Joao, Moreira
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Publication Open Access Oxfordshire Community Stroke Project Classification: A proposed automated algorithm(SAGE Publications, 2021-06-18) Andrade, Joao Brainer Clares de; Mohr, Jay P; Timbó, Felipe Brito; Nepomuceno, Camila Rodrigues; Moreira, João Vitor da Silva; Timbó, Isabelle da Costa Goes; Lima, Fabricio Oliveira; Silva, Gisele Sampaio; Bamford, JohnIntroduction: The Oxfordshire Community Stroke Project (OCSP) proposed a clinical classification for Stroke patients. This classification has proved helpful to predict the risk of neurological complications. However, the OCSP was initially based on findings on the neurological assesment, which can pose difficulties for classifying patients. We aimed to describe the development and the validation step of a computer-based algorithm based on the OCSP classification. Materials and methods: A flow-chart was created which was reviewed by five board-certified vascular neurologists from which a computer-based algorithm (COMPACT) was developed. Neurology residents from 12 centers were invited to participate in a randomized trial to assess the effect of using COMPACT. They answered a 20-item questionnaire for classifying the vignettes according to the OCSP classification. Each correct answer has been attributed to 1-point for calculating the final score. Results: Six-two participants agreed to participate and answered the questionnaire. Thirty-two were randomly allocated to use our algorithm, and thirty were allocated to adopt a list of symptoms alone. The group who adopted our algorithm had a median score of correct answers of 16.5[14.5, 17]/20 versus 15[13, 16]/20 points, p = 0.014. The use of our algorithm was associated with the overall rate of correct scores (p = 0.03). Discussion: Our algorithm seemed a useful tool for any postgraduate year Neurology resident. A computer-based algorithm may save time and improve the accuracy to classify these patients. Conclusion: An easy-to-use computer-based algorithm improved the accuracy of the OCSP classification, with the possible benefit of further improvement of the prediction of neurological complications and prognostication.Publication Open Access A mechanism for deviance detection and contextual routing in the thalamus: a review and theoretical proposal(Frontiers Media SA, 2024-02-29) Varela, Carmen; Moreira, Joao V. S.; Kocaoglu, Basak; Dura-Bernal, Salvador; Ahmad, SubutaiPredictive processing theories conceptualize neocortical feedback as conveying expectations and contextual attention signals derived from internal cortical models, playing an essential role in the perception and interpretation of sensory information. However, few predictive processing frameworks outline concrete mechanistic roles for the corticothalamic (CT) feedback from layer 6 (L6), despite the fact that the number of CT axons is an order of magnitude greater than that of feedforward thalamocortical (TC) axons. Here we review the functional architecture of CT circuits and propose a mechanism through which L6 could regulate thalamic firing modes (burst, tonic) to detect unexpected inputs. Using simulations in a model of a TC cell, we show how the CT feedback could support prediction-based input discrimination in TC cells by promoting burst firing. This type of CT control can enable the thalamic circuit to implement spatial and context selective attention mechanisms. The proposed mechanism generates specific experimentally testable hypotheses. We suggest that the L6 CT feedback allows the thalamus to detect deviance from predictions of internal cortical models, thereby supporting contextual attention and routing operations, a far more powerful role than traditionally assumed.Publication Embargo CLOSED-LOOP CONNECTIVITY BEST SUPPORTS INFORMATION PROCESSING AND SLEEP DYNAMICS IN THE MOUSE THALAMO-CORTICAL WHISKER PATHWAY: A COMPUTATIONAL STUDY(2025-06-27) Moreira, João Vitor da SilvaDespite recent advancements in mapping thalamic and cortical projections, the specific organization of intrathalamic connectivity remains elusive. Current experimental approaches cannot definitively determine whether these connections are arranged in reciprocal (closed-) or non-reciprocal (open-loop) circuits. Understanding the organization of intrathalamic projections could fundamentally reshape our view of thalamic processing. Closed-loop circuits may promote localized and recurrent processing, whereas open-loop circuits may facilitate broader integration of signals across thalamic regions. Computational modeling provides an alternative for probing the functional consequences of different intrathalamic architectures, circumventing experimental limitations. With this in mind, we developed a biophysically detailed multi-compartmental model of the mouse whisker pathway, built on anatomical and physiological data. Our goal was to determine whether closed- or open-loop connectivity can best reproduce key characteristics of cell and network responses in the mouse whisker pathway across wakefulness and sleep. We showed that closed-loop connectivity between the thalamocortical (TC) relay neurons in the ventral posteromedial nucleus and the inhibitory interneurons in the thalamic reticular nucleus (TRN) best reproduces thalamic spiking and local field potential responses across awake and sleep states. In this model, feedforward (TC→TRN) on-center projections (i.e., spatially aligned) regulate the angular tuning in the awake state, while on-center feedback (TRN→TC) supports spindle oscillations during sleep. We also showed that direct activation of closed-loop corticothalamic feedback (CT→TC and CT→TRN) by TC inputs can sharpen the angular tuning in the thalamus. These results underscore the importance of closed-loop connectivity in unifying wake and sleep dynamics, offering insights into how thalamo-cortical circuits balance precise sensory tuning with robust oscillatory rhythms across behavioral states.Publication Open Access Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics(Elsevier BV, 2023-06) Dura-Bernal, Salvador; Neymotin, Samuel A.; Suter, Benjamin A.; Dacre, Joshua; Moreira, Joao V.S.; Urdapilleta, Eugenio; Schiemann, Julia; Duguid, Ian; Shepherd, Gordon M.G.; Lytton, William W.Understanding cortical function requires studying multiple scales: molecular, cellular, circuit, and behavioral. We develop a multiscale, biophysically detailed model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity, and dendritic synapse locations are constrained by experimental data. The model includes long-range inputs from seven thalamic and cortical regions and noradrenergic inputs. Connectivity depends on cell class and cortical depth at sublaminar resolution. The model accurately predicts in vivo layer- and cell-type-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blockade and thalamus inactivation). We generate mechanistic hypotheses underlying the observed activity and analyzed low-dimensional population latent dynamics. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell-type-specific multiscale dynamics associated with several experimental conditions and behaviors.Publication Open Access Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics(Elsevier BV, 2023-11-28) Dura-Bernal, Salvador; Griffith, Erica Y.; Barczak, Annamaria; O’Connell, Monica N.; McGinnis, Tammy; Moreira, Joao V.S.; Schroeder, Charles E.; Lytton, William W.; Lakatos, Peter; Neymotin, Samuel A.We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded in vivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms.Publication Open Access Electromyography biofeedback system with visual and vibratory feedbacks designed for lower limb rehabilitation(Emerald, 2023-01-03) Moreira, Joao Vitor da Silva; Rodrigues, Karina; Pinheiro, Daniel José Lins Leal; Cardoso, Thaís; Vieira, João Luiz; Cavalheiro, Esper; Faber, JeanPurpose One of the main causes of long-term prosthetic abandonment is the lack of ownership over the prosthesis, which was caused mainly by the absence of sensory information regarding the lost limb. The period where the patient learns how to interact with a prosthetic device is critical in rehabilitation. This ideally happens within the first months after amputation, which is also a period associated with the consolidation of brain changes. Different studies have shown that the introduction of feedback mechanisms can be crucial to bypass the lack of sensorial information. To develop a biofeedback system for the rehabilitation of transfemoral amputees – controlled via electromyographic (EMG) activity from the leg muscles – that can provide real-time visual and/or vibratory feedback for the user. Design/methodology/approach The system uses surface EMG to control two feedback mechanisms, which are the knee joint of a prosthetic leg of a humanoid avatar in a virtual reality (VR) environment (visual feedback) and a matrix of 16 vibrotactile actuators placed in the back of the user (vibratory feedback). Data acquisition was inside a Faraday Cage using an OpenEphys® acquisition board for the surface EMG recordings. The tasks were performed on able-bodied participants, with no amputation, and for this, the dominant leg of the user was immobilized using an orthopedic boot fixed on the chair, allowing only isometric contractions of target muscles, according to the Surface EMG for Non-Invasive Assessment of Muscles (SENIAM) standard. The authors test the effectiveness of combining vibratory and visual feedback and how task difficulty affects overall performance. Findings The authors' results show no negative interference combining both feedback modalities and that performance peaked at the intermediate difficulty. These results provide powerful insights of what can be accomplished with the population of amputee people. By using this biofeedback system, the authors expect to engage another sensory modality in the process of spatial representation of a virtual leg, bypassing the lack of information associated with the disruption of afferent pathways following amputation. Research limitations/implications The authors developed a showcase with a new protocol and feedback mechanisms showing the protocol's safety, efficiency and reliability. However, since this system is designed for patients with leg amputation, the full extent of the effects of the biofeedback training can only be assessed after the evaluation with the amputees, and the results obtained so far establish a safe and operational protocol to accomplish this. Practical implications In this study, the authors proposed a new biofeedback device intended to be used in the preprosthetic rehabilitation phase for people with transfemoral amputation. With this new system, the authors propose a mechanism to bypass the lack of sensory information from a virtual prosthesis and help to assimilate visual and vibrotactile stimuli as a cue for movement representation. Social implications With this new system, the authors propose a mechanism to bypass the lack of sensory information from a virtual prosthesis and help to assimilate visual and vibrotactile stimuli as a cue for movement representation. Originality/value The authors' results show that all users were capable of recognizing both feedback modalities, both separate and combined, being able to respond accordingly throughout the tasks. The authors also show that for a one-session protocol, the last difficulty level imposed a greater challenge for most users, explained by the significant drop in performance disregarding the feedback modality. Lastly, the authors believe this paradigm can provide a better process for the embodiment of prosthetic devices, fulfilling the lack of sensory information for the users.Publication Open Access Embodiment of a virtual prosthesis through training using an EMG-based human-machine interface: Case series(Frontiers Media SA, 2022-08-04) Rodrigues, Karina Aparecida; Moreira, João Vitor da Silva; Pinheiro, Daniel José Lins Leal; Dantas, Rodrigo Lantyer Marques; Santos, Thaís Cardoso; Nepomuceno, João Luiz Vieira; Nogueira, Maria Angélica Ratier Jajah; Cavalheiro, Esper Abrão; Faber, JeanTherapeutic strategies capable of inducing and enhancing prosthesis embodiment are a key point for better adaptation to and acceptance of prosthetic limbs. In this study, we developed a training protocol using an EMG-based human-machine interface (HMI) that was applied in the preprosthetic rehabilitation phase of people with amputation. This is a case series with the objective of evaluating the induction and enhancement of the embodiment of a virtual prosthesis. Six men and a woman with unilateral transfemoral traumatic amputation without previous use of prostheses participated in the study. Participants performed a training protocol with the EMG-based HMI, composed of six sessions held twice a week, each lasting 30 mins. This system consisted of myoelectric control of the movements of a virtual prosthesis immersed in a 3D virtual environment. Additionally, vibrotactile stimuli were provided on the participant's back corresponding to the movements performed. Embodiment was investigated from the following set of measurements: skin conductance response (affective measurement), crossmodal congruency effect (spatial perception measurement), ability to control the virtual prosthesis (motor measurement), and reports before and after the training. The increase in the skin conductance response in conditions where the virtual prosthesis was threatened, recalibration of the peripersonal space perception identified by the crossmodal congruency effect, ability to control the virtual prosthesis, and participant reports consistently showed the induction and enhancement of virtual prosthesis embodiment. Therefore, this protocol using EMG-based HMI was shown to be a viable option to achieve and enhance the embodiment of a virtual prosthetic limb.Publication Open Access Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE.(2022-09-22) Borges, Fernando S; Moreira, Joao V S; Takarabe, Lavinia M; Lytton, William W; Dura-Bernal, SalvadorThe primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015, the Blue Brain Project (BBP) developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, and 37 million synapses, incorporating anatomical and physiological information from a wide range of experimental studies. We have implemented this highly detailed and complex S1 model in NetPyNE, using the data available in the Neocortical Microcircuit Collaboration Portal. NetPyNE provides a Python high-level interface to NEURON and allows defining complicated multiscale models using an intuitive declarative standardized language. It also facilitates running parallel simulations, automates the optimization and exploration of parameters using supercomputers, and provides a wide range of built-in analysis functions. This will make the S1 model more accessible and simpler to scale, modify and extend in order to explore research questions or interconnect to other existing models. Despite some implementation differences, the NetPyNE model preserved the original cell morphologies, electrophysiological responses and spatial distribution for all 207 cell types; and the connectivity properties of all 1941 pathways, including synaptic dynamics and short-term plasticity (STP). The NetPyNE S1 simulations produced reasonable physiological firing rates and activity patterns across all populations. When STP was included, the network generated a 1 Hz oscillation comparable to the original model -like state. By then reducing the extracellular calcium concentration, the model reproduced the original S1 -like states with asynchronous activity. These results validate the original study using a new modeling tool. Simulated local field potentials (LFPs) exhibited realistic oscillatory patterns and features, including distance- and frequency-dependent attenuation. The model was extended by adding thalamic circuits, including 6 distinct thalamic populations with intrathalamic, thalamocortical (TC) and corticothalamic connectivity derived from experimental data. The thalamic model reproduced single known cell and circuit-level dynamics, including burst and tonic firing modes and oscillatory patterns, providing a more realistic input to cortex and enabling study of TC interactions. Overall, our work provides a widely accessible, data-driven and biophysically-detailed model of the somatosensory TC circuits that can be employed as a community tool for researchers to study neural dynamics, function and disease.