An investigation into the effective role of astrocyte in the hippocampus pattern separation process: A computational modeling study

A physiologically realistic three layer neuron-astrocyte network model is used to evaluate the biological mechanism in pattern separation. The innovative feature of the model is the use of a combination of three elements: neuron, interneuron and astrocyte. In the input layer, a pyramidal neuron receives input patterns from stimulus current, while in the middle layer there are two pyramidal neurons coupled with two inhibitory interneurons and an astrocyte. Finally, in the third layer, a pyramidal neuron produces the output of the model by integrating the output of two neurons from the middle layer resulting from inhibitory and excitatory connections among neurons, interneurons and the astrocyte. Results of computer simulations show that the neuron-astrocyte network within the hippocampal dentate gyrus can generate diverse, complex and different output patterns to given inputs. It is concluded that astrocytes within the dentate gyrus play an important role in the pattern separation process.

Modelling the loading mechanics of anterior cruciate ligament

BACKGROUND AND OBJECTIVES

The anterior cruciate ligament (ACL) plays a crucial role in knee stability and is the most commonly injured knee ligament. Although ACL loading patterns have been investigated previously, the interactions between knee loadings transmitted to ACL remain elusive. Understanding the loading mechanism of ACL during dynamic tasks is essential to prevent ACL injuries. Therefore, we propose a computational model that predicts the force applied to ACL in response to knee loading in three planes of motion.

METHODS

First, a three-dimensional (3D) computational model was developed and validated using available cadaveric experimental data to predict ACL force. This 3D model was then combined with a neuromusculoskeletal model of lower limb and used to estimate in vivo ACL forces during a standardised drop-landing task. The neuromusculoskeletal model utilised movement data collected from female participants during a dynamic task and calculated lower limb joint kinematics and kinetics, as well as muscle forces.

RESULTS

The total ACL force predicted by the 3D computational ACL force model was in good agreement with cadaveric data, as strong correlation (r² = 0.96 and P < 0.001), minimal bias, and narrow limits of agreement were observed. The combined model further illustrated that the ACL is primarily loaded through the sagittal plane, mainly due to muscle loading.

CONCLUSIONS

The proposed computational model is the first validated model that can provide an accessible tool to develop and test knee ACL injury prevention programs for people with normal ACL. This method can be extended to study the abnormal ACL upon the availability of relevant experimental data.

Robust emergence of sharply tuned place-cell responses in hippocampal neurons with structural and biophysical heterogeneities

Hippocampal pyramidal neurons sustain propagation of fast electrical signals and are electrotonically non-compact structures exhibiting cell-to-cell variability in their complex dendritic arborization. In this study, we demonstrate that sharp place-field tuning and several somatodendritic functional maps concomitantly emerge despite the presence of geometrical heterogeneities in these neurons. We establish this employing an unbiased stochastic search strategy involving thousands of models that spanned several morphologies and distinct profiles of dispersed synaptic localization and channel expression. Mechanistically, employing virtual knockout models (VKMs), we explored the impact of bidirectional modulation in dendritic spike prevalence on place-field tuning sharpness. Consistent with the prior literature, we found that across all morphologies, virtual knockout of either dendritic fast sodium channels or N-methyl-D-aspartate receptors led to a reduction in dendritic spike prevalence, whereas A-type potassium channel knockouts resulted in a non-specific increase in dendritic spike prevalence. However, place-field tuning sharpness was critically impaired in all three sets of VKMs, demonstrating that sharpness in feature tuning is maintained by an intricate balance between mechanisms that promote and those that prevent dendritic spike initiation. From the functional standpoint of the emergence of sharp feature tuning and intrinsic functional maps, within this framework, geometric variability was compensated by a combination of synaptic democracy, the ability of randomly dispersed synapses to yield sharp tuning through dendritic spike initiation, and ion-channel degeneracy. Our results suggest electrotonically non-compact neurons to be endowed with several degrees of freedom, encompassing channel expression, synaptic localization and morphological microstructure, in achieving sharp feature encoding and excitability homeostasis.

Computational Modeling and Analysis to Predict Intracellular Parasite Epitope Characteristics Using Random Forest Technique

BACKGROUND

In a new approach, computational methods are used to design and evaluate the vaccine. The aim of the current study was to develop a computational tool to predict epitope candidate vaccines to be tested in experimental models.

METHODS

This study was conducted in the School of Allied Medical Sciences, and Center for Research and Training in Skin Diseases and Leprosy, Tehran University of Medical Sciences, Tehran, Iran in 2018. The random forest which is a classifier method was used to design computer-based tool to predict immunogenic peptides. Data was used to check the collected information from the IEDB, UniProt, and AAindex database. Overall, 1,264 collected data were used and divided into three parts; 70% of the data was used to train, 15% to validate and 15% to test the model. Five-fold cross-validation was used to find optimal hyper parameters of the model. Common performance metrics were used to evaluate the developed model.

RESULTS

Twenty seven features were identified as more important using RF predictor model and were used to predict the class of peptides. The RF model improves the performance of predictor model in comparison with the other predictor models (AUC±SE: 0.925±0.029). Using the developed RF model helps to identify the most likely epitopes for further experimental studies.

CONCLUSION

The current developed random forest model is able to more accurately predict the immunogenic peptides of intracellular parasites.

Data-driven characterization of thermal models for powder-bed-fusion additive manufacturing

Computational modeling for additive manufacturing has proven to be a powerful tool to understand physical mechanisms, predict fabrication quality, and guide design and optimization. Varieties of models have been developed with different assumptions and purposes, and these models are sometimes difficult to choose from, especially for end-users, due to the lack of quantitative comparison and standardization. Thus, this study is focused on quantifying model uncertainty due to the modeling assumptions, and evaluating differences based on whether or not selected physical factors are incorporated. Multiple models with different assumptions, including a high-fidelity thermal-fluid flow model resolving individual powder particles, a low-fidelity heat transfer model simplifying the powder bed as a continuum material, and a semi-analytical thermal model using a point heat source model, were run with a variety of manufacturing process parameters. Experiments were performed on the National Institute of Standards and Technology (NIST) Additive Manufacturing Metrology Testbed (AMMT) to validate the models. A data analytics-based methodology was utilized to characterize the models to estimate the error distribution. The cross comparison of the simulation results reveals the remarkable influence of fluid flow, while the significance of the powder layer varies across different models. This study aims to provide guidance on model selection and corresponding accuracy, and more importantly facilitate the development of AM models.

Biomechanical musculoskeletal models of the cervical spine: A systematic literature review

BACKGROUND

As the work load has been shifting from heavy manufacturing to office work, neck disorders are increasing. However, most of the current cervical spine biomechanical models were created to simulate crash situations. Therefore, the biomechanics of cervical spine during daily living and occupational activities remain unknown. In this effort, cervical spine biomechanical models were systematically reviewed based upon different features including approach, biomechanical properties, and validation methods.

METHODS

The objective of this review was to systematically categorize cervical spine models and compare the underlying logic in order to identify voids in the literature.

FINDINGS

Twenty-two models met our selection criteria and revealed several trends: 1) The multi-body dynamics modeling approach, equipped for simulating impact situations were the most common technique; 2) Straight muscle lines of action, inverse dynamic/optimization muscle force calculation, Hill-type muscle model with only active component were typically used in the majority of neck models; and 3) Several models have attempted to validate their results by comparing their approach with previous studies, but mostly were unable to provide task-specific validation.

INTERPRETATION

EMG-driven dynamic model for simulating occupational activities, with accurate muscle geometry and force representation, and person- or task-specific validation of the model would be necessary to improve model fidelity.

Effects of ramped-frequency thalamic deep brain stimulation on tremor and activity of modeled neurons

OBJECTIVE

We conducted intraoperative measurements of tremor to quantify the effects of temporally patterned ramped-frequency DBS trains on tremor.

METHODS

Seven patterns of stimulation were tested in nine subjects with thalamic DBS for essential tremor: stimulation 'off', three ramped-frequency stimulation (RFS) trains from 130 → 50 Hz, 130 → 60 Hz, and 235 → 90 Hz, and three constant frequency stimulation (CFS) trains at 72, 82, and 130 Hz. The same patterns were applied to a computational model of the thalamic neural network.

RESULTS

Temporally patterned 130 → 60 Hz ramped-frequency trains suppressed tremor relative to stimulation 'off,' but 130 → 50 Hz, 130 → 60 Hz, and 235 → 90 Hz ramped-frequency trains were no more effective than constant frequency stimulation with the same mean interpulse interval (IPI). Computational modeling revealed that rhythmic burst-driver inputs to thalamus were masked during DBS, but long IPIs, concurrent with pauses in afferent cerebellar and cortical firing, allowed propagation of bursting activity. The mean firing rate of bursting-type model neurons as well as the firing pattern entropy of model neurons were both strongly correlated with tremor power across stimulation conditions.

CONCLUSION

Frequency-ramped DBS produced equivalent tremor suppression as constant frequency thalamic DBS. Tremor-related thalamic burst activity may result from burst-driver input, rather than by an intrinsic rebound mechanism.

SIGNIFICANCE

Ramping stimulation frequency may exacerbate thalamic burst firing by introducing consecutive pauses of increasing duration to the stimulation pattern.

Significant group-level hotspots found in deep brain regions during transcranial direct current stimulation (tDCS): A computational analysis of electric fields

OBJECTIVE

Transcranial direct current stimulation (tDCS) is a neuromodulation scheme that delivers a small current via electrodes placed on the scalp. The target is generally assumed to be under the electrode, but deep brain regions could also be involved due to the large current spread between the electrodes. This study aims to computationally evaluate if group-level hotspots exist in deep brain regions for different electrode montages.

METHODS

We computed the tDCS-generated electric fields (EFs) in a group of subjects using interindividual registration methods that permitted the projection of EFs from individual realistic head models (n = 18) to a standard deep brain region.

RESULTS

The spatial distribution and peak values (standard deviation of 14%) of EFs varied significantly. Nevertheless, group-level EF hotspots appeared in deep brain regions. The caudate had the highest field peaks in particular for F3-F4 montage (70% of maximum cortical EF), while other regions reach field peaks of 50%.

CONCLUSIONS

tDCS at deeper regions may include not only modulation via underlying cortical or subcortical circuits but also modulation of deep brain regions.

SIGNIFICANCE

The presented EF atlas in deep brain regions can be used to explain tDCS mechanism or select the most appropriate tDCS montage.

Searching for simple rules in Pseudomonas aeruginosa biofilm formation

OBJECTIVE

Living cells display complex and non-linear behaviors, especially when posed to environmental threats. Here, to understand the self-organizing cooperative behavior of a microorganism Pseudomonas aeruginosa, we developed a discrete spatiotemporal cellular automata model based on simple physical rules, similar to Conway's game of life.

RESULTS

The time evolution model simulations were experimentally verified for P. aeruginosa biofilm for both control and antibiotic azithromycin (AZM) treated condition. Our model suggests that AZM regulates the single cell motility, thereby resulting in delayed, but not abolished, biofilm formation. In addition, the model highlights the importance of reproduction by cell to cell interaction is key for biofilm formation. Overall, this work highlights another example where biological evolutionary complexity may be interpreted using rules taken from theoretical disciplines.

Spontaneous synaptic drive in detrusor smooth muscle: computational investigation and implications for urinary bladder function

The detrusor, a key component of the urinary bladder wall, is a densely innervated syncytial smooth muscle tissue. Random spontaneous release of neurotransmitter at neuromuscular junctions (NMJs) in the detrusor gives rise to spontaneous excitatory junction potentials (SEJPs). These sub-threshold passive signals not only offer insights into the syncytial nature of the tissue, their spatio-temporal integration is critical to the generation of spontaneous neurogenic action potentials which lead to focal contractions during the filling phase of the bladder. Given the structural complexity and the contractile nature of the tissue, electrophysiological investigations on spatio-temporal integration of SEJPs in the detrusor are technically challenging. Here we report a biophysically constrained computational model of a detrusor syncytium overlaid with spatially distributed innervation, using which we explored salient features of the integration of SEJPs in the tissue and the key factors that contribute to this integration. We validated our model against experimental data, ascertaining that observations were congruent with theoretical predictions. With the help of comparative studies, we propose that the amplitude of the spatio-temporally integrated SEJP is most sensitive to the inter-cellular coupling strength in the detrusor, while frequency of observed events depends more strongly on innervation density. An experimentally testable prediction arising from our study is that spontaneous release frequency of neurotransmitter may be implicated in the generation of detrusor overactivity. Set against histological observations, we also conjecture possible changes in the electrical activity of the detrusor during pathology involving patchy denervation. Our model thus provides a physiologically realistic, heuristic framework to investigate the spread and integration of passive potentials in an innervated syncytial tissue under normal conditions and in pathophysiology.

System-based approaches as prognostic tools for glioblastoma

BACKGROUND

The evasion of apoptosis is a hallmark of cancer. Understanding this process holistically and overcoming apoptosis resistance is a goal of many research teams in order to develop better treatment options for cancer patients. Efforts are also ongoing to personalize the treatment of patients. Strategies to confirm the therapeutic efficacy of current treatments or indeed to identify potential novel additional options would be extremely beneficial to both clinicians and patients. In the past few years, system medicine approaches have been developed that model the biochemical pathways of apoptosis. These systems tools incorporate and analyse the complex biological networks involved. For their successful integration into clinical practice, it is mandatory to integrate systems approaches with routine clinical and histopathological practice to deliver personalized care for patients.

RESULTS

We review here the development of system medicine approaches that model apoptosis for the treatment of cancer with a specific emphasis on the aggressive brain cancer, glioblastoma.

CONCLUSIONS

We discuss the current understanding in the field and present new approaches that highlight the potential of system medicine approaches to influence how glioblastoma is diagnosed and treated in the future.

Computational simulations of thrombolysis in acute stroke: Effect of clot size and location on recanalisation

Acute ischaemic stroke can be treated by intravenous thrombolysis whereby tissue plasminogen activator (tPA) is infused to dissolve clots that block blood supply to the brain. In this study, we aim to examine the influence of clot location and size on lysis pattern and recanalisation by using a recently developed computational modelling framework for thrombolysis under physiological flow conditions. An image-based patient-specific model is reconstructed which consists of the internal carotid bifurcation with the A1 segment of anterior cerebral arteries and M1 segment of middle cerebral arteries, and the M1 bifurcation containing the M2 segments. By varying the clot size and location, 7 scenarios are simulated mimicking thrombolysis of M1 and M2 occlusions. Our results show that initial breakthrough always occurs along the inner curvature of the occluded cerebral artery, due to prolonged tPA residence time in the recirculation zone. For a given occlusion site, lysis completion time appears to increase almost quadratically with the initial clot volume; whereas for a given clot volume, the simulated M2 occlusions take up to 30% longer for complete lysis compared to the corresponding M1 occlusions.

A particle-based model for endothelial cell migration under flow conditions

Endothelial cells (ECs) play a major role in the healing process following angioplasty to inhibit excessive neointima. This makes the process of EC healing after injury, in particular EC migration in a stented vessel, important for recovery of normal vessel function. In that context, we present a novel particle-based model of EC migration and validate it against in vitro experimental data. We have developed a particle-based model of EC migration under flow conditions in an in vitro vessel with obstacles. Cell movement in the model is a combination of random walks and directed movement along the local flow velocity vector. For model calibration, a set of experimental data for cell migration in a similarly shaped channel has been used. We have calibrated the model for a baseline case of a channel with no obstacles and then applied it to the case of a channel with ridges on the bottom surface, representative of stent strut geometry. We were able to closely reproduce the cell migration speed and angular distribution of their movement relative to the flow direction reported in vitro. The model also reproduces qualitative aspects of EC migration, such as entrapment of cells downstream from the flow-disturbing ridge. The model has the potential, after more extensive in vitro validation, to study the effect of variation in strut spacing and shape, through modification of the local flow, on EC migration. The results of this study support the hypothesis that EC migration is strongly affected by the direction and magnitude of local wall shear stress.

Atrazine movement in corn cultivated soil using HYDRUS-2D: A comparison between real and simulated data

Atrazine is an herbicide that is applied in corn around the world and in sugarcane in Brazil. It is known to be hazardous for animals' health, mobile in the soil, and its analysis is considered expensive and onerous. Solute movement studies are essential to provide information about dangerous molecules movement, which can avoid contamination. While field investigations demand time and financial resources, numerical models are an alternative to describe water and solute distribution in the soil profile. Thus, the objective of this work was to use HYDRUS 2-D model for simulations of atrazine movement in containers packed with tropical soil cultivated with corn and to compare simulated and observed data through statistical parameters. The research was carried out in a greenhouse during 116 days after planting. Atrazine was analyzed in the soil solution at three different depths to validate HYDRUS-2D. Simulations were carried out using hydraulic properties fitted directly to measured retention data and parameters for corn growing and atmospheric characteristics. The mixed procedure analysis indicated that there are differences in atrazine concentration among depths and along time. In general, atrazine concentration is higher at shallow depths and right after application. However, it is possible to find atrazine in deeper soil layers, which might be a concern regarding contamination. RMSE, Willmott and Pearson coefficients indicated a favorable capacity of the model to simulate atrazine concentration on corn cultivation. HYDRUS-2D is a reliable tool to obtain trends in atrazine movement under these experiment's conditions. The uptake parameters, the crop root growth and distribution parameters depend on further specific studies to better describe the relationship between the plant and atrazine and meteorological parameters need to be updated.

Transfer and templates in scientific modelling

The notion of template has been advocated by Paul Humphreys and others as an illuminating unit of analysis in the philosophy of scientific modelling. Templates are supposed to have the dual functions of representing target systems and of facilitating quantitative manipulation. A resulting worry is that wide-ranging cross-disciplinary use of templates might compromise their representational function and reduce them to mere formalisms. In this paper, we argue that templates are valuable units of analysis in reconstructing cross-disciplinary modelling. Central to our discussion are the ways in which Lotka-Volterra models are used to analyse processes of technology diffusion. We illuminate both the similarities and differences between contributions to this case of cross-disciplinary modelling by reconstructing them as transfer of a template, without reducing the template to a mere formalism or a computational model. This requires differentiating the interpretation of templates from that of the models based on them. This differentiation allows us to claim that the LV models of technology diffusion that we review are the result of template transfer - conformist in some contributions, creative in others.

Model-Based Recommendations for Optimal Surgical Placement of Epiretinal Implants

A major limitation of current electronic retinal implants is that in addition to stimulating the intended retinal ganglion cells, they also stimulate passing axon fibers, producing perceptual 'streaks' that limit the quality of the generated visual experience. Recent evidence suggests a dependence between the shape of the elicited visual percept and the retinal location of the stimulating electrode. However, this knowledge has yet to be incorporated into the surgical placement of retinal implants. Here we systematically explored the space of possible implant configurations to make recommendations for optimal intraocular positioning of the electrode array. Using a psychophysically validated computational model, we demonstrate that better implant placement has the potential to reduce the spatial extent of axonal activation in existing implant users by up to ~55%. Importantly, the best implant location, as inferred from a population of simulated virtual patients, is both surgically feasible and is relatively stable across individuals. This study is a first step towards the use of computer simulations in patient-specific planning of retinal implant surgery.

A model for the peak-interval task based on neural oscillation-delimited states

Specific mechanisms underlying how the brain keeps track of time are largely unknown. Several existing computational models of timing reproduce behavioral results obtained with experimental psychophysical tasks, but only a few tackle the underlying biological mechanisms, such as the synchronized neural activity that occurs throughout brain areas. In this paper, we introduce a model for the peak-interval task based on neuronal network properties. We consider that Local Field Potential (LFP) oscillation cycles specify a sequence of states, represented as neuronal ensembles. Repeated presentation of time intervals during training reinforces the connections of specific ensembles to downstream networks - sets of neurons connected to the sequence of states. Later, during the peak-interval procedure, these downstream networks are reactivated by previously experienced neuronal ensembles, triggering behavioral responses at the learned time intervals. The model reproduces experimental response patterns from individual rats in the peak-interval procedure, satisfying relevant properties such as the Weber law. Finally, we provide a biological interpretation of the parameters of the model.

Acute effect of a peritoneal dialysis exchange on electrolyte concentration and QT interval in uraemic patients

BACKGROUND

Hemodialysis (HD) sessions induce changes in plasma electrolytes that lead to modifications of QT interval, virtually associated with dangerous arrhythmias. It is not known whether such a phenomenon occurs even during peritoneal dialysis (PD). The aim of the study is to analyze the relationship between dialysate and plasma electrolyte modifications and QT interval during a PD exchange.

METHODS

In 15 patients, two manual PD 4-h exchanges were performed, using two isotonic solutions with different calcium concentration (Ca⁺⁺1.25 and Ca1.75⁺⁺ mmol/L). Dialysate and plasma electrolyte concentration and QT interval (ECG Holter recording) were monitored hourly. A computational model simulating the ventricular action potential during the exchange was also performed.

RESULTS

Dialysis exchange induced a significant plasma alkalizing effect (p < 0.001). Plasma K⁺ significantly decreased at the third hour (p < 0.05). Plasma Na⁺ significantly decreased (p < 0.001), while plasma Ca⁺⁺ slightly increased only when using the Ca 1.75⁺⁺ mmol/L solution (p < 0.01). The PD exchange did not induce modifications of clinical relevance in the QT interval, while a significant decrease in heart rate (p < 0.001) was observed. The changes in plasma K⁺ values were significantly inversely correlated to QT interval modifications (p < 0.001), indicating that even small decreases of K⁺ were consistently paralleled by small QT prolongations. These results were perfectly confirmed by the computational model.

CONCLUSIONS

The PD exchange guarantees a greater cardiac electrical stability compared to the HD session and should be preferred in patients with a higher arrhythmic risk. Moreover, our study shows that ventricular repolarization is extremely sensitive to plasma K⁺ changes, also in normal range.

Contribution of nascent cohesive fiber-fiber interactions to the non-linear elasticity of fibrin networks under tensile load

Fibrin is a viscoelastic proteinaceous polymer that determines the deformability and integrity of blood clots and fibrin-based biomaterials in response to biomechanical forces. Here, a previously unnoticed structural mechanism of fibrin clots' mechanical response to external tensile loads is tested using high-resolution confocal microscopy and recently developed three-dimensional computational model. This mechanism, underlying local strain-stiffening of individual fibers as well as global stiffening of the entire network, is based on previously neglected nascent cohesive pairwise interactions between individual fibers (crisscrossing) in fibrin networks formed under tensile load. Existence of fiber-fiber crisscrossings of reoriented fibers was confirmed using 3D imaging of experimentally obtained stretched fibrin clots. The computational model enabled us to study structural details and quantify mechanical effects of the fiber-fiber cohesive crisscrossing during stretching of fibrin gels at various spatial scales. The contribution of the fiber-fiber cohesive contacts to the elasticity of stretched fibrin networks was characterized by changes in individual fiber stiffness, the length, width, and alignment of fibers, as well as connectivity and density of the entire network. The results show that the nascent cohesive crisscrossing of fibers in stretched fibrin networks comprise an underappreciated important structural mechanism underlying the mechanical response of fibrin to (patho)physiological stresses that determine the course and outcomes of thrombotic and hemostatic disorders, such as heart attack and ischemic stroke. STATEMENT OF SIGNIFICANCE: Fibrin is a viscoelastic proteinaceous polymer that determines the deformability and integrity of blood clots and fibrin-based biomaterials in response to biomechanical forces. In this paper, a novel structural mechanism of fibrin clots' mechanical response to external tensile loads is tested using high-resolution confocal microscopy and newly developed computational model. This mechanism, underlying local strain-stiffening of individual fibers as well as global stiffening of the entire network, is based on previously neglected nascent cohesive pairwise interactions between individual fibers (crisscrossing) in fibrin networks formed under tensile load. Cohesive crisscrossing is an important structural mechanism that influences the mechanical response of blood clots and which can determine the outcomes of blood coagulation disorders, such as heart attacks and strokes.

Numerical simulation of stent deployment within patient-specific artery and its validation against clinical data

BACKGROUND AND OBJECTIVE

One of the most widely adopted endovascular treatment procedures is the stent implantation. The effectiveness of the treatment depends on the appropriate stent expansion. However, it is difficult to accurately predict the outcome of such an endovascular intervention. Numerical simulations represent a useful tool to study the complex behavior of the stent during deployment. This study presents a numerical model capable of simulating this process.

METHODS

The numerical model consists of three parts: modeling of stent expansion, modeling the interaction of the stent with the arterial wall and the deformation of the arterial wall. The model is able to predict the shapes of both stent and arterial wall during the entire deployment process. Simulations are performed using patient-specific clinical data that ensures more realistic results.

RESULTS

The numerical simulations of stent deployment are performed using the extracted geometry of the coronary arteries of two patients. The obtained results are validated against clinical data from the follow up examination and both quantitative and qualitative analysis of the results is presented. The areas of several slices of the arterial wall are calculated for all the three states (before, after and follow up) and the standard error of the area when comparing simulation and follow up examination is 5.27% for patient #1 and 4.5% for patient #2.

CONCLUSIONS

The final goal of numerical simulations in stent deployment should be to provide a clinical tool that is capable of reliably predicting the treatment outcome. This study showed through the good agreement of results of the numerical simulations and clinical data that the presented numerical model represents a step towards this final goal. These simulations can also provide valuable information about distribution of forces and stress in the arterial wall that can improve pre-operative planning and treatment optimization.

Computational comparison of conventional and novel electroconvulsive therapy electrode placements for the treatment of depression

BACKGROUND

Electroconvulsive therapy (ECT) is a highly effective treatment for severe psychiatric disorders. Despite its high efficacy, the use of ECT would be greater if the risk of cognitive side effects were reduced. Over the last 20 years, developments in ECT technique, including improvements in the dosing methodology and modification of the stimulus waveform, have allowed for improved treatment methods with reduced adverse cognitive effects. There is increasing evidence that the electrode placement is important for orienting the electrical stimulus and therefore modifying treatment outcomes, with potential for further improvement of the placements currently used in ECT.

OBJECTIVE

We used computational modelling to perform an in-depth examination into regional differences in brain excitation by the ECT stimulus for several lesser known and novel electrode placements, in order to investigate the potential for an electrode placement that may optimise clinical outcomes.

METHODS

High resolution finite element human head models were generated from MRI scans of three subjects. The models were used to compare regional differences in average electric field (EF) magnitude among a total of thirteen bipolar ECT electrode placements, i.e. three conventional placements as well as ten lesser known and novel placements.

RESULTS AND CONCLUSION

In this exploratory study on a systemic comparison of thirteen ECT electrode placements, the EF magnitude at regions of interest (ROIs) was highly dependent upon the position of both electrodes, especially the ROIs close to the cortical surface. Compared to conventional right-unilateral (RUL) ECT using a temporo-parietal placement, fronto-parietal and supraorbito-parietal RUL also robustly stimulated brain regions considered important for efficacy, while sparing regions related to cognitive functions, and may be a preferrable approach to the currently used placement for RUL ECT. The simulations also found that regional average EF magnitude varied between individual subjects, due to factors such as head size, and results also depended on the size of the defined ROI.

Ionic and synaptic mechanisms of seizure generation and epileptogenesis

The biophysical mechanisms underlying epileptogenesis and the generation of seizures remain to be better understood. Among many factors triggering epileptogenesis are traumatic brain injury breaking normal synaptic homeostasis and genetic mutations disrupting ionic concentration homeostasis. Impairments in these mechanisms, as seen in various brain diseases, may push the brain network to a pathological state characterized by increased susceptibility to unprovoked seizures. Here, we review recent computational studies exploring the roles of ionic concentration dynamics in the generation, maintenance, and termination of seizures. We further discuss how ionic and synaptic homeostatic mechanisms may give rise to conditions which prime brain networks to exhibit recurrent spontaneous seizures and epilepsy.

Individual differences in fraction arithmetic learning

Understanding fractions is critical to mathematical development, yet many children struggle with fractions even after years of instruction. Fraction arithmetic is particularly challenging. The present study employed a computational model of fraction arithmetic learning, FARRA (Fraction Arithmetic Reflects Rules and Associations; Braithwaite, Pyke, and Siegler, 2017), to investigate individual differences in children's fraction arithmetic. FARRA predicted four qualitatively distinct patterns of performance, as well as differences in math achievement among the four patterns. These predictions were confirmed in analyses of two datasets using two methods to classify children's performance-a theory-based method and a data-driven method, Latent Profile Analysis. The findings highlight three dimensions of individual differences that may affect learning in fraction arithmetic, and perhaps other domains as well: effective learning after committing errors, behavioral consistency versus variability, and presence or absence of initial bias. Methodological and educational implications of the findings are discussed.

Evolving dynamic networks: An underlying mechanism of drug resistance in epilepsy?

At least one-third of all people with epilepsy have seizures that remain poorly controlled despite an increasing number of available anti-epileptic drugs (AEDs). Often, there is an initial good response to a newly introduced AED, which may last up to months, eventually followed by the return of seizures thought to be due to the development of tolerance. We introduce a framework within which the interplay between AED response and brain networks can be explored to understand the development of tolerance. We use a computer model for seizure generation in the context of dynamic networks, which allows us to generate an 'in silico' electroencephalogram (EEG). This allows us to study the effect of changes in excitability network structure and intrinsic model properties on the overall seizure likelihood. Within this framework, tolerance to AEDs - return of seizure-like activity - may occur in 3 different scenarios: 1) the efficacy of the drug diminishes while the brain network remains relatively constant; 2) the efficacy of the drug remains constant, but connections between brain regions change; 3) the efficacy of the drug remains constant, but the intrinsic excitability within brain regions varies dynamically. We argue that these latter scenarios may contribute to a deeper understanding of how drug resistance to AEDs may occur.

Computational Simulation of Synovial Fluid Kinematics of the Scapholunate Joint

Background: The interaction between wrist kinematics and synovial fluid pressure has yet to be studied. To our knowledge, this is the first study to determine the effect of scapholunate joint kinematics on synovial fluid pressure change using finite volume method. Methods: The carpal bones of a cadaveric hand were obtained from Computed Tomography (CT) scans. CT images of the carpal bones were segmented and reconstructed into 3D model. The 3D synovial fluid model between the scaphoid and lunate was constructed and then used for computational simulations. The kinematics data of scapholunate joint obtained from radioulnar deviation of the wrist was investigated. Results: It was found that the pressure in synovial fluid varied from -1.68 to 2.64 Pa with maximum pressure located at the scaphoid-fluid interface during the radial deviation. For ulnar deviation, the pressure increased gradually from the scaphoid-fluid interface towards the lunate-fluid interface (-1.37 to 0.37 Pa). Conclusions: This new computational model provides a basis for the study of pathomechanics of ligament injury with the inclusion of synovial fluid.

Effects of homogeneous and heterogeneous changes in the lung periphery on spirometry results

BACKGROUND AND OBJECTIVES

The most widespread chronic pulmonary disorders are associated with heterogeneous changes in the lung periphery and spirometry is the most commonly used test to monitor these diseases. So far only a few attempts have been undertaken to investigate the effects of lung inhomogeneity on spirometry results. The aim of this work was to evaluate whether the spirometric curve and indexes are sensitive to parallel peripheral inhomogeneities, and if the level of heterogeneity can be deduced from this test.

METHODS

To this end, an enhanced computational model for forced expiration, taking into account a heterogeneous structure and properties of the respiratory system, was used. Two main phenomena were mimicked: small airways narrowing and the loss of tissue elastic recoil. Numerical simulations were performed with the model having 76 separate peripheral compartments. For a given degree of mean change, three heterogeneity levels were investigated and compared to the effects of homogeneous alterations.

RESULTS

All spirometric curves representing different patterns of inhomogeneous constriction, computed for each of the investigated cases, almost coincided with the curve originating from homogeneous changes, regardless of the heterogeneity level. Also the differences between the spirometric indexes obtained for heterogeneous and homogeneous alterations were negligible in comparison to their values.

CONCLUSION

The main finding is that the spirometry results are insensitive to the level of heterogeneity in the lung periphery and that it is practically impossible to distinguish between the homogeneous or heterogeneous nature of pathological processes occurring in this lung region.

Elucidating the role of graft compliance mismatch on intimal hyperplasia using an ex vivo organ culture model

There is a growing clinical need to address high failure rates of small diameter (<6 mm) synthetic vascular grafts. Although there is a strong empirical correlation between low patency rates and low compliance of synthetic grafts, the mechanism by which compliance mismatch leads to intimal hyperplasia is poorly understood. To elucidate this relationship, synthetic vascular grafts were fabricated that varied compliance independent of other graft variables. A computational model was then used to estimate changes in fluid flow and wall shear stress as a function of graft compliance. The effect of compliance on arterial remodeling in an ex vivo organ culture model was then examined to identify early markers of intimal hyperplasia. The computational model prediction of low wall shear stress of low compliance grafts and clinical control correlated well with alterations in arterial smooth muscle cell marker, extracellular matrix, and inflammatory marker staining patterns at the distal anastomoses. Conversely, high compliance grafts displayed minimal changes in fluid flow and arterial remodeling, similar to the sham control. Overall, this work supports the intrinsic link between compliance mismatch and intimal hyperplasia and highlights the utility of this ex vivo organ culture model for rapid screening of small diameter vascular grafts. STATEMENT OF SIGNIFICANCE: We present an ex vivo organ culture model as a means to screen vascular grafts for early markers of intimal hyperplasia, a leading cause of small diameter vascular graft failure. Furthermore, a computational model was used to predict the effect of graft compliance on wall shear stress and then correlate these values to changes in arterial remodeling in the organ culture model. Combined, the ex vivo bioreactor system and computational model provide insight into the mechanistic relationship between graft-arterial compliance mismatch and the onset of intimal hyperplasia.

Addressing Interdisciplinary Difficulties in Developmental Biology/Mathematical Collaborations: A Neural Crest Example

Mathematical modeling can allow insight into the biological processes that can be difficult to access by conventional biological means alone. Such projects are becoming increasingly attractive with the appearance of faster and more powerful quantitative techniques in both biological data acquisition and data storage, manipulation, and presentation. However, as is frequent in interdisciplinary research, the main hurdles are not within the mindset and techniques of each discipline but are usually encountered in attempting to meld the different disciplines together. Based upon our experience in applying mathematical methods to investigate how neural crest cells interact to form the enteric nervous system, we present our views on how to pursue biomathematical modeling projects, what difficulties to expect, and how to overcome, or at least survive, these hurdles. The main advice being: persevere.

Spatial scaling in multiscale models: methods for coupling agent-based and finite-element models of wound healing

Multiscale models that couple agent-based modeling (ABM) and finite-element modeling (FEM) allow the dynamic simulation of tissue remodeling and wound healing, with mechanical environment influencing cellular behaviors even as tissue remodeling modifies mechanics. One of the challenges in coupling ABM to FEM is that these two domains typically employ grid or element sizes that differ by several orders of magnitude. Here, we develop and demonstrate an interpolation-based method for mapping between ABM and FEM domains of different resolutions that is suitable for linear and nonlinear FEM meshes and balances accuracy with computational demands. We then explore the effects of refining the FEM mesh and the ABM grid in the setting of a fully coupled model. ABM grid refinement studies showed unexpected effects of grid size whenever cells were present at a high enough density for crowding to affect proliferation and migration. In contrast to an FE-only model, refining the FE mesh in the coupled model increased strain differences between adjacent finite elements. Allowing strain-dependent feedback on collagen turnover magnified the effects of regional heterogeneity, producing highly nonlinear spatial and temporal responses. Our results suggest that the choice of both ABM grid and FEM mesh density in coupled models must be guided by experimental data and accompanied by careful grid and mesh refinement studies in the individual domains as well as the fully coupled model.

Presenting a Neuroid model of wind-up based on dynamic synapse

The treatment of chronic pain depends mainly on our understanding of the mechanisms such as central sensitization which is involved in it. Wind-up of spinal cord is one of the most important phenomena in the study of central sensitization which has received considerable attention in recent years. Wind-up is a form of short-term synaptic plasticity (STP) that can lead to central sensitivity. Although several models have been proposed for wind-up, none of them are based on the experimental evidence. In this study, a new network model is introduced according to the gate control theory of pain. Neuroids are used as neuron models in which their parameters are captured from available experimental data. Adjusting the weights of the network is based on the short-term synaptic plasticity. The results of the time and frequency domain show that the model can well simulate wind-up behavior. This model can be used for analyzing, predicting and controlling chronic pain in the future.

A noninvasive MRI based approach to estimate the mechanical properties of human knee ligaments

Characterization of the main tibiofemoral ligaments is an essential step in developing patient-specific computational models of the knee joint for personalized surgery pre-planning. Tensile tests are commonly performed in-vitro to characterize the mechanical stiffness and rupture force of the knee ligaments which makes the technique unsuitable for in-vivo application. The time required for the limited noninvasive approaches for properties estimation based on knee laxity remained the main obstacle in clinical implementation. Magnetic resonance imaging (MRI) technique can be a platform to noninvasively assess the knee ligaments. In this study the aim was to explore the potential role of quantitative MRI and dimensional properties, in characterizing the mechanical properties of the main tibiofemoral ligaments. After MR scanning of six cadaveric legs, all 24 main tibiofemoral bone-ligaments-bone specimens were tested in vitro. During the tensile test cross sectional area of the specimens was captured using ultrasound and force-displacement curve was extracted. Digital image correlation technique was implemented to check the strain behavior of the specimen and rupture region and to assure the fixation of ligament bony block during the test. The volume of the specimen was measured using manual segmentation data, and quantitative MR parameters as T₂^*, T_1ρ, and T₂ were calculated. Linear mixed statistical models for repeated measures were used to examine the association of MRI parameters and dimensional measurements with the mechanical properties (stiffness and rupture force). The results shows that while the mechanical properties were mostly correlated to the volume, inclusion of the MR parameters increased the correlation strength for stiffness (R² ≈ 0.48) and partial rupture force (R² = 0.53). Inclusion of ligament type in the statistical analysis enhanced the correlation of mechanical properties with MR parameters and volume as for stiffness (R² = 0.60) and partial rupture (R² = 0.57). In conclusion, this study revealed the potentials in using quantitative MR parameters, T_1ρ, T₂ and T₂^*, combined with specimen volume to estimate the essential mechanical properties of all main tibiofemoral ligaments required for subject-specific computational modeling of human knee joint.

Na+ microdomains and sparks: Role in cardiac excitation-contraction coupling and arrhythmias in ankyrin-B deficiency

Cardiac sodium (Na⁺) potassium ATPase (NaK) pumps, neuronal sodium channels (I_Na), and sodium calcium (Ca²⁺) exchangers (NCX1) may co-localize to form a Na⁺ microdomain. It remains controversial as to whether neuronal I_Na contributes to local Na⁺ accumulation, resulting in reversal of nearby NCX1 and influx of Ca²⁺ into the cell. Therefore, there has been great interest in the possible roles of a Na⁺ microdomain in cardiac Ca²⁺-induced Ca²⁺ release (CICR). In addition, the important role of co-localization of NaK and NCX1 in regulating localized Na⁺ and Ca²⁺ levels and CICR in ankyrin-B deficient (ankyrin-B^+/-) cardiomyocytes has been examined in many recent studies. Altered Na⁺ dynamics may contribute to the appearance of arrhythmias, but the mechanisms underlying this relationship remain unclear. In order to investigate this, we present a mechanistic canine cardiomyocyte model which reproduces independent local dyadic junctional SR (JSR) Ca²⁺ release events underlying cell-wide excitation-contraction coupling, as well as a three-dimensional super-resolution model of the Ca²⁺ spark that describes local Na⁺ dynamics as governed by NaK pumps, neuronal I_Na, and NCX1. The model predicts the existence of Na⁺ sparks, which are generated by NCX1 and exhibit significantly slower dynamics as compared to Ca²⁺ sparks. Moreover, whole-cell simulations indicate that neuronal I_Na in the cardiac dyad plays a key role during the systolic phase. Rapid inward neuronal I_Na can elevate dyadic [Na⁺] to 35-40 mM, which drives reverse-mode NCX1 transport, and therefore promotes Ca²⁺ entry into the dyad, enhancing the trigger for JSR Ca²⁺ release. The specific role of decreased co-localization of NaK and NCX1 in ankyrin-B^+/- cardiomyocytes was examined. Model results demonstrate that a reduction in the local NCX1- and NaK-mediated regulation of dyadic [Ca²⁺] and [Na⁺] results in an increase in Ca²⁺ spark activity during isoproterenol stimulation, which in turn stochastically activates NCX1 in the dyad. This alteration in NCX1/NaK co-localization interrupts the balance between NCX1 and NaK currents in a way that leads to enhanced depolarizing inward current during the action potential plateau, which ultimately leads to a higher probability of L-type Ca²⁺ channel reopening and arrhythmogenic early-afterdepolarizations.

A model for discovering 'containment' relations

Rapid developments in the fields of learning and object recognition have been obtained by successfully developing and using methods for learning from a large number of labeled image examples. However, such current methods cannot explain infants' learning of new concepts based on their visual experience, in particular, the ability to learn complex concepts without external guidance, as well as the natural order in which related concepts are acquired. A remarkable example of early visual learning is the category of 'containers' and the notion of 'containment'. Surprisingly, this is one of the earliest spatial relations to be learned, starting already around 3 month of age, and preceding other common relations (e.g., 'support', 'in-between'). In this work we present a model, which explains infants' capacity of learning 'containment' and related concepts by 'just looking', together with their empirical development trajectory. Learning occurs in the model fast and without external guidance, relying only on perceptual processes that are present in the first months of life. Instead of labeled training examples, the system provides its own internal supervision to guide the learning process. We show how the detection of so-called 'paradoxical occlusion' provides natural internal supervision, which guides the system to gradually acquire a range of useful containment-related concepts. Similar mechanisms of using implicit internal supervision can have broad application in other cognitive domains as well as artificial intelligent systems, because they alleviate the need for supplying extensive external supervision, and because they can guide the learning process to extract concepts that are meaningful to the observer, even if they are not by themselves obvious, or salient in the input.

Numerical simulation study on systolic anterior motion of the mitral valve in hypertrophic obstructive cardiomyopathy

BACKGROUND

The hydrodynamic mechanisms of systolic anterior motion (SAM) of the mitral valve in hypertrophic obstructive cardiomyopathy (HOCM) remain unclear.

METHODS

Based on computed tomography (CT) images and clinical data, pre- and post-operative computational models of the left ventricle were constructed for 6 HOCM patients receiving septal myectomy. SAM was abolished in 5 patients and persisted in one after septal myectomy surgery. The obtained simulation results including flow field of the left ventricle and mechanical behaviors of the mitral valve (MV) between pre- and post-operative FSI models were compared.

RESULTS

The pressure difference and shear stress on the mitral valve leaflets (MVL) were relatively high pre-operatively, and decreased significantly after satisfactory surgery, but remained high following failed surgery. The significant increase in coaptation-to-septal distance was found when SAM was abolished.

CONCLUSIONS

Our results indicated that high pressure difference and shear stress on the MVL might directly initiate SAM in HOCM. Successful septal myectomy enlarged the coaptation-to-septal distance sufficiently to keep the MVL away from the ejection flow, thereby eliminating SAM.

Simplified parametric models of the dielectric properties of brain and muscle tissue during electrical stimulation

Parametric models are commonly used to describe the dispersive dielectric properties of biological tissues. While distinct regions of dispersion have been identified, the relative contribution of each during electrical stimulation is unknown. This study quantified the contribution of individual poles in parametric models of brain and muscle dielectric properties during electrical stimulation. The effect on the extracellular voltage waveform and threshold current for nerve stimulation of selectively removing subsets of poles from Cole-Cole and Debye models was examined. Errors were introduced when dispersions below 100 kHz were removed in both brain and muscle tissue. Poles below 1 kHz influenced the amplitude of the extracellular voltage waveform and the predicted minimum stimulation current. Poles between 1 kHz and 100 kHz influenced the waveform shape, with a minor effect on stimulus amplitude. The results confirm that low frequency dispersion in conductivity and permittivity can fundamentally influence the electric field and neural response during stimulation and provide insight into the relative contribution of the different dispersive regimes. Furthermore, they provide justification for for simplifying parametric models of dielectric properties through the removal of high frequency poles above 100 kHz which could improve the efficiency of time-domain solvers for simulations involving time-varying or aperiodic stimuli as may be required for certain closed-loop stimulation paradigms.

Word frequency effects in sound change as a consequence of perceptual asymmetries: An exemplar-based model

Empirically-observed word frequency effects in regular sound change present a puzzle: how can high-frequency words change faster than low-frequency words in some cases, slower in other cases, and at the same rate in yet other cases? We argue that this puzzle can be answered by giving substantial weight to the role of the listener. We present an exemplar-based computational model of regular sound change in which the listener plays a large role, and we demonstrate that it generates sound changes with properties and word frequency effects seen in corpora. In particular, we consider the experimentally-supported assumption that high-frequency words may be more robustly recognized than low-frequency words in the face of acoustic ambiguity. We show that this assumption allows high-frequency words to change at the same rate as low-frequency words when a phoneme category moves without encroaching on the acoustic space of another, faster than low-frequency words when it moves toward another, and slower than low-frequency words when it moves away from another. We discuss how these predicted word frequency effects apply to different types of sound changes that have been observed in the literature. Importantly, these frequency effects follow from assumptions regarding processes in perception, not production. Frequency-based asymmetries in perception predict different frequency effects for different kinds of sound change.

From membrane receptors to protein synthesis and actin cytoskeleton: Mechanisms underlying long lasting forms of synaptic plasticity

Synaptic plasticity, the activity dependent change in synaptic strength, forms the molecular foundation of learning and memory. Synaptic plasticity includes structural changes, with spines changing their size to accomodate insertion and removal of postynaptic receptors, which are correlated with functional changes. Of particular relevance for memory storage are the long lasting forms of synaptic plasticity which are protein synthesis dependent. Due to the importance of spine structural plasticity and protein synthesis, this review focuses on the signaling pathways that connect synaptic stimulation with regulation of protein synthesis and remodeling of the actin cytoskeleton. We also review computational models that implement novel aspects of molecular signaling in synaptic plasticity, such as the role of neuromodulators and spatial microdomains, as well as highlight the need for computational models that connect activation of memory kinases with spine actin dynamics.

Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy

Patients with idiopathic generalised epilepsy (IGE) typically have normal conventional magnetic resonance imaging (MRI), hence diagnosis based on MRI is challenging. Anatomical abnormalities underlying brain dysfunctions in IGE are unclear and their relation to the pathomechanisms of epileptogenesis is poorly understood.

In this study, we applied connectometry, an advanced quantitative neuroimaging technique for investigating localised changes in white-matter tissues in vivo. Analysing white matter structures of 32 subjects we incorporated our in vivo findings in a computational model of seizure dynamics to suggest a plausible mechanism of epileptogenesis.

Patients with IGE have significant bilateral alterations in major white-matter fascicles. In the cingulum, fornix, and superior longitudinal fasciculus, tract integrity is compromised, whereas in specific parts of tracts between thalamus and the precentral gyrus, tract integrity is enhanced in patients. Combining these alterations in a logistic regression model, we computed the decision boundary that discriminated patients and controls. The computational model, informed with the findings on the tract abnormalities, specifically highlighted the importance of enhanced cortico-reticular connections along with impaired cortico-cortical connections in inducing pathological seizure-like dynamics.

We emphasise taking directionality of brain connectivity into consideration towards understanding the pathological mechanisms; this is possible by combining neuroimaging and computational modelling. Our imaging evidence of structural alterations suggest the loss of cortico-cortical and enhancement of cortico-thalamic fibre integrity in IGE. We further suggest that impaired connectivity from cortical regions to the thalamic reticular nucleus offers a therapeutic target for selectively modifying the brain circuit for reversing the mechanisms leading to epileptogenesis.

•

Significant focal alterations along major white-matter fascicles in IGE patients are characterised.

•

Increased white matter integrity found in thalamo-cortical connections.

•

Decreased white matter integrity found in cortico-cortical connections.

•

Disease mechanism is investigated by combining the neuroimaging findings with a dynamical model of seizure activity.

•

Model implicates cortical projections to the thalamic reticular nucleus in IGE.

Periprosthetic fracture fixation of the femur following total hip arthroplasty: A review of biomechanical testing - Part II

BACKGROUND

Periprosthetic femoral fracture is a severe complication of total hip arthroplasty. A previous review published in 2011 summarised the biomechanical studies regarding periprosthetic femoral fracture and its fixation techniques. Since then, there have been several commercially available fracture plates designed specifically for the treatment of these fractures. However, several clinical studies still report failure of fixation treatments used for these fractures.

METHODS

The current literature on biomechanical models of periprosthetic femoral fracture fixation since 2010 to present is reviewed. The methodologies involved in the experimental and computational studies of periprosthetic femoral fracture fixation are described and compared with particular focus on the recent developments.

FINDINGS

Several issues raised in the previous review paper have been addressed by current studies; such as validating computational results with experimental data. Current experimental studies are more sophisticated in design. Computational studies have been useful in studying fixation methods or conditions (such as bone healing) that are difficult to study in vivo or in vitro. However, a few issues still remain and are highlighted.

INTERPRETATION

The increased use of computational studies in investigating periprosthetic femoral fracture fixation techniques has proven valuable. Existing protocols for testing periprosthetic femoral fracture fixation need to be standardised in order to make more direct and conclusive comparisons between studies. A consensus on the 'optimum' treatment method for periprosthetic femoral fracture fixation needs to be achieved.

Dopaminergic drug treatment remediates exaggerated cingulate prediction error responses in obsessive-compulsive disorder

RATIONALE

Patients with obsessive-compulsive disorder (OCD) have been found to show exaggerated error responses and prediction error learning signals in a variety of EEG and fMRI tasks, with data converging on the anterior cingulate cortex as a key locus of dysfunction. Considerable evidence has linked prediction error processing to dopaminergic function.

OBJECTIVE

In this study, we investigate potential dopaminergic dysfunction during reward processing in the context of OCD.

METHODS

We studied OCD patients (n = 18) and controls (n = 18) whilst they learned probabilistic associations between abstract stimuli and monetary rewards in the fMRI scanner involving administration (on separate visits) of a dopamine receptor agonist, pramipexole 0.5 mg; a dopamine receptor antagonist, amisulpride 400 mg; and placebo. We fitted a Q-learning computational model to fMRI prediction error responses; group differences were examined in anterior cingulate and nucleus accumbens regions of interest.

RESULTS

There were no significant group, drug, or interaction effects in the number of correct choices; computational modeling suggested a marginally significant difference in learning rates between groups (p = 0.089, partial ƞ² = 0.1). In the imaging results, there was a significant interaction of group by drug (p = 0.013, partial ƞ² = 0.13). OCD patients showed abnormally strong cingulate signaling of prediction errors during omission of an expected reward, with unexpected reduction by both pramipexole and amisulpride (p = 0.014, partial ƞ² = 0.26, 1-β error probability = 0.94). Exaggerated cingulate prediction error signaling to omitted reward in placebo was related to trait subjective difficulty in self-regulating behavior in OCD.

CONCLUSIONS

Our data support cingulate dysfunction during reward processing in OCD, and bidirectional remediation by dopaminergic modulation, suggesting that exaggerated cingulate error signals in OCD may be of dopaminergic origin. The results help to illuminate the mechanisms through which dopamine receptor antagonists achieve therapeutic benefit in OCD. Further research is needed to disentangle the different functions of dopamine receptor agonists and antagonists during bidirectional modulation of cingulate activation.

Eliminating contraction during culture maintains global and local Ca2+ dynamics in cultured rabbit pacemaker cells

Pacemaker cells residing in the sinoatrial node generate the regular heartbeat. Ca²⁺ signaling controls the heartbeat rate-directly, through the effect on membrane molecules (NCX exchange, K⁺ channel), and indirectly, through activation of calmodulin-AC-cAMP-PKA signaling. Thus, the physiological role of signaling in pacemaker cells can only be assessed if the Ca²⁺ dynamics are in the physiological range. Cultured cells that can be genetically manipulated and/or virally infected with probes are required for this purpose. Because rabbit pacemaker cells in culture experience a decrease in their spontaneous action potential (AP) firing rate below the physiological range, Ca²⁺ dynamics are expected to be affected. However, Ca²⁺ dynamics in cultured pacemaker cells have not been reported before. We aim to a develop a modified culture method that sustains the global and local Ca²⁺ kinetics along with the AP firing rate of rabbit pacemaker cells. We used experimental and computational tools to test the viability of rabbit pacemaker cells in culture under various conditions. We tested the effect of culture dish coating, pH, phosphorylation, and energy balance on cultured rabbit pacemaker cells function. The cells were maintained in culture for 48 h in two types of culture media: one without the addition of a contraction uncoupler and one enriched with either 10 mM BDM (2,3-Butanedione 2-monoxime) or 25 μM blebbistatin. The uncoupler was washed out from the medium prior to the experiments. Cells were successfully infected with a GFP adenovirus cultured with either BDM or blebbistatin. Using either uncoupler during culture led to the cell surface area being maintained at the same level as fresh cells. Moreover, the phospholamban and ryanodine receptor densities and their phosphorylation level remained intact in culture when either blebbistatin or BDM were present. Spontaneous AP firing rate, spontaneous Ca²⁺ kinetics, and spontaneous local Ca²⁺ release parameters were similar in the cultured cells with blebbistatin as in fresh cells. However, BDM affects these parameters. Using experimental and a computational model, we showed that by eliminating contraction, phosphorylation activity is preserved and energy is reduced. However, the side-effects of BDM render it less effective than blebbistatin.

Computational Study of the Effect of Electrode Polarity on Neural Activation Related to Paresthesia Coverage in Spinal Cord Stimulation Therapy

OBJECTIVE

Using computer simulation, we investigated the effect of electrode polarity on neural activation in spinal cord stimulation and propose a new strategy to maximize the activating area in the dorsal column (DC) and, thus, paresthesia coverage in clinical practice.

MATERIALS AND METHODS

A new three-dimensional spinal cord model at the T10 vertebral level was developed to simulate neural activation induced by the electric field distribution produced by different typical four-contact electrode polarities in single- and dual-lead stimulation. Our approach consisted of the combination of a finite element model of the spinal cord developed in COMSOL Multiphysics and a nerve fiber model implemented in MATLAB. Five evaluation parameters were evaluated, namely, the recruitment ratio, the perception and discomfort thresholds, and the activating area and depth. The results were compared quantitatively.

RESULTS

The dual-guarded cathode presents the maximum activating area and depth in single- and dual-lead stimulation. However, the lowest value of the ratio between the perception threshold in DC and the perception threshold in the dorsal root (DR) is achieved when the guarded cathode is programmed. Although the two versions of bipolar polarity (namely bipolar 1 and bipolar 2) produce higher activating area and depth than the guarded cathode, they are suitable for producing DR stimulation. Similarly, dual-lead stimulation is likely to activate DR fibers because the electrodes are closer to these fibers.

CONCLUSIONS

The results suggest that the activating area in the DC is maximized by using the dual-guarded cathode both in single- and dual-lead stimulation modes. However, DC nerve fibers are preferentially stimulated when the guarded cathode is used. According to these results, the new electrode programming strategy that we propose for clinical practice first uses the dual-guarded cathode, but, if the DR nerve fibers are activated, it then uses guarded cathode polarity.

Offline encoding impaired by epigenetic regulations of monoamines in the guided propagation model of autism

Background

Environmental factors can modify the expression of genes, including those involved in the metabolism of neurotransmitters. Accounting for a control role of monoamine neurotransmitters, the guided propagation (GP) memory model may contribute to investigate the consequences of neuromodulation impairments on development disorders such as autism. A prenatal transient excess of ‘monoamine oxidase A’ enzyme is assumed here to trigger persistent epigenetic regulations that would induce imbalanced metabolisms of synaptic monoamines. When imported into the ‘offline’ encoding cycles of a GP model, the consequent ‘serotoninergic noise’ leads to aberrant memory structures that can be linked with autism symptoms.

Results

In computer experiments, different levels of uncoupling between representations of monoamines correlate with the amount of impaired GP modules, the severity of irrelevant connections, as well as network overgrowth. Two types of faulty connections are respectively assumed to underlie autism traits, namely repetitive behavior and perceptual oversensitivity. Besides computational modelling, a genetic family-tree shows how the autism sex-ratio can result from combinations of pharmacological and epigenetic features.

Conclusions

These results suggest that the current rise of autism is favored by three possible sources of biological masking: (1) during sleep, when cyclic variations of monoamines may undergo disrupted enzymatic activities; (2) across generations of ‘healthy carriers’ protected by the X-chromosome silencing and a specific genetic variant; (3) early in life, as long as the brain development draws on pools of neurons born when the transient enzymatic excess and its persistent epigenetic regulation overlapped, and as long as the B type of monoamine oxidase does not significantly impact dopamine. A disease-modifying therapy can be derived from this study, which involves relevant biomarkers to be first monitored over several months of clinical trial.

Electronic supplementary material

The online version of this article (10.1186/s12868-018-0477-1) contains supplementary material, which is available to authorized users.

What is a cognitive map? Unravelling its mystery using robots

Despite years of research into cognitive mapping, the process remains controversial and little understood. A computational theory of cognitive mapping is needed, but developing it is difficult due to the lack of a clear interpretation of the empirical findings. For example, without knowing what a cognitive map is or how landmarks are defined, how does one develop a computational theory for it? We thus face the conundrum of trying to develop a theory without knowing what is computed. In this paper, we overcome the conundrum by abandoning the idea that the process begins by integrating successive views to form a global map of the environment experienced. Instead, we argue that cognitive mapping begins by remembering views as local maps and we empower a mobile robot with the process and study its behaviour as it acquires its "cognitive map". Our results show that what is computed initially could be described as a "route" map and from it, some form of a "survey map" can be computed. The latter, as it turns out, bears much of the characteristics of a cognitive map. Based on our findings, we discuss what a cognitive map is, how cognitive mapping evolves and why such a process also supports the perception of a stable world.

Modeling a rotator cuff tear: Individualized shoulder muscle forces influence glenohumeral joint contact force predictions

BACKGROUND

Rotator cuff tears in older individuals may result in decreased muscle forces and changes to force distribution across the glenohumeral joint. Reduced muscle forces may impact functional task performance, altering glenohumeral joint contact forces, potentially contributing to instability or joint damage risk. Our objective was to evaluate the influence of rotator cuff muscle force distribution on glenohumeral joint contact force during functional pull and axilla wash tasks using individualized computational models.

METHODS

Fourteen older individuals (age 63.4 yrs. (SD 1.8)) were studied; 7 with rotator cuff tear, 7 matched controls. Muscle volume measurements were used to scale a nominal upper limb model's muscle forces to develop individualized models and perform dynamic simulations of movement tracking participant-derived kinematics. Peak resultant glenohumeral joint contact force, and direction and magnitude of force components were compared between groups using ANCOVA.

FINDINGS

Results show individualized muscle force distributions for rotator cuff tear participants had reduced peak resultant joint contact force for pull and axilla wash (P ≤ 0.0456), with smaller compressive components of peak resultant force for pull (P = 0.0248). Peak forces for pull were within the glenoid. For axilla wash, peak joint contact was directed near/outside the glenoid rim for three participants; predictions required individualized muscle forces since nominal muscle forces did not affect joint force location.

INTERPRETATION

Older adults with rotator cuff tear had smaller peak resultant and compressive forces, possibly indicating increased instability or secondary joint damage risk. Outcomes suggest predicted joint contact force following rotator cuff tear is sensitive to including individualized muscle forces.

Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increasing parasympathetic activity at peak effort and a decreasing vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS. The joint analysis of the extracted autonomic parameters and classic electrophysiological markers could improve BS risk stratification.

Modulations of dendritic Ca2+ spike with weak electric fields in layer 5 pyramidal cells

Weak electric fields (EFs) modulate input/output function of pyramidal cells. Dendritic Ca²⁺ spike is an important cellular mechanism for coupling synaptic inputs from different cortical layers, which plays a critical role in neuronal computation. This study aims to understand the effects of weak EFs on Ca²⁺ spikes initiated in the distal dendrites. We use a computational model to simulate dendritic Ca²⁺ spikes and backpropagating action potentials (APs) in layer 5 pyramidal cells. We apply uniform EFs (less than 20 mV/mm) to the model and examine how they affect the threshold for activation of Ca²⁺ spikes. We show that the effects of weak field on synaptically evoked Ca²⁺ spikes depend on the timing of synaptic inputs. When distal inputs coincide with the onset of EFs within a time window of several milliseconds, field-induced depolarization facilitates the initiation of Ca²⁺ spikes, while field-induced hyperpolarization suppresses dendritic APs. Sustained field-induced depolarization leads to the inactivation of Ca²⁺ channels and increases the threshold of Ca²⁺ spike. Sustained field-induced hyperpolarization de-inactivates Ca²⁺ channels and reduces the threshold of Ca²⁺ spike. By altering the threshold of backpropagation activated Ca²⁺ firing, field-induced depolarization increases the degree of coupling between inputs of the soma and distal dendrites, while field-induced hyperpolarization results in a decrease of coupling. The modulatory effects of weak EF are governed by the field direction with respect to the cell. Our study explains a fundamental link between field-induced polarization, dendritic Ca²⁺ spike, and somato-dendritic coupling. The findings are crucial to interpret how weak EFs achieve specific modulation of cellular activity.

Development of Fangjiomics for Systems Elucidation of Synergistic Mechanism Underlying Combination Therapy

The rapid development of omics technology provides an opportunity for fulfilling the understanding of the synergistic mechanism of combination therapy. However, a systems theory to analyze synergy remains an ongoing challenge. Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism which has been utilized to systematically elucidate the synergistic mechanisms underlying combination therapy using multi-target-, pathway- or network-based quantitative methods. Besides, our ability to understand the polyhierarchical structure in synergy is driven based on multi-level omics data fusion in Fangjiomics. According to the basic principle of “Jun-Chen-Zuo-Shi”, further global integration across various omics platforms and phenotype-driven quantitative multi-scale modeling would accelerate development in Fangjiomics-based dissection of synergy in multi-drug combination therapies.

•

Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism.

•

We developed the pathway-based analysis of synergistic mechanisms in Fangjiomics.

•

The theory of network-based synergistic targets is proposed in Fangjiomics.

•

The hierarchical relationship of synergy in multilevel omics is dissected in Fangjiomics.

•

The principle of “Jun-Chen-Zuo-Shi” is proposed to accelerate the development in Fangjiomics-based dissection of synergy.

Luminance gradients and non-gradients as a cue for distinguishing reflectance and illumination in achromatic images: A computational approach

The brain analyses the visual world through the luminance patterns that reach the retina. Formally, luminance (as measured by the retina) is the product of illumination and reflectance. Whereas illumination is highly variable, reflectance is a physical property that characterizes each object surface. Due to memory constraints, it seems plausible that the visual system suppresses illumination patterns before object recognition takes place. Since many combinations of reflectance and illumination can give rise to identical luminance values, finding the correct reflectance value of a surface is an ill-posed problem, and it is still an open question how it is solved by the brain. Here we propose a computational approach that first learns filter kernels ("receptive fields") for slow and fast variations in luminance, respectively, from achromatic real-world images. Distinguishing between luminance gradients (slow variations) and non-gradients (fast variations) could serve to constrain the mentioned ill-posed problem. The second stage of our approach successfully segregates luminance gradients and non-gradients from real-world images. Our approach furthermore predicts that visual illusions that contain luminance gradients (such as Adelson's checker-shadow display or grating induction) may occur as a consequence of this segregation process.

Development of Open-Source Dummy and Impactor Models for the Assessment of American Football Helmet Finite Element Models

The objective of this study was to develop and validate a set of Hybrid-III head and neck (HIII-HN) and impactor models that can be used to assess American football design modifications with established dummy-based injury metrics. The model was validated in two bare-head impact test configurations used by the National Football League and research groups to rank and assess helmet performance. The first configuration was a rigid pendulum impact to three locations on the HIII head (front, rear, side) at 3 m/s. The second configuration was a set of eight 5.5 m/s impacts to the HIII head at different locations using a linear impactor with a compliant end cap. The ISO/TS 18571 objective rating metric was used to quantify the correlation between the experimental and model head kinematics (linear and rotational velocity and acceleration) and neck kinetics (neck force and moment). The HIII-HN model demonstrated good correlation with overall mean ISO scores of 0.69-0.78 in the pendulum impacts and 0.65-0.81 in the linear impacts. These publically available models will serve as an in silico design platform that will be useful for investigating novel football helmet designs and studying human head impact biomechanics, in general.