1,721,051 research outputs found
A low-noise, modular, and versatile analog front-end intended for processing in vitro neuronal signals detected by microelectrode arrays
Full text linkThe collection of good quality extracellular neuronal spikes from neuronal cultures coupled to Microelectrode Arrays (MEAs) is
a binding requirement to gather reliable data. Due to physical constraints, low power requirement, or the need of customizability,
commercial recording platforms are not fully adequate for the development of experimental setups integrating MEA technology
with other equipment needed to perform experiments under clima
te controlled conditions, like environmental chambers or cell
culture incubators. To address this issue, we developed a custom MEA interfacing system featuring low noise, low power, and
the capability to be readily integrated inside an incubator-like environment. Two stages, a preamplifier and a filter amplifier, were
designed, implemented on printed circuit boards, and tested. The system is characterized by a low input-referred noise (
<
1
휇
V
RMS), a high channel separation (
>
70 dB), and signal-to-noise ratio values of neuronal recordings comparable to those obtained
with the benchmark commercial MEA system. In addition, the system was successfully integrated with an environmental MEA
chamber, without harming cell cultures during experiments and without being damaged by the high humidity level. The devised
system is of practical value in the development of
in vitro
platforms to study temporally extended neuronal network dynamics by
means of MEAs
Spike detection algorithm improvement, spike waveform projections with PCA and hierarchical classification
No full textDevelopment and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices
No full textAssessment of breathing parameters using an inertial measurement unit (IMU)-based system
Full text linkBreathing frequency (f B ) is an important vital sign that—if appropriately monitored—may help to predict clinical adverse events. Inertial sensors open the door to the development of low-cost, wearable, and easy-to-use breathing-monitoring systems. The present paper proposes a new posture-independent processing algorithm for breath-by-breath extraction of breathing temporal parameters from chest-wall inclination change signals measured using inertial measurement units. An important step of the processing algorithm is dimension reduction (DR) that allows the extraction of a single respiratory signal starting from 4-component quaternion data. Three different DR methods are proposed and compared in terms of accuracy of breathing temporal parameter estimation, in a group of healthy subjects, considering different breathing patterns and different postures; optoelectronic plethysmography was used as reference system. In this study, we found that the method based on PCA-fusion of the four quaternion components provided the best f B estimation performance in terms of mean absolute errors (<2 breaths/min), correlation (r > 0.963) and Bland–Altman Analysis, outperforming the other two methods, based on the selection of a single quaternion component, identified on the basis of spectral analysis; particularly, in supine position, results provided by PCA-based method were even better than those obtained with the ideal quaternion component, determined a posteriori as the one providing the minimum estimation error. The proposed algorithm and system were able to successfully reconstruct the respiration-induced movement, and to accurately determine the respiratory rate in an automatic, position-independent manner
A Reliable Reversible Bonding Method to Perfuse Microfluidic Devices
No full textMicrofl uidic devices made of poly(dimethylsiloxane) (PDMS) are suitable for cell culture applications, mainly due to both the advantageous volume and surface properties of the material itself. Bulk properties include optical transparency, gas permeability, and ease of fabrication, to name a few. On the other hand, silanol groups (SiOH) present on the surface can be easily activated through air/oxygen plasma treatments, and used to permanently bond to other materials, like silicon, glass or PDMS. The importance of a standard sealing method with no need of additional gluing materials is crucial for microfl uidic applications, where micrometer sized channels and chambers are involved. Despite the reliability of the plasma treatment to permanently seal microfl uidic devices, reversible-bonding methods are sometimes desirable e.g., high magnifi cation microscopy, sample retrieval, and multiple usages of valuable substrates. For this purpose, common techniques rely either on weakening the plasma treatment (partial treatment, only involving one of the surfaces of interest) or on increasing the self-sealing properties of PDMS (by adjusting the ratio of pre-polymer and curing agent). However, the adhesion strength of these methods is low, thus making them suitable only for static or quasi-static conditions. Whenever there is the requirement for continuous perfusion, other techniques are needed. Here, we describe a PDMS microfl uidic device for long term culture of cells, which can be reversibly sealed to different fl at substrates. The hydraulic tightness is guaranteed through magnetic forces, being the substrate interposed between a permanent magnet and the microfl uidic device, locally enriched with ferromagnetic material. In particular, neuronal networks were grown within the device, reversibly coupled to a fl at Microelectrode Array (MEA). Thus, the proposed approach allows to combine the advantageous features of microfl uidics and the multiple use of commercial MEA substrates. Indeed, it allows for electrophysiological investigations in highly controlled microenvironments
Are We “Motorically” Wired to Others? High-Level Motor Computations and Their Role in Autism
No full text High-level motor computations reflect abstract components far apart from the mere motor performance. Neural correlates of these computations have been explored both in nonhuman and human primates, supporting the idea that our brain recruits complex nodes for motor representations. Of note, these computations have exciting implications for social cognition, and they also entail important challenges in the context of autism. Here, we focus on these challenges benefiting from recent studies addressing motor interference, motor resonance, and high-level motor planning. In addition, we suggest new ideas about how one maps and shares the (motor) space with others. Taken together, these issues inspire intriguing and fascinating questions about the social tendency of our high-level motor computations, and this tendency may indicate that we are “motorically” wired to others. Thus, after furnishing preliminary insights on putative neural nodes involved in these computations, we focus on how the hypothesized social nature of high-level motor computations may be anomalous or limited in autism, and why this represents a critical challenge for the future. </jats:p
Prototype of a novel MEA bioreactor measuring neural network activity continuously over long period
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Development of a custom front-end for long-term multichannel recordings of in vitro neuronal activity
No full textRobot-assisted lower limb rehabilitation may improve locomotion performance in children with cerebral palsy
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