Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Dynamic functional connectivity: Promise, issues, and interpretations

https://www.cell.com/trends/cognitive-sciences/pdf/S1364-6613(12)00243-4.pdf

Alpha-band oscillations, attention, and controlled access to stored information

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.

Beta-band oscillations--signalling the status quo?

http://www.unicog.org/publications/DehaeneChangeux_ReviewConsciousness_Neuron2011.pdf

Experimental and Theoretical Approaches to Conscious Processing

Little is known about the brain-wide correlation of electrophysiological signals. We found that spontaneous oscillatory neuronal activity exhibited frequency-specific spatial correlation structure in the human brain. We developed an analysis approach that discounts spurious correlation of signal power caused by the limited spatial resolution of electrophysiological measures. We applied this approach to source estimates of spontaneous neuronal activity reconstructed from magnetoencephalography. Overall, correlation of power across cortical regions was strongest in the alpha to beta frequency range (8–32 Hz) and correlation patterns depended on the underlying oscillation frequency. Global hubs resided in the medial temporal lobe in the theta frequency range (4–6 Hz), in lateral parietal areas in the alpha to beta frequency range (8–23 Hz) and in sensorimotor areas for higher frequencies (32–45 Hz). Our data suggest that interactions in various large-scale cortical networks may be reflected in frequency-specific power envelope correlations.

/pdf/large-scale-cortical-correlation-structure-of-spontaneous-lwplexcefd.pdf

Large-scale cortical correlation structure of spontaneous oscillatory activity.

Time-Frequency Analysis.

http://www.markussiegel.net/download/hipp_neuron_2011.pdf

Oscillatory Synchronization in Large-Scale Cortical Networks Predicts Perception

Correlations in spontaneous brain activity provide powerful access to large-scale organizational principles of the CNS. However, making inferences about cognitive processes requires a detailed understanding of the link between these couplings and the structural integrity of the CNS. We studied the impact of multiple sclerosis, which leads to the severe disintegration of the central white matter, on functional connectivity patterns in spontaneous cortical activity. Using a data driven approach based on the strength of a salient pattern of cognitive pathology, we identified distinct networks that exhibit increases in functional connectivity despite the presence of strong and diffuse reductions of the central white-matter integrity. The default mode network emerged as a core target of these connectivity modulations, showing enhanced functional coupling in bilateral inferior parietal cortex, posterior cingulate, and medial prefrontal cortex. These findings imply a complex and diverging relation of anatomical and functional connectivity in early multiple sclerosis and, thus, add an important observation for understanding how cognitive abilities and CNS integrity may be reflected in the intrinsic covariance of functional signals.

/pdf/increased-functional-connectivity-indicates-the-severity-of-2ksgs221jh.pdf

Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis

EEG is the most common technique for studying neuronal dynamics of the human brain. However, electromyogenic artifacts from cranial muscles and ocular muscles executing involuntary microsaccades compromise estimates of neuronal activity in the gamma band (> 30 Hz). Yet, the relative contributions and practical consequences of these artifacts remain unclear. Here, we systematically dissected the effects of these different artifacts on studying visual gamma-band activity with EEG on the sensor and source level, and show strategies to cope with these confounds. We found that cranial muscle activity prevented a direct investigation of neuronal gamma-band activity at the sensor level. Furthermore, we found prolonged microsaccade-related artifacts beyond the well-known transient EEG confounds. We then show that if electromyogenic artifacts are carefully accounted for, the EEG nonetheless allows for studying visual gamma-band activity even at the sensor level. Furthermore, we found that source analysis based on spatial filtering does not only map the EEG signals to the cortical space of interest, but also efficiently accounts for cranial and ocular muscle artifacts. Together, our results clarify the relative contributions and characteristics of myogenic artifacts confounding visual gamma band activity in EEG, and provide practical guidelines for future experiments.

/pdf/dissociating-neuronal-gamma-band-activity-from-cranial-and-1epleolc7v.pdf

Joerg F. Hipp

Papers

Large-scale cortical correlation structure of spontaneous oscillatory activity.

Time-Frequency Analysis.

Oscillatory Synchronization in Large-Scale Cortical Networks Predicts Perception

Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis

Dissociating neuronal gamma-band activity from cranial and ocular muscle activity in EEG.