways trigger freezing based on visuomotor, attentional, and emotional processes.</p

Distance Estimation Is Influenced by Encoding Conditions

Background:\ud It is well established that foveating a behaviorally relevant part of the visual field improves localization performance as compared to the situation where the gaze is directed elsewhere. Reduced localization performance in the peripheral encoding conditions has been attributed to an eccentricity-dependent increase in positional uncertainty. It is not known, however, whether and how the foveal and peripheral encoding conditions can influence spatial interval estimation. In this study we compare observers' estimates of a distance between two co-planar dots in the condition where they foveate the two sample dots and where they fixate a central dot while viewing the sample dots peripherally.\ud \ud Methodology/Principal Findings:\ud Observers were required to reproduce, after a short delay, a distance between two sample dots based on a stationary reference dot and a movable mouse pointer. When both sample dots are foveated, we find that the distance estimation error is small but consistently increases with the dots-separation size. In comparison, distance judgment in peripheral encoding condition is significantly overestimated for smaller separations and becomes similar to the performance in foveal trials for distances from 10 to 16 degrees.\ud \ud Conclusions/Significance:\ud Although we find improved accuracy of distance estimation in the foveal condition, the fact that the difference is related to the reduction of the estimation bias present in the peripheral conditon, challenges the simple account of reducing the eccentricity-dependent positional uncertainty. Contrary to this, we present evidence for an explanation in terms of neuronal populations activated by the two sample dots and their inhibitory interactions under different visual encoding conditions. We support our claims with simulations that take into account receptive fields size differences between the two encoding conditions

Comparison of state-of-the-art deep learning architectures for detection of freezing of gait in Parkinson’s disease

Introduction: Freezing of gait (FOG) is one of the most debilitating motor symptoms experienced by patients with Parkinson’s disease (PD). FOG detection is possible using acceleration data from wearable sensors, and a convolutional neural network (CNN) is often used to determine the presence of FOG epochs. We compared the performance of a standard CNN for the detection of FOG with two more complex networks, which are well suited for time series data, the MiniRocket and the InceptionTime. Methods: We combined acceleration data of people with PD across four studies. The final data set was split into a training (80%) and hold-out test (20%) set. A fifth study was included as an unseen test set. The data were windowed (2 s) and five-fold cross-validation was applied. The CNN, MiniRocket, and InceptionTime models were evaluated using a receiver operating characteristic (ROC) curve and its area under the curve (AUC). Multiple sensor configurations were evaluated for the best model. The geometric mean was subsequently calculated to select the optimal threshold. The selected model and threshold were evaluated on the hold-out and unseen test set. Results: A total of 70 participants (23.7 h, 9% FOG) were included in this study for training and testing, and in addition, 10 participants provided an unseen test set (2.4 h, 11% FOG). The CNN performed best (AUC = 0.86) in comparison to the InceptionTime (AUC = 0.82) and MiniRocket (AUC = 0.76) models. For the CNN, we found a similar performance for a seven-sensor configuration (lumbar, upper and lower legs and feet; AUC = 0.86), six-sensor configuration (upper and lower legs and feet; AUC = 0.87), and two-sensor configuration (lower legs; AUC = 0.86). The optimal threshold of 0.45 resulted in a sensitivity of 77% and a specificity of 58% for the hold-out set (AUC = 0.72), and a sensitivity of 85% and a specificity of 68% for the unseen test set (AUC = 0.90). Conclusion: We confirmed that deep learning can be used to detect FOG in a large, heterogeneous dataset. The CNN model outperformed more complex networks. This model could be employed in future personalized interventions, with the ultimate goal of using automated FOG detection to trigger real-time cues to alleviate FOG in daily life.</p

Neural mechanisms of speed perception: transparent motion

Visual motion on the macaque retina is processed by direction- and speed-selective neurons in extrastriate middle temporal cortex (MT). There is strong evidence for a link between the activity of these neurons and direction perception. However, there is conflicting evidence for a link between speed selectivity of MT neurons and speed perception. Here we study this relationship by using a strong perceptual illusion in speed perception: when two transparently superimposed dot patterns move in opposite directions, their apparent speed is much larger than the perceived speed of a single pattern moving at that physical speed. Moreover, the sensitivity for speed discrimination is reduced for such bidirectional patterns. We first confirmed these behavioral findings in human subjects and extended them to a monkey subject. Second, we determined speed tuning curves of MT neurons to bidirectional motion and compared these to speed tuning curves for unidirectional motion. Consistent with previous reports, the response to bidirectional motion was often reduced compared with unidirectional motion at the preferred speed. In addition, we found that tuning curves for bidirectional motion were shifted to lower preferred speeds. As a consequence, bidirectional motion of some speeds typically evoked larger responses than unidirectional motion. Third, we showed that these changes in neural responses could explain changes in speed perception with a simple labeled line decoder. These data provide new insight into the encoding of transparent motion patterns and provide support for the hypothesis that MT activity can be decoded for speed perception with a labeled line model

Implied motion activation in cortical area MT can be explained by visual low-level features

To investigate form-related activity inmotion-sensitive cortical areas, we recorded cell responses to animate implied motion in macaque middle temporal (MT) and medial superior temporal (MST) cortex and investigated these areas using fMRI in humans. In the single-cell studies, we compared responses with static images of human or monkey figures walking or running left or right with responses to the same human and monkey figures standing or sitting still. We also investigated whether the view of the animate figure (facing left or right) that elicited the highest response was correlated with the preferred direction for moving random dot patterns. First, figures were presented inside the cell's receptive field. Subsequently, figures were presented at the fovea while a dynamic noise pattern was presented at the cell's receptive field location. The results show that MT neurons did not discriminate between figures on the basis of the implied motion content. Instead, response preferences for implied motion correlated with preferences for low-level visual features such as orientation and size. No correlation was found between the preferred view of figures implying motion and the preferred direction for moving random dot patterns. Similar findings were obtained in a smaller population of MST cortical neurons. Testing human MT+ responses with fMRI further corroborated the notion that low-level stimulus features might explain implied motion activation in human MT+. Together, these results suggest that prior human imaging studies demonstrating animate implied motion processing in area MT+ can be best explained by sensitivity for low-level features rather than sensitivity for the motion implied by animate figures.Publisher PDFPeer reviewe

Virtual reality distraction for patients to relieve pain and discomfort during colonoscopy

Contains fulltext : 220740.pdf (publisher's version ) (Open Access

Possible roles of neural gap junctions in Parkinson’s disease pathology

The pathology of Parkinson's disease (PD) is characterized by modified behavior of neuronal networks in the basal ganglia after depletion of dopamine. PD states show bursting neural activity and high synchronization among neurons as well as altered oscillations in local field potentials. These network modifications are thought to be directly related to PD motor symptoms such as tremor, akinesia and bradykinesia.\ud Computational models of the basal ganglia can reproduce physiological and pathological neuronal behavior depending on certain parameter values [1]. However, it is still a matter of debate what triggers and stabilizes the pathological behavior and how deep brain stimulation (DBS) influences it. In particular, computational models suffer from a lack of experimental data on structure and function. They commonly estimate the degree and course of chemical synapses and do not take electrical synapses (neuronal gap junctions) into account.\ud Gap junctions (GJs), constructed out of connexins (Cxs), are direct electrical connections between cells. In different parts of the brain, neuronal gap junctions have been shown to be able to lead to synchronization, bursting and oscillations. They are remodeled in a number of different diseases and can change their conductance under the influence of neurotransmitters such as dopamine [2]. Current research also demonstrated activity-dependent plasticity of GJs [3].\ud In our experiments, we look for the occurence of Cx36, a neuronal Cx, by immunohistochemistry and confocal microscopy in rat tissue of the subthalamic nucleus (STN), globus pallidus external segment (GPe) and internal segment (GPi). We found spots of Cx36 in all three nuclei at a level that is roughly comparable to the Cx36 level in the striatum, where coupling of neurons via gap junctions is well described in literature.\ud We investigated the impact of gap junctions in a computational model of the basal ganglia, the Rubin-Terman-Model [4] including STN, GPe and GPi. Gap junctions between neighboring neurons were implemented as ohmic resistors inside the three nuclei. At low conductances of the gap junctions, the network showed irregular (physiological) states. After uprising gap junction conductance, STN and GPe showed bursting and the firing rate of the GPi increased. In all neurons, synchronization was enhanced. These states are in high accordance with experimental measurements of neural activity in PD patients and animal models of PD.\ud Our results strongly suggest a role of neuronal gap junctions in PD pathology. The modulation of gap junctions by dopamine might be a candidate for the remodeling of oscillations, synchronization and bursting. A better understanding of these basic processes can in later stages lead to improved therapies such as refined stimulation protocols for DBS or novel medications. Currently we are extending our experiments to human post-mortem tissue of PD patients and controls. The aim is to quantify differences in Cx36 expression and adjust the computational model to these changes