scholarly journals Repurposing a digital kitchen scale for neuroscience research: a complete hardware and software cookbook for PASTA

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
D. Virag ◽  
J. Homolak ◽  
I. Kodvanj ◽  
A. Babic Perhoc ◽  
A. Knezovic ◽  
...  
Keyword(s):  
Low Cost ◽  
Sampling Rate ◽  
Acoustic Startle ◽  
Sensorimotor Gating ◽  
R Package ◽  
Open Science ◽  
Breathing Patterns ◽  
Experimental Protocol ◽  
Neuroscience Research ◽  
Software Codes

AbstractWidely available low-cost electronics encourage the development of open-source tools for neuroscientific research. In recent years, many neuroscientists recognized the open science movement for its potential to stimulate and encourage science that is less focused on money, and more on robustness, validity, questioning and understanding. Here, we wanted to contribute to this global community by creating a research platform based on a common digital kitchen scale. This everyday ordinary kitchen tool is sometimes used in neuroscience research in various ways; however, its use is limited by sampling rate and inability to store and analyze data. To tackle this problem we developed a Platform for Acoustic STArtle or PASTA. This robust and simple platform enables users to obtain data from kitchen scale load cells at a high sampling rate, store it and analyze it. Here, we used it to analyze acoustic startle and prepulse inhibition sensorimotor gating in rats treated intracerebroventricularly with streptozotocin, but the system can be easily modified and upgraded for other purposes. In accordance with open science principles, we shared complete hardware design with instructions. Furthermore, we also disclose our software codes written for PASTA data acquisition (C++, Arduino) and acoustic startle experimental protocol (Python) and analysis (ratPASTA R package—R-based Awesome Toolbox for PASTA, and pastaWRAP—Python wrapper package for ratPASTA). To further encourage the development of our PASTA platform we demonstrate its sensitivity by using PASTA-gathered data to extract breathing patterns during rat freezing behavior in our experimental protocol.

scholarly journals Repurposing a digital kitchen scale for neuroscience research: a complete hardware and software cookbook for PASTA

2020 ◽  
Author(s):  
D Virag ◽  
J Homolak ◽  
I Kodvanj ◽  
A Babic Perhoc ◽  
A Knezovic ◽  
...  
Keyword(s):  
Low Cost ◽  
Sampling Rate ◽  
Acoustic Startle ◽  
Sensorimotor Gating ◽  
R Package ◽  
Open Science ◽  
Breathing Patterns ◽  
Experimental Protocol ◽  
Neuroscience Research ◽  
Software Codes

AbstractWidely available low-cost electronics encourage the development of open-source tools for neuroscientific research. In recent years, many neuroscientists recognized the open science movement for its potential to stimulate and encourage science that is less focused on money, and more on robustness, validity, questioning and understanding. Here, we wanted to contribute to this global community by creating a research platform based on a common digital kitchen scale. This everyday ordinary kitchen tool is sometimes used in neuroscience research in various ways; however, its use is limited by sampling rate and inability to store and analyze data. To tackle this problem we developed a Platform for Auditory STArtle or PASTA. This robust and simple platform enables users to obtain data from kitchen scale load cells at a high sampling rate, store it and analyze it. Here, we used it to analyze acoustic startle and prepulse inhibition sensorimotor gating in rats treated intracerebroventricularly with streptozotocin, but the system can be easily modified and upgraded for other purposes. In accordance with open science principles, we shared complete hardware design with instructions. Furthermore, we also disclose our software codes written for PASTA data acquisition (C++, Arduino) and acoustic startle experimental protocol (Python) and analysis (R-based Awesome Toolbox for PASTA, ratPASTA R package). To further encourage the development of our PASTA platform we demonstrate its sensitivity by using PASTA-gathered data to extract breathing patterns during rat freezing behavior in our experimental protocol.

Embracing Collisions to Increase Fidelity of Sensing Systems with COTS Tags

2021 ◽  
Vol 5 (2) ◽  
pp. 1-20
Author(s):  
Jiaqi Xu ◽  
Wei Sun ◽  
Kannan Srinivasan
Keyword(s):  
Low Cost ◽  
Sampling Rate ◽  
Identification Algorithm ◽  
Current Standard ◽  
Tag Identification ◽  
Rfid Systems ◽  
Passive Tags ◽  
Sensing Systems ◽  
Channel Diversity ◽  
Channel Information

RFID techniques have been extensively used in sensing systems due to their low cost. However, limited by the structural simplicity, collision is one key issue which is inevitable in RFID systems, thus limiting the accuracy and scalability of such sensing systems. Existing anti-collision techniques try to enable parallel decoding without sensing based applications in mind, which can not operate on COTS RFID systems. To address the issue, we propose COFFEE, which enables parallel channel estimation of COTS passive tags by harnessing the collision. We revisit the physical layer design of current standard. By exploiting the characteristics of low sampling rate and channel diversity of RFID tags, we separate the collided data and extract the channels of the collided tags. We also propose a tag identification algorithm which explores history channel information and identify the tags without decoding. COFFEE is compatible with current COTS RFID standards which can be applied to all RFID-based sensing systems without any modification on tag side. To evaluate the real world performance of our system, we build a prototype and conduct extensive experiments. The experimental results show that we can achieve up to 7.33x median time resolution gain for the best case and 3.42x median gain on average.

scholarly journals WORCS: A workflow for open reproducible code in science

Data Science ◽  
2021 ◽  
pp. 1-21
Author(s):  
Caspar J. Van Lissa ◽  
Andreas M. Brandmaier ◽  
Loek Brinkman ◽  
Anna-Lena Lamprecht ◽  
Aaron Peikert ◽  
...  
Keyword(s):  
Best Practices ◽  
Source Code ◽  
R Package ◽  
Open Science ◽  
Research Projects ◽  
Tabular Data ◽  
Step Procedure ◽  
Starting Point ◽  
Conducting Research ◽  
And Training

Adopting open science principles can be challenging, requiring conceptual education and training in the use of new tools. This paper introduces the Workflow for Open Reproducible Code in Science (WORCS): A step-by-step procedure that researchers can follow to make a research project open and reproducible. This workflow intends to lower the threshold for adoption of open science principles. It is based on established best practices, and can be used either in parallel to, or in absence of, top-down requirements by journals, institutions, and funding bodies. To facilitate widespread adoption, the WORCS principles have been implemented in the R package worcs, which offers an RStudio project template and utility functions for specific workflow steps. This paper introduces the conceptual workflow, discusses how it meets different standards for open science, and addresses the functionality provided by the R implementation, worcs. This paper is primarily targeted towards scholars conducting research projects in R, conducting research that involves academic prose, analysis code, and tabular data. However, the workflow is flexible enough to accommodate other scenarios, and offers a starting point for customized solutions. The source code for the R package and manuscript, and a list of examplesof WORCS projects, are available at https://github.com/cjvanlissa/worcs.

scholarly journals Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2480
Author(s):  
Isidoro Ruiz-García ◽  
Ismael Navarro-Marchal ◽  
Javier Ocaña-Wilhelmi ◽  
Alberto J. Palma ◽  
Pablo J. Gómez-López ◽  
...  
Keyword(s):  
Data Fusion ◽  
Reference System ◽  
Inertial Sensor ◽  
Low Cost ◽  
Sampling Rate ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Improve Technique ◽  
Worst Case ◽  
Sensor Data Fusion

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

Impaired sensorimotor gating of the acoustic startle response in the prodrome of schizophrenia

2008 ◽  
Vol 23 ◽  
pp. S70 ◽  
Author(s):  
B.B. Quednow ◽  
I. Frommann ◽  
J. Berning ◽  
K.U. Kühn ◽  
W. Maier ◽  
...  
Keyword(s):  
Startle Response ◽  
Acoustic Startle ◽  
Acoustic Startle Response ◽  
Sensorimotor Gating

scholarly journals Investigating Capnography Innovation for Better Patient Monitoring in the Resource Limited Surgical Setting

2018 ◽  
Vol 26 (1) ◽  
pp. 124-128 ◽  
Author(s):  
Maziar M. Nourian ◽  
Patrick Kolbay ◽  
Soeren Hoehne ◽  
Ahrash E. Poursaid ◽  
Ann E. Rowley ◽  
...  
Keyword(s):  
In Silico ◽  
Low Cost ◽  
Sampling Rate ◽  
Middle Income ◽  
Resource Limited ◽  
Industry Standards ◽  
Environmental Sensor ◽  
Available Technology ◽  
Surgical Setting ◽  
Lung Simulation

Background. Access to basic anesthetic monitoring in the developing world is lacking, which contributes to the 100 times greater anesthesia-related mortality in low- and middle-income countries. We hypothesize that an environmental sensor with a lower sampling rate could provide some clinical utility by providing CO2 levels, respiratory rate, and support in detection of clinical abnormalities. Materials and Methods. A bench-top lung simulation was created to replicate CO2 waveforms, and an environmental sensor was compared with industry-available technology. Sensor response time and respiratory rates were compared between devices. Additionally, an in silico model was created to replicate capnography pathology as waveforms would appear using the environmental sensor. Results and Conclusion. Breath simulations using the bench-top lung simulation produced similar results to industry standards with a degree of variability. Respiratory rates did not differ between the environmental sensor and all other devices tested. Finally, pathological waveforms created in silico carried a certain level of detail regarding ventilatory pathology, which could provide some clinical insight to an anesthesiologist. We believe our prototype is the first step toward making low-cost and portable capnography available in the resource-limited setting, and future efforts should focus on bridging the gap to safer anesthesia and surgery globally.

scholarly journals Optimizing smartphone-based canopy hemispherical photography

2021 ◽  
Author(s):  
Gastón Mauro Díaz
Keyword(s):  
Large Scale ◽  
Forest Canopy ◽  
Accuracy Assessment ◽  
Low Cost ◽  
R Package ◽  
Coefficient Of Determination ◽  
Native Forest ◽  
Hemispherical Photography ◽  
Area Index ◽  
Plant Area Index

1) Hemispherical photography (HP) is a long-standing tool for forest canopy characterization. Currently, there are low-cost fisheye lenses to convert smartphones into high-portable HP equipment; however, they cannot be used whenever since HP is sensitive to illumination conditions. To obtain sound results outside diffuse light conditions, a deep-learning-based system needs to be developed. A ready-to-use alternative is the multiscale color-based binarization algorithm, but it can provide moderate-quality results only for open forests. To overcome this limitation, I propose coupling it with the model-based local thresholding algorithm. I call this coupling the MBCB approach. 2) Methods presented here are part of the R package CAnopy IMage ANalysis (caiman), which I am developing. The accuracy assessment of the new MBCB approach was done with data from a pine plantation and a broadleaf native forest. 3) The coefficient of determination (R^2) was greater than 0.7, and the root mean square error (RMSE) lower than 20 %, both for plant area index calculation. 4) Results suggest that the new MBCB approach allows the calculation of unbiased canopy metrics from smartphone-based HP acquired in sunlight conditions, even for closed canopies. This facilitates large-scale and opportunistic sampling with hemispherical photography.

scholarly journals Inhibition of the Deep and Intermediate Layers of the Superior Colliculus Disrupts Sensorimotor Gating in Monkeys

2020 ◽  
Vol 14 ◽  
Author(s):  
Hannah F. Waguespack ◽  
Brittany L. Aguilar ◽  
Ludise Malkova ◽  
Patrick A. Forcelli
Keyword(s):  
Superior Colliculus ◽  
Startle Response ◽  
Basolateral Amygdala ◽  
Rhesus Macaques ◽  
Species Difference ◽  
Acoustic Startle ◽  
Acoustic Startle Response ◽  
Sensorimotor Gating ◽  
Intermediate Layers ◽  
Association Area

The deep and intermediate layers of the superior colliculus (DLSC) respond to visual, auditory, and tactile inputs and act as a multimodal sensory association area. In turn, activity in the DLSC can drive orienting and avoidance responses—such as saccades and head and body movements—across species, including in rats, cats, and non-human primates. As shown in rodents, DLSC also plays a role in regulating pre-pulse inhibition (PPI) of the acoustic startle response (ASR), a form of sensorimotor gating. DLSC lesions attenuate PPI and electrical stimulation of DLSC inhibits the startle response. While the circuitry mediating PPI is well-characterized in rodents, less is known about PPI regulation in primates. Two recent studies from our labs reported a species difference in the effects of pharmacological inhibition of the basolateral amygdala and substantia nigra pars reticulata (SNpr) on PPI between rats and macaques: in rats, inhibition of these structures decreased PPI, while in macaques, it increased PPI. Given that the SNpr sends direct inhibitory projections to DLSC, we next sought to determine if this species difference was similarly evident at the level of DLSC. Here, we transiently inactivated DLSC in four rhesus macaques by focal microinfusion of the GABAA receptor agonist muscimol. Similar to findings reported in rodents, we observed that bilateral inhibition of the DLSC in macaques significantly disrupted PPI. The impairment was specific to the PPI as the ASR itself was not affected. These results indicate that our previously reported species divergence at the level of the SNpr is not due to downstream differences at the level of the DLSC. Species differences at the level of the SNpr and basolateral amygdala emphasize the importance of studying the underlying circuitry in non-human primates, as impairment in PPI has been reported in several disorders in humans, including schizophrenia, autism, and PTSD.

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