Research reportA distributed network critical for selecting among tool-directed actions
Introduction
A fundamental problem for the brain is the specification of potential actions and the need to select among these actions according to task goals. Substantial research indicates that the sensorimotor system prepares possible actions in parallel while awaiting additional information required to select between them (e.g., Cisek and Kalaska, 2005, Kim and Shadlen, 1999, Ledberg et al., 2007, Pastor-Bernier and Cisek, 2011; see Cisek and Kalaska, 2010, Gold and Shadlen, 2007 for reviews). As evidence for each action accumulates, candidate actions compete with one another for selection, and selection is biased in favor of actions consistent with context and goals (Cisek, 2007).
For humans, interacting with tools poses a special challenge for action selection: many tools can be used with more than one skilled action (e.g., a knife can be used for slicing, stabbing, or spreading). Furthermore, for some tools, actions associated with skillful use differ from actions for transport. For example, a calculator is used with a non-prehensile “poke”, but it is picked up and moved with a power grip. In fact, “grasp-to-move” and “use” actions are associated with different temporal dynamics of activation. While grasp-to-move actions are rapidly evoked but short-lasting, use actions show comparatively slower activation and decay (Jax and Buxbaum, 2010, Lee et al., 2012). Because of these differences in the time-course of their activation, grasp actions may interfere with use actions within single tools (Jax and Buxbaum, 2010, Osiurak et al., 2013). For example, Jax and Buxbaum (2010) found that participants were slower to initiate use actions to tools associated with different use and grasp actions (e.g., calculator) than to tools associated with the same use and grasp actions (e.g., beer mug). These results indicate that an inconsistent grasp action can interfere with the production of a tool use action. However, no such effect was observed when participants initiated grasp actions (that is, a different use did not interfere with grasping), unless they had completed a use task prior to grasping. These and other related data (e.g., Lee et al., 2012) indicate that interference from use actions on grasping takes longer to emerge and may arise during the retrieval and processing of semantic knowledge of tools. In contrast, grasp actions are more quickly computed, based on currently–visualized structural properties of objects, and so grasp can interfere with use even on an individual trial, within single objects. In light of these data, a critical question is what mechanisms—and which brain regions—enable selection of appropriate tool-related hand actions.
An important opportunity to examine this issue is afforded by studying the determinants and neuroanatomic substrates of errors in patients with limb apraxia, a disorder of skilled action characterized by spatiotemporal and postural hand action errors. Patients with apraxia after left hemisphere stroke (LCVA) exhibit slowed activation of “use” actions (Lee, Mirman, & Buxbaum, 2014), and, relative to control participants and non-apraxic patients, erroneously grasp (and subsequently erroneously use) tools when asked to use them but not when asked to transport them (Randerath, Li, Goldenberg, & Hermsdörfer, 2009). Furthermore, patients with apraxia have particular difficulty producing hand actions for tools associated with conflicting use and grasp actions, like a calculator (“conflict” tools) (Jax & Buxbaum, 2013). Even so, these patients perform normally when reaching and/or generating grasping actions based on object shape and size (Buxbaum et al., 2005a, Buxbaum et al., 2003, Haaland et al., 1999). In contrast to patients with limb apraxia, patients with optic ataxia exhibit impairments when grasping objects but can often correctly pantomime object use actions (Karnath and Perenin, 2005, Perenin and Vighetto, 1988).
This pattern of data suggests that functionally and/or neuroanatomically distinct cognitive systems subserve skilled use of tools and prehensile grasping. In addition, neuroimaging studies of healthy participants reveal different patterns of activation for these two kinds of actions with objects (Buxbaum et al., 2006, Creem-Regehr et al., 2007). Although visually-guided control of action relies on brain regions in the dorsal processing stream (Goodale and Milner, 1992, Goodale et al., 1991), several researchers have proposed further divisions of the dorsal stream for different kinds of object-directed actions (Binkofski and Buxbaum, 2013, Buxbaum and Kalénine, 2010, Fridman et al., 2006, Johnson-Frey, 2004, Rizzolatti and Matelli, 2003, Vingerhoets et al., 2009). Specifically, a bilateral dorso-dorsal “Grasp” system is specialized for prehensile actions based on object shape, size, and orientation, while a left-lateralized ventro-dorsal “Use” system mediates skilled object use actions that cannot be inferred from object structure.
The decision to use a tool or grasp it to move depends on context and task goals. Moreover, everyday actions often entail both moving and using in relatively rapid succession (e.g., when selecting a tool from a drawer or storage container, performing a task with the tool, and then clearing it from the workspace) and likely require coordination between Use and Grasp systems (Binkofski & Buxbaum, 2013). Yet, little is known about how different actions specified by these two systems compete for selection. Many important questions remain, including which regions within the left hemisphere normally select between tool-directed actions, the impact of deficient selection on apraxic errors, and the stage of cognitive processing at which such errors arise.
Neuroimaging studies implicate left inferior gyrus (IFG)/ventral premotor cortex (vPMC), inferior parietal cortex (IPL), and posterior middle temporal gyrus (pMTG) as key nodes in the network subserving skilled tool use (Lewis, 2006), and lesions to each of these regions are associated with apraxia (Buxbaum et al., 2014, Randerath et al., 2010). Two of these regions—IFG and IPL—may play a role in selection, broadly defined. On many accounts, IFG resolves competition that arises when selecting between incompatible representations (e.g., Thompson-Schill & Botvinick, 2006). Similarly, anterior parietal cortex/supramarginal gyrus (SMG) is activated during response competition (Hazeltine, Poldrack, & Gabrieli, 2000) and may update or suppress prepared but incorrect actions (Hartwigsen et al., 2012). However, studies of response conflict typically examine simple and/or arbitrary actions (e.g., button presses) with questionable relevance to tool actions.
In the present study, we used voxel-based lesion-symptom mapping (VLSM) with LCVA patients to test the hypothesis that within the key nodes of the tool-use network, IFG and SMG (but not pMTG) enable selection between different hand actions naturally associated with the same tool. While apraxia is apparent in actual tool use (e.g., Poizner, Mack, Verfaellie, Gonzalez Rothi, & Heilman, 1990), object structure constrains the degrees of freedom of movements (see Buxbaum, Johnson-Frey, et al., 2005). Consequently, we assessed performance using tool use pantomime since it is correlated with tool use (Jarry et al., 2013), is more likely to reveal subtle influences on apraxic performance (Buxbaum, Kyle, & Menon, 2005), and results in movement errors similar in character to those seen with tool use (Hermsdörfer, Li, Randerath, Roby-Brami, & Goldenberg, 2013). Additionally, we confirmed that the effects of deficient action selection are evident in action production but not in a task that merely requires recognition of tool use actions (tool use pantomime recognition). Finally, we tested the prediction that an inability to select between use and grasp actions results in inappropriate grasping responses (due to the relative preservation of the Grasp system in patients with limb apraxia, Jax & Buxbaum, 2013) and/or difficulty selecting a single response. The results of this study enable us to provide both computational and neuroanatomic specificity to our understanding of action selection.
Section snippets
Participants
We recruited 31 chronic left hemisphere stroke patients (48% female) from the Neuro-Cognitive Rehabilitation Research Registry at Moss Rehabilitation Research Institute (MRRI) (Schwartz, Brecher, Whyte, & Klein, 2005) (48% female; mean age = 57.0 years, SD = 10.6, range = 31–76 years; mean education = 15.7 years, SD = 1.5, range = 11–29 years). All patients were at least 6 months post-stroke. To ensure that patients understood instructions for the experimental tasks, we excluded patients with
Tool use pantomime
Descriptive information on overall tool use pantomime and tool use recognition accuracy is presented in Table 2. To determine the effects of use/grasp conflict on pantomime accuracy, we used a three-way mixed ANOVA with conflict (conflict tools, non-conflict tools) and action component (hand action, arm action, amplitude, timing) as within-subjects factors, and participant group (LCVA, control) as a between-subjects factor. We found main effects of conflict [F(1, 45) = 7.10, p = .01], action
Discussion
Although tools evoke their actions even when task-irrelevant (e.g., Jax & Buxbaum, 2010), the mechanisms by which appropriate tool actions are selected—and their neural correlates—are poorly understood. Here, we assessed the performance of LCVA patients on a production task in which the grasp-to-move and use actions for a tool were congruent or incongruent. We also used VLSM and tractographic overlap analyses to determine brain regions necessary for selecting among tool-directed actions.
Conclusions
We investigated the mechanisms and corresponding brain regions necessary for selecting between different “use” and “grasp-to-move” actions associated with the same tool. Our results revealed that while lesions to pMTG and aIPS impaired production of use actions for all tools, lesions to SMG, IFG/anterior insula, and the SLF specifically impaired production of use actions for tools used and grasped with different hand actions. Furthermore, the nature of patients' errors to “conflict” tools was
Acknowledgments
This research was funded by National Institutes of Health (NIH) grants R01NS065049 (LJB) and T32HD007425 (CEW, trainee). We thank Allison Shapiro and Alexis Kington for their help in stimulus development and data collection, H. Branch Coslett for his help with lesion segmentation, and Allison Shapiro, Alexis Kington, and Leyla Tarhan for coding patients' gestures.
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