Motor Cortex

Interference with Existing Memories Alters Offline Intrinsic Functional Brain Connectivity

This paper describes differences in the properties of single-cell activity in the primary and non-primary motor cortex of behaving monkeys (Macaca fuscata). New findings were obtained in relation to two different behavioural paradigms. First, we found that a large number of non-primary motor cortex neurons exhibit selective or preferential relationships to either signal-triggered or self-paced movement. In the second series of experiments, monkeys were trained to press a small key with the right or left hand, or with both hands. Most primary motor cortex neurons behaved like muscles in the contralateral hand. In contrast, a number of non-primary motor cortex neurons exhibited a selective relationship to the movement (right or left key press, or bilateral key press). The differences suggest the different roles of these two areas in motor control. Studies of this sort seem to start providing answers to the old question of why the non-primary motor cortex exists.

The primary motor (M1) and somatosensory (S1) cortices play critical roles in motor control but the signaling between these structures is poorly understood. To fill this gap, we recorded – in three participants in an ongoing human clinical trial (NCT01894802) for people with paralyzed hands – the responses evoked in the hand and arm representations of M1 during intracortical microstimulation (ICMS) in the hand representation of S1. We found that ICMS of S1 activated some M1 neurons at short, fixed latencies consistent with monosynaptic activation. Additionally, most of the ICMS-evoked responses in M1 were more variable in time, suggesting indirect effects of stimulation. The spatial pattern of M1 activation varied systematically: S1 electrodes that elicited percepts in a finger preferentially activated M1 neurons excited during that finger’s movement. Moreover, the indirect effects of S1 ICMS on M1 were context dependent, such that the magnitude and even sign relative to baseline varied across tasks. We tested the implications of these effects for brain-control of a virtual hand, in which ICMS conveyed tactile feedback. While ICMS-evoked activation of M1 disrupted decoder performance, this disruption was minimized using biomimetic stimulation, which emphasizes contact transients at the onset and offset of grasp, and reduces sustained stimulation.

To generate movements, the motor cortex acts on an intricate network of intermediate neurons in the brainstem and spinal cord, termed ‘premotor neurons’. Premotor neurons activate the motoneurons driving the muscles (Chakrabarti & Schwarz, 2014). Specifically, premotor networks are involved in the generation of reflexes, and form central pattern generators (CPGs) that contribute to stereotyped movement patterns. The precise anatomical organization of these premotor networks is poorly understood, because traditional tract tracing methods lack the specificity to trace tangled networks and are unable to reveal multi-synaptic networks. In this issue of EJN, Sreenivasan et al. (2015) describe evidence that extends previous work by Takatoh et al. (2013), and identify key components of the premotor networks in developing mouse pups. The authors used an elegant neuroanatomical technique called monosynaptic retrograde tracing (MRT) (Wickersham et al., 2007). MRT employs a genetically defective rabies virus that requires a glycoprotein complement in order for the virus to cross a synapse retrogradely and infect the presynaptic neuron. An essential component of this method is the use of genetic engineering to express the required glycoprotein exclusively in postsynaptic neurons, thereby allowing the virus to pass exactly one synapse and exclusively label ‘first-order’ presynaptic neurons. Applied in combination with immunohistochemistry to visualize transmitter content, MRT serves as a powerful tool with which to dissect the anatomical organization of premotor networks. The current study by Sreenivasan et al., and the former study by Takotah et al., investigated the rodent vibrissal system. Whisking movements consist of rhythmic protractions and retractions that are generated by the activation of two antagonistic muscle groups, the intrinsic and extrinsic muscles, respectively. Upon injection of the defective rabies virus into the antagonistic sets of whisker muscles, both studies revealed a fairly consistent anatomical organization of clusters of first-order ‘whisking’ premotor neurons. Among them are known CPGs in the reticular formation, reticular formation cell clusters with unknown function, cells in the spinal trigeminal nuclei, cells in the vestibular nuclei, and, interestingly, also motor cortex neurons. These results contribute greatly to our understanding of this specialized motor system in rodents. Moreover, the current work indicated a fundamental distinction between premotor networks driving extrinsic muscle groups and those driving intrinsic muscle groups. Extrinsic motoneurons are targeted predominantly by excitatory spinal trigeminal and vestibular neurons, whereas intrinsic motoneurons receive relatively more inputs from whisking CPGs. Sreenivasan et al. also combined MRT with anterograde tracing from primary sensorimotor whisker-related cortices [motor, whisker motor cortex (wM1); tactile, primary whisker somatosensory cortex (wS1)] to show that the target profiles of wM1 and wS1 complement the innervation pattern seen for the extrinsic vs. intrinsic premotor systems: wM1 preferentially controls the intrinsic muscle group via the whisking CPG, whereas wS1 controls the extrinsic muscle group via the spinal trigeminal nuclei. Furthermore, the authors could elicit distinct evoked whisker movements after optogenetic activation of the two areas: stimulation in wM1 initiated rhythmic movement, whereas in wS1 it evoked whisker retraction. Although this observation clearly points to differences in motor control between the two cortical areas, it is questionable whether these evoked movements reflect specialization in terms of movement types. First, wM1 is subdivided in several functionally distinct areas, at least in rats (Chakrabarti & Schwarz, 2014). Second, the interpretation of results from bulk activation of motor structures requires caution. Movements evoked from wS1 may merely reflect modulatory action on the whisking brainstem reflex arc (Nguyen & Kleinfeld, 2005), or alternatively its involvement in corticobulbar control of active touch (Furuta et al., 2010). Consistent with these assumptions, we used bulk stimulation to identify the rhythmic whisking subarea of the rat wM1 (Haiss & Schwarz, 2005), and found that it codes for both whisker position and whisking frequency. These effects occurred on the scale of seconds, and therefore possibly reflect indirect control of movement through various premotor networks (Gerdjikov et al., 2013). Rather than attributing distinct types of movement to specific cortical areas, it may be more informative to focus on the differential access of the sensorimotor cortex to specific premotor subsystems, such as CPGs and reflex arcs. In summary, the findings of Sreenivasan et al. (2015), together with the recent discovery of the whisking CPG (Moore et al., 2013), constitute considerable progress towards the description of the whisker-related premotor network. More work will be required to classify the premotor neuron clusters identified so far into functional subsystems. For example, some of the premotor neurons in reticular formation and spinal trigeminal nuclei may well be components of the brainstem reflex arc (Nguyen & Kleinfeld, 2005). Disentangling the entire polysynaptic premotor network will probably require a multifaceted strategy, including additional ingenious genetic trickery, tracing polysynaptic networks in adult animals, and old-fashioned monitoring of the activity of premotor neurons during whisking behavior.

Four electric field modeling methods of Dosing Prefrontal Transcranial Magnetic Stimulation (TMS): Introducing APEX MT dosimetry

Recent transcranial magnetic stimulation studies have shown that the motor output pathway shows a profound inhibition during the preparation of an action. This phenomenon, called “preparatory inhibition”, remains incompletely understood, as it is still unclear which neural structures support it and what function it exactly serves during action preparation. In the current study, we tested this preparatory inhibition in Parkinson’s disease (PD) patients and matched healthy control subjects. The aim was to better understand the role of basal ganglia (which are dysfunctional in PD) and the influence of dopamine replacement therapy on motor inhibition during action preparation.

<bold>Objective</bold> The contractions of abdominal muscle during voluntary urination is a motor control task, Which aims to explore the central activity characteristics of this action with functional near-infrared spectroscopy (fNIRS). <bold>Methods</bold> A total of 19 healthy subjects aged 18 years or older were recruited to undergo fNIRS testing twice, performing repetitive abdominal muscle contractions in the no-urine and strong-urine states. Brain activity under the corresponding no-abdominal muscle-contraction task was used as a baseline to analyze the cortical activities specific to abdominal muscle contractions in these two different states. <bold>Results</bold> Abdominal muscle contractions during the strong desire to urinate primarily activated the bilateral pre-motor/supplementary motor area (BA6), bilateral dorsolateral prefrontal cortex (BA9/46), bilateral frontal pole area (BA10), the anterior portion of the right inferior frontal gyrus (BA47), the right middle temporal gyrus (BA21), the right primary motor cortex (BA4), and the left primary somatosensory cortex (BA1/2/3) in conjunction with the left inferior frontal of pars triangularis Broca's area (BA45) (<italic>P</italic>&lt;0.05). In contrast, abdominal muscle contractions with no desire to urinate primarily activated the bilateral pre-motor/supplementary motor area (BA6) (<italic>P</italic>&lt;0.05), the right primary motor cortex (BA4), the right primary somatosensory cortex (BA1/2/3), the right inferior frontal of pars triangularis Broca's area (BA45), and the right supramarginal gyrus part of Wernicke's area (BA40) (<italic>P</italic>&lt;0.05). Compared to the strong urination state, stronger activation of the bilateral premotor/assistive motor area (BA6) was present in the non-urination state (<italic>P</italic>&lt;0.05). Compared to the non-urination state, stronger activation of the left dorsolateral prefrontal cortex (BA46) was present in the strong urination state (<italic>P</italic>&lt;0.05). <bold>Conclusion</bold> The primary somatosensory cortex, primary motor cortex, and pre-motor/supplementary motor area are jointly involved in the regulation of voluntary urination-associated random abdominal muscle contractions. And further activation of the prefrontal cortex can be induced during abdominal muscle contractions in the strong urination state, suggesting that the prefrontal cortex plays a positive role in facilitating abdominal muscle movements and initiating urination following the perception of urinary awareness.

Motor cortex modulation of exteroceptive information at bulbar and thalamic lemniscal relays in the cat

Our goal in this review is to provide an anatomical framework for the analysis of the motor functions of the medial wall of the hemisphere in humans and laboratory primates. Converging evidence indicates that this region of the frontal lobe contains multiple areas involved in motor control. In the monkey, the medial wall contains four premotor areas that project directly to both the primary motor cortex and the spinal cord. These are the supplementary motor area (SMA) on the superior frontal gyrus and three motor areas buried within the cingulate sulcus. In addition, there is evidence that a fifth motor field, the pre-SMA, lies rostral to the SMA proper. Recent physiological observations provide evidence for functional differences among these motor fields. In the human, no consensus exists on the number of distinct motor fields on the medial wall. In this review, we summarize the results of positron emission tomography (PET) studies that examined functional activation on the medial wall of humans. Our analysis suggests that it is possible to identify at least four separate cortical areas on the medial wall. Each area appears to be relatively more involved in some aspects of motor behavior than others. These cortical areas in the human appear to be analogous to the pre-SMA, the SMA proper, and two of the cingulate motor areas of the monkey. We believe that these correspondences and the anatomical framework we describe will be important for unraveling the motor functions of the medial wall of the hemisphere.

The orofacial sensorimotor cortex is known to play a role in motor learning. However, how motor learning changes the dynamics of neuronal activity and whether these changes differ between orofacial primary motor (MIo) and somatosensory (SIo) cortices remain unknown. To address these questions, we used chronically implanted microelectrode arrays to track learning-induced changes in the activity of simultaneously recorded neurons in MIo and SIo as two naive monkeys (Macaca mulatta) were trained in a novel tongue-protrusion task. Over a period of 8-12 d, the monkeys showed behavioral improvements in task performance that were accompanied by rapid and long-lasting changes in neuronal responses in MIo and SIo occurring in parallel: (1) increases in the proportion of task-modulated neurons, (2) increases in the mutual information between tongue-protrusive force and spiking activity, (3) reductions in the across-trial firing rate variability, and (4) transient increases in coherent firing of neuronal pairs. More importantly, the time-resolved mutual information in MIo and SIo exhibited temporal alignment. While showing parallel changes, MIo neurons exhibited a bimodal distribution of peak correlation lag times between spiking activity and force, whereas SIo neurons showed a unimodal distribution. Moreover, coherent activity between pairs of MIo neurons was higher and centered around force onset compared with pairwise coherence of SIo neurons. Overall, the results suggest that the neuroplasticity in MIo and SIo occurring in parallel serves as a substrate for linking sensation and movement during sensorimotor learning, whereas the differing dynamic organizations reflect specific ways to control movement parameters as learning progresses.

In the primate cerebral cortex there are at least two somatotopically organized, nonprimary motor fields rostral to the primary motor area. To understand the functions of these multiple motor representations we have compared the neuronal activity in each of these fields while monkeys performed a trained motor task, using right, left or both hands. In the nonprimary motor cortex, activity in a number of neurons was related to the movement the animal chose and performed, whereas in the primary motor cortex, changes in the firing of most neurons were simply related to activity in the contralateral muscles. This result indicates that the nonprimary motor cortex is involved in higher-order coding of the laterality of the motor response, implying that it exerts its motor control function at a higher hierarchical level than its counterpart in the primary motor cortex.

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that alters cortical excitability in a polarity specific manner and has been shown to influence learning and memory. tDCS may have both on-line and after-effects on learning and memory, and the latter are thought to be based upon tDCS-induced alterations in neurochemistry and synaptic function. We used ultra-high-field (7T) magnetic resonance spectroscopy (MRS), together with a robotic force adaptation and de-adaptation task, to investigate whether tDCS-induced alterations in GABA and Glutamate within motor cortex predict motor learning and memory. Note that adaptation to a robot-induced force field has long been considered to be a form of model-based learning that is closely associated with the computation and ‘supervised’ learning of internal ‘forward’ models within the cerebellum. Importantly, previous studies have shown that on-line tDCS to the cerebellum, but not to motor cortex, enhances model-based motor learning. Here we demonstrate that anodal tDCS delivered to the hand area of the left primary motor cortex induces a significant reduction in GABA concentration. This effect was specific to GABA, localised to the left motor cortex, and was polarity specific insofar as it was not observed following either cathodal or sham stimulation. Importantly, we show that the magnitude of tDCS-induced alterations in GABA concentration within motor cortex predicts individual differences in both motor learning and motor memory on the robotic force adaptation and de-adaptation task.

Neuronal correlates of the specification of movement direction and force in four cortical areas of the monkey

Animal studies have shown that cerebellar projections influence both excitatory and inhibitory neurones in the motor cortex but this connectivity has yet to be demonstrated in human subjects. In human subjects, magnetic or electrical stimulation of the cerebellum 5-7 ms before transcranial magnetic stimulation (TMS) of the motor cortex decreases the TMS-induced motor-evoked potential (MEP), indicating a cerebellar inhibition of the motor cortex (CBI). TMS also reveals inhibitory and excitatory circuits of the motor cortex, including a short-interval intracortical inhibition (SICI), long-interval intracortical inhibition (LICI) and intracortical facilitation (ICF). This study used magnetic cerebellar stimulation to investigate connections between the cerebellum and these cortical circuits. Three experiments were performed on 11 subjects. The first experiment showed that with increasing test stimulus intensities, LICI, CBI and ICF decreased, while SICI increased. The second experiment showed that the presence of CBI reduced SICI and increased ICF. The third experiment showed that the interaction between CBI and LICI reduced CBI. Collectively, these findings suggest that cerebellar stimulation results in changes to both inhibitory and excitatory neurones in the human motor cortex.

Sensory and motor responses of precentral cortex cells during comparable passive and active joint movements.