Neural activity shaping in visual prostheses with deep learning.

OBJECTIVE: The visual perception provided by retinal prostheses is limited by the overlapping current spread of adjacent electrodes. This reduces the spatial resolution attainable with unipolar stimulation. Conversely, simultaneous multipolar stimulation guided by the measured neural responses - Neural Activity Shaping (NAS) - can attenuate excessive spread of excitation allowing for more precise control over the pattern of neural activation. However, predicting the results of a multipolar stimulus pattern is a challenging task. Previous attempts focused on analytical solutions based on an assumed linear nonlinear model of retinal response; an Analytical Model Inversion (AMI) approach. Here, we propose a model-free solution for NAS, using Artificial Neural Networks (ANNs) that could be trained with data acquired from the implant. APPROACH: Our method consists of two ANNs trained sequentially. The Measurement Predictor Network (MPN) is trained on data from the implant and is used to predict how the retina responds to multipolar stimulation. The Stimulus Generator Network (STG) is trained on a large dataset of natural images and uses the trained MPN to determine efficient multipolar stimulus patterns by learning its inverse model. We validate our method in silico using a realistic model of retinal response to multipolar stimulation. Main Results: We show that our ANN-based NAS approach produces sharper retinal activations than the conventional unipolar stimulation strategy. As a theoretical bench-mark of optimal NAS results, we implemented AMI stimulation by inverting the model used to simulate the retina. Our ANN strategy produced equivalent results to AMI, while not being restricted to any specific type of retina model and being three orders of magnitude more computationally efficient. SIGNIFICANCE: Our novel protocol provides a method for efficient and personalized retinal stimulation, which may improve the visual experience and quality of life of retinal prosthesis users. .

Disrupting abnormal neuronal oscillations with adaptive delayed feedback control.

Closed-loop neuronal stimulation has a strong therapeutic potential for neurological disorders such as Parkinson's disease. However, at the moment, standard stimulation protocols rely on continuous open-loop stimulation and the design of adaptive controllers is an active field of research. Delayed feedback control (DFC), a popular method used to control chaotic systems, has been proposed as a closed-loop technique for desynchronisation of neuronal populations but, so far, was only tested in computational studies. We implement DFC for the first time in neuronal populations and access its efficacy in disrupting unwanted neuronal oscillations. To analyse in detail the performance of this activity control algorithm, we used specialised in vitro platforms with high spatiotemporal monitoring/stimulating capabilities. We show that the conventional DFC in fact worsens the neuronal population oscillatory behaviour, which was never reported before. Conversely, we present an improved control algorithm, adaptive DFC (aDFC), which monitors the ongoing oscillation periodicity and self-tunes accordingly. aDFC effectively disrupts collective neuronal oscillations restoring a more physiological state. Overall, these results support aDFC as a better candidate for therapeutic closed-loop brain stimulation.

Memristor-Based Neuromodulation Device for Real-Time Monitoring and Adaptive Control of Neuronal Populations.

Neurons are specialized cells for information transmission and information processing. In fact, many neurologic disorders are directly linked not to cellular viability/homeostasis issues but rather to specific anomalies in electrical activity dynamics. Consequently, therapeutic strategies based on the direct modulation of neuronal electrical activity have been producing remarkable results, with successful examples ranging from cochlear implants to deep brain stimulation. Developments in these implantable devices are hindered, however, by important challenges such as power requirements, size factor, signal transduction, and adaptability/computational capabilities. Memristors, neuromorphic nanoscale electronic components able to emulate natural synapses, provide unique properties to address these constraints, and their use in neuroprosthetic devices is being actively explored. Here, we demonstrate, for the first time, the use of memristive devices in a clinically relevant setting where communication between two neuronal populations is conditioned to specific activity patterns in the source population. In our approach, the memristor device performs a pattern detection computation and acts as an artificial synapse capable of reversible short-term plasticity. Using in vitro hippocampal neuronal cultures, we show real-time adaptive control with a high degree of reproducibility using our monitor-compute-actuate paradigm. We envision very similar systems being used for the automatic detection and suppression of seizures in epileptic patients.

Trackosome: a computational toolbox to study the spatiotemporal dynamics of centrosomes, nuclear envelope and cellular membrane.

During the initial stages of mitosis, multiple mechanisms drive centrosome separation and positioning. How they are coordinated to promote centrosome migration to opposite sides of the nucleus remains unclear. Here, we present Trackosome, an open-source image analysis software for tracking centrosomes and reconstructing nuclear and cellular membranes, based on volumetric live-imaging data. The toolbox runs in MATLAB and provides a graphical user interface for easy access to the tracking and analysis algorithms. It provides detailed quantification of the spatiotemporal relationships between centrosomes, nuclear envelope and cellular membrane, and can also be used to measure the dynamic fluctuations of the nuclear envelope. These fluctuations are important because they are related to the mechanical forces exerted on the nucleus by its adjacent cytoskeletal structures. Unlike previous algorithms based on circular or elliptical approximations, Trackosome measures membrane movement in a model-free condition, making it viable for irregularly shaped nuclei. Using Trackosome, we demonstrate significant correlations between the movements of the centrosomes, and identify specific oscillation modes of the nuclear envelope. Overall, Trackosome is a powerful tool that can be used to help unravel new elements in the spatiotemporal dynamics of subcellular structures.

Centrosome-nuclear axis repositioning drives the assembly of a bipolar spindle scaffold to ensure mitotic fidelity.

During the initial stages of cell division, the cytoskeleton is extensively reorganized so that a bipolar mitotic spindle can be correctly assembled. This process occurs through the action of molecular motors, cytoskeletal networks, and the nucleus. How the combined activity of these different components is spatiotemporally regulated to ensure efficient spindle assembly remains unclear. To investigate how cell shape, cytoskeletal organization, and molecular motors cross-talk to regulate initial spindle assembly, we use a combination of micropatterning with high-resolution imaging and 3D cellular reconstruction. We show that during prophase, centrosomes and nucleus reorient so that centrosomes are positioned on the shortest nuclear axis at nuclear envelope (NE) breakdown. We also find that this orientation depends on a combination of centrosome movement controlled by Arp2/3-mediated regulation of microtubule dynamics and Dynein-generated forces on the NE that regulate nuclear reorientation. Finally, we observe this centrosome configuration favors the establishment of an initial bipolar spindle scaffold, facilitating chromosome capture and accurate segregation, without compromising division plane orientation.

Identification of a Carbonized Body Using Implanted Surgical Plates: The Importance of Computed Tomography.

In addition to clinical examination, forensic odontologists can use diagnostic imaging as an auxiliary method for identification. This paper reports a case where forensic odontologists from the Afrânio Peixoto Legal Medicine Institute in Rio de Janeiro (Brazil) positively identified a carbonized and partially calcined body using oral and maxillofacial imaging. The cadaver showed several metallic plates fixed with metallic screws on bones of the neurocranium and viscerocranium. Family members provided spiral computed tomography scans of the skull and a panoramic radiograph that were acquired after an accident that required surgical procedures. Comparative analysis between the clinical exam and the maxillofacial images demonstrated complete coincidence, confirming the victim's identity. Dactyloscopy, which is the most commonly used method of identification, was not possible because of the body carbonization. Thus, diagnostic imaging, especially computed tomography, was essential for elucidation of this case.

Osteopetrosis--a review and report of two cases.

We present a brief review of the rare condition of osteopetrosis together with two case reports of this disease in the same family affecting the jaws. The first in a 41-year-old woman, and the second in her 39-year-old brother. Plain films and computed tomography showed marked sclerosis of the affected bones with obliteration of the medullary cavities and thickening of the cortices as well as multiple absent and unerupted teeth. In addition radiographs showed discrete mixed radiopaque/radiolucent areas consistent with the appearance of fibro-cemento-osseous dysplasia, but which may also represent part of the overall spectrum of bone changes in osteopetrosis.