John Kounios

New approaches to demystifying insight.

After a person has become stuck on a problem, they sometimes achieve a clear and sudden solution through insight--the so-called Aha! experience. Because of its distinctive experience, the origins and characteristics of insight have received considerable attention historically in psychological research. However, despite considerable progress in characterizing insight, the underlying mechanisms remain mysterious. We argue that research on insight could be greatly advanced by supplementing traditional insight research, which depends on a few complex problems, with paradigms common in other domains of cognitive science. We describe a large set of mini-insight problems to which multiple methods can be applied, together with subjective reports to identify insight problem-solving. Behavioral priming and neuroimaging methods are providing evidence about what, where, and how neural activity occurs during insight. Such evidence constrains theories of component processes, and will help to demystify insight.

The Aha! Moment The Cognitive Neuroscience of Insight

A sudden comprehension that solves a problem, reinterprets a situation, explains a joke, or resolves an ambiguous percept is called an insight (i.e., the “Aha! moment”). Psychologists have studied insight using behavioral methods for nearly a century. Recently, the tools of cognitive neuroscience have been applied to this phenomenon. A series of studies have used electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to study the neural correlates of the “Aha! moment” and its antecedents. Although the experience of insight is sudden and can seem disconnected from the immediately preceding thought, these studies show that insight is the culmination of a series of brain states and processes operating at different time scales. Elucidation of these precursors suggests interventional opportunities for the facilitation of insight.

EEG Neurofeedback: A Brief Overview and an Example of Peak Alpha Frequency Training for Cognitive Enhancement in the Elderly

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.

A brain mechanism for facilitation of insight by positive affect

Previous research has shown that people solve insight or creative problems better when in a positive mood (assessed or induced), although the precise mechanisms and neural substrates of this facilitation remain unclear. We assessed mood and personality variables in 79 participants before they attempted to solve problems that can be solved by either an insight or an analytic strategy. Participants higher in positive mood solved more problems, and specifically more with insight, compared with participants lower in positive mood. fMRI was performed on 27 of the participants while they solved problems. Positive mood (and to a lesser extent and in the opposite direction, anxiety) was associated with changes in brain activity during a preparatory interval preceding each solved problem; modulation of preparatory activity in several areas biased people to solve either with insight or analytically. Analyses examined whether (a) positive mood modulated activity in brain areas showing responsivity during preparation; (b) positive mood modulated activity in areas showing stronger activity for insight than noninsight trials either during preparation or solution; and (c) insight effects occurred in areas that showed mood-related effects during preparation. Across three analyses, the ACC showed sensitivity to both mood and insight, demonstrating that positive mood alters preparatory activity in ACC, biasing participants to engage in processing conducive to insight solving. This result suggests that positive mood enhances insight, at least in part, by modulating attention and cognitive control mechanisms via ACC, perhaps enhancing sensitivity to detect non-prepotent solution candidates.

Peak alpha frequency: an electroencephalographic measure of cognitive preparedness

OBJECTIVE Electroencephalographic (EEG) peak alpha frequency (PAF) (measured in Hz) has been correlated to cognitive performance between healthy and clinical individuals, and among healthy individuals. PAF also varies within individuals across developmental stages, among different cognitive tasks, and among physiological states induced by administration of various substances. The present study suggests that, among other things, PAF reflects a trait or state of cognitive preparedness. METHODS Experiment 1 involved 19-channel EEG recordings from 10 individuals with traumatic brain injury (TBI) and 12 healthy matched controls, before, during, and after tasks of visual and auditory attention. Experiment 2 involved EEG recordings from 19 healthy young adults before and after a working memory task (WAIS-R Digit Span), repeated on 2 different days to measure within-individual differences. RESULTS Experiment 1 showed significantly lower PAF in individuals with TBI, mostly during post-task rest. Experiment 2 showed PAF during pre-task baseline to be significantly correlated with Digit Span performance of the same day but not with Digit Span performance of another day. Moreover, PAF was significantly increased after Digit Span for those participants whose PAF was lower than the sample median before the task, but not for those who had it higher. Finally, both PAF and Digit Span performance were increased during the second day. CONCLUSIONS PAF was shown to detect both trait and state differences in cognitive preparedness, as well as to be affected by cognitive tasks. Traits are better reflected during post-task rest, whereas states are better reflected during initial resting baseline recordings.

Coherent oscillatory networks supporting short-term memory retention

Accumulating evidence suggests that top-down processes, reflected by frontal-midline theta-band (4-8 Hz) electroencephalogram (EEG) oscillations, strengthen the activation of a memory set during short-term memory (STM) retention. In addition, the amplitude of posterior alpha-band (8-13 Hz) oscillations during STM retention is thought to reflect a mechanism that protects fragile STM activations from interference by gating bottom-up sensory inputs. The present study addressed two important questions about these phenomena. First, why have previous studies not consistently found memory set-size effects on frontal-midline theta? Second, how does posterior alpha participate in STM retention? To answer these questions, large-scale network connectivity during STM retention was examined by computing EEG wavelet coherence during the retention period of a modified Sternberg task using visually-presented letters as stimuli. The results showed (a) increasing theta-band coherence between frontal-midline and left temporal-parietal sites with increasing memory load, and (b) increasing alpha-band coherence between midline parietal and left temporal/parietal sites with increasing memory load. These findings support the view that theta-band coherence, rather than amplitude, is the key factor in selective top-down strengthening of the memory set and demonstrate that posterior alpha-band oscillations associated with sensory gating are involved in STM retention by participating in the STM network.

An ensemble based data fusion approach for early diagnosis of Alzheimer's disease

As the number of the elderly population affected by Alzheimers disease (AD) rises rapidly, the need to find an accurate, inexpensive and non-intrusive diagnostic procedure that can be made available to community healthcare providers is becoming an increasingly urgent public health concern. Several recent studies have looked at analyzing electroencephalogram (EEG) signals through the use of wavelets and neural networks. While showing great promise, the final outcomes of these studies have been largely inconclusive. This is mostly due to inherent difficulty of the problem, but also - perhaps - due to inefficient use of the available information, as many of these studies have used a single EEG channel for the analysis. In this contribution, we describe an ensemble of classifiers based data fusion approach to combine information from two or more sources, believed to contain complementary information, for early diagnosis of Alzheimers disease. Our emphasis is on sequentially generating an ensemble of classifiers that explicitly seek the most discriminating information from each data source. Specifically, we use the event related potentials recorded from the Pz, Cz, and Fz electrodes of the EEG, decomposed into different frequency bands using multiresolution wavelet analysis. The proposed data fusion approach includes generating multiple classifiers trained with strategically selected subsets of the training data from each source, which are then combined through a modified weighted majority voting procedure. The implementation details and the promising outcomes of this implementation are presented.

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.

Asymmetric prefrontal cortex activation in relation to markers of overeating in obese humans

Dietary restraint is heavily influenced by affect, which has been independently related to asymmetrical activation in the prefrontal cortex (prefrontal asymmetry) in electroencephalograph (EEG) studies. In normal weight individuals, dietary restraint has been related to prefrontal asymmetry; however, this relationship was not mediated by affect. This study was designed to test the hypotheses that, in an overweight and obese sample, dietary restraint as well as binge eating, disinhibition, hunger, and appetitive responsivity would be related to prefrontal asymmetry independent of affect at the time of assessment. Resting EEG recordings and self-report measures of overeating and affect were collected in 28 overweight and obese adults. Linear regression analyses were used to predict prefrontal asymmetry from appetitive measures while controlling for affect. Cognitive restraint and binge eating were not associated with prefrontal asymmetry. However, disinhibition, hunger, and appetitive responsivity predicted left-, greater than right-, sided prefrontal cortex activation independent of affect. Findings in this study add to a growing literature implicating the prefrontal cortex in the cognitive control of dietary intake. Further research to specify the precise role of prefrontal asymmetry in the motivation toward, and cessation of, feeding in obese individuals is encouraged.

Semantic richness and the activation of concepts in semantic memory: Evidence from event-related potentials

Semantic richness refers to the amount of semantic information associated with a concept. Reaction-time (RT) studies have shown that words referring to rich concepts elicit faster responses than those referring to impoverished ones, suggesting that richer concepts are activated more quickly. In a recent functional neuroimaging study, richer concepts evoked less neural activity, which was interpreted as faster activation. The interpretations of these findings appear to conflict with event-related potential (ERP) studies showing no evidence that speed of concept activation is influenced by typical semantic variables. Resolution of this apparent contradiction is important because the interpretation of 40 years of semantic-memory RT studies depends on whether factors such as semantic richness influence the duration of initial concept activation or later decision and response processes. Consistent with previous studies of the effects of semantic factors on ERP, the present study shows that richness influences the magnitude, but not the latency, of the P2 and N400 ERP components (which are early relative to behavioral responses), suggesting that effects of richness on RT reflect temporal effects on downstream decision or response mechanisms rather than on upstream concept activation.