High-Gamma Activity Is Coupled to Low-Gamma Oscillations in Precentral Cortices and Modulates with Movement and Speech.

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated.

Identifying Naturalistic Movies from Human Brain Activity with High-Density Diffuse Optical Tomography.

Modern neuroimaging modalities, particularly functional MRI (fMRI), can decode detailed human experiences. Thousands of viewed images can be identified or classified, and sentences can be reconstructed. Decoding paradigms often leverage encoding models that reduce the stimulus space into a smaller yet generalizable feature set.

Ultra-high density imaging arrays for diffuse optical tomography of human brain improve resolution, signal-to-noise, and information decoding.

Functional magnetic resonance imaging (fMRI) has dramatically advanced non-invasive human brain mapping and decoding. Functional near-infrared spectroscopy (fNIRS) and high-density diffuse optical tomography (HD-DOT) non-invasively measure blood oxygen fluctuations related to brain activity, like fMRI, at the brain surface, using more-lightweight equipment that circumvents ergonomic and logistical limitations of fMRI. HD-DOT grids have smaller inter-optode spacing (∼13 mm) than sparse fNIRS (∼30 mm) and therefore provide higher image quality, with spatial resolution ∼1/2 that of fMRI.

Scalable, modular continuous wave functional near-infrared spectroscopy system (Spotlight).

Significance: We present a fiberless, portable, and modular continuous wave-functional near-infrared spectroscopy system, Spotlight, consisting of multiple palm-sized modules-each containing high-density light-emitting diode and silicon photomultiplier detector arrays embedded in a flexible membrane that facilitates optode coupling to scalp curvature.

Aim: Spotlight's goal is to be a more portable, accessible, and powerful functional near-infrared spectroscopy (fNIRS) device for neuroscience and brain-computer interface (BCI) applications. We hope that the Spotlight designs we share here can spur more advances in fNIRS technology and better enable future non-invasive neuroscience and BCI research.

High-gamma activity is coupled to low-gamma oscillations in precentral cortices and modulates with movement and speech.

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated.

Multivariate Kalman filter regression of confounding physiological signals for real-time classification of fNIRS data.

: Functional near-infrared spectroscopy (fNIRS) is a noninvasive technique for measuring hemodynamic changes in the human cortex related to neural function. Due to its potential for miniaturization and relatively low cost, fNIRS has been proposed for applications, such as brain-computer interfaces (BCIs). The relatively large magnitude of the signals produced by the extracerebral physiology compared with the ones produced by evoked neural activity makes real-time fNIRS signal interpretation challenging.

Hemicraniectomy in Traumatic Brain Injury: A Noninvasive Platform to Investigate High Gamma Activity for Brain Machine Interfaces.

Brain-machine interfaces (BMIs) translate brain signals into control signals for an external device, such as a computer cursor or robotic limb. These signals can be obtained either noninvasively or invasively. Invasive recordings, using electrocorticography (ECoG) or intracortical microelectrodes, provide higher bandwidth and more informative signals.

Myoelectric Computer Interface Training for Reducing Co-Activation and Enhancing Arm Movement in Chronic Stroke Survivors: A Randomized Trial.

Background: Abnormal muscle co-activation contributes to impairment after stroke. We developed a myoelectric computer interface (MyoCI) training paradigm to reduce abnormal co-activation. MyoCI provides intuitive feedback about muscle activation patterns, enabling decoupling of these muscles.

The effect of myoelectric computer interface training on arm kinematics and function after stroke.

Abnormal co-activation patterns of arm muscles is a substantial cause of impaired arm function after stroke. We designed a myoelectric computer interface (MCI) training paradigm to help stroke survivors reduce this abnormal coactivation. Here, we evaluated the effects of MCI training on function and arm kinematics in 32 chronic stroke survivors.

Differential Representation of Articulatory Gestures and Phonemes in Precentral and Inferior Frontal Gyri.

Speech is a critical form of human communication and is central to our daily lives. Yet, despite decades of study, an understanding of the fundamental neural control of speech production remains incomplete. Current theories model speech production as a hierarchy from sentences and phrases down to words, syllables, speech sounds (phonemes), and the actions of vocal tract articulators used to produce speech sounds (articulatory gestures).

Corneal Potential Maps Measured With Multi-Electrode Electroretinography in Rat Eyes With Experimental Lesions.

Purpose: Conventional full-field flash electroretinography (ERG) yields a single response waveform that can be useful in the early detection and diagnosis of many diseases affecting the retina. It is an objective measurement that probes the entire retina. However, localized areas of dysfunction have relatively small influence on ERG amplitudes compared to normal ranges.

Decoding of articulatory gestures during word production using speech motor and premotor cortical activity.

Brain-machine interfaces that directly translate attempted speech from the speech motor areas could change the lives of people with complete paralysis. However, it remains uncertain exactly how speech production is encoded in cortex. Improving this understanding could greatly improve brain-machine interface design.

Cortical encoding of phonemic context during word production.

Brain-computer interfaces that directly decode speech could restore communication to locked-in individuals. However, decoding speech from brain signals still faces many challenges. We investigated decoding of phonemes - the smallest separable parts of speech - from ECoG signals during word production.

Direct classification of all American English phonemes using signals from functional speech motor cortex.

Objective: Although brain-computer interfaces (BCIs) can be used in several different ways to restore communication, communicative BCI has not approached the rate or efficiency of natural human speech. Electrocorticography (ECoG) has precise spatiotemporal resolution that enables recording of brain activity distributed over a wide area of cortex, such as during speech production. In this study, we sought to decode elements of speech production using ECoG.

Design and implementation of a P300-based brain-computer interface for controlling an internet browser.

An electroencephalographic (EEG) brain-computer interface (BCI) internet browser was designed and evaluated with 10 healthy volunteers and three individuals with advanced amyotrophic lateral sclerosis (ALS), all of whom were given tasks to execute on the internet using the browser. Participants with ALS achieved an average accuracy of 73% and a subsequent information transfer rate (ITR) of 8.6 bits/min and healthy participants with no prior BCI experience over 90% accuracy and an ITR of 14.