Deconstructing insight: EEG correlates of insightful problem solving

Background

Cognitive insight phenomenon lies at the core of numerous discoveries. Behavioral research indicates four salient features of insightful problem solving: (i) mental impasse, followed by (ii) restructuring of the problem representation, which leads to (iii) a deeper understanding of the problem, and finally culminates in (iv) an “Aha!” feeling of suddenness and obviousness of the solution. However, until now no efforts have been made to investigate the neural mechanisms of these constituent features of insight in a unified framework.

Methodology/Principal Findings

In an electroencephalographic study using verbal remote associate problems, we identified neural correlates of these four features of insightful problem solving. Hints were provided for unsolved problems or after mental impasse. Subjective ratings of the restructuring process and the feeling of suddenness were obtained on trial-by-trial basis. A negative correlation was found between these two ratings indicating that sudden insightful solutions, where restructuring is a key feature, involve automatic, subconscious recombination of information. Electroencephalogram signals were analyzed in the space×time×frequency domain with a nonparametric cluster randomization test. First, we found strong gamma band responses at parieto-occipital regions which we interpreted as (i) an adjustment of selective attention (leading to a mental impasse or to a correct solution depending on the gamma band power level) and (ii) encoding and retrieval processes for the emergence of spontaneous new solutions. Secondly, we observed an increased upper alpha band response in right temporal regions (suggesting active suppression of weakly activated solution relevant information) for initially unsuccessful trials that after hint presentation led to a correct solution. Finally, for trials with high restructuring, decreased alpha power (suggesting greater cortical excitation) was observed in right prefrontal area.

Conclusions/Significance

Our results provide a first account of cognitive insight by dissociating its constituent components and potential neural correlates.     

Fluid intelligence and psychosocial outcome: from logical problem solving to social adaptation

Background

While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized.

Methodology/Principal Findings

A random-probabilistic sample of 2370 secondary school students completed measures of fluid intelligence (Raven''s Progressive Matrices, RPM) and several measures of psychological adaptation: bullying (Delaware Bullying Questionnaire), domestic abuse of adolescents (Conflict Tactic Scale), drug intake (ONUDD), self-esteem (Rosenberg''s Self Esteem Scale) and the Perceived Mental Health Scale (Spanish adaptation).Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher.

Conclusions/Significance

Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts.     

EEG dynamics reflect the distinct cognitive process of optic problem solving

This study explores the changes in electroencephalographic (EEG) activity associated with the performance of solving an optics maze problem. College students (N = 37) were instructed to construct three solutions to the optical maze in a Web-based learning environment, which required some knowledge of physics. The subjects put forth their best effort to minimize the number of convexes and mirrors needed to guide the image of an object from the entrance to the exit of the maze. This study examines EEG changes in different frequency bands accompanying varying demands on the cognitive process of providing solutions. Results showed that the mean power of θ, α1, α2, and β1 significantly increased as the number of convexes and mirrors used by the students decreased from solution 1 to 3. Moreover, the mean power of θ and α1 significantly increased when the participants constructed their personal optimal solution (the least total number of mirrors and lens used by students) compared to their non-personal optimal solution. In conclusion, the spectral power of frontal, frontal midline and posterior theta, posterior alpha, and temporal beta increased predominantly as the task demands and task performance increased.     

Influence of music on the solution of mathematical logical tasks

Musical accompaniment (of different styles and intensities) of the solution of mathematical logical tasks influenced the time required for their solution. Classical music 35 and 65 dB and rock music 65 and 85 dB in terms of loudness decreased the time of the solution. Louder classical music (85 dB) did not have this effect. Solution of tasks without musical accompaniment led to an increase in coherent values, especially in ??₁, ??₂, and ?? the frequency bands in the EEG of the occipital cortex. The intrahemispheric and interhemispheric coherences of frontal EEG increased and EEG asymmetry (in the number of Coh connections in the left and right hemispheres) arose during the solution of the tasks accompanied by music. Classical music (35 and 65 dB) caused left-side asymmetry in the EEG. The use of more powerful classical or rock music led to a prevalence of the number of Coh connections in the right hemisphere.     

Features of the dynamics of the forebrain EEG of Emys orbicularis during the solving of an extrapolation problem

Sharp EEG changes are recorded in bioelectrical activity of the dorsal cortex and dorsal ventricular edge in marsh tortoises in conditions of free movement during solving of an extrapolation task (a test of elementary reasoning ability). These changes of a pathological character, accompanied by neurotic states, were observed in some animals having correctly solved the task several times in succession (2-5), beginning with the first presentation. Such changes of EEG and behaviour were not found in tortoises that committed errors at first presentations of the task and only gradually learned correct solving. Formation of the adequate behaviour can proceed by two means: on the basis of elementary reasoning ability and learning. Disturbance of adequate behaviour in the experiment with characteristic changes of EEG testifies to a difficult state of the animal during solving of the extrapolation task.     

Decision of mathematical logical tasks in sensory enriched environment (classical music)

The time of a decision of mathematical logical tasks (MLT) was decreased during classical musical accompaniment (power 35 and 65 dB). Music 85 dB did not influence on the process of decision of MLT. Decision without the musical accompaniment led to increasing of coherent function values in beta1, beta2, gamma frequency ranges in EEG of occipital areas with prevalence in a left hemisphere. A coherence of potentials was decreased in EEG of frontal cortex. Music decreasing of making-decision time enhanced left-sided EEG asymmetry The intrahemispheric and the interhemispheric coherences of frontal cortex were increased during the decision of MLT accompanied by music. Using of musical accompaniment 85 dB produced a right-side asymmetry in EEG and formed a focus of coherent connections in EEG of temporal area of a right hemisphere.     

Insightful problem solving in an Asian elephant

The "aha" moment or the sudden arrival of the solution to a problem is a common human experience. Spontaneous problem solving without evident trial and error behavior in humans and other animals has been referred to as insight. Surprisingly, elephants, thought to be highly intelligent, have failed to exhibit insightful problem solving in previous cognitive studies. We tested whether three Asian elephants (Elephas maximus) would use sticks or other objects to obtain food items placed out-of-reach and overhead. Without prior trial and error behavior, a 7-year-old male Asian elephant showed spontaneous problem solving by moving a large plastic cube, on which he then stood, to acquire the food. In further testing he showed behavioral flexibility, using this technique to reach other items and retrieving the cube from various locations to use as a tool to acquire food. In the cube's absence, he generalized this tool utilization technique to other objects and, when given smaller objects, stacked them in an attempt to reach the food. The elephant's overall behavior was consistent with the definition of insightful problem solving. Previous failures to demonstrate this ability in elephants may have resulted not from a lack of cognitive ability but from the presentation of tasks requiring trunk-held sticks as potential tools, thereby interfering with the trunk's use as a sensory organ to locate the targeted food.     

Co-evolution and ecosystem based problem solving

Emergent cooperative relations in ecosystems are ill understood, but have the potential to strongly improve evolutionary computing. On the other hand, eco-evolutionary computation has the potential to provide new insights in the structuring and functioning of ecosystems. Here we study ecosystem based problem solving in a co-evolutionary framework of predators (solvers) and prey (problems), extended with a population of scavengers, which can eat the remains of prey (that is, cooperate with the predators in solving the problems). We show that such an artificial ecosystem of predators, prey and scavengers, with a selection and fitness regime favoring specialization, self-organizes in space and time such that (1) problems are automatically decomposed in easier to solve parts, (2) the predator, prey and scavenger populations differentiate in sub-populations according to this decomposition, and (3) predators and scavengers automatically co-localize in space such that the problems are indeed solved by predator–scavenger combinations which together correctly approximate the target function. That is, the use of a spatial co-evolutionary ecosystem as information processing unit for evolutionary computation gives rise to an emergent structure of niches, each consisting of complementary partial solutions. As a result, ecosystem based solutions are preferred over individual-based solutions in solving the studied function approximation task.     

A new mathematical approach for solving carrier-facilitated steady-state diffusion problems

Summary A new mathematical treatment is presented which simplifies the solution of carrier-diffusion problems. The method is generally applicable and is illustrated and tested for a specific, commonly occurring situation: facilitated diffusion of a single substrate through flat layers. Results predicted for total substrate flux are in excellent agreement with control computer calculations. The method also can be used to obtain concentration profiles for each species; here the results are good only if conditions at the boundaries are predicted correctly.     

Studying insight problem solving with neuroscientific methods

Insights are sporadic, unpredictable, short-lived moments of exceptional thinking where unwarranted assumptions need to be discarded before solutions to problems can be obtained. Insight requires a restructuring of the problem situation that is relatively rare and hard to elicit in the laboratory. One way of dealing with this problem is to catalyze such restructuring processes using solution hints. This allows one to obtain multiple insight events and their accurate onset times, which are required for event-related designs in functional magnetic resonance imaging (fMRI) and Electroencephalogram (EEG), and to reliably record the activity associated with the restructuring component of insight. In this article, we discuss in detail the methodological challenges that brain research on insight poses and describe how we dealt with these challenges in our recent studies on insight problem solving.     

On problem solving with Hopfield neural networks

Hopfield and Tank have shown that neural networks can be used to solve certain computationally hard problems, in particular they studied the Traveling Salesman Problem (TSP). Based on network simulation results they conclude that analog VLSI neural nets can be promising in solving these problems. Recently, Wilson and Pawley presented the results of their simulations which contradict the original results and cast doubts on the usefulness of neural nets. In this paper we give the results of our simulations that clarify some of the discrepancies. We also investigate the scaling of TSP solutions found by neural nets as the size of the problem increases. Further, we consider the neural net solution of the Clustering Problem, also a computationally hard problem, and discuss the types of problems that appear to be well suited for a neural net approach.