scholarly journals Analysis of an open source, closed-loop, realtime system for hippocampal sharp-wave ripple disruption

2018 ◽  
Author(s):  
Shayok Dutta ◽  
Etienne Ackermann ◽  
Caleb Kemere
Keyword(s):  
Open Source ◽  
Neural Activity ◽  
Closed Loop ◽  
Detection System ◽  
Detection Accuracy ◽  
Sharp Wave ◽  
Trade Offs ◽  
Wide Range ◽  
Realtime System

AbstractTransient neural activity pervades hippocampal electrophysiological activity. During more quiescent states, brief ≈100 ms periods comprising large ≈150–250 Hz oscillations known as sharp-wave ripples (SWR) which co-occur with ensemble bursts of spiking activity, are regularly found in local field potentials recorded from area CA1. SWRs and their concomitant neural activity are thought to be important for memory consolidation, recall, and memory-guided decision making. Temporally-selective manipulations of hippocampal neural activity upon online hippocampal SWR detection have been used as causal evidence of the importance of SWR for mnemonic process as evinced by behavioral and/or physiological changes. However, though this approach is becoming more wide spread, the performance trade-offs involved in building a SWR detection and disruption system have not been explored, limiting the design and interpretation of SWR detection experiments. We present an open source, plug-and-play, online ripple detection system with a detailed performance characterization. Our system has been constructed to interface with an open source software platform, Trodes, and two hardware acquisition platforms, Open Ephys and SpikeGadgets. We show that our in vivo results — approximately 80% detection latencies falling in between ≈20–66 ms with ≈2 ms closed-loop latencies while maintaining <10 false detections per minute — are dependent upon both algorithmic trade-offs and acquisition hardware. We discuss strategies to improve detection accuracy and potential limitations of online ripple disruptions. By characterizing this system in detail, we present a template for analyzing other closed-loop neural detection and perturbation systems. Thus, we anticipate our modular, open source, realtime system will facilitate a wide range of carefully-designed causal closed-loop neuroscience experiments.

scholarly journals Analysis of an open source, closed-loop, realtime system for hippocampal sharp-wave ripple disruption

2018 ◽  
Vol 16 (1) ◽  
pp. 016009
Author(s):  
Shayok Dutta ◽  
Etienne Ackermann ◽  
Caleb Kemere
Keyword(s):  
Open Source ◽  
Closed Loop ◽  
Sharp Wave ◽  
Realtime System

scholarly journals Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE)

2021 ◽  
Author(s):  
Mark Schatza ◽  
Ethan Blackwood ◽  
Sumedh Nagrale ◽  
Alik S Widge
Keyword(s):  
Open Source ◽  
Real Time ◽  
Closed Loop ◽  
Brain Activity ◽  
Loop Control ◽  
Oscillatory Phase ◽  
Wide Range ◽  
Real Time Tracking ◽  
Therapeutic Tools ◽  
And Behavior

Closing the loop between brain activity and behavior is one of the most active areas of development in neuroscience. There is particular interest in developing closed-loop control of neural oscillations. Many studies report correlations between oscillations and functional processes. Oscillation-informed closed-loop experiments might determine whether these relationships are causal and would provide important mechanistic insights which may lead to new therapeutic tools. These closed-loop perturbations require accurate estimates of oscillatory phase and amplitude, which are challenging to compute in real time. We developed an easy to implement, fast and accurate Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE). TORTE operates with the open-source Open Ephys GUI (OEGUI) system, making it immediately compatible with a wide range of acquisition systems and experimental preparations. TORTE efficiently extracts oscillatory phase and amplitude from a target signal and includes a variety of options to trigger closed-loop perturbations. Implementing these tools into existing experiments is easy and adds minimal latency to existing protocols. Most labs use in-house lab-specific approaches, limiting replication and extension of their experiments by other groups. Accuracy of the extracted analytic signal and accuracy of oscillation-informed perturbations with TORTE match presented results by these groups. However, TORTE provides access to these tools in a flexible, easy to use toolkit without requiring proprietary software. We hope that the availability of a high-quality, open-source, and broadly applicable toolkit will increase the number of labs able to perform oscillatory closed-loop experiments, and will improve the replicability of protocols and data across labs.

An Enhanced Approach for Number Plate Detection and Recognition

2020 ◽  
Vol 13 ◽  
Author(s):  
Diksha Kurchaniya ◽  
Mohd. Aquib Ansari ◽  
Durga Patel
Keyword(s):  
Character Recognition ◽  
High Speed ◽  
Detection System ◽  
Wiener Filter ◽  
Noise Removal ◽  
Motor Vehicles ◽  
Detection Accuracy ◽  
Morphological Operations ◽  
Wide Range ◽  
High Speed Vehicle

Introduction: The number of vehicles is increasing day by day in our life. The vehicle may violate traffic rules and cause accidents. The automatic number plate detection system (ANPR) plays a significant role to identify these vehicles. Number plate detection is very difficult sometimes because each country has its own format for representing the number plate and font types and sizes may also vary for different vehicles. The number of ANPR systems is available nowadays but still, it is a big problem to detect the number plate correctly in various scenarios like high-speed vehicle, number plate language, etc. Methods: In the development of this method, we mainly used wiener filter for noise removal, morphological operations for number plate localization, connected component algorithm for character segmentation, and template based matching for character recognition. Results: Our proposed methodology is providing promising results in terms of detection accuracy. Discussion: The automatic number plate detection system (ANPR) has wide range of applications because the license number is the crucial, commonly putative and essential identifier of motor vehicles. These applications include ticketless parking fee management, parking access automation, car theft prevention, security guide assistance, Motorway Road Tolling, Border Control, Journey Time Measurement, Law Enforcement and many more. Conclusion: In this paper, an enhanced approach of automatic number plate detection system is proposed using some different techniques which not only detect the number plate of the vehicle but also recognize each character present in the detected number plate image.

scholarly journals Rapid Motor Fluctuations Reveal Short-Timescale Neurophysiological Biomarkers of Parkinson’s Disease

2020 ◽  
Author(s):  
Minkyu Ahn ◽  
Shane Lee ◽  
Peter M. Lauro ◽  
Erin L. Schaeffer ◽  
Umer Akbar ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neural Activity ◽  
Motor Performance ◽  
Closed Loop ◽  
Oscillatory Activity ◽  
Patient Specific ◽  
Significant Information ◽  
Informative Signal ◽  
Wide Range

ABSTRACTIdentifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson’s Disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. Here, we recorded neural activity from the subthalamic nucleus (STN) of patients with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment. This approach leveraged natural motor performance variations as a basis to identify corresponding neurophysiological biomarkers. Using machine learning techniques, we show it was possible to use neural signals from the STN to decode the level of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic “β” oscillations, contributed to this decoding. While signals providing significant information about the quality of motor performance were found throughout the STN, the most informative signals tended to arise from locations in or near the dorsolateral, sensorimotor portion. Importantly, the informative patterns of neural oscillations were not fully generalizable across subjects, suggesting a patient-specific approach will be critical for optimal disease tracking and closed-loop neuromodulation.

scholarly journals Performance analysis of flow-based attacks detection on CSE-CIC-IDS2018 dataset using deep learning

2020 ◽  
Vol 20 (3) ◽  
pp. 1413
Author(s):  
Rawaa Ismael Farhan ◽  
Abeer Tariq Maolood ◽  
Nidaa Flaih Hassan
Keyword(s):  
Deep Learning ◽  
Cyber Security ◽  
Detection System ◽  
Detection Accuracy ◽  
Deep Model ◽  
Normal Behavior ◽  
Wide Range ◽  
High Level ◽  
Communications System ◽  
The Internet Of Things

<p>The emergence of the Internet of Things (IOT) as a result of the development of the communications system has made the study of cyber security more important. Day after day, attacks evolve and new attacks are emerged. Hence, network anomaly-based intrusion detection system is become very important, which plays an important role in protecting the network through early detection of attacks. Because of the development in  machine learning and the emergence of deep learning field,  and its ability to extract high-level features with high accuracy, made these systems involved to be worked with  real network traffic CSE-CIC-IDS2018 with a wide range of intrusions and normal behavior is an ideal way for testing and evaluation . In this paper , we  test and evaluate our  deep model (DNN) which achieved good detection accuracy about  90% .</p>

scholarly journals Toughening mechanisms for the attachment of architectured materials: The mechanics of the tendon enthesis

2021 ◽  
Author(s):  
Mikhail Golman ◽  
Adam C Abraham ◽  
Iden Kurtaliaj ◽  
Brittany P Marshall ◽  
Yizhong Jenny Hu ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Mouse Model ◽  
Energy Absorption ◽  
Protein Denaturation ◽  
Simultaneous Observation ◽  
In Vivo Models ◽  
Trade Offs ◽  
Wide Range ◽  
Architectured Materials

Architectured materials offer tailored mechanical properties but are limited in engineering applications due to challenges in maintaining toughness across their attachments. The enthesis connects tendon and bone, two vastly different architectured materials, and exhibits toughness across a wide range of loadings. Understanding the mechanisms by which this is achieved could inform the development of engineered attachments. Integrating experiments, simulations, and novel imaging that enabled simultaneous observation of mineralized and unmineralized tissues, we identified putative mechanisms of enthesis toughening in a mouse model and then manipulated these mechanisms via in vivo control of mineralization and architecture. Imaging uncovered a fibrous architecture within the enthesis that controls trade-offs between strength and toughness. In vivo models of pathology revealed architectural adaptations that optimize these trade-offs through cross-scale mechanisms including nanoscale protein denaturation, milliscale load-sharing, and macroscale energy absorption. Results suggest strategies for optimizing architecture for tough bimaterial attachments in medicine and engineering.

scholarly journals Learning to Control the Brain through Adaptive Closed-Loop Patterned Stimulation

2020 ◽  
Author(s):  
Sina Tafazoli ◽  
Camden J. MacDowell ◽  
Zongda Che ◽  
Katherine C. Letai ◽  
Cynthia Steinhardt ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Visual Stimulus ◽  
Neural Activity ◽  
Closed Loop ◽  
Neural Response ◽  
Learning System ◽  
Clinical Tool ◽  
Neuropsychiatric Diseases ◽  
Natural Response

AbstractStimulation of neural activity is an important scientific and clinical tool, causally testing hypotheses and treating neurodegenerative and neuropsychiatric diseases. However, current stimulation approaches cannot flexibly control the pattern of activity in populations of neurons. To address this, we developed an adaptive, closed-loop stimulation (ACLS) system that uses patterned, multi-site electrical stimulation to control the pattern of activity in a population of neurons. Importantly, ACLS is a learning system; it monitors the response to stimulation and iteratively updates the stimulation pattern to produce a specific neural response. In silico and in vivo experiments showed ACLS quickly learns to produce specific patterns of neural activity (∼15 minutes) and was robust to noise and drift in neural responses. In visual cortex of awake mice, ACLS learned electrical stimulation patterns that produced responses similar to the natural response evoked by visual stimuli. Similar to how repetition of a visual stimulus causes an adaptation in the neural response, the response to electrical stimulation was adapted when it was preceded by the associated visual stimulus. Altogether, our results show ACLS can learn, in real-time, to generate specific patterns of neural activity, providing a framework for using closed-loop learning to control neural activity.

scholarly journals Automated analysis of sleep in adult C. elegans with closed-loop assessment of state-dependent neural activity

2019 ◽  
Author(s):  
Daniel E. Lawler ◽  
Yee Lian Chew ◽  
Josh D. Hawk ◽  
Ahmad Aljobeh ◽  
William R. Schafer ◽  
...  
Keyword(s):  
Neural Activity ◽  
Closed Loop ◽  
Detection System ◽  
Automated Analysis ◽  
Simultaneous Recording ◽  
Neural Responses ◽  
Sleep Behavior ◽  
C Elegans ◽  
State Dependent ◽  
Genetic Perturbations

AbstractSleep, a state of quiescence associated with growth and restorative processes, is conserved across species. Invertebrates including the nematode Caenorhabditis elegans exhibit sleep-like states during development and periods of satiety and stress. Here we describe two methods to study behavior and associated neural activity during sleep and awake states in adult C. elegans. A large microfluidic device facilitates population-wide assessment of long-term sleep behavior over 12 h, including effects of fluid flow, oxygen, feeding, odors, and genetic perturbations. Smaller devices allow simultaneous recording of sleep behavior and neuronal activity, and a closed-loop sleep detection system delivers chemical stimuli to individual animals to assess sleep-dependent changes to neural responses. Sleep increased the arousal threshold to aversive chemical stimulation, yet sensory neuron (ASH) and first-layer interneuron (AIB) responses were unchanged. This localizes adult sleep-dependent neuromodulation within interneurons presynaptic to the AVA premotor interneurons, rather than afferent sensory circuits.

scholarly journals Precise spatial representations in the hippocampus of a food‑caching bird

2020 ◽  
Author(s):  
Hannah L. Payne ◽  
Galen F. Lynch ◽  
Dmitriy Aronov
Keyword(s):  
Neural Activity ◽  
Neural Circuit ◽  
Bird Species ◽  
Place Cells ◽  
Spatial Representations ◽  
Spatial Coding ◽  
Sharp Wave ◽  
Food Caching ◽  
Wide Range ◽  
Tufted Titmouse

SummaryThe hippocampus is an ancient neural circuit required for the formation of episodic memories. In mammals, this ability is thought to depend on well-documented patterns of neural activity, including place cells and sharp wave ripples. Notably, neither pattern has been found in non-mammals, despite compelling examples of episodic-like memory across a wide range of vertebrates. Does episodic memory nonetheless have a universal implementation across distant neural systems? We addressed this question by recording neural activity in the hippocampus of the tufted titmouse – an intense memory specialist from a food-caching family of birds. These birds cache large numbers of food items at scattered, concealed locations and use hippocampus-dependent memory to retrieve their caches. We found remarkably precise spatial representations akin to classic place cells, as well as sharp wave ripples, in the titmouse hippocampus. These patterns were organized along similar anatomical axes to those found in mammals. In contrast, spatial coding was weaker in a different, non-food-caching bird species. Our findings suggest a striking conservation of hippocampal mechanisms across distant vertebrates, in spite of vastly divergent anatomy and cytoarchitecture. At the same time, these results demonstrate that the exact implementation of such common mechanisms may conform to the unique ethological needs of different species.

Evaluation of 99mTc-Label led Vitamin K4 as an Agent for Testicular Imaging

1991 ◽  
Vol 30 (01) ◽  
pp. 35-39 ◽  
Author(s):  
H. S. Durak ◽  
M. Kitapgi ◽  
B. E. Caner ◽  
R. Senekowitsch ◽  
M. T. Ercan
Keyword(s):  
Soft Tissue ◽  
Room Temperature ◽  
Normal Subjects ◽  
Left Testis ◽  
Wide Range ◽  
Activity Ratios ◽  
The Right ◽  
Radioactivity Levels

Vitamin K4 was labelled with 99mTc with an efficiency higher than 97%. The compound was stable up to 24 h at room temperature, and its biodistribution in NMRI mice indicated its in vivo stability. Blood radioactivity levels were high over a wide range. 10% of the injected activity remained in blood after 24 h. Excretion was mostly via kidneys. Only the liver and kidneys concentrated appreciable amounts of radioactivity. Testis/soft tissue ratios were 1.4 and 1.57 at 6 and 24 h, respectively. Testis/blood ratios were lower than 1. In vitro studies with mouse blood indicated that 33.9 ±9.6% of the radioactivity was associated with RBCs; it was washed out almost completely with saline. Protein binding was 28.7 ±6.3% as determined by TCA precipitation. Blood clearance of 99mTc-l<4 in normal subjects showed a slow decrease of radioactivity, reaching a plateau after 16 h at 20% of the injected activity. In scintigraphic images in men the testes could be well visualized. The right/left testis ratio was 1.08 ±0.13. Testis/soft tissue and testis/blood activity ratios were highest at 3 h. These ratios were higher than those obtained with pertechnetate at 20 min post injection.99mTc-l<4 appears to be a promising radiopharmaceutical for the scintigraphic visualization of testes.

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