Patil, P. G., Carmena, J. M., Nicolelis, M. A. & Turner, D. A. Ensemble recordings of human subcortical neurons as a source of motor control signals for a brain-machine interface. Neurosurgery 55, 27-38

Division of Neurosurgery, Department of Neurobiology, Duke University Medical Center, Durham, North Carolina 27710, USA.
Neurosurgery (Impact Factor: 3.62). 08/2004; 55(1):27-35; discussion 35-8.
Source: PubMed


Patients with severe neurological injury, such as quadriplegics, might benefit greatly from a brain-machine interface that uses neuronal activity from motor centers to control a neuroprosthetic device. Here, we report an implementation of this strategy in the human intraoperative setting to assess the feasibility of using neurons in subcortical motor areas to drive a human brain-machine interface.
Acute ensemble recordings from subthalamic nucleus and thalamic motor areas (ventralis oralis posterior [VOP]/ventralis intermediate nucleus [VIM]) were obtained in 11 awake patients during deep brain stimulator surgery by use of a 32-microwire array. During extracellular neuronal recordings, patients simultaneously performed a visual feedback hand-gripping force task. Offline analysis was then used to explore the relationship between neuronal modulation and gripping force.
Individual neurons (n = 28 VOP/VIM, n = 119 subthalamic nucleus) demonstrated a variety of modulation responses both before and after onset of changes in gripping force of the contralateral hand. Overall, 61% of subthalamic nucleus neurons and 81% of VOP/VIM neurons modulated with gripping force. Remarkably, ensembles of 3 to 55 simultaneously recorded neurons were sufficiently information-rich to predict gripping force during 30-second test periods with considerable accuracy (up to R = 0.82, R(2) = 0.68) after short training periods. Longer training periods and larger neuronal ensembles were associated with improved predictive accuracy.
This initial feasibility study bridges the gap between the nonhuman primate laboratory and the human intraoperative setting to suggest that neuronal ensembles from human subcortical motor regions may be able to provide informative control signals to a future brain-machine interface.

1 Follower
23 Reads
  • Source
    • "A number of BMI systems have been studied in rodents12 and nonhuman primates.13–17 BMI technology also entered human clinical research where both non-invasive EEG-based systems5,18,19 and invasive BMIs based on brain implants20–22 have been tested. Notwithstanding the success of these pioneering experiments, a number of issues need to be resolved before a fully functional practical neuroprosthetic for long-term use can be built.7 "
    [Show abstract] [Hide abstract]
    ABSTRACT: Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the École Polytechnique Fédérale de Lausanne (EPFL) Center for Neuroprosthetics, to bring this new technology to clinical fruition.
    Clinics (São Paulo, Brazil) 06/2011; 66 Suppl 1(Suppl 1):25-32. DOI:10.1590/S1807-59322011001300004 · 1.19 Impact Factor
  • Source
    • "Early experiments on humans have shown that it is possible for profoundly paralyzed patients to control a computer cursor using just a single electrode 97 implanted in the brain, and experiments by Patil et al. have demonstrated that the kind of multielectrode recording devices used in monkeys would most likely function in humans too 98 . Experiments in localized chemical release from implanted chips also 87 (Weiser 1991) 88 (Sellen, Louie et al. 1996) 89 (Rhodes and Starner 1996) 90 (Mann 1997) 91 (Fan, Sun et al. 2005) (Fan, Sun et al. 2005) 92 (Singletary and Starner 2000) 93 (Jebara, Eyster et al. 1997) 94 (Healey and Picard 1998) 95 (Wolpaw, Birbaumer et al. 2000) 96 (Nicolelis, Dimitrov et al. 2003) (Shenoy, Meeker et al. 2003) (Carmena, Lebedev et al. 2003) 97 (Kennedy and Bakay 1998) 98 (Patil, Carmena et al. 2004) suggest the possibility of using neural growth factors to promote patterned local growth and interfacing 99 . "
    [Show abstract] [Hide abstract]
    ABSTRACT: Cognitive enhancement takes many and diverse forms. Various methods of cognitive enhancement have implications for the near future. At the same time, these technologies raise a range of ethical issues. For example, they interact with notions of authenticity, the good life, and the role of medicine in our lives. Present and anticipated methods for cognitive enhancement also create challenges for public policy and regulation.
    Science and Engineering Ethics 07/2009; 15(3):311-41. DOI:10.1007/s11948-009-9142-5 · 0.96 Impact Factor
  • Source
    • "Since locomotion defi cits are commonly associated with spinal cord injury (Dietz, 2001; Dietz and Colombo, 2004; Rossignol et al., 2007; Scivoletto and Di Donna, 2008; Wood- Dauphinee et al., 2002) and neurodegenerative diseases (Boonstra et al., 2008; Green and Hurvitz, 2007; Morris, 2006; Pearson et al., 2004; Sparrow and Tirosh, 2005; Yogev-Seligmann et al., 2008), there is a need to seek new potential therapies to restore gait control in such patients. While the feasibility of a BMI for upper limbs has been demonstrated in studies in monkeys (Carmena et al., 2003, 2005; Serruya et al., 2002; Taylor et al., 2002; Velliste et al., 2008; Wessberg et al., 2000) and humans (Hochberg et al., 2006; Patil et al., 2004), it remains unknown whether BMIs could aid patients suffering from lower limb paralysis, e.g. by driving a leg prosthesis or artifi cial exoskeleton (Fleischer et al., 2006; Hesse et al., 2003; Veneman et al., 2007). Pioneered by Borelli (Borelli, 1680), investigations in biological systems have generated a wealth of knowledge about the biomechanics (Alexander, 2004; Andriacchi and Alexander, 2000; Dickinson et al., 2000; Koditschek et al., 2004; Ounpuu, 1994; Saibene and Minetti, 2003; Stevens, 2006; Vaughan, 2003; Zajac et al., 2002; Zatsiorky et al., 1994) and neurophysiological mechanisms underlying locomotion (Beloozerova et al., 2003; Deliagina et al., 2008; Drew et al., 2004; Georgopoulos and Grillner, 1989; Grillner, 2006; Grillner and Wallen, 2002; Grillner et al., 2008; "
    [Show abstract] [Hide abstract]
    ABSTRACT: The ability to walk may be critically impacted as the result of neurological injury or disease. While recent advances in brain-machine interfaces (BMIs) have demonstrated the feasibility of upper-limb neuroprostheses, BMIs have not been evaluated as a means to restore walking. Here, we demonstrate that chronic recordings from ensembles of cortical neurons can be used to predict the kinematics of bipedal walking in rhesus macaques - both offline and in real time. Linear decoders extracted 3D coordinates of leg joints and leg muscle electromyograms from the activity of hundreds of cortical neurons. As more complex patterns of walking were produced by varying the gait speed and direction, larger neuronal populations were needed to accurately extract walking patterns. Extraction was further improved using a switching decoder which designated a submodel for each walking paradigm. We propose that BMIs may one day allow severely paralyzed patients to walk again.
    Frontiers in Integrative Neuroscience 02/2009; 3(3):3. DOI:10.3389/neuro.07.003.2009
Show more