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Miguel A L Nicolelis - One of the best experts on this subject based on the ideXlab platform.

  • licking induced synchrony in the taste reward circuit improves cue discrimination during learning
    The Journal of Neuroscience, 2010
    Co-Authors: Ranier Gutierrez, Sidney A. Simon, Miguel A L Nicolelis
    Abstract:

    Animals learn which foods to ingest and which to avoid. Despite many studies, the electrophysiological correlates underlying this behavior at the gustatory-reward circuit level remain poorly understood. For this reason, we measured the simultaneous electrical activity of neuronal Ensembles in the orbitofrontal cortex, insular cortex, amygdala, and nucleus accumbens while rats licked for taste cues and learned to perform a taste discrimination go/no-go task. This study revealed that rhythmic licking entrains the activity in all these brain regions, suggesting that the animal's licking acts as an "internal clock signal" against which single spikes can be synchronized. That is, as animals learned a go/no-go task, there were increases in the number of licking coherent neurons as well as synchronous spiking between neuron pairs from different brain regions. Moreover, a subpopulation of gustatory cue-selective neurons that fired in synchrony with licking exhibited a greater ability to discriminate among tastants than nonsynchronized neurons. This effect was seen in all four recorded areas and increased markedly after learning, particularly after the cue was delivered and before the animals made a movement to obtain an appetitive or aversive tastant. Overall, these results show that, throughout a large segment of the taste-reward circuit, appetitive and aversive associative learning improves spike-timing precision, suggesting that proficiency in solving a taste discrimination go/no-go task requires licking-induced Neural Ensemble synchronous activity.

  • principles of Neural Ensemble physiology underlying the operation of brain machine interfaces
    Nature Reviews Neuroscience, 2009
    Co-Authors: Miguel A L Nicolelis, Mikhail A Lebedev
    Abstract:

    Recent advances in brain–machine interface technology have allowed neuroscientists to gain insights into the principles underlying information processing in the CNS. Nicolelis and Lebedev propose a series of principles of Neural Ensemble physiology that have arisen from this research. Research on brain–machine interfaces has been ongoing for at least a decade. During this period, simultaneous recordings of the extracellular electrical activity of hundreds of individual neurons have been used for direct, real-time control of various artificial devices. Brain–machine interfaces have also added greatly to our knowledge of the fundamental physiological principles governing the operation of large Neural Ensembles. Further understanding of these principles is likely to have a key role in the future development of neuroprosthetics for restoring mobility in severely paralysed patients.

  • nicotine activates trpm5 dependent and independent taste pathways
    Proceedings of the National Academy of Sciences of the United States of America, 2009
    Co-Authors: Albino J Oliveiramaia, Miguel A L Nicolelis, Jennifer R Stapletonkotloski, Vijay Lyall, Tamhao T Phan, Shobha Mummalaneni, Pamela Melone, John A Desimone, Sidney A. Simon
    Abstract:

    The orosensory responses elicited by nicotine are relevant for the development and maintenance of addiction to tobacco products. However, although nicotine is described as bitter tasting, the molecular and Neural substrates encoding the taste of nicotine are unclear. Here, rats and mice were used to determine whether nicotine activates peripheral and central taste pathways via TRPM5-dependent mechanisms, which are essential for responses to other bitter tastants such as quinine, and/or via nicotinic acetylcholine receptors (nAChRs). When compared with wild-type mice, Trpm5−/− mice had reduced, but not abolished, chorda tympani (CT) responses to nicotine. In both genotypes, lingual application of mecamylamine, a nAChR-antagonist, inhibited CT nerve responses to nicotine and reduced behavioral responses of aversion to this stimulus. In accordance with these findings, rats were shown to discriminate between nicotine and quinine presented at intensity-paired concentrations. Moreover, rat gustatory cortex (GC) Neural Ensemble activity could also discriminate between these two bitter tastants. Mecamylamine reduced both behavioral and GC Neural discrimination between nicotine and quinine. In summary, nicotine elicits taste responses through peripheral TRPM5-dependent pathways, common to other bitter tastants, and nAChR-dependent and TRPM5-independent pathways, thus creating a unique sensory representation that contributes to the sensory experience of tobacco products.

  • Long-lasting novelty-induced neuronal reverberation during slow-wave sleep in multiple forebrain areas
    PLoS Biology, 2004
    Co-Authors: Sidarta Ribeiro, Shih-chieh Lin, Ernesto S Soares, Damien Gervasoni, Janaina Pantoja, Michael Lavine, Yi Zhou, Miguel A L Nicolelis
    Abstract:

    The discovery of experience-dependent brain reactivation during both slow-wave (SW) and rapid eye-movement (REM) sleep led to the notion that the consolidation of recently acquired memory traces requires Neural replay during sleep. To date, however, several observations continue to undermine this hypothesis. To address some of these objections, we investigated the effects of a transient novel experience on the long-term evolution of ongoing neuronal activity in the rat forebrain. We observed that spatiotemporal patterns of neuronal Ensemble activity originally produced by the tactile exploration of novel objects recurred for up to 48 h in the cerebral cortex, hippocampus, putamen, and thalamus. This novelty-induced recurrence was characterized by low but significant correlations values. Nearly identical results were found for neuronal activity sampled when animals were moving between objects without touching them. In contrast, negligible recurrence was observed for neuronal patterns obtained when animals explored a familiar environment. While the reverberation of past patterns of neuronal activity was strongest during SW sleep, waking was correlated with a decrease of neuronal reverberation. REM sleep showed more variable results across animals. In contrast with data from hippocampal place cells, we found no evidence of time compression or expansion of neuronal reverberation in any of the sampled forebrain areas. Our results indicate that persistent experience-dependent neuronal reverberation is a general property of multiple forebrain structures. It does not consist of an exact replay of previous activity, but instead it defines a mild and consistent bias towards salient Neural Ensemble firing patterns. These results are compatible with a slow and progressive process of memory consolidation, reflecting novelty-related neuronal Ensemble relationships that seem to be context- rather than stimulus-specific. Based on our current and previous results, we propose that the two major phases of sleep play distinct and complementary roles in memory consolidation: pretranscriptional recall during SW sleep and transcriptional storage during REM sleep.

  • encoding of tactile stimulus location by somatosensory thalamocortical Ensembles
    The Journal of Neuroscience, 2000
    Co-Authors: Asif A Ghazanfar, Christopher R Stambaugh, Miguel A L Nicolelis
    Abstract:

    The exquisite modular anatomy of the rat somatosensory system makes it an excellent model to test the potential coding strategies used to discriminate the location of a tactile stimulus. Here, we investigated how Ensembles of simultaneously recorded single neurons in layer V of primary somatosensory (SI) cortex and in the ventral posterior medial (VPM) nucleus of the thalamus of the anesthetized rat may encode the location of a single whisker stimulus on a single trial basis. An artificial Neural network based on a learning vector quantization algorithm, was used to identify putative coding mechanisms. Our data suggest that these Neural Ensembles may rely on a distributed coding scheme to represent the location of single whisker stimuli. Within this scheme, the temporal modulation of Neural Ensemble firing rate, as well as the temporal interactions between neurons, contributed significantly to the representation of stimulus location. The relative contribution of these temporal codes increased with the number of whiskers that the Ensembles must discriminate among. Our results also indicated that the SI cortex and the VPM nucleus may function as a single entity to encode stimulus location. Overall, our data suggest that the representation of somatosensory features in the rat trigeminal system may arise from the interactions of neurons within and between the SI cortex and VPM nucleus. Furthermore, multiple coding strategies may be used simultaneously to represent the location of tactile stimuli.

Leigh R Hochberg - One of the best experts on this subject based on the ideXlab platform.

  • Neural Ensemble dynamics in dorsal motor cortex during speech in people with paralysis
    eLife, 2019
    Co-Authors: Sergey D Stavisky, Robert F Kirsch, Francis R Willett, Guy H Wilson, Brian A Murphy, Paymon Rezaii, Donald T Avansino, William D Memberg, Jonathan P Miller, Leigh R Hochberg
    Abstract:

    Speaking is a sensorimotor behavior whose Neural basis is difficult to study with single neuron resolution due to the scarcity of human intracortical measurements. We used electrode arrays to record from the motor cortex 'hand knob' in two people with tetraplegia, an area not previously implicated in speech. Neurons modulated during speaking and during non-speaking movements of the tongue, lips, and jaw. This challenges whether the conventional model of a 'motor homunculus' division by major body regions extends to the single-neuron scale. Spoken words and syllables could be decoded from single trials, demonstrating the potential of intracortical recordings for brain-computer interfaces to restore speech. Two Neural population dynamics features previously reported for arm movements were also present during speaking: a component that was mostly invariant across initiating different words, followed by rotatory dynamics during speaking. This suggests that common Neural dynamical motifs may underlie movement of arm and speech articulators.

  • Neural Ensemble dynamics in dorsal motor cortex during speech in people with paralysis
    bioRxiv, 2018
    Co-Authors: Sergey D Stavisky, Robert F Kirsch, Francis R Willett, Brian A Murphy, Paymon Rezaii, William D Memberg, Jonathan P Miller, Leigh R Hochberg
    Abstract:

    ABSTRACT Speaking is a sensorimotor behavior whose Neural basis is difficult to study at the resolution of single neurons due to the scarcity of human intracortical measurements and the lack of animal models. We recorded from electrode arrays in the ‘hand knob’ area of motor cortex in people with tetraplegia. Neurons in this area, which have not previously been implicated in speech, modulated during speaking and during non-speaking movement of the tongue, lips, and jaw. This challenges whether the conventional model of a ‘motor homunculus’ division by major body regions extends to the single-neuron scale. Spoken words and syllables could be decoded from single trials, demonstrating the potential utility of intracortical recordings for brain-computer interfaces (BCIs) to restore speech. Two Neural population dynamics features previously reported for arm movements were also present during speaking: a large initial condition-invariant signal, followed by rotatory dynamics. This suggests that common Neural dynamical motifs may underlie movement of arm and speech articulators.

Robert F Kirsch - One of the best experts on this subject based on the ideXlab platform.

  • Neural Ensemble dynamics in dorsal motor cortex during speech in people with paralysis
    eLife, 2019
    Co-Authors: Sergey D Stavisky, Robert F Kirsch, Francis R Willett, Guy H Wilson, Brian A Murphy, Paymon Rezaii, Donald T Avansino, William D Memberg, Jonathan P Miller, Leigh R Hochberg
    Abstract:

    Speaking is a sensorimotor behavior whose Neural basis is difficult to study with single neuron resolution due to the scarcity of human intracortical measurements. We used electrode arrays to record from the motor cortex 'hand knob' in two people with tetraplegia, an area not previously implicated in speech. Neurons modulated during speaking and during non-speaking movements of the tongue, lips, and jaw. This challenges whether the conventional model of a 'motor homunculus' division by major body regions extends to the single-neuron scale. Spoken words and syllables could be decoded from single trials, demonstrating the potential of intracortical recordings for brain-computer interfaces to restore speech. Two Neural population dynamics features previously reported for arm movements were also present during speaking: a component that was mostly invariant across initiating different words, followed by rotatory dynamics during speaking. This suggests that common Neural dynamical motifs may underlie movement of arm and speech articulators.

  • Neural Ensemble dynamics in dorsal motor cortex during speech in people with paralysis
    bioRxiv, 2018
    Co-Authors: Sergey D Stavisky, Robert F Kirsch, Francis R Willett, Brian A Murphy, Paymon Rezaii, William D Memberg, Jonathan P Miller, Leigh R Hochberg
    Abstract:

    ABSTRACT Speaking is a sensorimotor behavior whose Neural basis is difficult to study at the resolution of single neurons due to the scarcity of human intracortical measurements and the lack of animal models. We recorded from electrode arrays in the ‘hand knob’ area of motor cortex in people with tetraplegia. Neurons in this area, which have not previously been implicated in speech, modulated during speaking and during non-speaking movement of the tongue, lips, and jaw. This challenges whether the conventional model of a ‘motor homunculus’ division by major body regions extends to the single-neuron scale. Spoken words and syllables could be decoded from single trials, demonstrating the potential utility of intracortical recordings for brain-computer interfaces (BCIs) to restore speech. Two Neural population dynamics features previously reported for arm movements were also present during speaking: a large initial condition-invariant signal, followed by rotatory dynamics. This suggests that common Neural dynamical motifs may underlie movement of arm and speech articulators.

  • velocity neurons improve performance more than goal or position neurons do in a simulated closed loop bci arm reaching task
    Frontiers in Computational Neuroscience, 2015
    Co-Authors: James Y Liao, Robert F Kirsch
    Abstract:

    Brain-Computer Interfaces (BCIs) that convert brain-recorded Neural signals into intended movement commands could eventually be combined with Functional Electrical Stimulation to allow individuals with Spinal Cord Injury to regain effective and intuitive control of their paralyzed limbs. To accelerate the development of such an approach, we developed a model of closed-loop BCI control of arm movements that (1) generates realistic arm movements (based on experimentally measured, visually-guided movements with real-time error correction), (2) simulates cortical neurons with firing properties consistent with literature reports, and (3) decodes intended movements from the noisy Neural Ensemble. With this model we explored (1) the relative utility of neurons tuned for different movement parameters (position, velocity, and goal) and (2) the utility of recording from larger numbers of neurons – critical issues for technology development and for determining appropriate brain areas for recording. We simulated arm movements that could be practically restored to individuals with severe paralysis, i.e., movements from an armrest to a volume in front of the person. Performance was evaluated by calculating the smallest movement endpoint target radius within which the decoded cursor position could dwell for one second. Our results show that goal, position, and velocity neurons all contribute to improve performance. However, velocity neurons enabled smaller targets to be reached in shorter amounts of time than goal or position neurons. Increasing the number of neurons also improved performance, although performance saturated at 30-50 neurons for most neuron types. Overall, our work presents a closed-loop BCI simulator that models error corrections and the firing properties of various movement-related neurons that can be easily modified to incorporate different Neural properties. We anticipate that this kind of tool will be important for development of future BCIs.

Bruce L Mcnaughton - One of the best experts on this subject based on the ideXlab platform.

  • Neural Ensemble reactivation in rapid eye movement and slow wave sleep coordinate with muscle activity to promote rapid motor skill learning
    Philosophical Transactions of the Royal Society B, 2020
    Co-Authors: M J Eckert, Bruce L Mcnaughton, Masami Tatsuno
    Abstract:

    Neural activity patterns of recent experiences are reactivated during sleep in structures critical for memory storage, including hippocampus and neocortex. This reactivation process is thought to aid memory consolidation. Although synaptic rearrangement dynamics following learning involve an interplay between slow-wave sleep (SWS) and rapid eye movement (REM) sleep, most physiological evidence implicates SWS directly following experience as a preferred window for reactivation. Here, we show that reactivation occurs in both REM and SWS and that coordination of REM and SWS activation on the same day is associated with rapid learning of a motor skill. We performed 6 h recordings from cells in rats' motor cortex as they were trained daily on a skilled reaching task. In addition to SWS following training, reactivation occurred in REM, primarily during the pre-task rest period, and REM and SWS reactivation occurred on the same day in rats that acquired the skill rapidly. Both pre-task REM and post-task SWS activation were coordinated with muscle activity during sleep, suggesting a functional role for reactivation in skill learning. Our results provide the first demonstration that reactivation in REM sleep occurs during motor skill learning and that coordinated reactivation in both sleep states on the same day, although at different times, is beneficial for skill learning. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

  • network and intrinsic cellular mechanisms underlying theta phase precession of hippocampal neurons
    Trends in Neurosciences, 2007
    Co-Authors: Andrew P Maurer, Bruce L Mcnaughton
    Abstract:

    Hippocampal ‘place cells' systematically shift their phase of firing in relation to the theta rhythm as an animal traverses the ‘place field'. These dynamics imply that the Neural Ensemble begins each theta cycle at a point in its state-space that might ‘represent' the current location of the rat, but that the Ensemble ‘looks ahead' during the rest of the cycle. Phase precession could result from intrinsic cellular dynamics involving interference of two oscillators of different frequencies, or from network interactions, similar to Hebb's ‘phase sequence' concept, involving asymmetric synaptic connections. Both models have difficulties accounting for all of the available experimental data, however. A hybrid model, in which the look-ahead phenomenon implied by phase precession originates in superficial entorhinal cortex by some form of interference mechanism and is enhanced in the hippocampus proper by asymmetric synaptic plasticity during sequence encoding, seems to be consistent with available data, but as yet there is no fully satisfactory theoretical account of this phenomenon. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast , based on presentations at the annual INMED/TINS symposium (http://inmednet.com).

  • coordinated reactivation of distributed memory traces in primate neocortex
    Science, 2002
    Co-Authors: Kari L Hoffman, Bruce L Mcnaughton
    Abstract:

    Conversion of new memories into a lasting form may involve the gradual refinement and linking together of Neural representations stored widely throughout neocortex. This consolidation process may require coordinated reactivation of distributed components of memory traces while the cortex is “offline,” i.e., not engaged in processing external stimuli. Simultaneous Neural Ensemble recordings from four sites in the macaque neocortex revealed such coordinated reactivation. In motor, somatosensory, and parietal cortex (but not prefrontal cortex), the behaviorally induced correlation structure and temporal patterning of Neural Ensembles within and between regions were preserved, confirming a major tenet of the trace-reactivation theory of memory consolidation.

Daryl R. Kipke - One of the best experts on this subject based on the ideXlab platform.

  • Development of Closed-Loop Neural Interface Technology in a Rat Model: Combining Motor Cortex Operant Conditioning With Visual Cortex Microstimulation
    IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2010
    Co-Authors: Timothy Charles Marzullo, Mark J. Lehmkuhle, Gregory J. Gage, Daryl R. Kipke
    Abstract:

    Closed-loop Neural interface technology that combines Neural Ensemble decoding with simultaneous electrical microstimulation feedback is hypothesized to improve deep brain stimulation techniques, neuromotor prosthetic applications, and epilepsy treatment. Here we describe our iterative results in a rat model of a sensory and motor neurophysiological feedback control system. Three rats were chronically implanted with microelectrode arrays in both the motor and visual cortices. The rats were subsequently trained over a period of weeks to modulate their motor cortex Ensemble unit activity upon delivery of intra-cortical microstimulation (ICMS) of the visual cortex in order to receive a food reward. Rats were given continuous feedback via visual cortex ICMS during the response periods that was representative of the motor cortex Ensemble dynamics. Analysis revealed that the feedback provided the animals with indicators of the behavioral trials. At the hardware level, this preparation provides a tractable test model for improving the technology of closed-loop Neural devices.