Eric C. Leuthardt

OBJECTIVE. Electrocortical stimulation (ECS) has long been established for delineating eloquent cortex in extraoperative mapping. However, ECS is still

Brain rhythms are more than just passive phenomena in visual cortex. For the first time, we show that the physiology underlying brain rhythms actively suppresses and releases cortical areas on a second-to-second basis during visual processing. Furthermore, their influence is specific at the scale of individual gyri. We quantified the interaction between broadband spectral change and brain rhythms on a second-to-second basis in electrocorticographic (ECoG) measurement of brain surface potentials in five human subjects during a visual search task. Comparison of visual search epochs with a blank screen baseline revealed changes in the raw potential, the amplitude of rhythmic activity, and in the decoupled broadband spectral amplitude. We present new methods to characterize the intensity and preferred phase of coupling between broadband power and band-limited rhythms, and to estimate the magnitude of rhythm-to-broadband modulation on a trial-by-trial basis. These tools revealed numerous coupling motifs between the phase of low-frequency (δ, θ, α, β, and γ band) rhythms and the amplitude of broadband spectral change. In the θ and β ranges, the coupling of phase to broadband change is dynamic during visual processing, decreasing in some occipital areas and increasing in others, in a gyrally specific pattern. Finally, we demonstrate that the rhythms interact with one another across frequency ranges, and across cortical sites.

Objective: Traditional electrocortical stimulation (ECS) mapping is limited by the lengthy serial investigation (one location at a time) and the risk of afterdischarges in localizing eloquent cortex. Electrocorticographic frequency alteration mapping (EFAM) allows the parallel investigation of many cortical sites in much less time and with no risk of afterdischarges because of its passive nature. We examined its use with ECS in the context of language mapping during an awake craniotomy for a tumor resection. Clinical Presentation: The patient was a 61-year-old right-handed Caucasian male who presented with headache and mild aphasia. Imaging demonstrated a 3-cm cystic mass in the posterior temporal-parietal lobe. The patient underwent an awake craniotomy for the mapping of his speech cortex and resection of the mass. Intervention: Using a 32-contact electrode array, electrocorticographic signals were recorded from the exposed cortex as the patient participated in a 3-min screening task involving active (patient naming visually presented words) and rest (patient silent) conditions. A spectral comparison of the 2 conditions revealed specific cortical locations associated with activation during speech. The patient was then widely mapped using ECS. Three of 4 sites identified by ECS were also identified passively and in parallel by EFAM, 2 with statistical significance and the third by qualitative inspection. Conclusion: EFAM was technically achieved in an awake craniotomy patient and had good concordance with ECS mapping. Because it poses no risk of afterdischarges and offers substantial time savings, EFAM holds promise for future development as an adjunct intraoperative mapping tool. Additionally, the cortical signals obtained by this modality can be utilized for localization in the presence of a tumor adjacent to the eloquent regions.

The majority of Brain Computer Interfaces have relied on signals related to primary motor cortex and the operation of the contralateral limb. Recently, the physiology associated with same-sided (ipsilateral) motor movements has been found to have a unique cortical physiology. This study sets out to assess whether more complex motor movements can be discerned utilizing ipsilateral cortical signals. In this study, three invasively monitored human subjects were recorded while performing a center out joystick task with the hand ipsilateral to the hemispheric subdural grid array. It was found that directional tuning was present in ipsilateral cortex. This information was encoded in both distinct anatomic populations and spectral distributions. These findings support the notion that ipsilateral signals may provide added information for BCI operation in the future.

Object: There is a growing interest in the use of recording from the surface of the brain, known as electrocorticography (ECoG), as a practical signal platform for brain-computer interface application. The signal has a combination of high signal quality and long-term stability that may be the ideal intermediate modality for future application. The research paradigm for studying ECoG signals uses patients requiring invasive monitoring for seizure localization. The implanted arrays span cortex areas on the order of centimeters. Currently, it is unknown what level of motor information can be discerned from small regions of human cortex with microscale ECoG recording. Methods: In this study, a patient requiring invasive monitoring for seizure localization underwent concurrent implantation with a 16-microwire array (1-mm electrode spacing) placed over primary motor cortex. Microscale activity was recorded while the patient performed simple contra- and ipsilateral wrist movements that were monitored in parallel with electromyography. Using various statistical methods, linear and nonlinear relationships between these microcortical changes and recorded electromyography activity were defined. Results: Small regions of primary motor cortex (< 5 mm) carry sufficient information to separate multiple aspects of motor movements (that is, wrist flexion/extension and ipsilateral/contralateral movements). Conclusions: These findings support the conclusion that small regions of cortex investigated by ECoG recording may provide sufficient information about motor intentions to support brain-computer interface operations in the future. Given the small scale of the cortical region required, the requisite implanted array would be minimally invasive in terms of surgical placement of the electrode array.

The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future.