Applying the IEEE BRAIN neuroethics framework to intra-cortical brain-computer interfaces

Objective. Brain-computer interfaces (BCIs) are neuroprosthetic devices that allow for direct interaction between brains and machines. These types of neurotechnologies have recently experienced a strong drive in research and development, given, in part, that they promise to restore motor and communication abilities in individuals experiencing severe paralysis. While a rich literature analyzes the ethical, legal, and sociocultural implications (ELSCI) of these novel neurotechnologies, engineers, clinicians and BCI practitioners often do not have enough exposure to these topics.Approach. Here, we present the IEEE Neuroethics Framework, an international, multiyear, iterative initiative aimed at developing a robust, accessible set of considerations for diverse stakeholders.Main results. Using the framework, we provide practical examples of ELSCI considerations for BCI neurotechnologies. We focus on invasive technologies, and in particular, devices that are implanted intra-cortically for medical research applications.Significance. We demonstrate the utility of our framework in exposing a wide range of implications across different intra-cortical BCI technology modalities and conclude with recommendations on how to utilize this knowledge in the development and application of ethical guidelines for BCI neurotechnologies.

Causal and Associational Language in Observational Health Research: A Systematic Evaluation

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers' ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.

Dual STDP processes at Purkinje cells contribute to distinct improvements in accuracy and speed of saccadic eye movements

Saccadic eye-movements play a crucial role in visuo-motor control by allowing rapid foveation onto new targets. However, the neural processes governing saccades adaptation are not fully understood. Saccades, due to the short-time of execution (20-100 ms) and the absence of sensory information for online feedback control, must be controlled in a ballistic manner. Incomplete measurements of the movement trajectory, such as the visual endpoint error, are supposedly used to form internal predictions about the movement kinematics resulting in predictive control. In order to characterize the synaptic and neural circuit mechanisms underlying predictive saccadic control, we have reconstructed the saccadic system in a digital controller embedding a spiking neural network of the cerebellum with spike timing-dependent plasticity (STDP) rules driving parallel fiber-Purkinje cell long-term potentiation and depression (LTP and LTD). This model implements a control policy based on a dual plasticity mechanism, resulting in the identification of the roles of LTP and LTD in regulating the overall quality of saccade kinematics: it turns out that LTD increases the accuracy by decreasing visual error and LTP increases the peak speed. The control policy also required cerebellar PCs to be divided into two subpopulations, characterized by burst or pause responses. To our knowledge, this is the first model that explains in mechanistic terms the visual error and peak speed regulation of ballistic eye movements in forward mode exploiting spike-timing to regulate firing in different populations of the neuronal network. This elementary model of saccades could be extended and applied to other more complex cases in which single jerks are concatenated to compose articulated and coordinated movements.

Recommendations for empowering early career researchers to improve research culture and practice

Early career researchers (ECRs) are important stakeholders leading efforts to catalyze systemic change in research culture and practice. Here, we summarize the outputs from a virtual unconventional conference (unconference), which brought together 54 invited experts from 20 countries with extensive experience in ECR initiatives designed to improve the culture and practice of science. Together, we drafted 2 sets of recommendations for (1) ECRs directly involved in initiatives or activities to change research culture and practice; and (2) stakeholders who wish to support ECRs in these efforts. Importantly, these points apply to ECRs working to promote change on a systemic level, not only those improving aspects of their own work. In both sets of recommendations, we underline the importance of incentivizing and providing time and resources for systems-level science improvement activities, including ECRs in organizational decision-making processes, and working to dismantle structural barriers to participation for marginalized groups. We further highlight obstacles that ECRs face when working to promote reform, as well as proposed solutions and examples of current best practices. The abstract and recommendations for stakeholders are available in Dutch, German, Greek (abstract only), Italian, Japanese, Polish, Portuguese, Spanish, and Serbian.

Brain-Inspired Spiking Neural Network Controller for a Neurorobotic Whisker System

It is common for animals to use self-generated movements to actively sense the surrounding environment. For instance, rodents rhythmically move their whiskers to explore the space close to their body. The mouse whisker system has become a standard model for studying active sensing and sensorimotor integration through feedback loops. In this work, we developed a bioinspired spiking neural network model of the sensorimotor peripheral whisker system, modeling trigeminal ganglion, trigeminal nuclei, facial nuclei, and central pattern generator neuronal populations. This network was embedded in a virtual mouse robot, exploiting the Human Brain Project's Neurorobotics Platform, a simulation platform offering a virtual environment to develop and test robots driven by brain-inspired controllers. Eventually, the peripheral whisker system was adequately connected to an adaptive cerebellar network controller. The whole system was able to drive active whisking with learning capability, matching neural correlates of behavior experimentally recorded in mice.

Leveraging Deep Learning Techniques to Improve P300-Based Brain Computer Interfaces

Brain-Computer Interface (BCI) has become an established technology to interconnect a human brain and an external device. One of the most popular protocols for BCI is based on the extraction of the so-called P300 wave from electroencephalography (EEG) recordings. P300 wave is an event-related potential with a latency of 300 ms after the onset of a rare stimulus. In this paper, we used deep learning architectures, namely convolutional neural networks (CNNs), to improve P300-based BCIs. We propose a novel BCI classifier, called P3CNET, that improved P300 classification accuracy performances of the best state-of-the-art classifier. In addition, we explored pre-processing and training choices that improved the usability of BCI systems. For the pre-processing of EEG data, we explored the optimal signal interval that would improve classification accuracies. Then, we explored the minimum number of calibration sessions to balance higher accuracy and shorter calibration time. To improve the explainability of deep learning architectures, we analyzed the saliency maps of the input EEG signal leading to a correct P300 classification, and we observed that the elimination of less informative electrode channels from the data did not result in better accuracy. All the methodologies and explorations were performed and validated on two different CNN classifiers, demonstrating the generalizability of the obtained results. Finally, we showed the advantages given by transfer learning when using the proposed novel architecture on other P300 datasets. The presented architectures and practical suggestions can be used by BCI practitioners to improve its effectiveness.

Removal of Partially Deployed Supera Stents: Case-Based Review and Technical Considerations

PURPOSE

Maldeployment of the Supera stent system can result in primary technical failure, inferior primary patency, and poorer patient outcomes. The purpose of this article is to present a case series illustrating the conditions required to perform optimal stent deployment, and if necessary, undertake successful stent removal following maldeployment.

TECHNIQUE

Two key failures of effective Supera deployment are elongation and invagination. Several technical factors should be considered to reduce the risk of maldeployment: aggressive target vessel predilation, the use of multiple fluoroscopic views, slow deployment with controlled forward pressure applied on the delivery device, "sandwich packing" of the stent above and below target lesions, and the "pulling back" of invagination. To successfully retrieve a partially deployed stent, 3 factors should be considered: the percentage of the stent already deployed, the distance from the distal tip of the introducing sheath to the proximal extent of the deployed stent, and the severity of proximal vessel disease. The higher these factors, the greater the risk of stent detachment and failed retrieval.

CONCLUSION

In this series of 6 cases of maldeployment, the removal of a partially deployed Supera stent appeared to be feasible and safe, with success dependent on selected technical and anatomical considerations.

The interplay between risk and protective factors during the initial height of the COVID-19 crisis in Italy: The role of risk aversion and intolerance of ambiguity on distress

The present study aimed to test a model of relations to ascertain the determinants of distress caused by lockdown for COVID-19. It was hypothesized that the exposure to the COVID-19 increased distress directly and through the mediation of worry, health-related information seeking, and perception of the utility of the lockdown. It was also expected that higher levels of ambiguity intolerance corresponded to higher distress directly and through the mediation of worry, health information seeking behaviors, and perceived utility of the lockdown. Finally, it was expected that risk aversion positively influenced distress directly and through the increasing of worry, health-related information seeking behavior, and more positive perception of the utility of the lockdown The study was conducted in Italy during the mandatory lockdown for COVID-19 pandemic on 240 individuals (age range 18-76). Data recruitment was conducted via snowball sampling. COVID-19 exposure was positively associated with worry and health-related information seeking. Risk-aversion was positively associated with health-related information seeking and perceived utility of the lockdown to contain the spread of the virus. Worry and health-related information seeking were positively associated with distress, whereas the perceived utility of the lockdown was negatively associated with distress. Intolerance for the ambiguity was directly linked to distress with a positive sign. Findings suggest that risk aversion represents both a risk factor and a protective factor, based on what kind of variable mediates the relationship with distress, and that the intolerance to the ambiguity is a risk factor that busters distress.

Creating clear and informative image-based figures for scientific publications

Scientists routinely use images to display data. Readers often examine figures first; therefore, it is important that figures are accessible to a broad audience. Many resources discuss fraudulent image manipulation and technical specifications for image acquisition; however, data on the legibility and interpretability of images are scarce. We systematically examined these factors in non-blot images published in the top 15 journals in 3 fields; plant sciences, cell biology, and physiology (n = 580 papers). Common problems included missing scale bars, misplaced or poorly marked insets, images or labels that were not accessible to colorblind readers, and insufficient explanations of colors, labels, annotations, or the species and tissue or object depicted in the image. Papers that met all good practice criteria examined for all image-based figures were uncommon (physiology 16%, cell biology 12%, plant sciences 2%). We present detailed descriptions and visual examples to help scientists avoid common pitfalls when publishing images. Our recommendations address image magnification, scale information, insets, annotation, and color and may encourage discussion about quality standards for bioimage publishing.

User-centred assistive SystEm for arm Functions in neUromuscuLar subjects (USEFUL): a randomized controlled study

Background

Upper limb assistive devices can compensate for muscular weakness and empower the user in the execution of daily activities. Multiple devices have been recently proposed but there is still a lack in the scientific comparison of their efficacy.

Methods

We conducted a cross-over multi-centric randomized controlled trial to assess the functional improvement at the upper limb level of two arms supports on 36 patients with muscular dystrophy. Participants tested a passive device (i.e., Wrex by Jaeco) and a semi-active solution for gravity compensation (i.e., Armon Ayura). We evaluated devices’ effectiveness with an externally-assessed scale (i.e., Performance of the Upper Limb-PUL-module), a self-perceived scale (i.e., Abilhand questionnaire), and a usability scale (i.e., System Usability Scale). Friedman’s test was used to assess significant functional gain for PUL module and Abilhand questionnaire. Moreover, PUL changes were compared by means of the Friedman’s test.

Results

Most of the patients improved upper limb function with the use of arm supports (median PUL scores increase of 1–3 points). However, the effectiveness of each device was related to the level of residual ability of the end-user. Slightly impaired patients maintained the same independence without and with assistive devices, even if they reported reduced muscular fatigue for both devices. Moderately impaired patients enhanced their arm functionality with both devices, and they obtained higher improvements with the semi-active one (median PUL scores increase of 9 points). Finally, severely impaired subjects benefited only from the semi-active device (median PUL scores increase of 12 points). Inadequate strength was recognized as a barrier to passive devices. The usability, measured by the System Usability Scale, was evaluated by end-users “good” (70/100 points) for the passive, and “excellent” (80/100 points) for the semi-active device.

Conclusions

This study demonstrated that assistive devices can improve the quality of life of people suffering from muscular dystrophy. The use of passive devices, despite being low cost and easy to use, shows limitations in the efficacy of the assistance to daily tasks, limiting the assistance to a predefined horizontal plane. The addition of one active degree of freedom improves efficacy and usability especially for medium to severe patients. Further investigations are needed to increase the evidence on the effect of arm supports on quality of life and diseases’ progression in subjects with degenerative disorders.

Trial registration clinicaltrials.gov, NCT03127241, Registered 25th April 2017. The clinical trial was also registered as a post-market study at the Italian Ministry of Health.

A Functional Model for Unifying Brain Computer Interface Terminology

Brain Computer Interface (BCI) technology is a critical area both for researchers and clinical practitioners. The IEEE P2731 working group is developing a comprehensive BCI lexicography and a functional model of BCI. The glossary and the functional model are inextricably intertwined. The functional model guides the development of the glossary. Terminology is developed from the basis of a BCI functional model. This paper provides the current status of the P2731 working group's progress towards developing a BCI terminology standard and functional model for the IEEE.

Test-retest reliability of the Performance of Upper Limb (PUL) module for muscular dystrophy patients

The Performance of the Upper Limb (PUL) module is an externally-assessed clinical scale, initially designed for the Duchenne muscular dystrophy population. It provides an upper extremity functional score suitable for both weaker ambulatory and non-ambulatory phases up to the severely impaired patients. It is capable of characterizing overall progression and severity of disease and of tracking the stereotypical proximal-to-distal progressive loss of upper limb function in muscular dystrophy. Since the PUL module has been validated only with Duchenne patients, its use also for Becker and Limb-Girdle muscular dystrophy patients has been here evaluated, to verify its reliability and extend its use. In particular, two different assessors performed this scale on 32 dystrophic subjects in two consecutive days. The results showed that the PUL module has high reliability, both absolute and relative, based on the calculation of Pearson's r (0.9942), Intraclass Correlation Coefficient (0.9943), Standard Error of Measurement (1.36), Minimum Detectable Change (3.77), and Coefficient of Variation (3%). The Minimum Detectable Change, in particular, can be used in clinical trials to perform a comprehensive longitudinal evaluation of the effects of interventions with the lapse of time. According to this analysis, an intervention is effective if the difference in the PUL score between subsequent evaluation points is equal or higher than 4 points; otherwise, the observed effect is not relevant. Inter-rater reliability with ten different assessors was evaluated, and it has been demonstrated that deviation from the mean is lower than calculated Minimum Detectable Change. The present work provides evidence that the PUL module is a reliable and valid instrument for measuring upper limb ability in people with different forms of muscular dystrophy. Therefore, the PUL module might be extended to other pathologies and reliably used in multicenter settings.

The Effectiveness of Wearable Upper Limb Assistive Devices in Degenerative Neuromuscular Diseases: A Systematic Review and Meta-Analysis

Background: This systematic review summarizes the current evidence about the effectiveness of wearable assistive technologies for upper limbs support during activities of daily living for individuals with neuromuscular diseases. Methods: Fourteen studies have been included in the meta-analysis, involving 184 participants. All included studies compared patients ability to perform functional tasks with and without assistive devices. Results: An overall effect size of 1.06 (95% CI = 0.76-1.36, p < 0.00001) was obtained, demonstrating that upper limbs assistive devices significantly improve the performance in activities of daily living in people with neuromuscular diseases. A significant interaction between studies evaluating functional improvement with externally-assessed outcome measures or self-perceived outcome measures has been detected. In particular, the effect size of the sub-group considering self-perceived scales was 1.38 (95% CI = 1.08-1.68), while the effect size of the other group was 0.77 (95% CI = 0.41-1.11), meaning that patients' perceived functional gain is often higher than the functional gain detectable through clinical scales. Conclusion: Overall, the quality of the evidence ranged from low to moderate, due to low number of studies and participants, limitations in the selection of participants and in the blindness of outcome assessors, and risk of publication bias. Significance: A large magnitude effect and a clear dose-response gradient were found, therefore, a strong recommendation, in favor of the use of assistive devices could be suggested.

Implementation of an Advanced Frequency-Based Hebbian Spike Timing Dependent Plasticity

The brain is provided with an enormous computing capability and exploits neural plasticity to store and elaborate complex information. One of the multiple mechanisms that neural circuits express is the Spike-timing-dependent plasticity (STDP), a form of long-term synaptic plasticity exploiting the time relationship between pre- and post-synaptic action potentials (i.e., neuron spikes). It has been found that in certain cases, for instance at the input stage of the cerebellum, between mossy fibers and granular neurons, the plasticity is not only driven by the timing of the spikes, but also by the oscillation frequency of the inputs. This complex behaviour has been implemented in this work, where we developed a novel form of advanced synaptic plasticity model to be used in a well-established neural network simulator (NEST). The subsequent tests proved the proper functioning of the plasticity and its range of applicability, demonstrating the possibility to adopt it in noisy and variable conditions, similar to the biological settings.

Interpersonal trust in doctor-patient relation: Evidence from dyadic analysis and association with quality of dyadic communication

RATIONALE

Although they form a dyadic relationship, doctor's and patient's levels of trust in the other have usually been investigated separately. As members of dyadic relationships, they influence each other's behaviors and are interdependent because they share a past history and eventually a common future.

OBJECTIVES

The aim of this paper was to examine the composition of trust in doctor-patients relationship and estimate its association with quality of doctor's communication. One-With-Many analyses (OWM) were used to examine the composition of trust variance into "doctor and patient effects", "relationship effects", and "reciprocity effects," taking into account the interdependence of the data.

METHOD

Twelve General Practitioners (GPs; Mage = 54.16, SD = 12.28, 8 men) and 189 of their patients (Mage = 47.48, SD = 9.88, 62% women) took part in the study. GPs and their patients completed postconsultation questionnaires on trust and quality of communication.

RESULTS

The findings revealed that "doctor" and "patient" effects were significant. However, the most important part of the variance was attributable to the relationship and reciprocity effects, meaning that if a doctor reported high trust in a particular patient, then the patient reported a similarly high level of trust. Higher quality of communication was positively associated to those relationship effects of trust.

CONCLUSIONS

Our study stresses the importance to investigate trust in doctor-patients relationship as a dyadic and interdependent phenomenon applying appropriate methodological design and analysis. Convergence between doctor's and patients' perceptions of their relationship may enhance trust more than conventional intervention and may ultimately contribute to better health outcomes.

Synergy-Based Myocontrol of a Multiple Degree-of-Freedom Humanoid Robot for Functional Tasks

In the context of sensor-based human-robot interaction, a particularly promising solution is represented by myoelectric control schemes based on synergy-derived signals. We developed and tested on healthy subjects a synergy-based control to achieve simultaneous, continuous actuation of three degrees of freedom of a humanoid robot, while performing functional reach-to-grasp movements. The control scheme exploits subject-specific muscle synergies extracted from eleven upper limb muscles through an easy semi-supervised calibration phase, and computes online activation coefficients to actuate the robot joints. The humanoid robot was able to well reproduce the subjects' motion, which consisted in free multi-degree-of-freedom reach-to-grasp movements at self-paced speeds. Furthermore, the synergy-based online control significantly outperformed a traditional muscle-pair approach (that uses a pair of antagonist muscles for each joint), in terms of decreased error, increased correlation, and peak correlation between the subjects' and the robot's joint angles. The delay introduced by the two algorithms was comparable. This work is a proof-of-concept for an intuitive and robust myocontrol interface, without the need for any training and practice. It has several potential applications, especially for functional assistive engaging devices in children with social and motor impairments.

Dynamic Redistribution of Plasticity in a Cerebellar Spiking Neural Network Reproducing an Associative Learning Task Perturbed by TMS

During natural learning, synaptic plasticity is thought to evolve dynamically and redistribute within and among subcircuits. This process should emerge in plastic neural networks evolving under behavioral feedback and should involve changes distributed across multiple synaptic sites. In eyeblink classical conditioning (EBCC), the cerebellum learns to predict the precise timing between two stimuli, hence EBCC represents an elementary yet meaningful paradigm to investigate the cerebellar network functioning. We have simulated EBCC mechanisms by reconstructing a realistic cerebellar microcircuit model and embedding multiple plasticity rules imitating those revealed experimentally. The model was tuned to fit experimental EBCC human data, estimating the underlying learning time-constants. Learning started rapidly with plastic changes in the cerebellar cortex followed by slower changes in the deep cerebellar nuclei. This process was characterized by differential development of long-term potentiation and depression at individual synapses, with a progressive accumulation of plasticity distributed over the whole network. The experimental data included two EBCC sessions interleaved by a trans-cranial magnetic stimulation (TMS). The experimental and the model response data were not significantly different in each learning phase, and the model goodness-of-fit was [Formula: see text] for all the experimental conditions. The models fitted on TMS data revealed a slowed down re-acquisition (sessions-2) compared to the control condition ([Formula: see text]). The plasticity parameters characterizing each model significantly differ among conditions, and thus mechanistically explain these response changes. Importantly, the model was able to capture the alteration in EBCC consolidation caused by TMS and showed that TMS affected plasticity at cortical synapses thereby altering the fast learning phase. This, secondarily, also affected plasticity in deep cerebellar nuclei altering learning dynamics in the entire sensory-motor loop. This observation reveals dynamic redistribution of changes over the entire network and suggests how TMS affects local circuit computation and memory processing in the cerebellum.

A Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies

The cerebellum plays a crucial role in sensorimotor control and cerebellar disorders compromise adaptation and learning of motor responses. However, the link between alterations at network level and cerebellar dysfunction is still unclear. In principle, this understanding would benefit of the development of an artificial system embedding the salient neuronal and plastic properties of the cerebellum and operating in closed-loop. To this aim, we have exploited a realistic spiking computational model of the cerebellum to analyze the network correlates of cerebellar impairment. The model was modified to reproduce three different damages of the cerebellar cortex: (i) a loss of the main output neurons (Purkinje Cells), (ii) a lesion to the main cerebellar afferents (Mossy Fibers), and (iii) a damage to a major mechanism of synaptic plasticity (Long Term Depression). The modified network models were challenged with an Eye-Blink Classical Conditioning test, a standard learning paradigm used to evaluate cerebellar impairment, in which the outcome was compared to reference results obtained in human or animal experiments. In all cases, the model reproduced the partial and delayed conditioning typical of the pathologies, indicating that an intact cerebellar cortex functionality is required to accelerate learning by transferring acquired information to the cerebellar nuclei. Interestingly, depending on the type of lesion, the redistribution of synaptic plasticity and response timing varied greatly generating specific adaptation patterns. Thus, not only the present work extends the generalization capabilities of the cerebellar spiking model to pathological cases, but also predicts how changes at the neuronal level are distributed across the network, making it usable to infer cerebellar circuit alterations occurring in cerebellar pathologies.

Model-Driven Analysis of Eyeblink Classical Conditioning Reveals the Underlying Structure of Cerebellar Plasticity and Neuronal Activity

The cerebellum plays a critical role in sensorimotor control. However, how the specific circuits and plastic mechanisms of the cerebellum are engaged in closed-loop processing is still unclear. We developed an artificial sensorimotor control system embedding a detailed spiking cerebellar microcircuit with three bidirectional plasticity sites. This proved able to reproduce a cerebellar-driven associative paradigm, the eyeblink classical conditioning (EBCC), in which a precise time relationship between an unconditioned stimulus (US) and a conditioned stimulus (CS) is established. We challenged the spiking model to fit an experimental data set from human subjects. Two subsequent sessions of EBCC acquisition and extinction were recorded and transcranial magnetic stimulation (TMS) was applied on the cerebellum to alter circuit function and plasticity. Evolutionary algorithms were used to find the near-optimal model parameters to reproduce the behaviors of subjects in the different sessions of the protocol. The main finding is that the optimized cerebellar model was able to learn to anticipate (predict) conditioned responses with accurate timing and success rate, demonstrating fast acquisition, memory stabilization, rapid extinction, and faster reacquisition as in EBCC in humans. The firing of Purkinje cells (PCs) and deep cerebellar nuclei (DCN) changed during learning under the control of synaptic plasticity, which evolved at different rates, with a faster acquisition in the cerebellar cortex than in DCN synapses. Eventually, a reduced PC activity released DCN discharge just after the CS, precisely anticipating the US and causing the eyeblink. Moreover, a specific alteration in cortical plasticity explained the EBCC changes induced by cerebellar TMS in humans. In this paper, for the first time, it is shown how closed-loop simulations, using detailed cerebellar microcircuit models, can be successfully used to fit real experimental data sets. Thus, the changes of the model parameters in the different sessions of the protocol unveil how implicit microcircuit mechanisms can generate normal and altered associative behaviors.The cerebellum plays a critical role in sensorimotor control. However, how the specific circuits and plastic mechanisms of the cerebellum are engaged in closed-loop processing is still unclear. We developed an artificial sensorimotor control system embedding a detailed spiking cerebellar microcircuit with three bidirectional plasticity sites. This proved able to reproduce a cerebellar-driven associative paradigm, the eyeblink classical conditioning (EBCC), in which a precise time relationship between an unconditioned stimulus (US) and a conditioned stimulus (CS) is established. We challenged the spiking model to fit an experimental data set from human subjects. Two subsequent sessions of EBCC acquisition and extinction were recorded and transcranial magnetic stimulation (TMS) was applied on the cerebellum to alter circuit function and plasticity. Evolutionary algorithms were used to find the near-optimal model parameters to reproduce the behaviors of subjects in the different sessions of the protocol. The main finding is that the optimized cerebellar model was able to learn to anticipate (predict) conditioned responses with accurate timing and success rate, demonstrating fast acquisition, memory stabilization, rapid extinction, and faster reacquisition as in EBCC in humans. The firing of Purkinje cells (PCs) and deep cerebellar nuclei (DCN) changed during learning under the control of synaptic plasticity, which evolved at different rates, with a faster acquisition in the cerebellar cortex than in DCN synapses. Eventually, a reduced PC activity released DCN discharge just after the CS, precisely anticipating the US and causing the eyeblink. Moreover, a specific alteration in cortical plasticity explained the EBCC changes induced by cerebellar TMS in humans. In this paper, for the first time, it is shown how closed-loop simulations, using detailed cerebellar microcircuit models, can be successfully used to fit real experimental data sets. Thus, the changes of the model parameters in the different sessions of the protocol unveil how implicit microcircuit mechanisms can generate normal and altered associative behaviors.

Frailty and resilience in an older population. The role of resilience during rehabilitation after orthopedic surgery in geriatric patients with multiple comorbidities

Hip fracture is common in the elderly and it is usually associated with comorbidities and physiological changes which may have an impact on functioning and quality of life. The concept of resilience may explain why this impact varies among patients. The aim of this open, prospective cohort study was to explore the relationships between resilience, frailty and quality of life in orthopedic rehabilitation patients, and also to assess whether these factors might affect rehabilitation outcome. Eighty-one patients, older than 60 years, underwent a multidisciplinary assessment at the beginning and at the end of the rehabilitation period following orthopedic surgery to the lower limb. The assessments were performed using the Resilience Scale, the Multidimensional Prognostic Index (as a measure of frailty), the WHO Quality of Life-BRIEF, the Geriatric Depression Scale, and the Functional Independence Frailty and resilience in an older population. The role of resilience during rehabilitation after orthopedic surgery in geriatric patients with multiple comorbidities Measure (as a measure of the rehabilitation outcome). A negative correlation between disability and resilience emerged and this association interacted with frailty level. We also found that resilience and quality of life are positive predictors of functional status at discharge.

Categorisation of tibial artery disease on computer tomography angiography according to the TASC II classification

Purpose Computer tomography angiography is used to assess peripheral arterial disease. Its preference over other imaging modalities is based upon its rapid acquisition and high spatial resolution, along with ease of access. TASC II have recently updated their vascular lesion classification to include infrapopliteal lesions, and our aim is to assess the reproducibility of TASC II on infrapopliteal disease when using computer tomography angiography. Methods A retrospective analysis of a series of consecutive computer tomography angiographies was performed by seven assessors (three consultant radiologists, two consultant vascular surgeons and two vascular specialty trainees). Each assessor was asked to classify the target vessel based on the TASC II classification. Statistical analysis was performed using Cohen's weighted kappa. Results Seven assessors analysed 48 target vessels in 25 patients (20 men), with a mean age of 72.9 years. Twenty posterior tibial, 27 anterior tibial and one peroneal artery were analysed. Poor agreement was demonstrated between the two vascular consultants, with a kappa of 0.094. Weak agreement was demonstrated among the radiologists, with a kappa of 0.547. The total group of assessors had a kappa of 0.176. Conclusion This study showed poor agreement between assessors when applying the TASC II classification to infrapopliteal lesions on computer tomography angiography. TASC II should not be used to classify lesions, for clinical or research purposes, with this image modality.

Representation of Mental Imagery Functions

A questionnaire was administered to 250 undergraduates to study their conceptions about the efficacy of mental images in thinking. Analysis showed that subjects rated differently the usefulness of visual imagery according to the kind of content rather than the mental process involved.

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate “realistic” models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems.

Healthy and pathological cerebellar Spiking Neural Networks in Vestibulo-Ocular Reflex

Since the Marr-Albus model, computational neuroscientists have been developing a variety of models of the cerebellum, with different approaches and features. In this work, we developed and tested realistic artificial Spiking Neural Networks inspired to this brain region. We tested in computational simulations of the Vestibulo-Ocular Reflex protocol three different models: a network equipped with a single plasticity site, at the cortical level; a network equipped with a distributed plasticity, at both cortical and nuclear levels; a network with a pathological plasticity mechanism at the cortical level. We analyzed the learning performance of the three different models, highlighting the behavioral differences among them. We proved that the model with a distributed plasticity produces a faster and more accurate cerebellar response, especially during a second session of acquisition, compared with the single plasticity model. Furthermore, the pathological model shows an impaired learning capability in Vestibulo-Ocular Reflex acquisition, as found in neurophysiological studies. The effect of the different plasticity conditions, which change fast and slow dynamics, memory consolidation and, in general, learning capabilities of the cerebellar network, explains differences in the behavioral outcome.

Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks

The cerebellum plays a crucial role in motor learning and it acts as a predictive controller. Modeling it and embedding it into sensorimotor tasks allows us to create functional links between plasticity mechanisms, neural circuits and behavioral learning. Moreover, if applied to real-time control of a neurorobot, the cerebellar model has to deal with a real noisy and changing environment, thus showing its robustness and effectiveness in learning. A biologically inspired cerebellar model with distributed plasticity, both at cortical and nuclear sites, has been used. Two cerebellum-mediated paradigms have been designed: an associative Pavlovian task and a vestibulo-ocular reflex, with multiple sessions of acquisition and extinction and with different stimuli and perturbation patterns. The cerebellar controller succeeded to generate conditioned responses and finely tuned eye movement compensation, thus reproducing human-like behaviors. Through a productive plasticity transfer from cortical to nuclear sites, the distributed cerebellar controller showed in both tasks the capability to optimize learning on multiple time-scales, to store motor memory and to effectively adapt to dynamic ranges of stimuli.

Adaptive robotic control driven by a versatile spiking cerebellar network

The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

Prostatic artery embolization in benign prostatic hyperplasia: preliminary results in 13 patients

AIM

The aim of the paper is to report the clinical outcome after prostatic artery embolisation (PAE) in 13 consecutive patients with benign prostatic hyperplasia (BPH) and lower urinary tract symptoms (LUTS).

MATERIALS AND METHODS

From May 2012 to October 2013, we performed PAE in 13 consecutive patients (mean age 75.9 years) with BPH and LUTS and refractory to medical therapy; seven patients had an indwelling bladder catheter. Clinical follow-up (mean follow-up time 244 days) was performed using the international prostate symptoms score (IPSS), quality of life (QoL), the international index of erectile function (IIEF), blood prostatic specific antigen (PSA) testing and transrectal prostatic ultrasound (US) scan with volume and weight calculation at 3, 6 and 12 months. Pre-procedural CT angiography (CTA) was done for vascular mapping. Embolisation was performed using Embosphere (300-500 micron). Technical success was defined when selective prostatic arterial embolisation was completed in at least one pelvic side. Clinical success was defined when symptoms and quality of life were improved.

RESULTS

PAE was technically successful in 12/13 patients (92%). In one patient, PAE was not performed because of tortuosity and atherosclerosis of iliac arteries. PAE was completed bilaterally in 9/13 (75%) patients and unilaterally in three (27%). All patients removed the bladder catheter from 4 days to 4 weeks after PAE. We obtained a reduction in IPSS (mean, 17.1 points), an increase in IIEF (mean, 2.6 points), an improvement in Qol (mean, 2.6 points) and a volume reduction (mean, 28%) at 12 months.

CONCLUSIONS

Consistent with the literature, our experience showed the feasibility, safety and efficacy of PAE in the management of patients with LUTS related to BPH. PAE may play an important role in patients in whom medical therapy has failed, who are not candidates for surgery or transurethral prostatic resection (TURP) or refuse any surgical treatment. Larger case series and comparative studies with standard TURP can confirm the validity of the technique.

Endovascular treatment of visceral artery aneurysms and pseudoaneurysms: our experience

PURPOSE

The aim of this study was to analyse our 8 years of experience with endovascular treatment of visceral aneurysms and pseudoaneurysms.

MATERIALS AND METHODS

From January 2002 to September 2009, we used an endovascular approach to treat 30 patients (22 men, eight women) affected by aneurysm (n=18) or pseudoaneurysm (n=13) of the splenic (n=11), hepatic (n=6), renal (n=5), pancreaticoduodenal (n=3), left gastric (n=2), gastroduodenal (n=1), rectal (n=1) or middle colic (n=1) arteries and the coeliac axis (n=1). Of these, 26/31 were treated with metal coils, 3/31 with Cardiatis multilayer stent, 1/31 with a coated stent and 1/31 with coils and Amplatzer plug. Procedures were performed electively in 10/30 cases and during haemorrhage in 20/30 cases. Follow-up was performed clinically (cessation of bleeding) and at 1, 6 and 12 months by colour-Doppler ultrasound (CDUS) and computed tomography (CT) angiography.

RESULTS

In 31/31 aneurysms and pseudoaneurysms we obtained immediate exclusion. In four patients with aneurysm and in four with pseudoaneurysm, parenchymal ischaemia occurred; one was treated with surgical splenectomy. One patient with pseudoaneurysm of the coeliac axis died 10 days later because of new bleeding. During follow-up, all aneurysms and pseudoaneurysms remained excluded.

CONCLUSIONS

Percutaneous treatment is effective and safe, with a small number of complications, especially when compared with traditional surgery.

Accessing source information in analogical problem-solving

Several studies showed that people presented with source information fail to apply it to an analogous target problem unless they are instructed to use the source. Seven experiments were carried out to assess whether such a lack of spontaneous transfer occurs because individuals do not activate the source during the target task or because they do not realize the source-target relationship. Experiment 1 compared a condition in which the source was activated with no cue about the source-target connection to conditions in which subjects were informed about this connection. Results suggested that the lack of spontaneous transfer does not depend on failure in activating source information. Experiments 2, 3, and 4 were devised to falsify this finding by activating the source closer and closer to the target and by focusing participants' attention toward the relevant aspects of the source. Experiments 5, 6, and 7 were aimed at stressing source-target correspondences by introducing surface similarities. All experiments showed that the mere activation of the source does not facilitate analogical transfer. Results suggested that two processes should be distinguished in the access phase of analogical problem-solving: Source retrieval and identification of the source-target connection.

Suggesting strategies improves creative visual synthesis

An experiment assessed whether a figural or an interpretative strategy can enhance creative visual synthesis. 45 undergraduates were presented a set of simple figures and asked to imagine combining them to obtain a whole pattern corresponding to a creative product. In the figurative condition participants were instructed to combine figures in unusual ways; in the interpretative condition they were induced to look for unusual meanings embedded in the combinations; in the control condition no strategy was suggested. Results showed that certain strategies induced a more flexible visual synthesis.

Metacognitive knowledge about problem-solving methods

BACKGROUND

The effective application of a problem-solving method requires the knowledge of what task is relevant, what the abilities involved are and how much effort is needed. However, as yet too little is known about these metacognitive representations.

AIM

This study was aimed at describing beliefs about problem-solving methods and at assessing whether they vary according to the kind of method and of problem and are modified by psychological courses attended.

SAMPLE

Forty-six Italian undergraduates in psychology and 37 in non-psychological disciplines.

METHODS

Participants had to rate how frequently each of five problem-solving methods (free production, analogy, step-by-step analysis, visualisation and combining) is employed and how effective and easy each one is to apply. Ratings were requested for interpersonal, practical and study problems. Participants were also asked to identify which abilities they thought would be involved in each method.

RESULTS

According to students' ratings, the most frequently used problem-solving method was analogy, which was also considered the easiest method to apply, whereas step-by-step analysis and combining were considered the most difficult. Problem-solving techniques were perceived as being relevant above all for practical problems, whereas they were conceived as less suitable for interpersonal problems. For study problems the most relevant strategy was step-by-step analysis. Students were aware of the abilities relevant to each problem-solving method.

CONCLUSIONS

Undergraduates both in psychology and non-psychological disciplines can identify some critical features in the methods used to solve problems, even though some misconceptions emerged. Since metacognition plays a causal role in problem-solving, trainers should take into account trainees' folk representations of problem-solving strategies.

The Verbalizer-Visualizer Questionnaire: a review

The psychometric properties of Richardson's 1977 Verbalizer-Visualizer Questionnaire have been studied by analyzing papers in which this questionnaire was employed. Such review showed that the Verbalizer-Visualizer Questionnaire does not measure a unidimensional construct and does not predict the actual use of mental imagery in thinking. Further, a lack of long-term reliability of the questionnaire emerged. In conclusion, use of the questionnaire to assess the verbal-visual cognitive style appears questionable.

Creative synthesis of visual images is not associated with individual differences

50 undergraduates were tested on a mental synthesis task aimed at producing creative visual patterns and were administered three questionnaires measuring imagery vividness and control. Analysis did not support a relationship between scores on visual synthesis and imagery and showed that neither kind of score was influenced by sex and studies attended.

Representation of mental imagery functions

A questionnaire was administered to 250 undergraduates to study their conceptions about the efficacy of mental images in thinking. Analysis showed that subjects rated differently the usefulness of visual imagery according to the kind of content rather than the mental process involved.