Response preparation and inhibition: the role of the cortical sensorimotor beta rhythm

Beta-band oscillations--signalling the status quo?

In this review, we consider the potential functional role of beta-band oscillations, which at present is not yet well understood. We discuss evidence from recent studies on top-down mechanisms involved in cognitive processing, on the motor system and on the pathophysiology of movement disorders that suggest a unifying hypothesis: beta-band activity seems related to the maintenance of the current sensorimotor or cognitive state. We hypothesize that beta oscillations and/or coupling in the beta-band are expressed more strongly if the maintenance of the status quo is intended or predicted, than if a change is expected. Moreover, we suggest that pathological enhancement of beta-band activity is likely to result in an abnormal persistence of the status quo and a deterioration of flexible behavioural and cognitive control.

Fast and slow oscillations in human primary motor cortex predict oncoming behaviorally relevant cues

Beta oscillations (12-30 Hz) in local field potentials are prevalent in the motor system, yet their functional role within the context of planning a movement is still debated. In this study, a human participant implanted with a multielectrode array in the hand area of primary motor cortex (MI) was instructed to plan a movement using either the second or fourth of five sequentially presented instruction cues. The beta amplitude increased from the start of the trial until the informative (second or fourth) cue, and was diminished afterwards. Moreover, the beta amplitude peaked just prior to each instruction cue and the delta frequency (0.5-1.5 Hz) entrained to the interval between the cues-but only until the informative cue. This result suggests that the beta amplitude and delta phase in MI reflect the subject's engagement with the rhythmically presented cues and work together to enhance sensitivity to predictable and task-relevant visual cues.

Using Granger-Geweke causality model to evaluate the effective connectivity of primary motor cortex (M1), supplementary motor area (SMA) and cerebellum

Currently, Granger-Geweke causality models have been widely applied to investigate the dynamic direction relationships among brain regions. In a previous study, we have found that the right hand finger-tapping task can produce relatively reliable brain response. As an extension of our previous study, we developed an algorithm based on the classical Granger-Geweke causality model to further investigate the effective connectivity of three brain regions (left primary motor cortex (M1), supplementary motor area (SMA) and right cerebellum) that showed the most robust brain activations. Our computational results not only confirm the strong linear feedback among SMA, M1 and right cerebellum, but also demonstrate that M1 is the hub of these three regions indicated by the anatomy research. Moreover, the model predicts the high intermediate node density existing in the area between SMA and M1, which will stimulate the imaging experimentalists to carry out new experiments to validate this postulation.

Unconscious errors enhance prefrontal-occipital oscillatory synchrony

The medial prefrontal cortex (MFC) is critical for our ability to learn from previous mistakes. Here we provide evidence that neurophysiological oscillatory long-range synchrony is a mechanism of post-error adaptation that occurs even without conscious awareness of the error. During a visually signaled Go/No-Go task in which half of the No-Go cues were masked and thus not consciously perceived, response errors enhanced tonic (i.e., over 1–2 s) oscillatory synchrony between MFC and occipital cortex (OCC) leading up to and during the subsequent trial. Spectral Granger causality analyses demonstrated that MFC → OCC directional synchrony was enhanced during trials following both conscious and unconscious errors, whereas transient stimulus-induced occipital → MFC directional synchrony was independent of errors in the previous trial. Further, the strength of pre-trial MFC-occipital synchrony predicted individual differences in task performance. Together, these findings suggest that synchronous neurophysiological oscillations are a plausible mechanism of MFC-driven cognitive control that is independent of conscious awareness.

Boosting cortical activity at Beta-band frequencies slows movement in humans

Neurons have a striking tendency to engage in oscillatory activities. One important type of oscillatory activity prevalent in the motor system occurs in the beta frequency band, at about 20 Hz. It is manifest during the maintenance of tonic contractions and is suppressed prior to and during voluntary movement [1–7]. This and other correlative evidence suggests that beta activity might promote tonic contraction, while impairing motor processing related to new movements [3, 8, 9]. Hence, bursts of beta activity in the cortex are associated with a strengthening of the motor effects of sensory feedback during tonic contraction and with reductions in the velocity of voluntary movements [9–11]. Moreover, beta activity is increased when movement has to be resisted or voluntarily suppressed [7, 12, 13]. Here we use imperceptible transcranial alternating-current stimulation to entrain cortical activity at 20 Hz in healthy subjects and show that this slows voluntary movement. The present findings are the first direct evidence of causality between any physiological oscillatory brain activity and concurrent motor behavior in the healthy human and help explain how the exaggerated beta activity found in Parkinson's disease can lead to motor slowing in this illness [14].

Prestimulus alpha and mu activity predicts failure to inhibit motor responses

Do certain brain states predispose humans to commit errors in monotonous tasks? We used MEG to investigate how oscillatory brain activity indexes the brain state in subjects performing a Go-noGo task. Elevated occipital alpha and sensorimotor mu activity just prior to the presentation of the stimuli predicted an upcoming error. An error resulted in increased frontal theta activity and decreased posterior alpha activity. This theta increase and alpha decrease correlated on a trial-by-trial basis reflecting post-error functional connectivity between the frontal and occipital regions. By examining the state of the brain before a stimulus, we were able to show that it is possible to predict lapses of attention before they actually occur. This supports the case that the state of the brain is important for how incoming stimuli are processed and for how subjects respond.

Optimizing microsurgical skills with EEG neurofeedback

Background

By enabling individuals to self-regulate their brainwave activity in the field of optimal performance in healthy individuals, neurofeedback has been found to improve cognitive and artistic performance. Here we assessed whether two distinct EEG neurofeedback protocols could develop surgical skill, given the important role this skill plays in medicine.

Results

National Health Service trainee ophthalmic microsurgeons (N = 20) were randomly assigned to either Sensory Motor Rhythm-Theta (SMR) or Alpha-Theta (AT) groups, a randomized subset of which were also part of a wait-list 'no-treatment' control group (N = 8). Neurofeedback groups received eight 30-minute sessions of EEG training. Pre-post assessment included a skills lab surgical procedure with timed measures and expert ratings from video-recordings by consultant surgeons, together with state/trait anxiety self-reports. SMR training demonstrated advantages absent in the control group, with improvements in surgical skill according to 1) the expert ratings: overall technique (d = 0.6, p < 0.03) and suture task (d = 0.9, p < 0.02) (judges' intraclass correlation coefficient = 0.85); and 2) with overall time on task (d = 0.5, p = 0.02), while everyday anxiety (trait) decreased (d = 0.5, p < 0.02). Importantly the decrease in surgical task time was strongly associated with SMR EEG training changes (p < 0.01), especially with continued reduction of theta (4–7 Hz) power. AT training produced marginal improvements in technique and overall performance time, which were accompanied by a standard error indicative of large individual differences. Notwithstanding, successful within session elevation of the theta-alpha ratio correlated positively with improvements in overall technique (r = 0.64, p = 0.047).

Conclusion

SMR-Theta neurofeedback training provided significant improvement in surgical technique whilst considerably reducing time on task by 26%. There was also evidence that AT training marginally reduced total surgery time, despite suboptimal training efficacies. Overall, the data set provides encouraging evidence of optimised learning of a complex medical specialty via neurofeedback training.

Denoising neural data with state-space smoothing: method and application

Neural data are inevitably contaminated by noise. When such noisy data are subjected to statistical analysis, misleading conclusions can be reached. Here we attempt to address this problem by applying a state-space smoothing method, based on the combined use of the Kalman filter theory and the Expectation-Maximization algorithm, to denoise two datasets of local field potentials recorded from monkeys performing a visuomotor task. For the first dataset, it was found that the analysis of the high gamma band (60-90 Hz) neural activity in the prefrontal cortex is highly susceptible to the effect of noise, and denoising leads to markedly improved results that were physiologically interpretable. For the second dataset, Granger causality between primary motor and primary somatosensory cortices was not consistent across two monkeys and the effect of noise was suspected. After denoising, the discrepancy between the two subjects was significantly reduced.

Olfactory oscillations: the what, how and what for

Olfactory system oscillations play out with beautiful temporal and behavioral regularity on the oscilloscope and seem to scream 'meaning'. Always there is the fear that, although attractive, these symbols of dynamic regularity might be just seductive epiphenomena. There are now many studies that have isolated some of the neural mechanisms involved in these oscillations, and recent work argues that they are functional and even necessary at the physiological and cognitive levels. However, much remains to be done for a full understanding of their functions.

Analyzing multiple spike trains with nonparametric Granger causality

Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation.

Decomposing neural synchrony: toward an explanation for near-zero phase-lag in cortical oscillatory networks

Background

Synchronized oscillation in cortical networks has been suggested as a mechanism for diverse functions ranging from perceptual binding to memory formation to sensorimotor integration. Concomitant with synchronization is the occurrence of near-zero phase-lag often observed between network components. Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles.

Methodology/Principal Findings

Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1) positively correlated common input with no significant relative time delay and (2) bidirectional interaction. Thus far, no empirical test of these hypotheses has been possible for lack of means to tease apart the specific causes underlying the observed synchrony. In this work simulation examples were first used to illustrate the ideas. A quantitative method that decomposes the statistical interdependence between two cortical areas into a feed-forward, a feed-back and a common-input component was then introduced and applied to test the hypotheses on multichannel local field potential recordings from two behaving monkeys.

Conclusion/Significance

The near-zero phase-lag phenomenon is important in the study of large-scale oscillatory networks. A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon. Given the critical role that oscillatory activity is likely to play in the regulation of biological processes at all levels, the significance of the proposed method may extend beyond systems neuroscience, the level at which the present analysis is conceived and performed.

Left inferior frontal gyrus is critical for response inhibition

Background

Lesion studies in human and non-human primates have linked several different regions of prefrontal cortex (PFC) with the ability to inhibit inappropriate motor responses. However, recent functional neuroimaging studies have specifically implicated right inferior PFC in response inhibition. Right frontal dominance for inhibitory motor control has become a commonly accepted view, although support for this position has not been consistent. Particularly conspicuous is the lack of data on the importance of the homologous region in the left hemisphere. To investigate whether the left inferior frontal gyrus (IFG) is critical for response inhibition, we used neuropsychological methodology with carefully characterized brain lesions in neurological patients.

Results

Twelve individuals with damage in the left IFG and the insula were tested in a Go/NoGo response inhibition task. In alternating blocks, the difficulty of response inhibition was easy (50% NoGo trials) or hard (10% NoGo trials). Controls showed the predicted pattern of faster reaction times and more false alarm errors in the hard condition. Left IFG patients had higher error rates than controls in both conditions, but were more impaired in the hard condition, when a greater degree of inhibitory control was required. In contrast, a patient control group with orbitofrontal cortex lesions showed intact performance.

Conclusion

Recent neuroimaging studies have focused on a highly specific association between right IFG and inhibitory control. The present results indicate that the integrity of left IFG is also critical for successful implementation of inhibitory control over motor responses. Our findings demonstrate the importance of obtaining converging evidence from multiple methodologies in cognitive neuroscience.