Statistical Methods for Neuroscience Research Papers (original) (raw)

A Turbo Pascal program for data acquisition and analysis is presented. The program detects incoming data as TTL pulses through the serial port of an IBM-PC and compatible computers and displays the instantaneous frequency plot and the... more

A Turbo Pascal program for data acquisition and analysis is presented. The program detects incoming data as TTL pulses through the serial port of an IBM-PC and compatible computers and displays the instantaneous frequency plot and the interval histogram on-line. Novel features of this Pascal program are: (1) no special hardware requirements and (2) on-line analysis of more than one source at a time. No hardware additions to the supplied computer and easy operation make this program a valuable tool, directly useable in an IBM-PC and compatible computers.

The study of human behaviour ultimately requires the documentation of human movement. In some instances movements can be recorded through a simple button press on a computer input device. In other situations responses can be captured... more

The study of human behaviour ultimately requires the documentation of human movement. In some instances movements can be recorded through a simple button press on a computer input device. In other situations responses can be captured through questionnaire surveys. Nevertheless, there is a need within many neuroscience settings to capture how complex movements unfold over time (human kinematics). Current methods of measuring human kinematics range from accurate but multifarious laboratory configurations to ...

On November 11, 2007, as the 2008 U.S. presidential election was kicking into high gear, the New York Times ran a now infamous op-ed column “This is your brain on politics” (Iacoboni et al., 2007). The author team was led by Marco... more

On November 11, 2007, as the 2008 U.S. presidential election was kicking into high gear, the New York Times ran a now infamous op-ed column “This is your brain on politics” (Iacoboni et al., 2007). The author team was led by Marco Iacoboni, a professor of psychiatry at the University of California at Los Angeles. Iacoboni and his coinvestigators hoped to harness the power of brain-imaging technology, functional magnetic resonance imaging (fMRI) in particular, to ascertain the political preferences of a sample of undecided voters. Like many proponents of the use of fMRI for real-world applications, they began with the assumption that brain-imaging data could help them discern preferences that prospective voters are either unable or unwilling to acknowledge. “Our results reveal some voter impressions on which this election may well turn,” the scientists proclaimed. As revealed by fMRI, voters’ brains ostensibly displayed marked ambivalence toward Hillary Clinton; while viewing her, th...

The organophosphorous compound soman is an acetylcholinesterase inhibitor that causes damage to the brain. Exposure to soman causes neuropathology as a result of prolonged and recurrent seizures. In the present study, long-term recordings... more

The organophosphorous compound soman is an acetylcholinesterase inhibitor that causes damage to the brain. Exposure to soman causes neuropathology as a result of prolonged and recurrent seizures. In the present study, long-term recordings of cortical EEG were used to develop an unbiased means to quantify measures of seizure activity in a large data set while excluding other signal types. Rats were implanted with telemetry transmitters and exposed to soman followed by treatment with therapeutics similar to those administered in the field after nerve agent exposure. EEG, activity and temperature were recorded continuously for a minimum of 2 days pre-exposure and 15 days post-exposure. A set of automatic MATLAB algorithms have been developed to remove artifacts and measure the characteristics of long-term EEG recordings. The algorithms use short-time Fourier transforms to compute the power spectrum of the signal for 2-s intervals. The spectrum is then divided into the delta, theta, alpha, and beta frequency bands. A linear fit to the power spectrum is used to distinguish normal EEG activity from artifacts and high amplitude spike wave activity. Changes in time spent in seizure over a prolonged period are a powerful indicator of the effects of novel therapeutics against seizures. A graphical user interface has been created that simultaneously plots the raw EEG in the time domain, the power spectrum, and the wavelet transform. Motor activity and temperature are associated with EEG changes. The accuracy of this algorithm is also verified against visual inspection of video recordings up to 3 days after exposure.

The physical basis for electrical stimulation of excitable tissue, as used by electrophysiological researchers and clinicians in functional electrical stimulation, is presented with emphasis on the fundamental mechanisms of charge... more

The physical basis for electrical stimulation of excitable tissue, as used by electrophysiological researchers and clinicians in functional electrical stimulation, is presented with emphasis on the fundamental mechanisms of charge injection at the electrode/tissue interface. Faradaic and non-Faradaic charge transfer mechanisms are presented and contrasted. An electrical model of the electrode/tissue interface is given. The physical basis for the origin of electrode potentials is given. Various methods of controlling charge delivery during pulsing are presented. Electrochemical reversibility is discussed. Commonly used electrode materials and stimulation protocols are reviewed in terms of stimulation efficacy and safety. Principles of stimulation of excitable tissue are reviewed with emphasis on efficacy and safety. Mechanisms of damage to tissue and the electrode are reviewed.

In experiments involving small animals, the electroencephalogram (EEG) recorded during severe injury and accompanying resuscitation exhibit the strong presence of electrocardiogram (ECG). For improved quantitative EEG (qEEG) analysis, it... more

In experiments involving small animals, the electroencephalogram (EEG) recorded during severe injury and accompanying resuscitation exhibit the strong presence of electrocardiogram (ECG). For improved quantitative EEG (qEEG) analysis, it is therefore imperative to remove ECG interference from EEG. In this paper, we validate the use of independent component analysis (ICA) to effectively suppress the interference of ECG from EEG recordings during normal activity, asphyxia and recovery following asphyxia. Two channels of EEG from five rats were recorded continuously for 2 h. Simultaneous recording of one channel ECG was also made. Epochs of 4 s and 1 min were selected from baseline, asphyxia and recovery (every 10 min) and their independent components and power spectra were calculated. The improvement in normalized power spectrum of EEG obtained for all animals was 7.71+/-3.63 db at the 3rd minute of recovery and dropped to 1.15+/-0.60 db at 63rd minute. The application of ICA has been particularly useful when the power of EEG is low, such as that observed during early brain hypoxic-asphyxic injury. The method is also useful in situations where accurate indications of EEG signal power and frequency content are needed.

Interaction with machines is mediated by human–machine interfaces (HMIs). Brain–machine interfaces (BMIs) are a particular class of HMIs and have so far been studied as a communication means for people who have little or no voluntary... more

Interaction with machines is mediated by human–machine interfaces (HMIs). Brain–machine interfaces (BMIs) are a particular class of HMIs and have so far been studied as a communication means for people who have little or no voluntary control of muscle activity. In this context, low-performing interfaces can be considered as prosthetic applications. On the other hand, for able-bodied users, a BMI would only be practical if conceived as an augmenting interface. In this paper, a method is introduced for pointing out effective ...