The development of methodology to identify specific cell populations and circuits within the basal ganglia is rapidly transforming our ability to understand the function of this complex circuit. This mini-symposium highlights recent advances in delineating the organization and function of neural circuits in the external segment of the globus pallidus (GPe). Although long considered a homogeneous structure in the motor-suppressing "indirect-pathway," the GPe consists of a number of distinct cell types and anatomical subdomains that contribute differentially to both motor and nonmotor features of behavior. Here, we integrate recent studies using techniques, such as viral tracing, transgenic mice, electrophysiology, and behavioral approaches, to create a revised framework for understanding how the GPe relates to behavior in both health and disease.

Morrow, M. M. and L. E. Miller. Prediction of muscle activity by populations of sequentially recorded primary motor cortex neurons. J Neurophysiol 89: 2279 -2288, 2003. First published December 18, 2002 10.1152/jn.00632.2002. We have adopted an analysis that produces a post hoc prediction of the time course of electromyogram (EMG) activity from the discharge of ensembles of neurons recorded sequentially from the primary motor cortex (M1) of a monkey. Over several recording sessions, we collected data from 50 M1 neurons and several distal forelimb muscles during a stereotyped precision grip task. Ensemble averages were constructed from 5 to 10 trials for each neuron and EMG signal. We used multiple linear regression on randomly chosen subsets of these neurons to find the best fit between the neuronal and EMG data. The fixed delay between neuronal and EMG signals that yielded the largest coefficient of determination (R 2 ) between predicted and actual EMG was 50 ms. R 2 averaged 0.83 for ensembles composed of 15 neurons. If, instead, each neuronal signal was delayed by the time of its peak cross-correlation with the EMG signal, R 2 increased to 0.88. Using all 50 neurons, R 2 under these conditions averaged nearly 0.97. A similar analysis was conducted with signals recorded during both a power grip and a precision grip task. Quality of the fit dropped dramatically when parameters from the precision grip for a given set of neurons were used to fit data recorded during the power grip. However, when a single set of regression parameters was used to fit a combination of the two tasks, the quality of the fits decreased by Ͻ10% from that of a single task. I N T R O D U C T I O NSingle neuron recording methods applied to behaving animals have contributed dramatically to our understanding of the limb movement-related signals present in the CNS. Despite this success, however, recording neurons one at a time affords the smallest of windows through which to observe command signals that are encoded across tens or hundreds of thousands of neurons.Nearly 20 years ago, Georgopoulos and his colleagues published a now classic study in which they demonstrated that the discharge of ensembles of neurons recorded sequentially in the primary motor cortex (M1) during a highly stereotypic task could be used to make a post hoc "prediction" of the direction of hand motion (Georgopoulos et al. 1983). Since that time, many other studies have been published using similar methods to explore the nature of population coding of motor command signals (Caminiti et al. 1990;Fu et al. 1993;Kalaska et al. 1989;Moran and Schwartz 1999;Scott and Kalaska 1997;Shen and Alexander 1997; Taira et al. 1996). Although many of these experimental studies have concluded that M1 signals encode movement in a hand-centered coordinate system, several theoretical studies have shown that the directional modulation of M1 discharge may arise from a system that fundamentally controls muscle activation (MussaIvaldi 1988; Todorov 2000). While many studies have used spike-t...

Signal transduction through the RAF-MEK-ERK pathway, the first described mitogen-associated protein kinase (MAPK) cascade, mediates multiple cellular processes and participates in early and late developmental programs. Aberrant signaling through this cascade contributes to oncogenesis and underlies the RASopathies, a family of cancer-prone disorders. Here, we report that de novo missense variants in MAPK1, encoding the mitogen-activated protein kinase 1 (i.e., extracellular signal-regulated protein kinase 2, ERK2), cause a neurodevelopmental disease within the RASopathy phenotypic spectrum, reminiscent of Noonan syndrome in some subjects. Pathogenic variants promote increased phosphorylation of the kinase, which enhances translocation to the nucleus and boosts MAPK signaling in vitro and in vivo. Two variant classes are identified, one of which directly disrupts binding to MKP3, a dual-specificity protein phosphatase negatively regulating ERK function. Importantly, signal dysregulation driven by pathogenic MAPK1 variants is stimulus reliant and retains dependence on MEK activity. Our data support a model in which the identified pathogenic variants operate with counteracting effects on MAPK1 function by differentially impacting the ability of the kinase to interact with regulators and substrates, which likely explains the minor role of these variants as driver events contributing to oncogenesis. After nearly 20 years from the discovery of the first gene implicated in Noonan syndrome, PTPN11, the last tier of the MAPK cascade joins the group of genes mutated in RASopathies.

Morrow MM, Jordan LR, Miller LE. Direct comparison of the task-dependent discharge of M1 in hand space and muscle space. J Neurophysiol 97: 1786 -1798, 2007. First published November 22, 2006 doi:10.1152/jn.00150.2006. Since its introduction in the early 1980s, the concept of a "preferred direction" for neuronal discharge has proven to be a powerful means of studying motor areas of the brain. In the current paper, we introduce the concept of a "musclespace"-preferred direction (PD M ) that is analogous to the familiar hand-space-preferred direction (PD H ). PD M reflects the similarity between the discharge of a given neuron and the activity of each muscle in much the way that PD H reflects the similarity of discharge with motion along each of the three Cartesian coordinate axes. We used PD M to analyze the data recorded from neurons in the primary motor cortex (M1) of three different monkeys. The monkeys performed center-out movements within two different cubical workspaces centered either to the left or right of the monkey's shoulder while we simultaneously recorded neuronal discharge, muscle activity, and limb orientation. We calculated preferred directions in both hand space and muscle space, and computed the angles between these vectors under a variety of conditions. PDs for different neurons were broadly distributed throughout both hand space and muscle space, but the muscle-space vectors appeared to form clusters of functionally similar neurons. In general, repeated estimates of PD M were more stable over time than were similar estimates of PD H . Likewise, there was less change in PD M than in PD H for data recorded from the two different workspaces. However, although a majority of neurons had this muscle-like property, a significant minority was more stable in Cartesian hand space, reflecting a heterogeneity of function within M1.

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