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

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.

Electroencephalographic data are easily contaminated by signals of non-neural origin. Independent component analysis (ICA) can help correct EEG data for such artifacts. Artifact independent components (ICs) can be identified by experts... more

Electroencephalographic data are easily contaminated by signals of non-neural origin. Independent component analysis (ICA) can help correct EEG data for such artifacts. Artifact independent components (ICs) can be identified by experts via visual inspection. But artifact features are sometimes ambiguous or difficult to notice, and even experts may disagree about how to categorise a particular component. It is therefore important to inform users on artifact properties, and give them the opportunity to intervene. Here we first describe artifacts captured by ICA. We review current methods to automatically select artifactual components for rejection, and introduce the SASICA software, implementing several novel selection algorithms as well as two previously described automated methods (ADJUST, Mognon et al. Psychophysiology 2011;48(2):229; and FASTER, Nolan et al. J Neurosci Methods 2010;48(1):152). We evaluate these algorithms by comparing selections suggested by SASICA and other metho...

Brain–computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available.... more

Brain–computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available. Debilitating neurological disorders however, may lead to loss of intact vision. The current study explores the feasibility of an auditory BCI. Sixteen healthy volunteers participated in three training sessions consisting of 30 2–3 min runs in which they learned to increase or decrease the amplitude of sensorimotor rhythms (SMR) of the EEG. Half of the participants were presented with visual and half with auditory feedback. Mood and motivation were assessed prior to each session.Although BCI performance in the visual feedback group was superior to the auditory feedback group there was no difference in performance at the end of the third session. Participants in the auditory feedback group learned slower, but four out of eight reached an accuracy of over 70% correct in the last session comparable to the visual feedback group. Decreasing performance of some participants in the visual feedback group is related to mood and motivation. We conclude that with sufficient training time an auditory BCI may be as efficient as a visual BCI. Mood and motivation play a role in learning to use a BCI.

The neurochip is a silicon micromachined device upon which cultured mammalian neurons can be continuously and individually monitored and stimulated. The neurochip is based upon a 4×4 array of metal electrodes, each of which has a caged... more

The neurochip is a silicon micromachined device upon which cultured mammalian neurons can be continuously and individually monitored and stimulated. The neurochip is based upon a 4×4 array of metal electrodes, each of which has a caged well structure designed to hold a single mature cell body while permitting normal outgrowth of neural processes. We demonstrate that this device is capable of maintaining cell survival, and that the electrodes can both record and stimulate electrical activity in individual cells with no crosstalk between channels.

The mouse is an excellent model for investigations of stroke and neural injury. However, there is a paucity of long term functional outcome measurements for the mouse. We, therefore, developed a sensorimotor functional test (corner test)... more

The mouse is an excellent model for investigations of stroke and neural injury. However, there is a paucity of long term functional outcome measurements for the mouse. We, therefore, developed a sensorimotor functional test (corner test) and applied this test to a model of focal cerebral ischemia in the mouse. Male C57/6J mice (n=20) were subjected to embolic middle cerebral

Artifacts in functional magnetic resonance imaging (fMRI) data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI... more

Artifacts in functional magnetic resonance imaging (fMRI) data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI preprocessing. Independent component analysis’ demonstrated capacity to separate sources of neural signal, structured noise, and random noise into separate components might be utilized in improved procedures to remove artifacts from fMRI data. Such procedures require a method for labeling independent components (ICs) as representing artifacts to be removed or neural signals of interest to be spared. Visual inspection is often considered an accurate method for such labeling as well as a standard to which automated labeling methods are compared. However, detailed descriptions of methods for visual inspection of ICs are lacking in the literature. Here we describe the details of, and the rationale for, an operationalized fMRI data denoising procedure that involves visual inspection of ICs (96% inter-rater agreement). We estimate that dozens of subjects/sessions can be processed within a few hours using the described method of visual inspection. Our hope is that continued scientific discussion of and testing of visual inspection methods will lead to the development of improved, cost-effective fMRI denoising procedures.