Browsing by Keyword "Cellular and Molecular Neuroscience"
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Item Acellular human corneal matrix sheets seeded with human adipose-derived mesenchymal stem cells integrate functionally in an experimental animal model(2015-03-01) Alio del Barrio, Jorge L.; Chiesa, Massimo; Garagorri, Nerea; Garcia-Urquia, Nerea; Fernandez-Delgado, Jorge; Bataille, Laurent; Rodriguez, Alejandra; Arnalich-Montiel, Francisco; Zarnowski, Tomasz; Álvarez de Toledo, Juan P.; Alio, Jorge L.; De Miguel, Maria P.; Tecnalia Research & Innovation; BiomaterialesPurpose: To evaluate the invivo biocompatibility of grafts composed of sheets of decellularized human corneal stroma with or without the recellularization of human adipose derived adult stem cells (h-ADASC) into the rabbit cornea. Methods: Sheets of human corneal stroma of 90μm thickness were decellularized, and their lack of cytotoxicity was assayed. The recellularization was achieved by the injection of 2×105 labeled h-ADASC in the graft followed by five days of cell culture. The grafts were implanted invivo into a stromal pocket at 50% depth. After a triple-masked three-month follow-up, the animals were euthanized and the biointegration of the graft, the viability of the stem cells and the expression of keratocan (human keratocyte-specific protein) were assessed. Results: The decellularized stromal sheets showed an intact extracellular matrix with a decellularization rate of 92.8% and an excellent recellularization capacity invitro with h-ADASC. A complete and stable graft transparency was observed during the full follow-up, with absence of any clinical sign of rejection. The postmortem analysis demonstrated the survival of the transplanted human stem cells inside the graft and their differentiation into functional keratocytes, as assessed by the expression of human keratocan. Conclusions: We report a new model of lamellar keratoplasty that requires only a simple and safe procedure of liposuction and a donor allogeneic cornea to provide an optically transparent autologous stromal graft with excellent biocompatibility and integration into the host tissue in a rabbit model.Item Amplitude versus spatially modulated electrotactile feedback for myoelectric control of two degrees of freedom(2020-08) Garenfeld, Martin A.; Mortensen, Christian K.; Strbac, Matija; Dideriksen, Jakob L.; Dosen, Strahinja; SGObjective. Artificial proprioceptive feedback from a myoelectric prosthesis is an important aspect in enhancing embodiment and user satisfaction, possibly lowering the demand for visual attention while controlling a prosthesis in everyday tasks. Contemporary myoelectric prostheses are advanced mechatronic systems with multiple degrees of freedom, and therefore, to communicate the prosthesis state, the feedback interface needs to transmit several variables simultaneously. In the present study, two different configurations for conveying proprioceptive information of wrist rotation and hand aperture through multichannel electrotactile stimulation were developed and evaluated during online myoelectric control. Approach. Myoelectric recordings were acquired from the dominant forearm and electrotactile stimulation was delivered on the non-dominant forearm using a compact interface. The first feedback configuration, which was based on spatial coding, transmitted the information using a moving tactile stimulus, whereas the second, amplitude-based configuration conveyed the position via sensation intensity. Thirteen able-bodied subjects used pattern classification-based myoelectric control with both feedback configurations to accomplish a target-reaching task. Main results. High task performance (completion rate > 90%) was observed for both configurations, with no significant difference in completion rate, time to reach the target, distance error and path efficiency, respectively. Significance. Overall, the results demonstrated that both feedback configurations allowed subjects to perceive and interpret two feedback variables delivered simultaneously, despite using a compact stimulation interface. This is an encouraging result for the prospect of communicating the full state of a multifunctional hand prosthesis.Item Assessing attention and cognitive function in completely locked-in state with event-related brain potentials and epidural electrocorticography(2014-04) Bensch, Michael; Martens, Suzanne; Halder, Sebastian; Hill, Jeremy; Nijboer, Femke; Ramos, Ander; Birbaumer, Niels; Bogdan, Martin; Kotchoubey, Boris; Rosenstiel, Wolfgang; Schölkopf, Bernhard; Gharabaghi, Alireza; Medical TechnologiesObjective. Patients in the completely locked-in state (CLIS), due to, for example, amyotrophic lateral sclerosis (ALS), no longer possess voluntary muscle control. Assessing attention and cognitive function in these patients during the course of the disease is a challenging but essential task for both nursing staff and physicians. Approach. An electrophysiological cognition test battery, including auditory and semantic stimuli, was applied in a late-stage ALS patient at four different time points during a six-month epidural electrocorticography (ECoG) recording period. Event-related cortical potentials (ERP), together with changes in the ECoG signal spectrum, were recorded via 128 channels that partially covered the left frontal, temporal and parietal cortex. Main results. Auditory but not semantic stimuli induced significant and reproducible ERP projecting to specific temporal and parietal cortical areas. N1/P2 responses could be detected throughout the whole study period. The highest P3 ERP was measured immediately after the patient's last communication through voluntary muscle control, which was paralleled by low theta and high gamma spectral power. Three months after the patient's last communication, i.e., in the CLIS, P3 responses could no longer be detected. At the same time, increased activity in low-frequency bands and a sharp drop of gamma spectral power were recorded. Significance. Cortical electrophysiological measures indicate at least partially intact attention and cognitive function during sparse volitional motor control for communication. Although the P3 ERP and frequency-specific changes in the ECoG spectrum may serve as indicators for CLIS, a close-meshed monitoring will be required to define the exact time point of the transition.Item Brain-computer interfaces for communication and rehabilitation(2016-09-01) Chaudhary, Ujwal; Birbaumer, Niels; Ramos-Murguialday, Ander; Medical TechnologiesBrain-computer interfaces (BCIs) use brain activity to control external devices, thereby enabling severely disabled patients to interact with the environment. A variety of invasive and noninvasive techniques for controlling BCIs have been explored, most notably EEG, and more recently, near-infrared spectroscopy. Assistive BCIs are designed to enable paralyzed patients to communicate or control external robotic devices, such as prosthetics; rehabilitative BCIs are designed to facilitate recovery of neural function. In this Review, we provide an overview of the development of BCIs and the current technology available before discussing experimental and clinical studies of BCIs. We first consider the use of BCIs for communication in patients who are paralyzed, particularly those with locked-in syndrome or complete locked-in syndrome as a result of amyotrophic lateral sclerosis. We then discuss the use of BCIs for motor rehabilitation after severe stroke and spinal cord injury. We also describe the possible neurophysiological and learning mechanisms that underlie the clinical efficacy of BCIs.Item Chapter 8 Neurofeedback and Brain-Computer Interface. Clinical Applications(2009) Birbaumer, Niels; Ramos Murguialday, Ander; Weber, Cornelia; Montoya, Pedro; Rossini, Luca; Izzo, Dario; Summerer, Leopold; Medical TechnologiesMost of the research devoted to BMI development consists of methodological studies comparing different online mathematical algorithms, ranging from simple linear discriminant analysis (LDA) (Dornhege et al., 2007) to nonlinear artificial neural networks (ANNs) or support vector machine (SVM) classification. Single cell spiking for the reconstruction of hand movements requires different statistical solutions than electroencephalography (EEG)-rhythm classification for communication. In general, the algorithm for BMI applications is computationally simple and differences in classification accuracy between algorithms used for a particular purpose are small. Only a very limited number of clinical studies with neurological patients are available, most of them single case studies. The clinical target populations for BMI-treatment consist primarily of patients with amyotrophic lateral sclerosis (ALS) and severe CNS damage including spinal cord injuries and stroke resulting in substantial deficits in communication and motor function. However, an extensive body of literature started in the 1970s using neurofeedback training. Such training implemented to control various EEG-measures provided solid evidence of positive effects in patients with otherwise pharmacologically intractable epilepsy, attention deficit disorder, and hyperactivity ADHD. More recently, the successful introduction and testing of real-time fMRI and a NIRS-BMI opened an exciting field of interest in patients with psychopathological conditions.Item Classification of different reaching movements from the same limb using EEG(2017-06-12) Shiman, Farid; López-Larraz, Eduardo; Sarasola-Sanz, Andrea; Irastorza-Landa, Nerea; Spüler, Martin; Birbaumer, Niels; Ramos-Murguialday, Ander; Tecnalia Research & Innovation; Medical TechnologiesObjective. Brain–computer-interfaces (BCIs) have been proposed not only as assistive technologies but also as rehabilitation tools for lost functions. However, due to the stochastic nature, poor spatial resolution and signal to noise ratio from electroencephalography (EEG), multidimensional decoding has been the main obstacle to implement non-invasive BCIs in real-live rehabilitation scenarios. This study explores the classification of several functional reaching movements from the same limb using EEG oscillations in order to create a more versatile BCI for rehabilitation. Approach. Nine healthy participants performed four 3D center-out reaching tasks in four different sessions while wearing a passive robotic exoskeleton at their right upper limb. Kinematics data were acquired from the robotic exoskeleton. Multiclass extensions of Filter Bank Common Spatial Patterns (FBCSP) and a linear discriminant analysis (LDA) classifier were used to classify the EEG activity into four forward reaching movements (from a starting position towards four target positions), a backward movement (from any of the targets to the starting position and rest). Recalibrating the classifier using data from previous or the same session was also investigated and compared. Main results. Average EEG decoding accuracy were significantly above chance with 67%, 62.75%, and 50.3% when decoding three, four and six tasks from the same limb, respectively. Furthermore, classification accuracy could be increased when using data from the beginning of each session as training data to recalibrate the classifier. Significance. Our results demonstrate that classification from several functional movements performed by the same limb is possible with acceptable accuracy using EEG oscillations, especially if data from the same session are used to recalibrate the classifier. Therefore, an ecologically valid decoding could be used to control assistive or rehabilitation mutli-degrees of freedom (DoF) robotic devices using EEG data. These results have important implications towards assistive and rehabilitative neuroprostheses control in paralyzed patients.Item Corrigendum: Brain-computer interfaces for communication and rehabilitation(2017-02-17) Chaudhary, Ujwal; Birbaumer, Niels; Ramos-Murguialday, Ander; Medical TechnologiesItem Cortical processing during robot and functional electrical stimulation(2023) Cho, Woosang; Vidaurre, Carmen; An, Jinung; Birbaumer, Niels; Ramos-Murguialday, Ander; Tecnalia Research & Innovation; Medical TechnologiesIntroduction: Like alpha rhythm, the somatosensory mu rhythm is suppressed in the presence of somatosensory inputs by implying cortical excitation. Sensorimotor rhythm (SMR) can be classified into two oscillatory frequency components: mu rhythm (8–13 Hz) and beta rhythm (14–25 Hz). The suppressed/enhanced SMR is a neural correlate of cortical activation related to efferent and afferent movement information. Therefore, it would be necessary to understand cortical information processing in diverse movement situations for clinical applications. Methods: In this work, the EEG of 10 healthy volunteers was recorded while fingers were moved passively under different kinetic and kinematic conditions for proprioceptive stimulation. For the kinetics aspect, afferent brain activity (no simultaneous volition) was compared under two conditions of finger extension: (1) generated by an orthosis and (2) generated by the orthosis simultaneously combined and assisted with functional electrical stimulation (FES) applied at the forearm muscles related to finger extension. For the kinematic aspect, the finger extension was divided into two phases: (1) dynamic extension and (2) static extension (holding the extended position). Results: In the kinematic aspect, both mu and beta rhythms were more suppressed during a dynamic than a static condition. However, only the mu rhythm showed a significant difference between kinetic conditions (with and without FES) affected by attention to proprioception after transitioning from dynamic to static state, but the beta rhythm was not. Discussion: Our results indicate that mu rhythm was influenced considerably by muscle kinetics during finger movement produced by external devices, which has relevant implications for the design of neuromodulation and neurorehabilitation interventions.Item Coupling BCI and cortical stimulation for brain-state-dependent stimulation: Methods for spectral estimation in the presence of stimulation after-effects(2012-11-16) Walter, Armin; Murguialday, Ander R.; Rosenstiel, Wolfgang; Birbaumer, Niels; Bogdan, Martin; Medical TechnologiesBrain-state-dependent stimulation (BSDS) combines brain-computer interfaces (BCIs) and cortical stimulation into one paradigm that allows the online decoding for example of movement intention from brain signals while simultaneously applying stimulation. If the BCI decoding is performed by spectral features, stimulation after-effects such as artefacts and evoked activity present a challenge for a successful implementation of BSDS because they can impair the detection of targeted brain states. Therefore, efficient and robust methods are needed to minimize the influence of the stimulation-induced effects on spectral estimation without violating the real-time constraints of the BCI. In this work, we compared four methods for spectral estimation with autoregressive (AR) models in the presence of pulsed cortical stimulation. Using combined EEG-TMS (electroencephalography-transcranial magnetic stimulation) as well as combined electrocorticography (ECoG) and epidural electrical stimulation, three patients performed a motor task using a sensorimotor-rhythm BCI. Three stimulation paradigms were varied between sessions: (1) no stimulation, (2) single stimulation pulses applied independently (open-loop), or (3) coupled to the BCI output (closed-loop) such that stimulation was given only while an intention to move was detected using neural data. We found that removing the stimulation after-effects by linear interpolation can introduce a bias in the estimation of the spectral power of the sensorimotor rhythm, leading to an overestimation of decoding performance in the closed-loop setting. We propose the use of the Burg algorithm for segmented data to deal with stimulation after-effects. This work shows that the combination of BCIs controlled with spectral features and cortical stimulation in a closed-loop fashion is possible when the influence of stimulation after-effects on spectral estimation is minimized.Item Decoding of motor intentions from epidural ECoG recordings in severely paralyzed chronic stroke patients(2014-12-01) Spüler, M.; Walter, A.; Ramos-Murguialday, A.; Naros, G.; Birbaumer, N.; Gharabaghi, A.; Rosenstiel, W.; Bogdan, M.; Medical TechnologiesObjective. Recently, there have been several approaches to utilize a brain-computer interface (BCI) for rehabilitation with stroke patients or as an assistive device for the paralyzed. In this study we investigated whether up to seven different hand movement intentions can be decoded from epidural electrocorticography (ECoG) in chronic stroke patients. Approach. In a screening session we recorded epidural ECoG data over the ipsilesional motor cortex from four chronic stroke patients who had no residual hand movement. Data was analyzed offline using a support vector machine (SVM) to decode different movement intentions. Main results. We showed that up to seven hand movement intentions can be decoded with an average accuracy of 61% (chance level 15.6%). When reducing the number of classes, average accuracies up to 88% can be achieved for decoding three different movement intentions. Significance. The findings suggest that ipsilesional epidural ECoG can be used as a viable control signal for BCI-driven neuroprosthesis. Although patients showed no sign of residual hand movement, brain activity at the ipsilesional motor cortex still shows enough intention-related activity to decode different movement intentions with sufficient accuracy.Item Erratum: Coupling BCI and cortical stimulation for brain-state-dependent stimulation: Methods for spectral estimation in the presence of stimulation after-effects(2013-01-09) Walter, Armin; Murguialday, Ander Ramos; Rosenstiel, Wolfgang; Birbaumer, Niels; Bogdan, Martin; Medical TechnologiesItem Functional synergy recruitment index as a reliable biomarker of motor function and recovery in chronic stroke patients(2021-05-18) Irastorza-Landa, Nerea; García-Cossio, Eliana; Sarasola-Sanz, Andrea; Brötz, Doris; Birbaumer, Niels; Ramos-Murguialday, Ander; Tecnalia Research & Innovation; Medical TechnologiesObjective. Stroke affects the expression of muscle synergies underlying motor control, most notably in patients with poorer motor function. The majority of studies on muscle synergies have conventionally approached this analysis by assuming alterations in the inner structures of synergies after stroke. Although different synergy-based features based on this assumption have to some extent described pathological mechanisms in post-stroke neuromuscular control, a biomarker that reliably reflects motor function and recovery is still missing. Approach. Based on the theory of muscle synergies, we alternatively hypothesize that functional synergy structures are physically preserved and measure the temporal correlation between the recruitment profiles of healthy modules by paretic and healthy muscles, a feature hereafter reported as the FSRI. We measured clinical scores and extracted the muscle synergies of both ULs of 18 chronic stroke survivors from the electromyographic activity of 8 muscles during bilateral movements before and after 4 weeks of non-invasive BMI controlled robot therapy and physiotherapy. We computed the FSRI as well as features quantifying inter-limb structural differences and evaluated the correlation of these synergy-based measures with clinical scores. Main results. Correlation analysis revealed weak relationships between conventional features describing inter-limb synergy structural differences and motor function. In contrast, FSRI values during specific or combined movement data significantly correlated with UL motor function and recovery scores. Additionally, we observed that BMI-based training with contingent positive proprioceptive feedback led to improved FSRI values during the specific trained finger extension movement. Significance. We demonstrated that FSRI can be used as a reliable physiological biomarker of motor function and recovery in stroke, which can be targeted via BMI-based proprioceptive therapies and adjuvant physiotherapy to boost effective rehabilitation.Item Gene expression profiling of human gliomas reveals differences between GBM and LGA related to energy metabolism and notch signaling pathways(2007-05) Margareto, Javier; Leis, Olatz; Larrarte, Eider; Idoate, Miguel A.; Carrasco, Alejandro; Lafuente, José Vicente; Genética; GeneralesHuman malignant astrocytic tumors are the most common primary brain malignancies. Human gliomas are classified according to the extent of anaplasia or 'de-differentiation' appearance. Although this type of histological classification is widely accepted, the extensive heterogeneity of astrocytic tumors has made their pathological classification rather difficult. New genome-scale high throughput technologies for gene expression profiling, such as DNA microarrays, are emerging as new tools to allow a more accurate identification and characterization of different tumor degrees by discovering new specific markers and pathways of each stage. Present work reports interesting results that might be useful to differentiate between tumor grades. Data presented here provides new evidences about the molecular basis underlying different tumor stages. In this sense, we identified key metabolic pathways, crucial for tumor progression, as being differentially regulated in different tumor stages. On the other hand, remarkable findings regarding Notch pathway are reported, as some members of this receptor family were found to be differentially expressed depending on the malignancy degree. Our results clearly point out important molecular differences between different tumor stages and suggest that more studies are needed to understand specific molecular events characteristic of each stage. These types of studies represent a first step to deepen into the tumor physiology, which may potentially help for better and a more precise diagnosis of gliomas.Item How Tilting the Head Interferes With Eye-Hand Coordination: The Role of Gravity in Visuo-Proprioceptive, Cross-Modal Sensory Transformations: The Role of Gravity in Visuo-Proprioceptive, Cross-Modal Sensory Transformations(2022-03-10) Bernard-Espina, Jules; Dal Canto, Daniele; Beraneck, Mathieu; McIntyre, Joseph; Tagliabue, Michele; Tecnalia Research & Innovation; Robótica MédicaTo correctly position the hand with respect to the spatial location and orientation of an object to be reached/grasped, visual information about the target and proprioceptive information from the hand must be compared. Since visual and proprioceptive sensory modalities are inherently encoded in a retinal and musculo-skeletal reference frame, respectively, this comparison requires cross-modal sensory transformations. Previous studies have shown that lateral tilts of the head interfere with the visuo-proprioceptive transformations. It is unclear, however, whether this phenomenon is related to the neck flexion or to the head-gravity misalignment. To answer to this question, we performed three virtual reality experiments in which we compared a grasping-like movement with lateral neck flexions executed in an upright seated position and while lying supine. In the main experiment, the task requires cross-modal transformations, because the target information is visually acquired, and the hand is sensed through proprioception only. In the other two control experiments, the task is unimodal, because both target and hand are sensed through one, and the same, sensory channel (vision and proprioception, respectively), and, hence, cross-modal processing is unnecessary. The results show that lateral neck flexions have considerably different effects in the seated and supine posture, but only for the cross-modal task. More precisely, the subjects’ response variability and the importance associated to the visual encoding of the information significantly increased when supine. We show that these findings are consistent with the idea that head-gravity misalignment interferes with the visuo-proprioceptive cross-modal processing. Indeed, the principle of statistical optimality in multisensory integration predicts the observed results if the noise associated to the visuo-proprioceptive transformations is assumed to be affected by gravitational signals, and not by neck proprioceptive signals per se. This finding is also consistent with the observation of otolithic projections in the posterior parietal cortex, which is involved in the visuo-proprioceptive processing. Altogether these findings represent a clear evidence of the theorized central role of gravity in spatial perception. More precisely, otolithic signals would contribute to reciprocally align the reference frames in which the available sensory information can be encoded.Item Integrated and flexible multichannel interface for electrotactile stimulation(2016-06-14) Štrbac, Matija; Belić, Minja; Isaković, Milica; Kojić, Vladimir; Bijelić, Goran; Popović, Igor; Radotić, Milutin; Došen, Strahinja; Marković, Marko; Farina, Dario; Keller, Thierry; SG; Mercado; Tecnalia Research & InnovationObjective. The aim of the present work was to develop and test a flexible electrotactile stimulation system to provide real-time feedback to the prosthesis user. The system requirements were to accommodate the capabilities of advanced multi-DOF myoelectric hand prostheses and transmit the feedback variables (proprioception and force) using intuitive coding, with high resolution and after minimal training. Approach. We developed a fully-programmable and integrated electrotactile interface supporting time and space distributed stimulation over custom designed flexible array electrodes. The system implements low-level access to individual stimulation channels as well as a set of high-level mapping functions translating the state of a multi-DoF prosthesis (aperture, grasping force, wrist rotation) into a set of predefined dynamic stimulation profiles. The system was evaluated using discrimination tests employing spatial and frequency coding (10 able-bodied subjects) and dynamic patterns (10 able-bodied and 6 amputee subjects). The outcome measure was the success rate (SR) in discrimination. Main results. The more practical electrode with the common anode configuration performed similarly to the more usual concentric arrangement. The subjects could discriminate six spatial and four frequency levels with SR >90% after a few minutes of training, whereas the performance significantly deteriorated for more levels. The dynamic patterns were intuitive for the subjects, although amputees showed lower SR than able-bodied individuals (86% 10% versus 99% 3%). Significance. The tests demonstrated that the system was easy to setup and apply. The design and resolution of the multipad electrode was evaluated. Importantly, the novel dynamic patterns, which were successfully tested, can be superimposed to transmit multiple feedback variables intuitively and simultaneously. This is especially relevant for closing the loop in modern multifunction prostheses. Therefore, the proposed system is convenient for practical applications and can be used to implement sensory perception training and/or closed-loop control of myoelectric prostheses, providing grasping force and proprioceptive feedback.Item Metastable Resting State Brain Dynamics(2019-09-06) beim Graben, Peter; Jimenez-Marin, Antonio; Diez, Ibai; Cortes, Jesus M.; Desroches, Mathieu; Rodrigues, Serafim; Tecnalia Research & InnovationMetastability refers to the fact that the state of a dynamical system spends a large amount of time in a restricted region of its available phase space before a transition takes place, bringing the system into another state from where it might recur into the previous one. beim Graben and Hutt (2013) suggested to use the recurrence plot (RP) technique introduced by Eckmann et al. (1987) for the segmentation of system's trajectories into metastable states using recurrence grammars. Here, we apply this recurrence structure analysis (RSA) for the first time to resting-state brain dynamics obtained from functional magnetic resonance imaging (fMRI). Brain regions are defined according to the brain hierarchical atlas (BHA) developed by Diez et al. (2015), and as a consequence, regions present high-connectivity in both structure (obtained from diffusion tensor imaging) and function (from the blood-level dependent-oxygenation—BOLD—signal). Remarkably, regions observed by Diez et al. were completely time-invariant. Here, in order to compare this static picture with the metastable systems dynamics obtained from the RSA segmentation, we determine the number of metastable states as a measure of complexity for all subjects and for region numbers varying from 3 to 100. We find RSA convergence toward an optimal segmentation of 40 metastable states for normalized BOLD signals, averaged over BHA modules. Next, we build a bistable dynamics at population level by pooling 30 subjects after Hausdorff clustering. In link with this finding, we reflect on the different modeling frameworks that can allow for such scenarios: heteroclinic dynamics, dynamics with riddled basins of attraction, multiple-timescale dynamics. Finally, we characterize the metastable states both functionally and structurally, using templates for resting state networks (RSNs) and the automated anatomical labeling (AAL) atlas, respectively.Item Modeling neural differentiation on micropatterned substrates coated with neural matrix components(2012-03-14) García-Parra, Patricia; Cavaliere, Fabio; Maroto, Marcos; Bilbao, Leire; Obieta, Isabel; de Munain, Adolfo López; Álava, José Iñaki; Izeta, Ander; PRINTEX; Tecnalia Research & InnovationTopographical and biochemical characteristics of the substrate are critical for neuronal differentiation including axonal outgrowth and regeneration of neural circuits in vivo. Contact stimuli and signaling molecules allow neurons to develop and stabilize synaptic contacts. Here we present the development, characterization and functional validation of a new polymeric support able to induce neuronal differentiation in both PC12 cell line and adult primary skin-derived precursor cells (SKPs) in vitro. By combining a photolithographic technique with use of neural extracellular matrix (ECM) as a substrate, a biocompatible and efficient microenvironment for neuronal differentiation was developed.Item On the extraction of purely motor EEG neural correlates during an upper limb visuomotor task(2022-10-01) Bibián, Carlos; Irastorza-Landa, Nerea; Schönauer, Monika; Birbaumer, Niels; López-Larraz, Eduardo; Ramos-Murguialday, Ander; Medical TechnologiesDeciphering and analyzing the neural correlates of different movements from the same limb using electroencephalography (EEG) would represent a notable breakthrough in the field of sensorimotor neurophysiology. Functional movements involve concurrent posture co-ordination and head and eye movements, which create electrical activity that affects EEG recordings. In this paper, we revisit the identification of brain signatures of different reaching movements using EEG and present, test, and validate a protocol to separate the effect of head and eye movements from a reaching task-related visuomotor brain activity. Ten healthy participants performed reaching movements under two different conditions: avoiding head and eye movements and moving with no constrains. Reaching movements can be identified from EEG with unconstrained eye and head movement, whereas the discriminability of the signals drops to chance level otherwise. These results show that neural patterns associated with different arm movements could only be extracted from EEG if the eye and head movements occurred concurrently with the task, polluting the recordings. Although these findings do not imply that brain correlates of reaching directions cannot be identified from EEG, they show the consequences that ignoring these events can have in any EEG study that includes a visuomotor task.Item Optimizing genipin concentration for corneal collagen cross-linking: An ex vivo study(2018-07-01) Gharaibeh, Almutez M.; Saez, Virginia; Garcia, Nerea; Bataille, Laurent; Alió, Jorge L.; BiomaterialesPurpose: Studying genipin variable concentrations, treatment durations, and delivery methods as a substance to increase corneal stiffness by inducing corneal collagen cross-linking (CXL). Materials and Methods: 100 bovine corneas treated with different genipin concentrations (0.1, 0.5, and 1%) and treatment durations (15 min, 40 min, 2 h, and 3 days) through different delivery methods compared to 10 controls treated with riboflavin/UV. Histology examination, enzymatic digestion with collagenase and thermal differential scanning calorimetry were performed on the different samples. Results: Bovine corneas soaked in 0.5% genipin morphologically showed 4.7% CXL in comparison to 5.6% in controls (p < 0.05). Corneas treated with topical 0.5% genipin, by a 140-μL drop applied hourly for 2 h, showed 7% corneal CXL. Corneas treated with topical genipin 0.5% for 30 min, 1 and 2 h showed 54 ± 6, 40 ± 7, and 39 ± 9% enzymatic degradation, respectively, in comparison to controls (74%). Corneas treated with 0.5% genipin for 1, 2, and 8 h showed higher thermal denaturation resistance (Td values of 64.9 ± 0.3, 64.7 ± 0.0 and 67.3 ± 0.9), respectively, in comparison to the control group (64.6 ± 0.5) (p < 0.05). Conclusions: Genipin 0.5%, in a 140-μL drop applied hourly for 2 h, showed better potential to enhance corneal stiffness and stability through inducing CXL.Item Physiological modules for generating discrete and rhythmic movements: Action identification by a dynamic recurrent neural network(2014-09-17) Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M.; Dan, Bernard; McIntyre, Joseph; Cheron, Guy; Medical TechnologiesIn this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.