Prediction Errors and Attention in the Presence and Absence of Feedback

ABSTRACT— Contemporary theories of learning typically assume that learning is driven by prediction errors—in other words, that we learn more when our predictions turn out to be incorrect than we do when our predictions are correct. Results from the recording of electrical brain activity suggest one mechanism by which this might happen; we seem to direct visual attention toward the likely causes of previous prediction errors. This can happen very rapidly—within less than 200 milliseconds of the error-causing object being presented. It is tempting to infer that if learning is driven by prediction errors, then little can be learned in the absence of feedback. Such a conclusion is unwarranted. In fact, the substantial learning that is sometimes the result of simple exposure to objects can also be explained by processes of directing attention toward the likely causes of previous prediction errors.     

The electrophysiological correlates of stimulus visibility and metacontrast masking

There are conflicting views concerning the electrophysiological correlates of visual consciousness. Whereas one view considers a relatively late positive deflection (LP) as a primary correlate of consciousness, another model links consciousness with earlier negativity (VAN). The present experiment utilized metacontrast masking in investigating the electrophysiological correlates of visual consciousness. The participants were presented with target-mask sequences in three stimulus onset asynchronies. The target stimuli were followed by either a metacontrast mask or a similar-looking, but ineffective pseudomask. The results showed that the first deflection that correlated with target visibility was VAN which was followed by LP. We argue that the VAN is the primary correlate target visibility, while the LP reflects later, postperceptual processing stages.     

Brain and mind operational architectonics and man-made “machine” consciousness

To build a true conscious robot requires that a robot’s “brain” be capable of supporting the phenomenal consciousness as human’s brain enjoys. Operational Architectonics framework through exploration of the temporal structure of information flow and inter-area interactions within the network of functional neuronal populations [by examining topographic sharp transition processes in the scalp electroencephalogram (EEG) on the millisecond scale] reveals and describes the EEG architecture which is analogous to the architecture of the phenomenal world. This suggests that the task of creating the “machine” consciousness would require a machine implementation that can support the kind of hierarchical architecture found in EEG.

Hostility‐ and gender‐related differences in oscillatory responses to emotional facial expressions

Hostility is associated with biases in the perception of emotional facial expressions, such that ambiguous or neutral expressions tend to be perceived as threatening or angry. In this study, the effects of hostility and gender on the perception of angry, neutral, and happy faces and on the oscillatory dynamics of cortical responses elicited by these presentations were investigated using time–frequency decomposition by means of wavelet transforms. Feelings of hostility predisposed subjects to perceive happy and neutral faces as less friendly. This effect was more pronounced in women. In hostile subjects, presentation of emotional facial expressions also evoked stronger posterior synchronization in the theta and diminished desynchronization in the alpha band. This may signify a prevalence of emotional responding over cognitive processing. These effects were also more pronounced in females. Hostile females, but not hostile males, additionally showed a widespread synchronization in the alpha band. This synchronization is tentatively explained as a manifestation of inhibitory control which is present in aggressive females, but not in aggressive males. Aggr. Behav. 35:502–513, 2009. © 2009 Wiley‐Liss, Inc.     

Sex differences in brain activity related to general and emotional intelligence

The study investigated gender differences in resting EEG (in three individually determined narrow alpha frequency bands) related to the level of general and emotional intelligence. Brain activity of males decreased with the level of general intelligence, whereas an opposite pattern of brain activity was observed in females. This difference was most pronounced in the upper-alpha band which is related to semantic memory processes. It was further found that highly intelligent males displayed greater decoupling of frontal brain areas, whereas highly intelligent females showed more coupling between frontal and parietal/occipital brain areas. Similar, but less significant differences were observed for the two area scores of strategic and experiential emotional intelligence. It appears that males and females have different resting EEG correlates of IQ.     

Electrophysiological correlates of dispositional mindfulness: A quantitative and complexity EEG study

While growing evidence supports that dispositional mindfulness relates to psychological health and cognitive enhancement, to date there have been only a few attempts to characterize its neural underpinnings. In the present study, we aimed at exploring the electrophysiological (EEG) signature of dispositional mindfulness using quantitative and complexity measures of EEG during resting state and while performing a learning task. Hundred twenty participants were assessed with the Five Facet Mindfulness Questionnaire and underwent 5 min eyes-closed resting state and 5 min at task EEG recording. We hypothesized that high mindfulness individuals would show patterns of brain activity related to (a) lower involvement of the default mode network (DMN) at rest (reduced frontal gamma power) and (b) a state of ‘task readiness’ reflected in a more similar pattern from rest to task (reduced overall q-EEG power at rest but not at task), as compared to their low mindfulness counterparts. Dispositional mindfulness was significantly linked to reduced frontal gamma power at rest and lower overall power during rest but not at task. In addition, we found a trend towards higher entropy during task performance in mindful individuals, which has recently been reported during mindfulness meditation. Altogether, our results add to those from expert meditators to show that high (dispositional) mindfulness seems to have a specific electrophysiological pattern characteristic of less involvement of the DMN and mind-wandering processes.     

Psychological defense mechanisms and electroencephalographic arousal

The aim of this study was to examine the relationship between psychological defense as measured by the Kragh tachistoscopic Defense Mechanisms Test (DMT), and general arousal properties of the individual as measured with electroencephalogram (EEG). The DMT assesses defense by presenting neutral and threatening pictures with very short exposure times. EEG characteristics were measured in the 8–12 Hz EEG frequency band during DMT testing. Twenty-one male subjects participated in the study. All were US Air Force personnel on active duty. Personnel with high defense mechanisms, defined in this connection as slow perception of the threat, tended to have higher cortical arousal after Stimulus exposure than the subjects with low defense mechanisms. The differences occurred mainly with new stimulus material without any threatening content. The differences in arousal response to novel stimuli may contribute to an understanding of the relationships between the Kragh DMT test and performance in life-threatening situations.     

Evaluation of human consciousness level by means of “automated fluctuation analysis” of high frequency electroencephalogram fitted by double Lorentzians

Since Berger’s discovery of the electroencephalogram (EEG), its analysis has been generally restricted to the visual range (upmost 100Hz) and has ignored higher frequency components. One reason should be that there are no reliable methods to distinguish the brain potentials from muscle activity. We have introduced fluctuation analysis, which is popular method especially in the field of basic physiology to clinical electrophysiology. In our previous study, it was declared that power spectral density (PSD) of human high frequency EEG was composed of double Lorentzians and vanished into white level within 1kHz. Then the purpose of this study is to elucidate the “Automated Fluctuation Analysis,” which enables us to evaluate these higher frequency components and its physiological meaning especially focused on conscious level from wakefulness to sleep stage 1. Seventy-four scalp recording EEGs in twenty normal subjects were studied. In short, “Automated Fluctuation Analysis” is made of three steps: amplification of EEG signal, A/D conversion and Fast Fourier Transform by signal processor and extraction of Lorentzian parameters. PSD of high frequency EEG was displayed on log-log graph and the algorithm fit to the following Lorentzian formula were mathematically based on Brown & Dennis. S(f)=S1/ [1+(f/fc₁)²] + S2/ [1+(f/fc₂)²], where S(f) is PSD (μ V²/Hz) at each frequency (f;Hz), S1 and S2 are the plateau level or zero-frequency power of the initial and second Lorentz, and fc₁ and fc₂ are the corner or half-power frequency of the initial and second Lorentz, respectively. As results, during wakefulness the PSD of high frequency EEG activity was composed of double Lorentzian fluctuations and the power distribution of S1 value in topographical display was frontal dominant. This pattern of S1 value disappeared and S2 value became lower during sleepiness and the second Lorentz disappeared during sleep.     

Shedding light on words and sentences: near-infrared spectroscopy in language research

Investigating the neuronal network underlying language processing may contribute to a better understanding of how the brain masters this complex cognitive function with surprising ease and how language is acquired at a fast pace in infancy. Modern neuroimaging methods permit to visualize the evolvement and the function of the language network. The present paper focuses on a specific methodology, functional near-infrared spectroscopy (fNIRS), providing an overview over studies on auditory language processing and acquisition. The methodology detects oxygenation changes elicited by functional activation of the cerebral cortex. The main advantages for research on auditory language processing and its development during infancy are an undemanding application, the lack of instrumental noise, and its potential to simultaneously register electrophysiological responses. Also it constitutes an innovative approach for studying developmental issues in infants and children. The review will focus on studies on word and sentence processing including research in infants and adults.