Fast-scale network dynamics in human cortex have specific spectral covariance patterns.

Whether measured by MRI or direct cortical physiology, infraslow rhythms have defined state invariant cortical networks. The time scales of this functional architecture, however, are unlikely to be able to accommodate the more rapid cortical dynamics necessary for an active cognitive task. Using invasively monitored epileptic patients as a research model, we tested the hypothesis that faster frequencies would spectrally bind regions of cortex as a transient mechanism to enable fast network interactions during the performance of a simple hear-and-repeat speech task. We term these short-lived spectrally covariant networks functional spectral networks (FSNs). We evaluated whether spectrally covariant regions of cortex, which were unique in their spectral signatures, provided a higher degree of task-related information than any single site showing more classic physiologic responses (i.e., single-site amplitude modulation). Taken together, our results showing that FSNs are a more sensitive measure of task-related brain activation and are better able to discern phonemic content strongly support the concept of spectrally encoded interactions in cortex. Moreover, these findings that specific linguistic information is represented in FSNs that have broad anatomic topographies support a more distributed model of cortical processing.

Frequency-specific mechanism links human brain networks for spatial attention.

Selective attention allows us to filter out irrelevant information in the environment and focus neural resources on information relevant to our current goals. Functional brain-imaging studies have identified networks of broadly distributed brain regions that are recruited during different attention processes; however, the dynamics by which these networks enable selection are not well understood. Here, we first used functional MRI to localize dorsal and ventral attention networks in human epileptic subjects undergoing seizure monitoring. We subsequently recorded cortical physiology using subdural electrocorticography during a spatial-attention task to study network dynamics. Attention networks become selectively phase-modulated at low frequencies (δ, θ) during the same task epochs in which they are recruited in functional MRI. This mechanism may alter the excitability of task-relevant regions or their effective connectivity. Furthermore, different attention processes (holding vs. shifting attention) are associated with synchrony at different frequencies, which may minimize unnecessary cross-talk between separate neuronal processes.

Stable and dynamic cortical electrophysiology of induction and emergence with propofol anesthesia.

The mechanism(s) by which anesthetics reversibly suppress consciousness are incompletely understood. Previous functional imaging studies demonstrated dynamic changes in thalamic and cortical metabolic activity, as well as the maintained presence of metabolically defined functional networks despite the loss of consciousness. However, the invasive electrophysiology associated with these observations has yet to be studied. By recording electrical activity directly from the cortical surface, electrocorticography (ECoG) provides a powerful method to integrate spatial, temporal, and spectral features of cortical electrophysiology not possible with noninvasive approaches. In this study, we report a unique comprehensive recording of invasive human cortical physiology during both induction and emergence from propofol anesthesia. Propofol-induced transitions in and out of consciousness (defined here as responsiveness) were characterized by maintained large-scale functional networks defined by correlated fluctuations of the slow cortical potential (<0.5 Hz) over the somatomotor cortex, present even in the deeply anesthetized state of burst suppression. Similarly, phase-power coupling between θ- and γ-range frequencies persisted throughout the induction and emergence from anesthesia. Superimposed on this preserved functional architecture were alterations in frequency band power, variance, covariance, and phase-power interactions that were distinct to different frequency ranges and occurred in separable phases. These data support that dynamic alterations in cortical and thalamocortical circuit activity occur in the context of a larger stable architecture that is maintained despite anesthetic-induced alterations in consciousness.

Nonuniform high-gamma (60-500 Hz) power changes dissociate cognitive task and anatomy in human cortex.

High-gamma-band (>60 Hz) power changes in cortical electrophysiology are a reliable indicator of focal, event-related cortical activity. Despite discoveries of oscillatory subthreshold and synchronous suprathreshold activity at the cellular level, there is an increasingly popular view that high-gamma-band amplitude changes recorded from cellular ensembles are the result of asynchronous firing activity that yields wideband and uniform power increases. Others have demonstrated independence of power changes in the low- and high-gamma bands, but to date, no studies have shown evidence of any such independence above 60 Hz. Based on nonuniformities in time-frequency analyses of electrocorticographic (ECoG) signals, we hypothesized that induced high-gamma-band (60-500 Hz) power changes are more heterogeneous than currently understood. Using single-word repetition tasks in six human subjects, we showed that functional responsiveness of different ECoG high-gamma sub-bands can discriminate cognitive task (e.g., hearing, reading, speaking) and cortical locations. Power changes in these sub-bands of the high-gamma range are consistently present within single trials and have statistically different time courses within the trial structure. Moreover, when consolidated across all subjects within three task-relevant anatomic regions (sensorimotor, Broca's area, and superior temporal gyrus), these behavior- and location-dependent power changes evidenced nonuniform trends across the population. Together, the independence and nonuniformity of power changes across a broad range of frequencies suggest that a new approach to evaluating high-gamma-band cortical activity is necessary. These findings show that in addition to time and location, frequency is another fundamental dimension of high-gamma dynamics.

Spatiotemporal dynamics of electrocorticographic high gamma activity during overt and covert word repetition.

Language is one of the defining abilities of humans. Many studies have characterized the neural correlates of different aspects of language processing. However, the imaging techniques typically used in these studies were limited in either their temporal or spatial resolution. Electrocorticographic (ECoG) recordings from the surface of the brain combine high spatial with high temporal resolution and thus could be a valuable tool for the study of neural correlates of language function. In this study, we defined the spatiotemporal dynamics of ECoG activity during a word repetition task in nine human subjects. ECoG was recorded while each subject overtly or covertly repeated words that were presented either visually or auditorily. ECoG amplitudes in the high gamma (HG) band confidently tracked neural changes associated with stimulus presentation and with the subject's verbal response. Overt word production was primarily associated with HG changes in the superior and middle parts of temporal lobe, Wernicke's area, the supramarginal gyrus, Broca's area, premotor cortex (PMC), primary motor cortex. Covert word production was primarily associated with HG changes in superior temporal lobe and the supramarginal gyrus. Acoustic processing from both auditory stimuli as well as the subject's own voice resulted in HG power changes in superior temporal lobe and Wernicke's area. In summary, this study represents a comprehensive characterization of overt and covert speech using electrophysiological imaging with high spatial and temporal resolution. It thereby complements the findings of previous neuroimaging studies of language and thus further adds to current understanding of word processing in humans.

Characterization of the effects of the human dura on macro- and micro-electrocorticographic recordings.

OBJECTIVE: Electrocorticography (ECoG) electrodes implanted on the surface of the brain have recently emerged as a potential signal platform for brain-computer interface (BCI) systems. While clinical ECoG electrodes are currently implanted beneath the dura, epidural electrodes could reduce the invasiveness and the potential impact of a surgical site infection. Subdural electrodes, on the other hand, while slightly more invasive, may have better signals for BCI application. Because of this balance between risk and benefit between the two electrode positions, the effect of the dura on signal quality must be determined in order to define the optimal implementation for an ECoG BCI system. APPROACH: This study utilized simultaneously acquired baseline recordings from epidural and subdural ECoG electrodes while patients rested. Both macro-scale (2 mm diameter electrodes with 1 cm inter-electrode distance, one patient) and micro-scale (75 µm diameter electrodes with 1 mm inter-electrode distance, four patients) ECoG electrodes were tested. Signal characteristics were evaluated to determine differences in the spectral amplitude and noise floor. Furthermore, the experimental results were compared to theoretical effects produced by placing epidural and subdural ECoG contacts of different sizes within a finite element model. MAIN RESULTS: The analysis demonstrated that for micro-scale electrodes, subdural contacts have significantly higher spectral amplitudes and reach the noise floor at a higher frequency than epidural contacts. For macro-scale electrodes, while there are statistical differences, these differences are small in amplitude and likely do not represent differences relevant to the ability of the signals to be used in a BCI system. CONCLUSIONS: Our findings demonstrate an important trade-off that should be considered in developing a chronic BCI system. While implanting electrodes under the dura is more invasive, it is associated with increased signal quality when recording from micro-scale electrodes with very small sizes and spacing. If recording from larger electrodes, such as traditionally used clinically, the signal quality of epidural recordings is similar to that of subdural recordings.

Brain mapping in a patient with congenital blindness - a case for multimodal approaches.

Recent advances in basic neuroscience research across a wide range of methodologies have contributed significantly to our understanding of human cortical electrophysiology and functional brain imaging. Translation of this research into clinical neurosurgery has opened doors for advanced mapping of functionality that previously was prohibitively difficult, if not impossible. Here we present the case of a unique individual with congenital blindness and medically refractory epilepsy who underwent neurosurgical treatment of her seizures. Pre-operative evaluation presented the challenge of accurately and robustly mapping the cerebral cortex for an individual with a high probability of significant cortical re-organization. Additionally, a blind individual has unique priorities in one's ability to read Braille by touch and sense the environment primarily by sound than the non-vision impaired person. For these reasons we employed additional measures to map sensory, motor, speech, language, and auditory perception by employing a number of cortical electrophysiologic mapping and functional magnetic resonance imaging methods. Our data show promising results in the application of these adjunctive methods in the pre-operative mapping of otherwise difficult to localize, and highly variable, functional cortical areas.

Mapping sensorimotor cortex with slow cortical potential resting-state networks while awake and under anesthesia.

BACKGROUND: The emerging insight into resting-state cortical networks has been important in our understanding of the fundamental architecture of brain organization. These networks, which were originally identified with functional magnetic resonance imaging, are also seen in the correlation topography of the infraslow rhythms of local field potentials. Because of the fundamental nature of these networks and their independence from task-related activations, we posit that, in addition to their neuroscientific relevance, these slow cortical potential networks could play an important role in clinical brain mapping. OBJECTIVE: To assess whether these networks would be useful in identifying eloquent cortex such as sensorimotor cortex in patients both awake and under anesthesia. METHODS: This study included 9 subjects undergoing surgical treatment for intractable epilepsy. Slow cortical potentials were recorded from the cortical surface in patients while awake and under propofol anesthesia. To test brain-mapping utility, slow cortical potential networks were identified with data-driven (seed-independent) and anatomy-driven (seed-based) approaches. With electrocortical stimulation used as the gold standard for comparison, the sensitivity and specificity of these networks for identifying sensorimotor cortex were calculated. RESULTS: Networks identified with a data-driven approach in patients under anesthesia and awake were 90% and 93% sensitive and 58% and 55% specific for sensorimotor cortex, respectively. Networks identified with systematic seed selection in patients under anesthesia and awake were 78% and 83% sensitive and 67% and 60% specific, respectively. CONCLUSION: Resting-state networks may be useful for tailoring stimulation mapping and could provide a means of identifying eloquent regions in patients while under anesthesia.

Decoding motor signals from the pediatric cortex: implications for brain-computer interfaces in children.

OBJECTIVE: To demonstrate the decodable nature of pediatric brain signals for the purpose of neuroprosthetic control. We hypothesized that children would achieve levels of brain-derived computer control comparable to performance previously reported for adults. PATIENTS AND METHODS: Six pediatric patients with intractable epilepsy who were invasively monitored underwent screening for electrocortical control signals associated with specific motor or phoneme articulation tasks. Subsequently, patients received visual feedback as they used these associated electrocortical signals to direct one dimensional cursor movement to a target on a screen. RESULTS: All patients achieved accuracies between 70% and 99% within 9 minutes of training using the same screened motor and articulation tasks. Two subjects went on to achieve maximum accuracies of 73% and 100% using imagined actions alone. Average mean and maximum performance for the 6 pediatric patients was comparable to that of 5 adults. The mean accuracy of the pediatric group was 81% (95% confidence interval [CI]: 71.5-90.5) over a mean training time of 11.6 minutes, whereas the adult group had a mean accuracy of 72% (95% CI: 61.2-84.3) over a mean training time of 12.5 minutes. Maximum performance was also similar between the pediatric and adult groups (89.6% [95% CI: 83-96.3] and 88.5% [95% CI: 77.1-99.8], respectively). CONCLUSIONS: Similarly to adult brain signals, pediatric brain signals can be decoded and used for BCI operation. Therefore, BCI systems developed for adults likely hold similar promise for children with motor disabilities.