Sydney S. Cash

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

Paralysis following spinal cord injury, brainstem stroke, amyotrophic lateral sclerosis and other disorders can disconnect the brain from the body, eliminating the ability to perform volitional movements. A neural interface system could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with long-standing tetraplegia can use a neural interface system to move and click a computer cursor and to control physical devices. Able-bodied monkeys have used a neural interface system to control a robotic arm, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here we demonstrate the ability of two people with long-standing tetraplegia to use neural interface system-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm and hand over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor 5 years earlier, also used a robotic arm to drink coffee from a bottle. Although robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after injury to the central nervous system, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals.

Sequential Processing of Lexical, Grammatical, and Phonological Information Within Broca’s Area

Seeing the Brains One, Two, Three Taking advantage of the rare opportunity to record neuronal activity in the human brain using intracranial electrodes, Sahin et al. (p. 445; see the Perspective by Hagoort and Levelt) document the spatial and temporal pattern of neuronal populations within Brocas area as patients thought of a single word, changed its tense (for verbs) or number (for nouns), and articulated the word silently. For these three stages, they detected activity at 200, 320, and 450 milliseconds, moving in a caudal to rostral direction. These data fit neatly within the roughly 600 milliseconds required for the onset of speech and map the distinct neural computations within an area of the brain, known for almost a century and a half, as important for the production of language. Intracranial electrodes record activity in a language-associated area of the brain as words are identified and produced. Words, grammar, and phonology are linguistically distinct, yet their neural substrates are difficult to distinguish in macroscopic brain regions. We investigated whether they can be separated in time and space at the circuit level using intracranial electrophysiology (ICE), namely by recording local field potentials from populations of neurons using electrodes implanted in language-related brain regions while people read words verbatim or grammatically inflected them (present/past or singular/plural). Neighboring probes within Broca’s area revealed distinct neuronal activity for lexical (~200 milliseconds), grammatical (~320 milliseconds), and phonological (~450 milliseconds) processing, identically for nouns and verbs, in a region activated in the same patients and task in functional magnetic resonance imaging. This suggests that a linguistic processing sequence predicted on computational grounds is implemented in the brain in fine-grained spatiotemporally patterned activity.TRCs, with taste at the periphery proposed to be encoded via labeled lines [i.e., a sweet line, a sour line, a bitter line, etc. (21)]. Given that Car4 is specifically tethered to the surface of sour-sensing cells, and thus ideally poised to provide a highly localized acid signal to the sour TRCs, we reasoned that carbonation might be sensed through activation of the sour-labeled line. A prediction of this postulate is that prevention of sour cell activation should eliminate CO2 detection, even in the presence of wild-type Car4 function. To test this hypothesis, we engineered animals in which the activation of nerve fibers innervating sour-sensing cells was blocked by preventing neurotransmitter release from the PKD2L1-expressing TRCs. In essence, we transgenically targeted expression of tetanus toxin light chain [TeNT, an endopeptidase that removes an essential component of the synaptic machinery (34–36)] to sour-sensing TRCs, and then monitored the physiological responses of these mice to sweet, sour, bitter, salty, umami and CO2 stimulation. As predicted, taste responses to sour stimuli were selectively and completely abolished, whereas responses to sweet, bitter, salty and umami tastants remained unaltered (Fig. 4 and fig. S5). However, these animals also displayed a complete loss of taste responses to CO2 even though they still expressed Car4 on the surface of PKD2L1 cells. Together, these results implicate the extracellular generation of protons, rather than intracellular acidification (15), as the primary signal that mediates the taste of CO2, and demonstrate that sour cells not only provide the membrane anchor for Car4 but also serve as the cellular sensors for carbonation. Why do animals need CO2 sensing? CO2 detection could have evolved as a mechanism to recognize CO2-producing sources (18, 37)—for instance, to avoid fermenting foods. This view would be consistent with the recent discovery of a specialized CO2 taste detection in insects where it mediates robust innate taste behaviors (38). Alternatively, Car4 may be important to maintain the pH balance within taste buds, and might gratuitously function as a detector for carbonation only as an accidental consequence. Although CO2 activates the sour-sensing cells, it does not simply taste sour to humans. CO2 (like acid) acts not only on the taste system but also in other orosensory pathways, including robust stimulation of the somatosensory system (17, 22); thus, the final percept of carbonation is likely to be a combination of multiple sensory inputs. Nonetheless, the “fizz” and “tingle” of heavily carbonated water is often likened to mild acid stimulation of the tongue, and in some cultures seltzer is even named for its salient sour taste (e.g., saurer Sprudel or Sauerwasser).

The human K-complex represents an isolated cortical down-state.

Down But Not Out The K-complex, a defining characteristic of slow wave sleep, is the largest spontaneously occurring component of the healthy human electroencephalogram (EEG) but little is known about its physiological characteristics in the human cortex. Cash et al. (p. 1084) investigated the intracortical origin of K-complexes in humans undergoing surgery for epileptic seizures. In simultaneous subdural EEG and intracortical multisite microelectrode recordings, K complexes represented cortical downstates reflecting a decrease in neural firing. These down-states are a fundamental mode of cortical operation that have been well studied in animals and may contribute to sleep preservation and memory consolidation. A characteristic electroencephalogram pattern seen during sleep is accompanied by a steep decline in neural activity. The electroencephalogram (EEG) is a mainstay of clinical neurology and is tightly correlated with brain function, but the specific currents generating human EEG elements remain poorly specified because of a lack of microphysiological recordings. The largest event in healthy human EEGs is the K-complex (KC), which occurs in slow-wave sleep. Here, we show that KCs are generated in widespread cortical areas by outward dendritic currents in the middle and upper cortical layers, accompanied by decreased broadband EEG power and decreased neuronal firing, which demonstrate a steep decline in network activity. Thus, KCs are isolated “down-states,” a fundamental cortico-thalamic processing mode already characterized in animals. This correspondence is compatible with proposed contributions of the KC to sleep preservation and memory consolidation.

Rapid fragmentation of neuronal networks at the onset of propofol-induced unconsciousness

The neurophysiological mechanisms by which anesthetic drugs cause loss of consciousness are poorly understood. Anesthetic actions at the molecular, cellular, and systems levels have been studied in detail at steady states of deep general anesthesia. However, little is known about how anesthetics alter neural activity during the transition into unconsciousness. We recorded simultaneous multiscale neural activity from human cortex, including ensembles of single neurons, local field potentials, and intracranial electrocorticograms, during induction of general anesthesia. We analyzed local and global neuronal network changes that occurred simultaneously with loss of consciousness. We show that propofol-induced unconsciousness occurs within seconds of the abrupt onset of a slow (<1 Hz) oscillation in the local field potential. This oscillation marks a state in which cortical neurons maintain local patterns of network activity, but this activity is fragmented across both time and space. Local (<4 mm) neuronal populations maintain the millisecond-scale connectivity patterns observed in the awake state, and spike rates fluctuate and can reach baseline levels. However, neuronal spiking occurs only within a limited slow oscillation-phase window and is silent otherwise, fragmenting the time course of neural activity. Unexpectedly, we found that these slow oscillations occur asynchronously across cortex, disrupting functional connectivity between cortical areas. We conclude that the onset of slow oscillations is a neural correlate of propofol-induced loss of consciousness, marking a shift to cortical dynamics in which local neuronal networks remain intact but become functionally isolated in time and space.

Long-term treatment with responsive brain stimulation in adults with refractory partial seizures.

Objective: The long-term efficacy and safety of responsive direct neurostimulation was assessed in adults with medically refractory partial onset seizures. Methods: All participants were treated with a cranially implanted responsive neurostimulator that delivers stimulation to 1 or 2 seizure foci via chronically implanted electrodes when specific electrocorticographic patterns are detected (RNS System). Participants had completed a 2-year primarily open-label safety study (n = 65) or a 2-year randomized blinded controlled safety and efficacy study (n = 191); 230 participants transitioned into an ongoing 7-year study to assess safety and efficacy. Results: The average participant was 34 (±11.4) years old with epilepsy for 19.6 (±11.4) years. The median preimplant frequency of disabling partial or generalized tonic-clonic seizures was 10.2 seizures a month. The median percent seizure reduction in the randomized blinded controlled trial was 44% at 1 year and 53% at 2 years (p < 0.0001, generalized estimating equation) and ranged from 48% to 66% over postimplant years 3 through 6 in the long-term study. Improvements in quality of life were maintained (p < 0.05). The most common serious device-related adverse events over the mean 5.4 years of follow-up were implant site infection (9.0%) involving soft tissue and neurostimulator explantation (4.7%). Conclusions: The RNS System is the first direct brain responsive neurostimulator. Acute and sustained efficacy and safety were demonstrated in adults with medically refractory partial onset seizures arising from 1 or 2 foci over a mean follow-up of 5.4 years. This experience supports the RNS System as a treatment option for refractory partial seizures. Classification of evidence: This study provides Class IV evidence that for adults with medically refractory partial onset seizures, responsive direct cortical stimulation reduces seizures and improves quality of life over a mean follow-up of 5.4 years.

Epilepsy as a Disorder of Cortical Network Organization

The brain is naturally considered as a network of interacting elements which, when functioning properly, produces an enormous range of dynamic, adaptable behavior. However, when elements of this network fail, pathological changes ensue, including epilepsy, one of the most common brain disorders. This review examines some aspects of cortical network organization that distinguish epileptic cortex from normal brain as well as the dynamics of network activity before and during seizures, focusing primarily on focal seizures. The review is organized around four phases of the seizure: the interictal period, onset, propagation, and termination. For each phase, the authors discuss the most common rhythmic characteristics of macroscopic brain voltage activity and outline the observed functional network features. Although the characteristics of functional networks that support the epileptic seizure remain an area of active research, the prevailing trends point to a complex set of network dynamics between, before, and during seizures.

Coalescence and Fragmentation of Cortical Networks during Focal Seizures

Epileptic seizures reflect a pathological brain state characterized by specific clinical and electrical manifestations. The proposed mechanisms are heterogeneous but united by the supposition that epileptic activity is hypersynchronous across multiple scales, yet principled and quantitative analyses of seizure dynamics across space and throughout the entire ictal period are rare. To more completely explore spatiotemporal interactions during seizures, we examined electrocorticogram data from a population of male and female human patients with epilepsy and from these data constructed dynamic network representations using statistically robust measures. We found that these networks evolved through a distinct topological progression during the seizure. Surprisingly, the overall synchronization changed only weakly, whereas the topology changed dramatically in organization. A large subnetwork dominated the network architecture at seizure onset and preceding termination but, between, fractured into smaller groups. Common network characteristics appeared consistently for a population of subjects, and, for each subject, similar networks appeared from seizure to seizure. These results suggest that, at the macroscopic spatial scale, epilepsy is not so much a manifestation of hypersynchrony but instead of network reorganization.

Laminar analysis of slow wave activity in humans

Brain electrical activity is largely composed of oscillations at characteristic frequencies. These rhythms are hierarchically organized and are thought to perform important pathological and physiological functions. The slow wave is a fundamental cortical rhythm that emerges in deep non-rapid eye movement sleep. In animals, the slow wave modulates delta, theta, spindle, alpha, beta, gamma and ripple oscillations, thus orchestrating brain electrical rhythms in sleep. While slow wave activity can enhance epileptic manifestations, it is also thought to underlie essential restorative processes and facilitate the consolidation of declarative memories. Animal studies show that slow wave activity is composed of rhythmically recurring phases of widespread, increased cortical cellular and synaptic activity, referred to as active- or up-state, followed by cellular and synaptic inactivation, referred to as silent- or down-state. However, its neural mechanisms in humans are poorly understood, since the traditional intracellular techniques used in animals are inappropriate for investigating the cellular and synaptic/transmembrane events in humans. To elucidate the intracortical neuronal mechanisms of slow wave activity in humans, novel, laminar multichannel microelectrodes were chronically implanted into the cortex of patients with drug-resistant focal epilepsy undergoing cortical mapping for seizure focus localization. Intracortical laminar local field potential gradient, multiple-unit and single-unit activities were recorded during slow wave sleep, related to simultaneous electrocorticography, and analysed with current source density and spectral methods. We found that slow wave activity in humans reflects a rhythmic oscillation between widespread cortical activation and silence. Cortical activation was demonstrated as increased wideband (0.3-200 Hz) spectral power including virtually all bands of cortical oscillations, increased multiple- and single-unit activity and powerful inward transmembrane currents, mainly localized to the supragranular layers. Neuronal firing in the up-state was sparse and the average discharge rate of single cells was less than expected from animal studies. Action potentials at up-state onset were synchronized within +/-10 ms across all cortical layers, suggesting that any layer could initiate firing at up-state onset. These findings provide strong direct experimental evidence that slow wave activity in humans is characterized by hyperpolarizing currents associated with suppressed cell firing, alternating with high levels of oscillatory synaptic/transmembrane activity associated with increased cell firing. Our results emphasize the major involvement of supragranular layers in the genesis of slow wave activity.

Input Summation by Cultured Pyramidal Neurons Is Linear and Position-Independent

The role of dendritic morphology in integration and processing of neuronal inputs is still unknown. Models based on passive cable theory suggest that dendrites serve to isolate synapses from one another. Because of decreases in driving force or resistance, two inputs onto the same dendrite would diminish their joint effect, resulting in sublinear summation. When on different dendrites, however, inputs would not interact and therefore would sum linearly. These predictions have not been rigorously tested experimentally. In addition, recent results indicate that dendrites have voltage-sensitive conductances and are not passive cables. To investigate input integration, we characterized the effects of dendritic morphology on the summation of subthreshold excitatory inputs on cultured hippocampal neurons with pyramidal morphologies. We used microiontophoresis of glutamate to systematically position inputs throughout the dendritic tree and tested the summation of two inputs by measuring their individual and joint effects. We find that summation was surprisingly linear regardless of input position. For small inputs, this linearity arose because no significant shunts or changes in driving force occurred and no voltage-dependent channels were opened. Larger inputs also added linearly, but this linearity was caused by balanced action of NMDA and IA potassium conductances. Therefore, active conductances can maintain, paradoxically, a linear input arithmetic. Furthermore, dendritic morphology does not interfere with this linearity, which may be essential for particular neuronal computations.

Individualized localization and cortical surface-based registration of intracranial electrodes

In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain-mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals-and coregistering functional results across subjects-remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individuals neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians.