Enhanced control of a brain-computer interface by tetraplegic participants via neural-network-mediated feature extraction.

To infer intent, brain-computer interfaces must extract features that accurately estimate neural activity. However, the degradation of signal quality over time hinders the use of feature-engineering techniques to recover functional information. By using neural data recorded from electrode arrays implanted in the cortices of three human participants, here we show that a convolutional neural network can be used to map electrical signals to neural features by jointly optimizing feature extraction and decoding under the constraint that all the electrodes must use the same neural-network parameters.

Quantifying physical degradation alongside recording and stimulation performance of 980 intracortical microelectrodes chronically implanted in three humans for 956-2246 days.

Motivation: The clinical success of brain-machine interfaces depends on overcoming both biological and material challenges to ensure a long-term stable connection for neural recording and stimulation. Therefore, there is a need to quantify any damage that microelectrodes sustain when they are chronically implanted in the human cortex.

Methods: Using scanning electron microscopy (SEM), we imaged 980 microelectrodes from Neuroport arrays chronically implanted in the cortex of three people with tetraplegia for 956-2246 days.

Neural representations of economic decision variables in human posterior parietal cortex.

Decision making has been intensively studied in the posterior parietal cortex in non-human primates on a single neuron level. In humans decision making has mainly been studied with psychophysical tools or with fMRI. Here, we investigated how single neurons from human posterior parietal cortex represent numeric values informing future decisions during a complex two-player game.

Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex.

. Enable neural control of individual prosthetic fingers for participants with upper-limb paralysis..

Stability of motor representations after paralysis.

Neural plasticity allows us to learn skills and incorporate new experiences. What happens when our lived experiences fundamentally change, such as after a severe injury? To address this question, we analyzed intracortical population activity in the posterior parietal cortex (PPC) of a tetraplegic adult as she controlled a virtual hand through a brain-computer interface (BCI). By attempting to move her fingers, she could accurately drive the corresponding virtual fingers.

Preserved cortical somatotopic and motor representations in tetraplegic humans.

A rich literature has documented changes in cortical representations of the body in somatosensory and motor cortex. Recent clinical studies of brain-machine interfaces designed to assist paralyzed patients have afforded the opportunity to record from and stimulate human somatosensory, motor, and action-related areas of the posterior parietal cortex. These studies show considerable preserved structure in the cortical somato-motor system.

Implicit mechanisms of intention.

High-level cortical regions encode motor decisions before or even absent awareness, suggesting that neural processes predetermine behavior before conscious choice. Such early neural encoding challenges popular conceptions of human agency. It also raises fundamental questions for brain-machine interfaces (BMIs) that traditionally assume that neural activity reflects the user's conscious intentions.

Exploring Cognition with Brain-Machine Interfaces.

Traditional brain-machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in the human posterior parietal cortex during neuroprosthetic clinical trials.

Neural encoding of actual and imagined touch within human posterior parietal cortex.

In the human posterior parietal cortex (PPC), single units encode high-dimensional information with representations that enable small populations of neurons to encode many variables relevant to movement planning, execution, cognition, and perception. Here, we test whether a PPC neuronal population previously demonstrated to encode visual and motor information is similarly engaged in the somatosensory domain. We recorded neurons within the PPC of a human clinical trial participant during actual touch presentation and during a tactile imagery task.

The human primary somatosensory cortex encodes imagined movement in the absence of sensory information.

Classical systems neuroscience positions primary sensory areas as early feed-forward processing stations for refining incoming sensory information. This view may oversimplify their role given extensive bi-directional connectivity with multimodal cortical and subcortical regions. Here we show that single units in human primary somatosensory cortex encode imagined reaches in a cognitive motor task, but not other sensory-motor variables such as movement plans or imagined arm position.

A shared neural substrate for action verbs and observed actions in human posterior parietal cortex.

High-level sensory and motor cortical areas are activated when processing the meaning of language, but it is unknown whether, and how, words share a neural substrate with corresponding sensorimotor representations. We recorded from single neurons in human posterior parietal cortex (PPC) while participants viewed action verbs and corresponding action videos from multiple views. We find that PPC neurons exhibit a common neural substrate for action verbs and observed actions.

Preservation of Partially Mixed Selectivity in Human Posterior Parietal Cortex across Changes in Task Context.

Recent studies in posterior parietal cortex (PPC) have found multiple effectors and cognitive strategies represented within a shared neural substrate in a structure termed "partially mixed selectivity" (Zhang et al., 2017). In this study, we examine whether the structure of these representations is preserved across changes in task context and is thus a robust and generalizable property of the neural population.

From thought to action: The brain-machine interface in posterior parietal cortex.

A dramatic example of translational monkey research is the development of neural prosthetics for assisting paralyzed patients. A neuroprosthesis consists of implanted electrodes that can record the intended movement of a paralyzed part of the body, a computer algorithm that decodes the intended movement, and an assistive device such as a robot limb or computer that is controlled by these intended movement signals. This type of neuroprosthetic system is also referred to as a brain-machine interface (BMI) since it interfaces the brain with an external machine.

Cognition in Sensorimotor Control: Interfacing With the Posterior Parietal Cortex.

Millions of people worldwide are afflicted with paralysis from a disruption of neural pathways between the brain and the muscles. Because their cortical architecture is often preserved, these patients are able to plan movements despite an inability to execute them. In such people, brain machine interfaces have great potential to restore lost function through neuroprosthetic devices, circumventing dysfunctional corticospinal circuitry.

Intrinsic Variable Learning for Brain-Machine Interface Control by Human Anterior Intraparietal Cortex.

Although animal studies provided significant insights in understanding the neural basis of learning and adaptation, they often cannot dissociate between different learning mechanisms due to the lack of verbal communication. To overcome this limitation, we examined the mechanisms of learning and its limits in a human intracortical brain-machine interface (BMI) paradigm. A tetraplegic participant controlled a 2D computer cursor by modulating single-neuron activity in the anterior intraparietal area (AIP).

Single-Neuron Representation of Memory Strength and Recognition Confidence in Left Human Posterior Parietal Cortex.

The human posterior parietal cortex (PPC) is thought to contribute to memory retrieval, but little is known about its specific role. We recorded single PPC neurons of two human tetraplegic subjects implanted with microelectrode arrays, who performed a recognition memory task. We found two groups of neurons that signaled memory-based choices.

Partially Mixed Selectivity in Human Posterior Parietal Association Cortex.

To clarify the organization of motor representations in posterior parietal cortex, we test how three motor variables (body side, body part, cognitive strategy) are coded in the human anterior intraparietal cortex. All tested movements were encoded, arguing against strict anatomical segregation of effectors. Single units coded for diverse conjunctions of variables, with different dimensions anatomically overlapping.

Hand Shape Representations in the Human Posterior Parietal Cortex.

Unlabelled: Humans shape their hands to grasp, manipulate objects, and to communicate. From nonhuman primate studies, we know that visual and motor properties for grasps can be derived from cells in the posterior parietal cortex (PPC). Are non-grasp-related hand shapes in humans represented similarly? Here we show for the first time how single neurons in the PPC of humans are selective for particular imagined hand shapes independent of graspable objects.

Neurophysiology. Decoding motor imagery from the posterior parietal cortex of a tetraplegic human.

Nonhuman primate and human studies have suggested that populations of neurons in the posterior parietal cortex (PPC) may represent high-level aspects of action planning that can be used to control external devices as part of a brain-machine interface. However, there is no direct neuron-recording evidence that human PPC is involved in action planning, and the suitability of these signals for neuroprosthetic control has not been tested. We recorded neural population activity with arrays of microelectrodes implanted in the PPC of a tetraplegic subject.

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.

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.

Organization of the macaque extrastriate visual cortex re-examined using the principle of spatial continuity of function.

How is the macaque monkey extrastriate cortex organized? Is vision divisible into separate tasks, such as object recognition and spatial processing, each emphasized in a different anatomical stream? If so, how many streams exist? What are the hierarchical relationships among areas? The present study approached the organization of the extrastriate cortex in a novel manner. A principled relationship exists between cortical function and cortical topography. Similar functions tend to be located near each other, within the constraints of mapping a highly dimensional space of functions onto the two-dimensional space of the cortex.

Four-dimensional spatial reasoning in humans.

Human subjects practiced navigation in a virtual, computer-generated maze that contained 4 spatial dimensions rather than the usual 3. The subjects were able to learn the spatial geometry of the 4-dimensional maze as measured by their ability to perform path integration, a standard test of spatial ability. They were able to travel down a winding corridor to its end and then point back accurately toward the occluded origin.

Complex organization of human primary motor cortex: a high-resolution fMRI study.

A traditional view of the human motor cortex is that it contains an overlapping sequence of body part representations from the tongue in a ventral location to the foot in a dorsal location. In this study, high-resolution functional MRI (1.5x1.

Mapping behavioral repertoire onto the cortex.

A traditional view of the motor cortex in the primate brain is that it contains a map of the body arranged across the cortical surface. This traditional topographic scheme, however, does not capture the actual pattern of overlaps, fractures, re-representations, and multiple areas separated by fuzzy borders. Here, we suggest that the organization of the motor cortex, premotor cortex, supplementary motor cortex, frontal eye field, and supplementary eye field can in principle be understood as a best-fit rendering of the motor repertoire onto the two-dimensional cortical sheet in a manner that optimizes local continuity.