Post-operative deep brain stimulation assessment: Automatic data integration and report generation.

BACKGROUND: The gold standard for post-operative deep brain stimulation (DBS) parameter tuning is a monopolar review of all stimulation contacts, a strategy being challenged by recent developments of more complex electrode leads. OBJECTIVE: Providing a method to guide clinicians on DBS assessment and parameter tuning by automatically integrating patient individual data. METHODS: We present a fully automatic method for visualization of individual deep brain structures in relation to a DBS lead by combining precise electrode recovery from post-operative imaging with individual estimates of deep brain morphology utilizing a 7T-MRI deep brain atlas. RESULTS: The method was evaluated on 20 STN DBS cases. It demonstrated robust automatic creation of 3D-enabled PDF reports visualizing electrode to brain structure relations and proved valuable in detecting miss placed electrodes. DISCUSSION: Automatic DBS assessment is feasible and can conveniently provide clinicians with relevant information on DBS contact positions in relation to important anatomical structures

Competition-based model of pheromone component ratio detection in the moth

For some moth species, especially those closely interrelated and sympatric, recognizing a specific pheromone component concentration ratio is essential for males to successfully locate conspecific females. We propose and determine the properties of a minimalist competition-based feed-forward neuronal model capable of detecting a certain ratio of pheromone components independently of overall concentration. This model represents an elementary recognition unit for the ratio of binary mixtures which we propose is entirely contained in the macroglomerular complex (MGC) of the male moth. A set of such units, along with projection neurons (PNs), can provide the input to higher brain centres. We found that (1) accuracy is mainly achieved by maintaining a certain ratio of connection strengths between olfactory receptor neurons (ORN) and local neurons (LN), much less by properties of the interconnections between the competing LNs proper. An exception to this rule is that it is beneficial if connections between generalist LNs (i.e. excited by either pheromone component) and specialist LNs (i.e. excited by one component only) have the same strength as the reciprocal specialist to generalist connections. (2) successful ratio recognition is achieved using latency-to-first-spike in the LN populations which, in contrast to expectations with a population rate code, leads to a broadening of responses for higher overall concentrations consistent with experimental observations. (3) when longer durations of the competition between LNs were observed it did not lead to higher recognition accuracy

Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks.

Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of different control strategies. In this paper, we tackle this question with an extended epidemic SEIR model, informed by a socio-political classification of different interventions. First, we inquire the conceptual effect of mitigation parameters on the infection curve. Then, we illustrate the potential of our model to reproduce and explain empirical data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lockdown is an effective pandemic mitigation measure, a combination of social distancing and early contact tracing can achieve similar mitigation synergistically, while keeping lower isolation rates. This quantitative understanding can support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model

PaCER - A fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation

Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N = 44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.Andreas Husch’s work is funded by the Fonds National de la Recherch´e (FNR), Luxembourg, Grant AFR 5748689 and Jorge Goncalves’ is supported by FNR Grant CORE C14/BM/8231540. Mikkel V. Petersen’s work is funded by the Danish Parkinson Association

An active vesicle priming machinery suppresses axon regeneration upon adult CNS injury

Axons in the adult mammalian central nervous system fail to regenerate after spinal cord injury. Neurons lose their capacity to regenerate during development, but the intracellular processes underlying this loss are unclear. We found that critical components of the presynaptic active zone prevent axon regeneration in adult mice. Transcriptomic analysis combined with live-cell imaging revealed that adult primary sensory neurons downregulate molecular constituents of the synapse as they acquire the ability to rapidly grow their axons. Pharmacogenetic reduction of neuronal excitability stimulated axon regeneration after adult spinal cord injury. Genetic gain- and loss-of-function experiments uncovered that essential synaptic vesicle priming proteins of the presynaptic active zone, but not clostridial-toxin-sensitive VAMP-family SNARE proteins, inhibit axon regeneration. Systemic administration of Baclofen reduced voltage-dependent Ca2+ influx in primary sensory neurons and promoted their regeneration after spinal cord injury. These findings indicate that functional presynaptic active zones constitute a major barrier to axon regeneration

Residual biomass calculation from individual tree architecture using terrestrial laser scanner and ground-level measurements

Large quantity of residual biomass with possible energy and industrial end can be obtained from management operations of urban forests. The profitability of exploiting this resource is conditioned by the amount of existing biomass within urban community ecosystems. Prior research pointed out that residual biomass from Platanus hispanica and other tree species can be calculated from dendrometric parameters. In this study, two approaches have been analyzed: First, applicability of TLS was tested for residual biomass calculation from crown volume. In addition, traditional models for residual biomass prediction were developed from dendrometric parameters (tree height, crown diameter, and diameter at breast height). Next, a comparison between parameters obtained with both methodologies (standard methodologies vs TLS) was carried out. The results indicate a strong relationship (R2 = 0.906) between crown diameters and between total tree heights (R2 = 0.868). The crown volumes extracted from the TLS point cloud were calculated by 4 different methods: convex hull; convex hull by slices of 5 cm height in the XY plane; triangulation by XY flat sections, and voxel modeling. The highest accuracy was found when the voxel method was used for pruned biomass prediction (R2 = 0.731). The results revealed the potential of TLS data to determine dendrometric parameters and biomass yielded from pruning quitar of urban forestsFernández-Sarría, A.; Velázquez Martí, B.; Sajdak, M.; Martinez, L.; Estornell Cremades, J. (2013). Residual biomass calculation from individual tree architecture using terrestrial laser scanner and ground-level measurements. Computers and Electronics in Agriculture. 93:90-97. doi:10.1016/j.compag.2013.01.012S90979

Spiking Patterns and Their Functional Implications in the Antennal Lobe of the Tobacco Hornworm Manduca sexta

Bursting as well as tonic firing patterns have been described in various sensory systems. In the olfactory system, spontaneous bursts have been observed in neurons distributed across several synaptic levels, from the periphery, to the olfactory bulb (OB) and to the olfactory cortex. Several in vitro studies indicate that spontaneous firing patterns may be viewed as “fingerprints” of different types of neurons that exhibit distinct functions in the OB. It is still not known, however, if and how neuronal burstiness is correlated with the coding of natural olfactory stimuli. We thus conducted an in vivo study to probe this question in the OB equivalent structure of insects, the antennal lobe (AL) of the tobacco hornworm Manduca sexta. We found that in the moth's AL, both projection (output) neurons (PNs) and local interneurons (LNs) are spontaneously active, but PNs tend to produce spike bursts while LNs fire more regularly. In addition, we found that the burstiness of PNs is correlated with the strength of their responses to odor stimulation – the more bursting the stronger their responses to odors. Moreover, the burstiness of PNs was also positively correlated with the spontaneous firing rate of these neurons, and pharmacological reduction of bursting resulted in a decrease of the neurons' responsiveness. These results suggest that neuronal burstiness reflects a physiological state of these neurons that is directly linked to their response characteristics

Lead-DBS v3.0: Mapping Deep Brain Stimulation Effects to Local Anatomy and Global Networks.

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics