Doctor of Philosophy

dissertationThis dissertation describes the use of cortical surface potentials, recorded with dense grids of microelectrodes, for brain-computer interfaces (BCIs). The work presented herein is an in-depth treatment of a broad and interdisciplinary topic, covering issues from electronics to electrodes, signals, and applications. Within the scope of this dissertation are several significant contributions. First, this work was the first to demonstrate that speech and arm movements could be decoded from surface local field potentials (LFPs) recorded in human subjects. Using surface LFPs recorded over face-motor cortex and Wernickes area, 150 trials comprising vocalized articulations of ten different words were classified on a trial-by-trial basis with 86% accuracy. Surface LFPs recorded over the hand and arm area of motor cortex were used to decode continuous hand movements, with correlation of 0.54 between the actual and predicted position over 70 seconds of movement. Second, this work is the first to make a detailed comparison of cortical field potentials recorded intracortically with microelectrodes and at the cortical surface with both micro- and macroelectrodes. Whereas coherence in macroelectrocorticography (ECoG) decayed to half its maximum at 5.1 mm separation in high frequencies, spatial constants of micro-ECoG signals were 530-700 ?m-much closer to the 110-160 ?m calculated for intracortical field potentials than to the macro-ECoG. These findings confirm that cortical surface potentials contain millimeter-scale dynamics. Moreover, these fine spatiotemporal features were important for the performance of speech and arm movement decoding. In addition to contributions in the areas of signals and applications, this dissertation includes a full characterization of the microelectrodes as well as collaborative work in which a custom, low-power microcontroller, with features optimized for biomedical implants, was taped out, fabricated in 65 nm CMOS technology, and tested. A new instruction was implemented in this microcontroller which reduced energy consumption when moving large amounts of data into memory by as much as 44%. This dissertation represents a comprehensive investigation of surface LFPs as an interfacing medium between man and machine. The nature of this work, in both the breadth of topics and depth of interdisciplinary effort, demonstrates an important and developing branch of engineering

Toward More Versatile and Intuitive Cortical Brain–Machine Interfaces

Brain–machine interfaces have great potential for the development of neuroprosthetic applications to assist patients suffering from brain injury or neurodegenerative disease. One type of brain–machine interface is a cortical motor prosthetic, which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. These include using: recordings from cortical areas outside motor cortex; local field potentials as a source of recorded signals; somatosensory feedback for more dexterous control of robotics; and new decoding methods that work in concert to form an ecology of decode algorithms. These new advances promise to greatly accelerate the applicability and ease of operation of motor prosthetics

Decoding stimulus identity from multi-unit activity and local field potentials along the ventral auditory stream in the awake primate: implications for cortical neural prostheses

Objective. Hierarchical processing of auditory sensory information is believed to occur in two streams: a ventral stream responsible for stimulus identity and a dorsal stream responsible for processing spatial elements of a stimulus. The objective of the current study is to examine neural coding in this processing stream in the context of understanding the possibility for an auditory cortical neural prosthesis. Approach. We examined the selectivity for species-specific primate vocalizations in the ventral auditory processing stream by applying a statistical classifier to neural data recorded from microelectrode arrays. Multi-unit activity (MUA) and local field potential (LFP) data recorded simultaneously from primary auditory complex (AI) and rostral parabelt (PBr) were decoded on a trial-by-trial basis. Main results. While decode performance in AI was well above chance, mean performance in PBr did not deviate >15% from chance level. Mean performance levels were similar for MUA and LFP decodes. Increasing the spectral and temporal resolution improved decode performance; while inter-electrode spacing could be as large as 1.14 mm without degrading decode performance. Significance. These results serve as preliminary guidance for a human auditory cortical neural prosthesis; instructing interface implementation, microstimulation patterns and anatomical placement

Decoding stimulus identity from multi-unit activity and local field potentials along the ventral auditory stream in the awake primate: implications for cortical neural prostheses

Objective. Hierarchical processing of auditory sensory information is believed to occur in two streams: a ventral stream responsible for stimulus identity and a dorsal stream responsible for processing spatial elements of a stimulus. The objective of the current study is to examine neural coding in this processing stream in the context of understanding the possibility for an auditory cortical neural prosthesis. Approach. We examined the selectivity for species-specific primate vocalizations in the ventral auditory processing stream by applying a statistical classifier to neural data recorded from microelectrode arrays. Multi-unit activity (MUA) and local field potential (LFP) data recorded simultaneously from primary auditory complex (AI) and rostral parabelt (PBr) were decoded on a trial-by-trial basis. Main results. While decode performance in AI was well above chance, mean performance in PBr did not deviate >15% from chance level. Mean performance levels were similar for MUA and LFP decodes. Increasing the spectral and temporal resolution improved decode performance; while inter-electrode spacing could be as large as 1.14 mm without degrading decode performance. Significance. These results serve as preliminary guidance for a human auditory cortical neural prosthesis; instructing interface implementation, microstimulation patterns and anatomical placement

Electronic color charts for dielectric films on silicon

This paper presents the calculation of the perceived color of dielectric films on silicon. A procedure is shown for computing the perceived color for an arbitrary light source, light incident angle, and film thickness. The calculated color is converted into RGB parameters that can be displayed on a color monitor, resulting in the generation of electronic color charts for dielectric films. This paper shows generated electronic color charts for both silicon dioxide and silicon nitride films on silicon

Electronic color charts for dielectric films on silicon

This paper presents the calculation of the perceived color of dielectric films on silicon. A procedure is shown for computing the perceived color for an arbitrary light source, light incident angle, and film thickness. The calculated color is converted into RGB parameters that can be displayed on a color monitor, resulting in the generation of electronic color charts for dielectric films. This paper shows generated electronic color charts for both silicon dioxide and silicon nitride films on silicon

Non ictal onset zone: A window to ictal dynamics

The focal and network concepts of epilepsy present different aspects of electroclinical phenomenon of seizures. Here, we present a 23-year-old man undergoing surgical evaluation with left fronto-temporal electrocorticography (ECoG) and microelectrode-array (MEA) in the middle temporal gyrus (MTG). We compare action-potential (AP) and local field potentials (LFP) recorded from MEA with ECoG. Seizure onset in the mesial-temporal lobe was characterized by changes in the pattern of AP-firing without clear changes in LFP or ECoG in MTG. This suggests simultaneous analysis of neuronal activity in differing spatial scales and frequency ranges provide complementary insights into how focal and network neurophysiological activity contribute to ictal activity

Multi-scale recordings for neuroprosthetic control of finger movements

We trained a rhesus monkey to perform individuated and combined finger flexions and extensions of the thumb, index, and middle finger. A Utah Electrode Array (UEA) was implanted into the hand region of the motor cortex contralateral to the monkey's trained hand. We also implanted a microwire electrocorticography grid (µECoG) epidurally so that it covered the UEA. The µECoG grid spanned the arm and hand regions of both the primary motor and somatosensory cortices. Previously this monkey had Implantable MyoElectric Sensors (IMES) surgically implanted into the finger muscles of the monkey's forearm. Action potentials (APs), local field potentials (LFPs), and µECoG signals were recorded from wired head-stage connectors for the UEA and µECoG grids, while EMG was recorded wirelessly. The monkey performed a finger flexion/extension task while neural and EMG data were acquired. We wrote an algorithm that uses the spike data from the UEA to perform a real-time decode of the monkey's finger movements. Also, analyses of the LFP and µECoG data indicate that these data show trial-averaged differences between different finger movements, indicating the data are potentially decodeable

Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task

Objective. To date, the majority of Brain–Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. Approach. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like 'Face in a Crowd' task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the 'Crowd') using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a 'Crowd Off' condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Main results. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Significance. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet computers

Decoding spoken words using local field potentials recorded from the cortical surface

Pathological conditions such as amyotrophic lateral sclerosis or damage to the brainstem can leave patients severely paralyzed but fully aware, in a condition known as 'locked-in syndrome'. Communication in this state is often reduced to selecting individual letters or words by arduous residual movements. More intuitive and rapid communication may be restored by directly interfacing with language areas of the cerebral cortex. We used a grid of closely spaced, nonpenetrating micro-electrodes to record local field potentials (LFPs) from the surface of face motor cortex and Wernicke's area. From these LFPs we were successful in classifying a small set of words on a trial-by-trial basis at levels well above chance. We found that the pattern of electrodes with the highest accuracy changed for each word, which supports the idea that closely spaced micro-electrodes are capable of capturing neural signals from independent neural processing assemblies. These results further support using cortical surface potentials (electrocorticography) in brain–computer interfaces. These results also show that LFPs recorded from the cortical surface (micro-electrocorticography) of language areas can be used to classify speech-related cortical rhythms and potentially restore communication to locked-in patients