Responses to Noisy Periodic Stimuli Reveal Properties of a Neural Predictor

2006 ◽  
Vol 96 (4) ◽  
pp. 2121-2126 ◽  
Author(s):  
Wilsaan M. Joiner ◽  
Mark Shelhamer
Keyword(s):  
Normal Subjects ◽  
External Noise ◽  
Saccade Latency ◽  
Noise Sources ◽  
Periodic Stimulus ◽  
Timing Variability ◽  
Response Variance ◽  
The Face ◽  
Stimulus Timing ◽  
Response Timing

In programming motor acts, the brain must consider both internal and external noise sources: inherent variation in sensory estimates and changes within the environment. An interesting question in motor control is how reliable responses can be programmed in the face of noise and how these two noise sources interact. We study this by investigating the generation of sequences of predictive saccades to visual targets. First, eight normal subjects tracked targets that alternated at a pacing frequency (0.9 Hz) that promoted predictive behavior, for 300 trials. When tracking this perfectly periodic stimulus, there was variability in the timing of the saccades (intersaccade intervals) that was distributed around the interval of the stimulus (556 ms). We used this inherent variability to set the timing of subsequent stimuli; subjects completed three additional sessions in which the variance of the stimulus timing (the interstimulus intervals) had the same (1.0 SD), less (0.5 SD), or more (2.0 SD) variability than the subject displayed when tracking the perfectly periodic stimulus. Despite changes in stimulus timing variability, variance of the response timing (intersaccade intervals) was equal to the variance of the stimulus plus “inherent variance” (response variance when tracking a perfectly periodic stimulus). Examining the correlations between saccade latency and interstimulus interval, this relationship is interpreted as a tradeoff between reliance on previous saccade performance (intertrial correlations) and reliance on the current stimulus.

scholarly journals Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings

2021 ◽  
Vol 11 (6) ◽  
pp. 761
Author(s):  
Gert Dehnen ◽  
Marcel S. Kehl ◽  
Alana Darcher ◽  
Tamara T. Müller ◽  
Jakob H. Macke ◽  
...  
Keyword(s):  
Data Quality ◽  
Single Unit ◽  
Human Subjects ◽  
External Noise ◽  
Hospital Environment ◽  
Noise Sources ◽  
Recording Channels ◽  
Waveform Similarity ◽  
Therapeutic Procedures ◽  
Single Unit Recordings

Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other aspects of the hospital environment limit the control of electrical noise compared to animal laboratory environments. Here, we highlight the problem of an increased occurrence of simultaneous spike events on different recording channels in human single-unit recordings. Most of these simultaneous events were detected in clusters previously labeled as artifacts and showed similar waveforms. These events may result from common external noise sources or from different micro-electrodes recording activity from the same neuron. To address the problem of duplicate recorded events, we introduce an open-source algorithm to identify these artificial spike events based on their synchronicity and waveform similarity. Applying our method to a comprehensive dataset of human single-unit recordings, we demonstrate that our algorithm can substantially increase the data quality of these recordings. Given our findings, we argue that future studies of single-unit activity recorded under noisy conditions should employ algorithms of this kind to improve data quality.

Steady-state response of quadriplegic subjects to inspiratory resistive load

1986 ◽  
Vol 60 (5) ◽  
pp. 1482-1492 ◽  
Author(s):  
V. Im Hof ◽  
H. Dubo ◽  
V. Daniels ◽  
M. Younes
Keyword(s):  
Steady State ◽  
Chest Wall ◽  
Muscle Spindles ◽  
Normal Subjects ◽  
Afferent Feedback ◽  
Resistive Load ◽  
State Response ◽  
The Face ◽  
Inspiratory Resistance

Normal subjects preserve tidal volume (VT) in the face of added inspiratory resistance by increasing maximal amplitude and duration of the rising phase of respiratory driving pressure (DP) and by changing the shape of this phase to one that is more concave to the time axis. To explore the possible role of chest wall afferents in mediating these responses, we determined averaged DP in eight quadriplegic subjects during steady-state unloaded breathing and while breathing through an inspiratory resistance (8.5 cmH2O X 1(-1) X s). As with normal subjects, quadriplegics preserved VT (loaded VT = 106% control) by utilizing all three mechanisms. However, prolongation of the inspiratory duration derived from the DP waveform (+22% vs. +42%) and shape response were significantly less in the quadriplegic subjects. Shape response was completely absent in subjects with C4 lesions. The results provide strong evidence that respiratory muscle spindles are responsible for shape response and that changes in afferent feedback from the chest wall play an important role in mediating inspiratory prolongation.

scholarly journals A source-synchronous filter for uncorrelated receiver traces from a swept-frequency seismic source

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. P47-P55 ◽  
Author(s):  
Neal Lord ◽  
Herbert Wang ◽  
Dante Fratta
Keyword(s):  
Seismic Waves ◽  
Seismic Source ◽  
Propagation Delay ◽  
External Noise ◽  
Sweep Rate ◽  
Noise Sources ◽  
Frequency Domain Methods ◽  
Phase Alignment ◽  
Source Signal ◽  
Downhole Array

We have developed a novel algorithm to reduce noise in signals obtained from swept-frequency sources by removing out-of-band external noise sources and distortion caused from unwanted harmonics. The algorithm is designed to condition nonstationary signals for which traditional frequency-domain methods for removing noise have been less effective. The source synchronous filter (SSF) is a time-varying narrow band filter, which is synchronized with the frequency of the source signal at all times. Because the bandwidth of the filter needs to account for the source-to-receiver propagation delay and the sweep rate, SSF works best with slow sweep rates and moveout-adjusted waveforms to compensate for source-receiver delays. The SSF algorithm was applied to data collected during a field test at the University of California Santa Barbara’s Garner Valley downhole array site in Southern California. At the site, a 45 kN shaker was mounted on top of a one-story structure and swept from 0 to 10 Hz and back over 60 s (producing useful seismic waves greater than 1.6 Hz). The seismic data were captured with small accelerometer and geophone arrays and with a distributed acoustic sensing array, which is a fiber-optic-based technique for the monitoring of elastic waves. The result of the application of SSF on the field data is a set of undistorted and uncorrelated traces that can be used in different applications, such as measuring phase velocities of surface waves or applying convolution operations with the encoder source function to obtain traveltimes. The results from the SSF were used with a visual phase alignment tool to facilitate developing dispersion curves and as a prefilter to improve the interpretation of the data.

scholarly journals Automatic Estimation of Food Intake Amount Using Visual and Ultrasonic Signals

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2153
Author(s):  
Ki-Seung Lee
Keyword(s):  
Food Intake ◽  
Metabolic Diseases ◽  
Ultrasonic Method ◽  
Audio Signal ◽  
Neck Region ◽  
External Noise ◽  
Estimation Accuracy ◽  
The Face ◽  
Noise Robust ◽  
Contact Sensing

The continuous monitoring and recording of food intake amount without user intervention is very useful in the prevention of obesity and metabolic diseases. I adopted a technique that automatically recognizes food intake amount by combining the identification of food types through image recognition and a technique that uses acoustic modality to recognize chewing events. The accuracy of using audio signal to detect eating activity is seriously degraded in a noisy environment. To alleviate this problem, contact sensing methods have conventionally been adopted, wherein sensors are attached to the face or neck region to reduce external noise. Such sensing methods, however, cause dermatological discomfort and a feeling of cosmetic unnaturalness for most users. In this study, a noise-robust and non-contact sensing method was employed, wherein ultrasonic Doppler shifts were used to detect chewing events. The experimental results showed that the mean absolute percentage errors (MAPEs) of an ultrasonic-based method were comparable with those of the audio-based method (15.3 vs. 14.6) when 30 food items were used for experiments. The food intake amounts were estimated for eight subjects in several noisy environments (cafeterias, restaurants, and home dining rooms). For all subjects, the estimation accuracy of the ultrasonic method was not degraded (the average MAPE was 15.02) even under noisy conditions. These results show that the proposed method has the potential to replace the manual logging method.

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