Spike-wave discharges during low-current thalamic deep brain stimulation in mice.

BACKGROUND: Deep brain stimulation of central thalamus (CT-DBS) has potential for modulating states of consciousness, but it can also trigger spike-wave discharges (SWDs). OBJECTIVES: To report the probability of inducing SWDs during CT-DBS in awake mice. METHODS: Mice were implanted with electrodes to deliver unilateral and bilateral CT-DBS at different frequencies while recording EEG. We titrated stimulation current by gradually increasing it at each frequency until an SWD appeared. Subsequent stimulations to test arousal modulation were performed at the current one step below the current that caused an SWD during titration. RESULTS: In 2.21% of the test stimulations (10 out of 12 mice), CT-DBS caused SWDs at currents lower than the titrated current, at currents as low as 20 uA. CONCLUSION: Our study found a small but significant probability of inducing SWDs even after titration and at relatively low currents. EEG should be closely monitored for SWDs when performing CT-DBS in both research and clinical settings.

Propofol-mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy.

A critical component of anesthesia is the loss of sensory perception. Propofol is the most widely used drug for general anesthesia, but the neural mechanisms of how and when it disrupts sensory processing are not fully understood. We analyzed local field potential and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of nonhuman primates before and during propofol-mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-related synchronization between brain areas in the local field potential of Awake animals. By contrast, propofol-mediated unconsciousness eliminated stimulus-related synchrony and drastically weakened stimulus responses and information in all brain areas except for auditory cortex, where responses and information persisted. However, we found stimuli occurring during spiking Up states triggered weaker spiking responses than in Awake animals in auditory cortex, and little or no spiking responses in higher order areas. These results suggest that propofol's effect on sensory processing is not just because of asynchronous Down states. Rather, both Down states and Up states reflect disrupted dynamics.

Propofol Mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy.

A critical component of anesthesia is the loss sensory perception. Propofol is the most widely used drug for general anesthesia, but the neural mechanisms of how and when it disrupts sensory processing are not fully understood. We analyzed local field potential (LFP) and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of non-human primates before and during propofol mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-induced coherence between brain areas in the LFP of awake animals. By contrast, propofol mediated unconsciousness eliminated stimulus-induced coherence and drastically weakened stimulus responses and information in all brain areas except for auditory cortex, where responses and information persisted. However, we found stimuli occurring during spiking Up states triggered weaker spiking responses than in awake animals in auditory cortex, and little or no spiking responses in higher order areas. These results suggest that propofol's effect on sensory processing is not just due to asynchronous down states. Rather, both Down states and Up states reflect disrupted dynamics.

Robust and brain-like working memory through short-term synaptic plasticity.

Working memory has long been thought to arise from sustained spiking/attractor dynamics. However, recent work has suggested that short-term synaptic plasticity (STSP) may help maintain attractor states over gaps in time with little or no spiking. To determine if STSP endows additional functional advantages, we trained artificial recurrent neural networks (RNNs) with and without STSP to perform an object working memory task. We found that RNNs with and without STSP were able to maintain memories despite distractors presented in the middle of the memory delay. However, RNNs with STSP showed activity that was similar to that seen in the cortex of a non-human primate (NHP) performing the same task. By contrast, RNNs without STSP showed activity that was less brain-like. Further, RNNs with STSP were more robust to network degradation than RNNs without STSP. These results show that STSP can not only help maintain working memories, it also makes neural networks more robust and brain-like.

Implantable brain-computer interface for neuroprosthetic-enabled volitional hand grasp restoration in spinal cord injury.

Loss of hand function after cervical spinal cord injury severely impairs functional independence. We describe a method for restoring volitional control of hand grasp in one 21-year-old male subject with complete cervical quadriplegia (C5 American Spinal Injury Association Impairment Scale A) using a portable fully implanted brain-computer interface within the home environment. The brain-computer interface consists of subdural surface electrodes placed over the dominant-hand motor cortex and connects to a transmitter implanted subcutaneously below the clavicle, which allows continuous reading of the electrocorticographic activity. Movement-intent was used to trigger functional electrical stimulation of the dominant hand during an initial 29-weeks laboratory study and subsequently via a mechanical hand orthosis during in-home use. Movement-intent information could be decoded consistently throughout the 29-weeks in-laboratory study with a mean accuracy of 89.0% (range 78-93.3%). Improvements were observed in both the speed and accuracy of various upper extremity tasks, including lifting small objects and transferring objects to specific targets. At-home decoding accuracy during open-loop trials reached an accuracy of 91.3% (range 80-98.95%) and an accuracy of 88.3% (range 77.6-95.5%) during closed-loop trials. Importantly, the temporal stability of both the functional outcomes and decoder metrics were not explored in this study. A fully implanted brain-computer interface can be safely used to reliably decode movement-intent from motor cortex, allowing for accurate volitional control of hand grasp.

Multitaper Infinite Hidden Markov Model for EEG.

Electroencephalographam (EEG) monitoring of neural activity is widely used for identifying underlying brain states. For inference of brain states, researchers have often used Hidden Markov Models (HMM) with a fixed number of hidden states and an observation model linking the temporal dynamics embedded in EEG to the hidden states. The use of fixed states may be limiting, in that 1) pre-defined states might not capture the heterogeneous neural dynamics across individuals and 2) the oscillatory dynamics of the neural activity are not directly modeled. To this end, we use a Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM), which discovers the set of hidden states that best describes the EEG data, without a-priori specification of state number. In addition, we introduce an observation model based on classical asymptotic results of frequency domain properties of stationary time series, along with the description of the conditional distributions for Gibbs sampler inference. We then combine this with multitaper spectral estimation to reduce the variance of the spectral estimates. By applying our method to simulated data inspired by sleep EEG, we arrive at two main results: 1) the algorithm faithfully recovers the spectral characteristics of the true states, as well as the right number of states and 2) the incorporation of the multitaper framework produces a more stable estimate than traditional periodogram spectral estimates.

A subset of sweet-sensing neurons identified by IR56d are necessary and sufficient for fatty acid taste.

Fat represents a calorically potent food source that yields approximately twice the amount of energy as carbohydrates or proteins per unit of mass. The highly palatable taste of free fatty acids (FAs), one of the building blocks of fat, promotes food consumption, activates reward circuitry, and is thought to contribute to hedonic feeding underlying many metabolism-related disorders. Despite a role in the etiology of metabolic diseases, little is known about how dietary fats are detected by the gustatory system to promote feeding. Previously, we showed that a broad population of sugar-sensing taste neurons expressing Gustatory Receptor 64f (Gr64f) is required for reflexive feeding responses to both FAs and sugars. Here, we report a genetic silencing screen to identify specific populations of taste neurons that mediate fatty acid (FA) taste. We find neurons identified by expression of Ionotropic Receptor 56d (IR56d) are necessary and sufficient for reflexive feeding response to FAs. Functional imaging reveals that IR56d-expressing neurons are responsive to short- and medium-chain FAs. Silencing IR56d neurons selectively abolishes FA taste, and their activation is sufficient to drive feeding responses. Analysis of co-expression with Gr64f identifies two subpopulations of IR56d-expressing neurons. While physiological imaging reveals that both populations are responsive to FAs, IR56d/Gr64f neurons are activated by medium-chain FAs and are sufficient for reflexive feeding response to FAs. Moreover, flies can discriminate between sugar and FAs in an aversive taste memory assay, indicating that FA taste is a unique modality in Drosophila. Taken together, these findings localize FA taste within the Drosophila gustatory center and provide an opportunity to investigate discrimination between different categories of appetitive tastants.

Elevated levels of the vesicular monoamine transporter and a novel repetitive behavior in the Drosophila model of fragile X syndrome.

Fragile X Syndrome (FXS) is characterized by mental impairment and autism in humans, and it often features hyperactivity and repetitive behaviors. The mechanisms for the disease, however, remain poorly understood. Here we report that the dfmr1 mutant in the Drosophila model of FXS grooms excessively, which may be regulated differentially by two signaling pathways. Blocking metabotropic glutamate receptor signaling enhances grooming in dfmr1 mutant flies, whereas blocking the vesicular monoamine transporter (VMAT) suppresses excessive grooming. dfmr1 mutant flies also exhibit elevated levels of VMAT mRNA and protein. These results suggest that enhanced monoamine signaling correlates with repetitive behaviors and hyperactivity associated with FXS.