Electroencephalogram (EEG) Recording Protocol for Cognitive and Affective Human Neuroscience Research

Electroencephalography (EEG) is one of the most widely used techniques to measure human brain activity. EEG recordings provide a direct, high temporal resolution measure of cortical activity from noninvasive scalp electrodes. However, the signals are small relative to the noise, and optimizing the quality of the recorded EEG data can significantly improve the ability to identify signatures of brain processing. This protocol provides a step-by-step guide to recording the EEG from human research participants using strategies optimized for producing the best quality EEG.

Electroencephalogram (EEG) Recording Protocol for Cognitive and Affective Human Neuroscience Research

Electroencephalography (EEG) is one of the most widely used techniques to measure human brain activity. EEG recordings provide a direct, high temporal resolution measure of cortical activity from noninvasive scalp electrodes. However, the signals are small relative to the noise, and optimizing the quality of the recorded EEG data can significantly improve the ability to identify signatures of brain processing. This protocol provides a step-by-step guide to recording the EEG from human research participants using strategies optimized for producing the best quality EEG.

Particle diameter, signal-to-noise ratio and beam requirements for extended Rayleigh resolution measurements in the scanning electron microscope

The extended Rayleigh resolution measure was introduced to give a generalized resolution measure that can be readily applied to imaging and resolving particles that have finite size. Here, we make a detailed analysis of the influence of the particle size on this resolution measure. We apply this to scanning electron microscopy, under simple assumption of a Gaussian electron beam intensity distribution and a directly proportional emitted signal yield without detailed consideration of scattering internal to the sample, other than being proportional to the sample thickness. From this, we produce beam-width normalized characteristics relating the particle diameter and resolution measure, while also taking consideration of the reduced signal yield that occurs from smaller particles. From our analysis of these characteristics, which we fit to experimental image data, we see that particle diameters <0.7 times the beam 1/e full width, d, give agreement better than 10% with the true extended Rayleigh resolution. Furthermore, we consider the signal current that must be collected to reliably distinguish between the mid-gap and peak intensity regions in the particle images. This leads to a practical guide that the signal-to-noise ratio (SNR) occurring between large area, continuous regions made of the same materials as the particle and background should typically be 10–30 times greater than the SNR that is desired to be achieved between the peak and mid-gap regions of just resolved adjacent identical particles having diameters in the size range 0.4–0.7d.

Small eye movements cannot be reliably measured by video-based P-CR eye-trackers

For evaluating whether an eye-tracker is suitable for measuring microsaccades, Poletti & Rucci (2016) propose that a measure called ‘resolution’ could be better than the more established root-mean-square of the sample-to-sample distances (RMS-S2S). Many open questions exist around the resolution measure, however. Resolution needs to be calculated using data from an artificial eye that can be turned in very small steps. Furthermore, resolution has an unclear and uninvestigated relationship to the RMS-S2S and STD (standard deviation) measures of precision (Holmqvist & Andersson, 2017, p. 159-190), and there is another metric by the same name (Clarke, Ditterich, Drüen, Schönfeld, and Steineke 2002), which instead quantifies the errors of amplitude measurements. In this paper, we present a mechanism, the Stepperbox, for rotating artificial eyes in arbitrary angles from 1′ (arcmin) and upward. We then use the Stepperbox to find the minimum reliably detectable rotations in 11 video-based eye-trackers (VOGs) and the Dual Purkinje Imaging (DPI) tracker. We find that resolution correlates significantly with RMS-S2S and, to a lesser extent, with STD. In addition, we find that although most eye-trackers can detect some small rotations of an artificial eye, the rotations of amplitudes up to 2∘ are frequently erroneously measured by video-based eye-trackers. We show evidence that the corneal reflection (CR) feature of these eye-trackers is a major cause of erroneous measurements of small rotations of artificial eyes. Our data strengthen the existing body of evidence that video-based eye-trackers produce errors that may require that we reconsider some results from research on reading, microsaccades, and vergence, where the amplitude of small eye movements have been measured with past or current video-based eye-trackers. In contrast, the DPI reports correct rotation amplitudes down to 1′.

Electroencephalogram (EEG) Recording Protocol for Cognitive and Affective Human Neuroscience Research

Electroencephalography (EEG) is one of the most widely used techniques to measure human brain activity. EEG recordings provide a direct, high temporal resolution measure of cortical activity from noninvasive scalp electrodes. However, the signals are small relative to the noise, and optimizing the quality of the recorded EEG data can significantly improve the ability to identify signatures of brain processing. This protocol provides a step-by-step guide to recording the EEG from human research participants using strategies optimized for producing the best quality EEG.

Electroencephalogram (EEG) Recording Protocol for Cognitive and Affective Human Neuroscience Research

Electroencephalography (EEG) is one of the most widely used techniques to measure human brain activity. EEG recordings provide a direct, high temporal resolution measure of cortical activity from noninvasive scalp electrodes. However, the signals are small relative to the noise, and optimizing the quality of the recorded EEG data can significantly improve the ability to identify signatures of brain processing. This protocol provides a step-by-step guide to recording the EEG from human research participants using strategies optimized for producing the best quality EEG.

Resolution measures for 3D magnetic inversions

Inversion of magnetic data into 3D models is becoming commonplace. The theoretical basis of the method is well established and has been extended to include constraints based on physical properties and geologic information. Nevertheless, only limited attention is paid to assessing the reliability of computed models, which usually involves deriving some measure of how well features within the models can be resolved. Resolution lengths determined from resolution matrices can be unrealistically small, suggesting that the recovered models are more reliable than they really are. One cause of this effect is the calculated model itself, which directly influences the character of the resolving functions. We have developed an approximate resolution measure not affected by the calculated model, and we found it to give more realistic resolving lengths. This approximation is computationally less demanding and can be calculated prior to inversion. It suggests that the resolution length is equal to the depth of the parameter or model feature of interest.

Frontal Oscillatory Dynamics Predict Feedback Learning and Action Adjustment

Frontal oscillatory dynamics in the theta (4–8 Hz) and beta (20–30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after specific, randomly selected time intervals (300–2000 msec) using the feedback after each button press (correct, too fast, too slow). Consistent with previous findings, theta-band activity over medial frontal scalp sites (presumably reflecting medial frontal cortex activity) was stronger after negative feedback, whereas beta-band activity was stronger after positive feedback. Theta-band power predicted learning only after negative feedback, and beta-band power predicted learning after positive and negative feedback. Furthermore, negative feedback increased theta-band intersite phase synchrony (a millisecond resolution measure of functional connectivity) among right lateral prefrontal, medial frontal, and sensorimotor sites. These results demonstrate the importance of frontal theta- and beta-band oscillations and intersite communication in the realization of reinforcement learning.

A Real-Time Transport System for High-Resolution Measure Image

This document explains and demonstrates how to use SRIO interface in the real-time transport platform for high-resolution measure image. The raw CCD data is first captured in a FIFO implemented in FPGA, and then transferred from FPGA to DSP through the SRIO interface. When one frame image data is captured, it is displayed on the screen of PC computer.