EEG neurofeedback: a brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly

Clinical Neuropsychologist, 21(1): pp. 110-129.Neurofeedback (NF) is an electroencephalographic (EEG) biofeedback technique for training individuals to alter their brain activity via operant conditioning. Research has shown that NF helps reduce symptoms of several neurological and psychiatric disorders, with ongoing research currently investigating applications to other disorders and to the enhancement of non-disordered cognition. The present article briefly reviews the fundamentals and current status of NF therapy and research and illustrates the basic approach with an interim report on a pilot study aimed at developing a new NF protocol for improving cognitive function in the elderly. EEG peak alpha frequency (PAF) has been shown to correlate positively with cognitive performance and to correlate negatively with age after childhood. The present pilot study used a double-blind controlled design to investigate whether training older individuals to increase PAF would result in improved cognitive performance. The results suggested that PAF NF improved cognitive processing speed and executive function, but that it had no clear effect on memory. In sum, the results suggest that the PAF NF protocol is a promising technique for improving selected cognitive functions

Anodal tDCS to right dorsolateral prefrontal cortex facilitates performance for novice jazz improvisers but hinders experts

Research on creative cognition reveals a fundamental disagreement about the nature of creative thought, specifically, whether it is primarily based on automatic, associative (Type-1) or executive, controlled (Type-2) processes. We hypothesized that Type-1 and Type-2 processes make differential contributions to creative production that depend on domain expertise. We tested this hypothesis with jazz pianists whose expertise was indexed by the number of public performances given. Previous fMRI studies of musical improvisation have reported that domain expertise is characterized by deactivation of the right-dorsolateral prefrontal cortex (r-DLPFC), a brain area associated with Type-2 executive processing. We used anodal, cathodal, and sham transcranial direct-current stimulation (tDCS) applied over r-DLPFC with the reference electrode on the contralateral mastoid (1.5mA for 15 min., except for sham) to modulate the quality of the pianists’ performances while they improvised over chords with drum and bass accompaniment. Jazz experts rated each improvisation for creativity, aesthetic appeal, and technical proficiency. There was no main effect of anodal or cathodal stimulation on ratings compared to sham; however, a significant interaction between anodal tDCS and expertise emerged such that stimulation benefitted musicians with less experience but hindered those with more experience. We interpret these results as evidence for a dual-process model of creativity in which novices and experts differentially engage Type-1 and Type-2 processes during creative production

A New Approach to the Study of Human Semantic Memory: Analyzing the Intermediate Products of Rapid Semantic Processes (Cognitive Psychology, Science, Reaction Time, Speed-Accuracy Tradeoff, Information-Processing).

Most experimental studies of human semantic memory have used subjects' reaction times to verify different classes of categorical propositions as the main dependent variable. Unfortunately, the data-base provided by such experiments has not proven to be rich enough to allow us to answer certain important theoretical questions about semantic memory. This has led to a proliferation of models based on radically different assumptions. A new experimental procedure called speed-accuracy decomposition is applied toward this problem. This technique permits the analysis of the intermediate products of semantic processing, that is, the partial outputs generated by incomplete processing. Results obtained with this procedure allow us to reject several classes of semantic-memory models. The data from three reported experiments suggest that sentence verification is comprised of two parallel processes that race against each other to determine the response, the first being a memory search yielding a single, discrete output, the other being an algorithmic computation that generates gradually-accumulating response information at a rate that depends upon the type of semantic relation being processed. The implications and prospects for further applications of this procedure are discussed.Ph.D.Experimental psychologyUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/160813/1/8600475.pd

Visual Attention Modulates Insight Versus Analytic Solving of Verbal Problems

Behavioral and neuroimaging findings indicate that distinct cognitive and neural processes underlie solving problems with sudden insight. Moreover, people with less focused attention sometimes perform better on tests of insight and creative problem solving. However, it remains unclear whether different states of attention, within individuals, influence the likelihood of solving problems with insight or with analysis. In this experiment, participants (N = 40) performed a baseline block of verbal problems, then performed one of two visual tasks, each emphasizing a distinct aspect of visual attention, followed by a second block of verbal problems to assess change in performance. After participants engaged in a center-focused flanker task requiring relatively focused visual attention, they reported solving more verbal problems with analytic processing. In contrast, after participants engaged in a rapid object identification task requiring attention to broad space and weak associations, they reported solving more verbal problems with insight. These results suggest that general attention mechanisms influence both visual attention task performance and verbal problem solving

Combining Multichannel ERP Data for Early Diagnosis of Alzheimer’s Disease

Abstract – As the average age of our population increases, the prevalence of Alzheimer's Disease (AD), the most common form of dementia, has grown sharply. Current diagnosis of AD primarily uses longitudinal clinical evaluations and/or invasive lumbar punctures for CSF analysis, available only at specialized hospitals, which are generally outside of financial and geographical reach of most patients. We expand on our previous work and describe an ensemble of classifiers based approach that combines decision and data fusion techniques for the early diagnosis of AD using event related potentials (ERP) obtained in response to different audio stimuli. In this contribution, we specifically examine various feature set combinations, obtained from different EEG electrode locations and in response to different stimulus tones to illustrate the accuracy of such a system for AD diagnosis at the earliest stage on a clinicall