Brain-Computer Interfaces for Communication in Patients with Disorders of Consciousness: A Gap Analysis and Scientific Roadmap.

Background: We developed a gap analysis that examines the role of brain-computer interfaces (BCI) in patients with disorders of consciousness (DoC), focusing on their assessment, establishment of communication, and engagement with their environment.

Methods: The Curing Coma Campaign convened a Coma Science work group that included 16 clinicians and neuroscientists with expertise in DoC. The work group met online biweekly and performed a gap analysis of the primary question.

Local changes in network structure contribute to late communication recovery after severe brain injury.

Spontaneous recovery of brain function after severe brain injury may evolve over a long time period and is likely to involve both structural and functional reorganization of brain networks. We longitudinally tracked the recovery of communication in a patient with severe brain injury using multimodal brain imaging techniques and quantitative behavioral assessments measured at the bedside over a period of 2 years and 9 months (21 months after initial injury). Structural diffusion tensor imaging revealed changes in brain structure across interhemispheric connections and in local brain regions that support language and visuomotor function.

Phase-Amplitude Coupling in Spontaneous Mouse Behavior.

The level of activity of many animals including humans rises and falls with a period of ~ 24 hours. The intrinsic biological oscillator that gives rise to this circadian oscillation is driven by a molecular feedback loop with an approximately 24 hour cycle period and is influenced by the environment, most notably the light:dark cycle. In addition to the circadian oscillations, behavior of many animals is influenced by multiple oscillations occurring at faster-ultradian-time scales.

A perceptual space of local image statistics.

Local image statistics are important for visual analysis of textures, surfaces, and form. There are many kinds of local statistics, including those that capture luminance distributions, spatial contrast, oriented segments, and corners. While sensitivity to each of these kinds of statistics have been well-studied, much less is known about visual processing when multiple kinds of statistics are relevant, in large part because the dimensionality of the problem is high and different kinds of statistics interact.

Perception of second- and third-order orientation signals and their interactions.

Orientation signals, which are crucial to many aspects of visual function, are more complex and varied in the natural world than in the stimuli typically used for laboratory investigation. Gratings and lines have a single orientation, but in natural stimuli, local features have multiple orientations, and multiple orientations can occur even at the same location. Moreover, orientation cues can arise not only from pairwise spatial correlations, but from higher-order ones as well.