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Front. Cell. Neurosci. | doi: 10.3389/fncel.2018.00065

Commentary: Injecting instructions into premotor cortex

  • 1Duke University, United States
  • 2National Research University Higher School of Economics, Russia

A commentary on
Injecting instructions into premotor cortex
by Mazurek, K.A., Schieber. M.H. (2017) Neuron. doi: 10.1016/j.neuron.2017.11.006.

Here we call attention to a scholarly paper of particular note, where Mazurek and Schieber (Mazurek and Schieber 2017) reported for the first time that arm reaching tasks performed by rhesus monkeys can be instructed by intracortical stimulation (ICMS) applied to dorsal premotor cortex (PMd). Monkeys started each trial by grasping a home handle that was surrounded by four target handles. Next, reach direction was instructed by either turning on a display composed of light emitting diodes (LEDs) at the base of the target handle and/or applying ICMS to different sites in PMd. ICMS of the primary somatosensory cortex (S1) was also tested. Monkeys responded to the instruction by releasing the home handle and grasping the target handle. They learned to respond correctly to both LED and ICMS instructions, with very high success rate (96-99%).

Previously, motor responses have been instructed by ICMS of S1 in owl monkeys (Fitzsimmons, Drake et al. 2007), rhesus monkeys (Romo, Hernández et al. 1998, O'Doherty, Lebedev et al. 2009) and rats (Talwar, Xu et al. 2002, Pais-Vieira, Lebedev et al. 2013). In rats, ICMS of M1 has been used for the same purpose (Pais-Vieira, Lebedev et al. 2013). The study of Mazurek and Schieber is innovative because they stimulated a higher-order motor area known to be related to motor preparation (Weinrich and Wise 1982), visuomotor transformations (Caminiti, Ferraina et al. 1998), nostandard sensorimotor mapping (Wise, Di Pellegrino et al. 1996), but not primary processing of movements or sensations. Therefore, these results could not be readily attributed to ICMS-evoked motor responses (Graziano, Taylor et al. 2002) or artificial sensations (Romo, Hernández et al. 1998, Fitzsimmons, Drake et al. 2007, O'Doherty, Lebedev et al. 2009).

Mazurek and Schieber kept the amplitude of the ICMS applied to PMd low to make sure that no muscle activations were evoked. While the absence of such activations was confirmed by the pulse-triggered EMG averages, the authors did not illustrate how arm EMG were modulated during task performance. Such an illustration would be useful because in the video of their experiment, hand movements are visible that occurred before the instruction stimuli and during the reaction time period. Quite surprisingly, lower ICMS currents could be applied to PMd than to S1 to accurately instruct the reach target. Mazurek and Schieber commented, “ICMS thus may be experienced more readily in PM than S1.” Overall, Mazurek and Schieber did not speculate excessively about the nature of experiences evoked by ICMS of PMd but proposed that ICMS “may have evoked somatosensory and/or visual percepts, desires to move particular body parts, or other internal urges or thoughts, any of which the monkeys could have used as instructions.” Percepts in the form of a desire to initiate movement have been reported previously for electrical stimulation of premotor cortex in humans (Penfield and Rasmussen 1950).

While these results can be generally described as a type of associative learning (Pearce and Bouton 2001), it is unclear whether monkey’s awareness of the experiences evoked by ICMS was essential for such learning. Although Mazurek and Schieber suggest that their monkeys had conscious experiences of ICMS and reported these experiences with arm movements, it is also possible that ICMS induced Hebbian learning (Hebb 2005) of a nonconscious type (Lewicki, Hill et al. 1992, Shanks and John 1994), where repeated coupling of ICMS with the activation of PMd circuitry during target selection caused specific modifications of synaptic weights for a subset of PMd neurons. Indeed, monkeys were first overtrained on the visually-instructed task. Next, ICMS was repeatedly coupled with the instructions provided by LEDs. Under these conditions, specific populations of PMd neurons were activated while the monkeys responded to each instructed target, and ICMS simultaneously activated axons passing through the stimulated area (Tehovnik, Tolias et al. 2006). Some of these axons projected to the active neurons in PMd, as well as cortical areas interconnected with PMd. Consequently, the effect of Hebbian plasticity was likely to strengthen the responses of specific neuronal populations to ICMS. It is reasonable to suggest that ICMS eventually started triggering PMd activity in the absence of LED instructions. For such Hebbian plasticity to occur, conscious discrimination of different ICMS patterns is not required. On the other hand, it is possible that Hebbian plasticity contributed to the emergence and shaping of the monkeys’ conscious experiences caused by ICMS in this experimental context.

Our view deemphasizes the role of conscious experience, and this is different from the traditional interpretations of ICMS effects. Historically, ICMS has been used for two main purposes: (1) to disrupt cortical processing (Tehovnik and Slocum 2003, Wegener, Johnston et al. 2008), and (2) evoke neural responses that mimic functions of the stimulated area (Salzman, Britten et al. 1990, Romo, Hernández et al. 1998, Graziano, Taylor et al. 2002, Tehovnik, Tolias et al. 2006, Tehovnik and Slocum 2007). For the electrical stimulation of cortical sensory areas in humans, such as S1 (Cushing 1909, Penfield and Boldrey 1937, Penfield and Rasmussen 1950, Flesher, Collinger et al. 2016) and primary visual cortex (Brindley 1970, Dobelle and Mladejovsky 1974, Bak, Girvin et al. 1990), the focus has been traditionally on the perceptions experienced by the subjects. The possibility has received less attention that stimulation may connect to the ongoing cortical activity via a Hebbian mechanism irrespective of the perceptual experience it causes. Yet, several studies have shown that pairing stimulation with motor activity or another stimulus evokes cortical plasticity, such as pairing of transcranial magnetic stimulation in humans with the stimulation of peripheral nerves (Stefan, Kunesch et al. 2000) and artificially connecting two sites in monkey primary motor cortex (Jackson, Mavoori et al. 2006) and S1 (Song, Kerr et al. 2013). Additionally, cortical plasticity has been demonstrated using cross-modal pairing. For example, Lahav et al. (Lahav, Saltzman et al. 2007) trained non-musicians to play a piece of music on a piano. Following this training, the sound of music started to activate cortical motor areas even when the subjects did not move their hands. Such cortical plasticity is also consistent with embodied language framework (Pulvermüller 2013). The fact that subjects could remain unaware of the plastic changes has been elegantly demonstrated using a neurofeedback paradigm (Kaplan, Byeon et al. 2005). Additionally, it has been shown that visual sensitivity can be improved by training in patients with blindsight (Sahraie, Trevethan et al. 2006, Chokron, Perez et al. 2008).

Electrical stimulation of somatosensory system has started to be implemented in bidirectional neural prostheses of the limbs (O’Doherty, Lebedev et al. 2011, Raspopovic, Capogrosso et al. 2014, Lebedev and Ossadtchi 2018). In such systems, Hebbian plasticity could be employed to improve learning of the artificial tactile feedback: electrical stimulation could be paired with virtual reality, tactile stimulation applied to the healthy hand, or verbal stimuli. Such pairing could facilitate the formation of a new percept associated with different sensory modalities and higher-order representations. As pointed out above, stimulation does not necessarily have to mimic the natural activity of the stimulated neuronal circuitry; Hebbian plasticity would eventually make this artificial input more meaningful and possibly consciously perceived. It is possible that Hebbian mechanisms played a role in the previous experiments on ICMS-induced somatosensory perceptions, particularly the ones where training was conducted over the course of many days (Fitzsimmons, Drake et al. 2007, O'Doherty, Lebedev et al. 2009, O’Doherty, Lebedev et al. 2011, Tabot, Dammann et al. 2013). Moreover, the findings of Mazurek and Schieber suggest that the developers of bidirectional neural prostheses could use non-sensory areas as sites for the application of ICMS, such as premotor cortex; and Hebbian associative learning could eventually result in the emergence of realistic perceptions associated with such stimulation.

Finally, ICMS-based neuroprosthetic systems may work optimally if they operate as systems with prediction (Montague and Sejnowski 1994, Sejnowski, Dayan et al. 1995, Mirabella and Lebedev 2017). In such predictive prostheses, ICMS patterns should reflect the properties of prediction error defined as the difference between the internal state and the observed sensory signals. Implementation of such Kalman filtering based operations (Friston 2005, Clark 2015) could incorporate the prosthetic system into the brain more naturally.

Keywords: Intracortical microstimulation, premotor cortex, monkey, Hebbian Learning, Hebbian plasticity, Neural Prostheses, predictive coding, predictive processing

Received: 26 Dec 2017; Accepted: 23 Feb 2018.

Edited by:

Tycho Hoogland, Erasmus Medical Center, Erasmus University Rotterdam, Netherlands

Reviewed by:

Nandakumar Narayanan, University of Iowa, United States
Shenbing Kuang, Institute of Psychology (CAS), China  

Copyright: © 2018 Lebedev and Ossadtchi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Mikhail Lebedev, Duke University, Durham, United States,