Induced Gamma-band Activity Elicited by Visual Representation of Unattended Objects

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High frequency oscillations as a correlate of visual perception

“NOTICE: this is the author’s version of a work that was accepted for publication in International journal of psychophysiology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International journal of psychophysiology , 79, 1, (2011) DOI 10.1016/j.ijpsycho.2010.07.004Peer reviewedPostprin

Posterior Beta and Anterior Gamma Oscillations Predict Cognitive Insight

Pioneering neuroimaging studies on insight have revealed neural correlates of the emotional “Aha!” component of the insight process, but neural substrates of the cognitive component, such as problem restructuring (a key to transformative reasoning), remain a mystery. Here, multivariate electroencephalogram signals were recorded from human participants while they solved verbal puzzles that could create a small-scale experience of cognitive insight. Individuals responded as soon as they reached a solution and provided a rating of subjective insight. For unsolved puzzles, hints were provided after 60 to 90 sec. Spatio-temporal signatures of brain oscillations were analyzed using Morlet wavelet transform followed by exploratory parallel-factor analysis. A consistent reduction in beta power (15–25 Hz) was found over the parieto-occipital and centro-temporal electrode regions on all four conditions—(a) correct (vs. incorrect) solutions, (b) solutions without (vs. with) external hint, (c) successful (vs. unsuccessful) utilization of the external hint, and d) self-reported high (vs. low) insight. Gamma band (30–70 Hz) power was increased in right fronto-central and frontal electrode regions for conditions (a) and (c). The effects occurred several (up to 8) seconds before the behavioral response. Our findings indicate that insight is represented by distinct spectral, spatial, and temporal patterns of neural activity related to presolution cognitive processes that are intrinsic to the problem itself but not exclusively to one's subjective assessment of insight

Space-by-time non-negative matrix factorization for single-trial decoding of M/EEG activity

We develop a novel methodology for the single-trial analysis of multichannel time-varying neuroimaging signals. We introduce the space-by-time M/EEG decomposition, based on Non-negative Matrix Factorization (NMF), which describes single-trial M/EEG signals using a set of non-negative spatial and temporal components that are linearly combined with signed scalar activation coefficients. We illustrate the effectiveness of the proposed approach on an EEG dataset recorded during the performance of a visual categorization task. Our method extracts three temporal and two spatial functional components achieving a compact yet full representation of the underlying structure, which validates and summarizes succinctly results from previous studies. Furthermore, we introduce a decoding analysis that allows determining the distinct functional role of each component and relating them to experimental conditions and task parameters. In particular, we demonstrate that the presented stimulus and the task difficulty of each trial can be reliably decoded using specific combinations of components from the identified space-by-time representation. When comparing with a sliding-window linear discriminant algorithm, we show that our approach yields more robust decoding performance across participants. Overall, our findings suggest that the proposed space-by-time decomposition is a meaningful low-dimensional representation that carries the relevant information of single-trial M/EEG signals

Time Pressure Modulates Electrophysiological Correlates of Early Visual Processing

BACKGROUND: Reactions to sensory events sometimes require quick responses whereas at other times they require a high degree of accuracy-usually resulting in slower responses. It is important to understand whether visual processing under different response speed requirements employs different neural mechanisms. METHODOLOGY/PRINCIPAL FINDINGS: We asked participants to classify visual patterns with different levels of detail as real-world or non-sense objects. In one condition, participants were to respond immediately, whereas in the other they responded after a delay of 1 second. As expected, participants performed more accurately in delayed response trials. This effect was pronounced for stimuli with a high level of detail. These behavioral effects were accompanied by modulations of stimulus related EEG gamma oscillations which are an electrophysiological correlate of early visual processing. In trials requiring speeded responses, early stimulus-locked oscillations discriminated real-world and non-sense objects irrespective of the level of detail. For stimuli with a higher level of detail, oscillatory power in a later time window discriminated real-world and non-sense objects irrespective of response speed requirements. CONCLUSIONS/SIGNIFICANCE: Thus, it seems plausible to assume that different response speed requirements trigger different dynamics of processing

Individual differences in LPP amplitude and theta power predict cue-induced eating during a cued food delivery task

Due to individual differences in the brain’s reward system, some individuals are more vulnerable than others to maladaptive, reward-seeking behaviors, such as substance use or compulsive eating. A body of research has demonstrated that individuals who attribute higher levels of incentive salience to reward-associated cues than to pleasant images (termed “C\u3eP group” throughout) are more vulnerable to compulsive eating than those who attribute higher incentive salience to pleasant images than reward- associated cues (P\u3eC group). Meanwhile, a separate body of research has demonstrated that cognitive control also regulates eating by enabling top-down attentional control. This dissertation aims to identify how both cognitive control and incentive salience act in tandem to regulate cue-induced eating. A central question of this research is: do individuals in the C\u3eP group also show attenuated cognitive control? Because the animal literature indicates that individuals who attribute high incentive salience to reward-associated cues also show attenuated top-down attentional control, I hypothesized that C\u3eP individuals would also show attenuated cognitive control relative to P\u3eC individuals. To test this hypothesis, I analyzed electroencephalogram (EEG) data collected during a controlled cued food delivery task, in which participants viewed images and were dispensed food rewards (candy) that they could choose to eat or discard, and non-food objects (beads, control condition). From the EEG recordings, I calculated the amplitude of the late positive potential (LPP) and power (µV2) in the theta (θ, 4-8 Hz) frequency band as metrics of affective and cognitive processing, respectively. To identify individual differences in both affective and cognitive processing, I then conducted two separate K-means (k = 2) cluster analyses using LPP and theta power data. The LPP-based cluster analysis replicated previous findings: C\u3eP individuals ate significantly more candies during the experiment than P\u3eC individuals. However, I found no significant differences in theta power between the P\u3eC and C\u3eP groups. Meanwhile, the theta-based cluster analysis found that some individuals show higher theta during the candy condition than the bead condition (θCA\u3eθBE), while others show higher theta power during the bead condition than the candy condition (θBE\u3eθCA). Furthermore, the θCA\u3eθBE group ate significantly more during the experiment than the θBE\u3eθCA group. Finally, I crossed group assignments from both the LPP- and theta-based cluster analyses to create four groups based on LPP- and theta-based risk factors: those with no risk factors (P\u3eC & θBE\u3eθCA group), those with only an LPP risk factor (C\u3eP & θCA\u3eθBE), those with only a theta risk factor (P\u3eC & θCA\u3eθBE), and finally those with both risk factors (C\u3eP & θCA\u3eθBE). I found that individuals with no risk factors ate the least of all four groups, and the other three groups showed significantly higher levels of eating behavior on average. From these results, I can conclude that both cognitive and affective brain systems are involved in regulating cue-induced eating. However, the finding that P\u3eC and C\u3eP individuals do not show significant differences in theta power suggests that cognitive and affective mechanisms may act independently in humans. Because an individual with an affective vulnerability to cue-induced eating may not also have a cognitive vulnerability, this underscores the need for targeted, individualized treatments for maladaptive behaviors. For example, these research findings could be applied to the use of transcranial magnetic stimulation (TMS) to ameliorate addictive disorders: individuals with higher theta power during food-related decision-making may be selected for excitatory stimulation of brain regions associated with cognitive control, such as dorsolateral prefrontal cortex (dlPFC), whereas individuals who attribute high incentive salience to reward-related cues may benefit from inhibitory stimulation of reward-associated areas, such as medial prefrontal cortex (mPFC)