Beyond establishing involvement: quantifying the contribution of anticipatory α- and β-band suppression to perceptual improvement with attention

2012 ◽  
Vol 108 (9) ◽  
pp. 2352-2362 ◽  
Author(s):  
Freek van Ede ◽  
Malte Köster ◽  
Eric Maris

Systems and cognitive neuroscience aim at understanding the neurophysiological mechanisms that underlie cognition and behavior. Many studies have revealed the involvement of many types of neural signals in diverse cognitive and behavioral phenomena. Here, we go beyond establishing such involvement and address two fundamental, yet largely unaddressed, questions: 1) exactly how much does a given neural signal contribute to a cognitive or behavioral phenomenon of interest; and 2) to what extent are distinct neural signals independently related to this phenomenon? We recorded brain activity using magnetoencephalography while human participants performed a cued somatosensory detection task. Using a novel method, we then quantified the contribution (in a predictive but not causal sense) of two well-established neural phenomena to the improvement in perception with attentional orienting. In our sample, the anticipatory suppression of extracranially recorded oscillatory α- and β-band amplitudes from contralateral primary somatosensory cortex could account for maximally 29% of the attention-induced improvement in tactile perception. In addition, although amplitude suppressions in the α- and β-frequency bands both contributed to this improvement, their contribution was largely shared. These data reveal the upper limit of the cognitive/behavioral relevance of this type of signal and show that at least 71% of the perceptual improvement with attention must be accounted for by other signals.

Author(s):  
Yiwen Wang ◽  
Yuxiao Lin ◽  
Chao Fu ◽  
Zhihua Huang ◽  
Rongjun Yu ◽  
...  

Abstract The desire for retaliation is a common response across a majority of human societies. However, the neural mechanisms underlying aggression and retaliation remain unclear. Previous studies on social intentions are confounded by low-level response related brain activity. Using an EEG-based brain-computer interface (BCI) combined with the Chicken Game, our study examined the neural dynamics of aggression and retaliation after controlling for nonessential response related neural signals. Our results show that aggression is associated with reduced alpha event-related desynchronization (ERD), indicating reduced mental effort. Moreover, retaliation and tit-for-tat strategy use are also linked with smaller alpha-ERD. Our study provides a novel method to minimize motor confounds and demonstrates that choosing aggression and retaliation is less effortful in social conflicts.


2012 ◽  
Vol 24 (4) ◽  
pp. 775-777 ◽  
Author(s):  
Juha Silvanto ◽  
Alvaro Pascual-Leone

A central aim in cognitive neuroscience is to explain how neural activity gives rise to perception and behavior; the causal link of paramount interest is thus from brain to behavior. Functional neuroimaging studies, however, tend to provide information in the opposite direction by informing us how manipulation of behavior may affect neural activity. Although this may provide valuable insights into neuronal properties, one cannot use such evidence to make inferences about the behavioral significance of the observed activations; if A causes B, it does not necessarily follow that B causes A. In contrast, brain stimulation techniques enable us to directly modulate brain activity as the source of behavior and thus establish causal links.


2021 ◽  
Vol 11 (3) ◽  
pp. 330
Author(s):  
Dalton J. Edwards ◽  
Logan T. Trujillo

Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4–7 Hz, alpha: 8–13 Hz, low beta: 14–20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Abdelrahman M. Alhilou ◽  
Akiko Shimada ◽  
Camilla I. Svensson ◽  
Peter Svensson ◽  
Malin Ernberg ◽  
...  

AbstractThe neurophysiological mechanisms underlying NGF-induced masseter muscle sensitization and sex-related differences in its effect are not well understood in humans. Therefore, this longitudinal cohort study aimed to investigate the effect of NGF injection on the density and expression of substance P, NMDA-receptors and NGF by the nerve fibers in the human masseter muscle, to correlate expression with pain characteristics, and to determine any possible sex-related differences in these effects of NGF. The magnitude of NGF-induced mechanical sensitization and pain during oral function was significantly greater in women than in men (P < 0.050). Significant positive correlations were found between nerve fiber expression of NMDA-receptors and peak pain intensity (rs = 0.620, P = 0.048), and expression of NMDA-receptors by putative nociceptors and change in temporal summation pain after glutamate injection (rs = 0.561, P = 0.003). In women, there was a significant inverse relationship between the degree of NGF-induced mechanical sensitization and the change in nerve fiber expression of NMDA-receptors alone (rs = − 0.659, P = 0.013), and in combination with NGF (rs = − 0.764, P = 0.001). In conclusion, women displayed a greater magnitude of NGF-induced mechanical sensitization that also was associated with nerve fibers expression of NMDA-receptors, when compared to men. The present findings suggest that, in women, increased peripheral NMDA-receptor expression could be associated with masseter muscle pain sensitivity.


2018 ◽  
Vol 30 (12) ◽  
pp. 1883-1901 ◽  
Author(s):  
Nicolò F. Bernardi ◽  
Floris T. Van Vugt ◽  
Ricardo Ruy Valle-Mena ◽  
Shahabeddin Vahdat ◽  
David J. Ostry

The relationship between neural activation during movement training and the plastic changes that survive beyond movement execution is not well understood. Here we ask whether the changes in resting-state functional connectivity observed following motor learning overlap with the brain networks that track movement error during training. Human participants learned to trace an arched trajectory using a computer mouse in an MRI scanner. Motor performance was quantified on each trial as the maximum distance from the prescribed arc. During learning, two brain networks were observed, one showing increased activations for larger movement error, comprising the cerebellum, parietal, visual, somatosensory, and cortical motor areas, and the other being more activated for movements with lower error, comprising the ventral putamen and the OFC. After learning, changes in brain connectivity at rest were found predominantly in areas that had shown increased activation for larger error during task, specifically the cerebellum and its connections with motor, visual, and somatosensory cortex. The findings indicate that, although both errors and accurate movements are important during the active stage of motor learning, the changes in brain activity observed at rest primarily reflect networks that process errors. This suggests that error-related networks are represented in the initial stages of motor memory formation.


2019 ◽  
Author(s):  
Jennifer Stiso ◽  
Marie-Constance Corsi ◽  
Javier Omar Garcia ◽  
Jean M Vettel ◽  
Fabrizio De Vico Fallani ◽  
...  

Motor imagery-based brain-computer interfaces (BCIs) use an individual’s ability to volitionally modulate localized brain activity, often as a therapy for motor dysfunction or to probe causal relations between brain activity and behavior. However, many individuals cannot learn to successfully modulate their brain activity, greatly limiting the efficacy of BCI for therapy and for basic scientific inquiry. Formal experiments designed to probe the nature of BCI learning have offered initial evidence that coherent activity across diverse cognitive systems is a hallmark of individuals who can successfully learn to control the BCI. However, little is known about how these distributed networks interact through time to support learning. Here, we address this gap in knowledge by constructing and applying a multimodal network approach to decipher brain-behavior relations in motor imagery-based brain-computer interface learning using magnetoencephalography. Specifically, we employ a minimally constrained matrix decomposition method -- non-negative matrix factorization -- to simultaneously identify regularized, covarying subgraphs of functional connectivity and behavior, and to detect the time-varying expression of each subgraph. We find that learning is marked by distributed brain-behavior relations: swifter learners displayed many subgraphs whose temporal expression tracked performance. Learners also displayed marked variation in the spatial properties of subgraphs such as the connectivity between the frontal lobe and the rest of the brain, and in the temporal properties of subgraphs such as the stage of learning at which they reached maximum expression. From these observations, we posit a conceptual model in which certain subgraphs support learning by modulating brain activity in networks important for sustaining attention. After formalizing the model in the framework of network control theory, we test the model and find that good learners display a single subgraph whose temporal expression tracked performance and whose architecture supports easy modulation of brain regions important for attention. The nature of our contribution to the neuroscience of BCI learning is therefore both computational and theoretical; we first use a minimally-constrained, individual specific method of identifying mesoscale structure in dynamic brain activity to show how global connectivity and interactions between distributed networks supports BCI learning, and then we use a formal network model of control to lend theoretical support to the hypothesis that these identified subgraphs are well suited to modulate attention.


2021 ◽  
Vol 11 (10) ◽  
pp. 1286
Author(s):  
Francesco Di Russo ◽  
Stefania Lucia

The main aim of Cognitive Neuroscience is investigating how brain functions lead to mental processes and behavior [...]


Author(s):  
Juergen Dukart ◽  
Ross D. Markello ◽  
Adrian Raine ◽  
Simon B. Eickhoff ◽  
Timm B. Poeppl

Sign in / Sign up

Export Citation Format

Share Document