Abstract

Impaired tool use despite preserved basic motor functions occurs after stroke in the context of apraxia, a cognitive motor disorder. To elucidate the neuroanatomical underpinnings of different tool use deficits, prospective behavioral assessments of 136 acute left-hemisphere stroke patients were combined with lesion delineation on magnetic resonance imaging (MRI) images for voxel-based lesion-symptom mapping. Deficits affecting both the selection of the appropriate recipient for a given tool (ToolSelect, e.g., choosing the nail for the hammer), and the performance of the typical tool-associated action (ToolUse, e.g., hammering in the nail) were associated with ventro-dorsal stream lesions, particularly within inferior parietal lobule. However, ToolSelect compared with ToolUse deficits were specifically related to damage within ventral stream regions including anterior temporal lobe. Additional retrospective error dichotomization based on the videotaped performances of ToolUse revealed that spatio-temporal errors (movement errors) were mainly caused by inferior parietal damage adjacent to the intraparietal sulcus while content errors, that is, perplexity, unrecognizable, or semantically incorrect movements, resulted from lesions within supramarginal gyrus and superior temporal lobe. In summary, our results suggest that in the use of tools, conceptual and production-related aspects can be differentiated and are implemented in anatomically distinct streams.

Introduction

Even the most mundane tasks in our lives depend on the use of tools. We use a spoon to eat soup, a key to open a door, and a toothbrush to clean our teeth. Deficient tool use despite intact basic sensorimotor functions such as strength or coordination may occur after stroke and is one of the main features of apraxia, a cognitive motor disorder (Leiguarda and Marsden 2000; Goldenberg 2009; Dovern et al. 2012). Tool use deficits greatly diminish patients' potential to resume an independent and self-determined lifestyle (Hanna-Pladdy et al. 2003; Vanbellingen and Bohlhalter 2011; Bieńkiewicz et al. 2014).

Dissociable error types in the clinical presentations of apraxic tool deficits suggest different brain systems involved (Rothi et al. 1991; van Elk et al. 2014a). Patients may associate tools with incorrect objects, for example, when using a toothbrush to clean their fingers, perform actions with inappropriate tools, such as when cutting bread with a spoon, or display spatio-temporal errors, for example, by attempting to cut bread with a knife held in a wrong orientation (de Renzi and Lucchelli 1988; Ochipa et al. 1989, 1992; Heilman et al. 1997; Buxbaum 2001; Bieńkiewicz et al. 2014).

This variability has informed influential cognitive models of praxis that distinguish between conceptual and production-related action components (Roy and Square 1985; Rothi et al. 1991; Cubelli et al. 2000; Stamenova et al. 2012; van Elk et al. 2014a). Incorrect tool-object or tool-action associations are proposed to result from disturbances within the conceptual system (Ochipa et al. 1989, 1992; Heilman et al. 1997). Conversely, errors affecting spatio-temporal movement characteristics, such as the tool's orientation, the grip used to hold the tool, or the movement amplitude, are thought to reflect damage to the action production system (Poizner et al. 1990; Rothi et al. 1991; Heilman et al. 1997).

Despite considerable research efforts, the neural bases underlying conceptual and production-related action components have remained uncertain. Subdividing the originally proposed (single) dorsal stream for spatial properties in visual perception (Ungerleider and Mishkin 1982), and for actions related to visually presented stimuli (Goodale and Milner 1992; Jeannerod 1994), several authors suggested that different aspects of tool-associated actions are mediated by 2 distinct dorsal pathways (Rizzolatti and Matelli 2003; Pisella et al. 2006; Buxbaum and Kalénine 2010; Binkofski and Buxbaum 2013; Vingerhoets 2014). First, the bilateral dorso-dorsal stream traverses from visual area V3a through V6 toward the superior parietal lobule, and, via association fibers such as, the superior longitudinal fascicle (SLF) II, reaches the dorsal premotor cortex (Rizzolatti and Matelli 2003; Vry et al. 2012; Binkofski and Buxbaum 2013). The dorso-dorsal stream is particularly relevant for online movement control and for “structure-based” movements, for example, when transforming an object's location or size into appropriate motor commands for reaching (Blangero et al. 2009; Binkofski and Buxbaum 2013; Brandi et al. 2014). Second, the ventro-dorsal stream encompasses higher order visual areas like MT/V5+, the inferior parietal lobule (IPL, angular and supramarginal gyri), as well as the ventral premotor cortex and inferior frontal gyrus connected by long-distance fibers including the SLF III or the arcuate fascicle (Rizzolatti and Matelli 2003; Saur et al. 2008; Binkofski and Buxbaum 2013; Hoeren et al. 2014; Hamzei et al. 2015; Vry et al. 2015). This ventro-dorsal stream is thought to store sensorimotor “engrams” specifying the invariant characteristics of skilled actions that have been acquired by experience (Heilman et al. 1982; Rijntjes et al. 1999; Buxbaum et al. 2007; Niessen et al. 2014; Vry et al. 2015). Alternatively, the left IPL may be more critical for mechanisms related to online movement control, including the monitoring and the adaption of movement amplitude and timing, whereas tool-action posture representations may primarily depend on the posterior middle temporal gyrus (Hermsdörfer and Goldenberg 2002; Schaefer et al. 2009; Buxbaum et al. 2014).

Moreover, the role of the “ventral stream,” originally described as related to object recognition (Ungerleider and Mishkin 1982; Goodale and Milner 1992) remains disputed for tool use. The emerging concept of a domain-general dual loop model (Weiller et al. 2011; Rijntjes et al. 2012; Weiller, Bormann et al. 2015) assumes 2 major parallel processing streams connecting postrolandic (temporal/parietal) and prerolandic association cortices via 2 long association tract systems, above (dorsal: SLF II and III) or below (ventral: extreme capsule, inferior orbital fascicle [IFOF], uncinated fascicle) the sylvian fissure (Makris et al. 1999; Saur et al. 2008; Hamzei et al. 2015; Vry et al. 2015). In this model, the ventral stream not only includes inferotemporal regions, but also middle and superior temporal cortices including the anterior temporal pole (Rauschecker and Scott 2009; Garcea and Mahon 2014; Willmes et al. 2014) as well as pars triangularis and orbitalis of the inferior frontal gyrus (IFG) (Vry et al. 2012). The ventral stream has been found involved in the auditory system (Rauschecker and Scott 2009), language (Hickok and Poeppel 2007; Saur et al. 2008; Kümmerer et al. 2013), syntax (Weiller et al. 2009; Musso et al. 2015), arithmetics (Klein et al. 2013), spatial attention (Umarova et al. 2010), as well as in imagery, pantomime, and recognition of actions (Vry et al. 2012, 2015; Hoeren et al. 2013). The ventral stream has been related to the processing of amodal semantic concepts and hierarchical structural relationships (Patterson et al. 2007; Weiller et al. 2011; Rijntjes et al. 2012; Lambon Ralph 2014). Throughout the manuscript, we use the term “ventral stream” in accordance with these proposals. In line with its putative functions, some authors implicated the ventral stream in conceptual aspects of tool use (Hodges et al. 1999; Bozeat et al. 2002; Milner and Goodale 2008; Almeida et al. 2013; Hoeren et al. 2013, 2014). Contrary, others proposed that tool-object and tool-action associations are processed mainly within the ventro-dorsal stream (Buxbaum 2001; Kalénine et al. 2010). Consistent with the latter view, in a voxel-based lesion-symptom mapping (VLSM) study with 38 chronic stroke patients, deficits affecting the ability to match common tools to objects and the performance of tool-associated actions were both associated with fronto-parietal lesions (Goldenberg and Spatt 2009).

To further clarify the differential involvement of dorsal and ventral streams in conceptual and production-related aspects of tool-associated actions, we prospectively examined a cohort of 136 acute stroke patients using an established test comprising 5 common tools (Goldenberg and Spatt 2009). Two subscores were determined for each patient. First, patients' ability to select the appropriate recipient from a set of different objects was evaluated (ToolSelect, e.g., selecting the nail and not the screw or the bolt when handed a hammer). Secondly, the performance of the actual tool-associated action was assessed (ToolUse, e.g., hammering in the nail).

In addition, prompted by recent results on pantomimed tool use indicating distinct anatomical bases for the selection and execution of tool-associated actions (Hoeren et al. 2014), we retrospectively re-evaluated all videotaped performances of patients with ToolUse deficiencies to classify the ToolUse errors as either movement or content related. In analogy to the recently described scoring system used for pantomime (Hoeren et al. 2014), movement errors referred to incorrect spatio-temporal features of overall recognizable movements, while content errors were scored for helpless perplexity as well as unrecognizable and semantically incorrect actions (see Table 1 for an overview of the scores obtained). In summary, we thus report 2 kinds of conceptual errors, that is, incorrect tool-recipient associations (ToolSelect errors) and content errors during ToolUse. Conversely, movement errors during ToolUse may be aligned with impairments of the production system (Ochipa et al. 1989, 1992; Rothi et al. 1991; Heilman et al. 1997).

Table 1

Overview over the scores obtained

Score Description FABERS type FABERS category Adapted FABERS definition 
ToolSelecta Selecting the correct recipient for a given tool out of a set of 5 objects (selecting the nail for the hammer)    
ToolUse Applying the tool to the recipient (hammering in the nail)    
Detailed error classification for ToolUse 
 ToolUseContenta Only items with “content” errors scored as incorrect    
  Semantic Performing a non-typical skilled action with the tool (Hammering onto the bolt with the wrench) Perserverative Content Response includes all/part of previous response 
 Related Content An accurate action semantically related to the tool 
 Nonrelated Content An accurate action semantically unrelated to the tool 
 Hand Content Not use the tool, for example, turn the screw by hand 
  Unrecognizable No recognizable skilled action (rubbing on the nail with the hammerhead) Unrecognizable response Other Shares no spatial or temporal features of target action 
  Perplexity Patient appears perplexed and makes no response No response Other Participant makes no response 
 ToolUseMovementb Only items with “movement” errors scored as incorrect (overall recognizable movements with spatio-temporal errors)    
  Configuration Inaccurate grip (Thumb not inserted into the hole in the scissor handle) Internal configuration Spatial Abnormality of finger/hand posture with respect to the tool 
  Orientation Tool incorrectly oriented (Small surface of the hammerhead facing down) External configuration Spatial Abnormality of the relationships between hand, arm, tool, and recipient 
  Movement Incorrect amplitude/movement dynamics/sequence (Amplitude too small when turning the screwdriver) Amplitude Spatial Amplification, reduction, or irregularity of amplitude 
Movement Spatial Any disturbance of the characteristic action required to complete the goal 
Sequencing Temporal Movement structure recognizable, but addition, deletion of inaccurate order of sequence 
Timing Temporal Alteration of timing/speed (including increase, decrease, or irregular) 
Occurrence Temporal Repetitive production of single movements or single production of multiple movements 
ToolComplete Overall performance (ToolSelect + ToolUse)    
Score Description FABERS type FABERS category Adapted FABERS definition 
ToolSelecta Selecting the correct recipient for a given tool out of a set of 5 objects (selecting the nail for the hammer)    
ToolUse Applying the tool to the recipient (hammering in the nail)    
Detailed error classification for ToolUse 
 ToolUseContenta Only items with “content” errors scored as incorrect    
  Semantic Performing a non-typical skilled action with the tool (Hammering onto the bolt with the wrench) Perserverative Content Response includes all/part of previous response 
 Related Content An accurate action semantically related to the tool 
 Nonrelated Content An accurate action semantically unrelated to the tool 
 Hand Content Not use the tool, for example, turn the screw by hand 
  Unrecognizable No recognizable skilled action (rubbing on the nail with the hammerhead) Unrecognizable response Other Shares no spatial or temporal features of target action 
  Perplexity Patient appears perplexed and makes no response No response Other Participant makes no response 
 ToolUseMovementb Only items with “movement” errors scored as incorrect (overall recognizable movements with spatio-temporal errors)    
  Configuration Inaccurate grip (Thumb not inserted into the hole in the scissor handle) Internal configuration Spatial Abnormality of finger/hand posture with respect to the tool 
  Orientation Tool incorrectly oriented (Small surface of the hammerhead facing down) External configuration Spatial Abnormality of the relationships between hand, arm, tool, and recipient 
  Movement Incorrect amplitude/movement dynamics/sequence (Amplitude too small when turning the screwdriver) Amplitude Spatial Amplification, reduction, or irregularity of amplitude 
Movement Spatial Any disturbance of the characteristic action required to complete the goal 
Sequencing Temporal Movement structure recognizable, but addition, deletion of inaccurate order of sequence 
Timing Temporal Alteration of timing/speed (including increase, decrease, or irregular) 
Occurrence Temporal Repetitive production of single movements or single production of multiple movements 
ToolComplete Overall performance (ToolSelect + ToolUse)    

Note: aIndicative of damage to the conceptual system.

bReflecting damage to the production system as defined by Heilman et al. (1997). The error types and categories used in our present study are derived from the scoring system for pantomimed tool use as described by Hoeren et al. (2014, p.412) and Bartolo (2008, p.112}. For comparability, the presently used classification system is aligned with the error types and error categories described in the Florida Apraxia Battery – Extended and Revised Sydney (FABERS) for pantomimed tool use (Rothi 1997, p.571; Power 2010, p.102) in so far as they may be applied to actual tool use; the definitions are adapted as far as necessary.

We hypothesized that deficient recipient selection (ToolSelect) would be associated with lesions within the ventral (Milner and Goodale 2008), but possibly also within the ventro-dorsal stream (Goldenberg and Spatt 2009). Conversely, we predicted that the performance of the tool-associated action (ToolUse) would rely comparatively more on the integrity of ventro-dorsal regions such as the IPL, as well as on the dorso-dorsal stream for online movement control (Hodges et al. 1999; Buxbaum, Giovannetti et al. 2000; Buxbaum and Saffran 2002; Binkofski and Buxbaum 2013; Brandi et al. 2014). Moreover, in line with recent results from pantomime of tool use (Hoeren et al. 2014), we expected to find dissociable parietal and temporal lesion patterns related to movement and content errors, respectively. To avoid effects of brain reorganization, patients were tested as soon as possible in the acute period, that is, within the first 10 days after stroke.

Materials and Methods

Subjects

Patients were consecutively recruited from the Department of Neurology at the University Medical Center Freiburg, Germany. For a period of 43 months (from February 2011 until August 2014), we screened all patients with ischemic stroke. Patients with first ever ischemic left-hemisphere infarct confirmed by MRI were considered for inclusion. Exclusion criteria included 1) age >90 years; 2) reduced general health status; 3) previous infarcts; 4) pre-existing structural brain changes (e.g., patients with more than very little white matter changes corresponding approximately to an ARWMC [age-related white matter changes] score of 1 [Wahlund et al. 2001] were excluded); 5) major cognitive impairment or pre-existing neuropsychiatric diseases (e.g., schizophrenia); 6) hemodynamic alterations (e.g., carotid occlusion with insufficient collateralization); 7) lacunar infarcts; and 8) other reasons, for example, contraindications for MRI. On the basis of these criteria, 138 patients received neuropsychological testing. Of these, 2 were excluded due to excessive sleepiness during the testing session. Thus, in total, here we report data of 136 patients. Patients were tested as soon as possible after admission, mean ± SD, 5.1 ± 1.9 days (min 1, max 10) after symptom onset. Ninety-two patients also participated in a study on pantomime of tool use and imitation of meaningless gestures (Hoeren et al. 2014). In addition, 30 healthy elderly subjects were recruited to obtain normative data for the tool use test (see Supplementary Materials). Full written consent was obtained from all patients and control subjects. In cases of severe aphasia, detailed information was given to the patient's relatives or the legal guardian. The study was approved by local ethics authorities.

Behavioral Testing

Testing Procedures

All patients were tested by one of 5 specially trained occupational therapists with extensive experience in working with stroke patients. For scoring, performances of 123/136 patients were videotaped and evaluated separately by 2 raters (M.H. and V.M.L.). V.M.L. was blind to location and extent of the stroke. The items that had been scored differently by the 2 raters were reviewed jointly and a consensus rating was established. The remaining 13 patients who either declined being recorded on video or could not be filmed for technical reasons were scored directly by the examining occupational therapist with the exception of the characterization of errors during action execution as content or movement that was done only post hoc and video based (see below). All examiners were familiarized with the scoring system before starting the study.

Use of Common Tools

Testing was conducted as described by Goldenberg and Spatt (2009). The patient was seated in front of a rack on which a nail, a screw, a padlock, a thread, and a bolt were fixed. All items could be manipulated by the appropriate tool (e.g., the screw could be turned, the nail could be hammered in). One after another, the patient was then handed one out of 5 tools (e.g., a hammer) and was asked to demonstrate its use on the rack. The matching recipient was indicated by the examiner if the patient was unable to perform the selection correctly. One minor modification to the original test was that 2 additional wing screws were visible on the rack. These were necessary to be able to disassemble the rack from its base for transportation to different wards, for example, the stroke unit, if the patient could not be brought to our lab. Patients were asked to use the left hand in the case of relevant right upper extremity impairment (tested beforehand).

Table 1 provides an overview of the scores obtained. Scoring followed a 2-step approach (Goldenberg and Spatt 2009): First, for the ToolSelect subscore, for each of the 5 tools, patients were given 2 points for the prompt selection of the matching recipient, 1 point for correct selection after a brief period of trial and error during which patients revised their decisions, or zero points when failing to achieve the correct selection. Since we could not formally exclude that correct selections after trial and error were made by chance, for a confirmatory analysis, alternative scores without the distinction between “trial and error” and complete recipient selection failure were calculated (1 point for prompt selection, 0 points for any type of error, i.e., either correct selection after “trial and error” or complete selection failure; maximum score 5 points). Secondly, for the ToolUse subscore, 2 or 1 points were credited for flawless application without hesitation, or success after trial and error (e.g., when using the key correctly after first unsuccessfully trying to insert the key with the teeth upwards) or success despite spatio-temporal abnormalities (see below), respectively. The maximum score was 10 points for each subscore and 20 points for the combined score, ToolComplete.

Following a similar error classification for pantomimed tool use (Hoeren et al. 2014), all available videotaped performances of items with ToolUse errors were carefully reviewed post hoc to characterize the errors as either movement or content (Table 1). Movement errors (ToolUseMovement) concerned orientation (e.g., hammering with the small surface of the head facing downwards), hand configuration (e.g., scissors held incorrectly), or movement (e.g., amplitude too small when using the scissors or the spanner [wrench]). Content errors (ToolUseContent), indicative of incorrect tool-action associations, included 3 subcategories (Table 1): First, unrecognizable movements bearing no resemblance to the target action (e.g., rubbing the thread with closed scissors instead of cutting) were conceived to reflect ad-hoc exploratory behavior upon the inability to access stored motor knowledge (Heilman et al. 1997). Second, a state of helpless perplexity (even after the correct recipient was pointed out by the examiner in cases of recipient selection failure) was thought to similarly result from the inability to evoke the suitable action (Ochipa et al. 1989, 1992; Hoeren et al. 2014). Third, recognizable skilled actions that did not match the tool (e.g., hammering on the bolt with the wrench) were regarded as evidence for an incorrect tool-action selection and classified as semantic errors; note, however, that no patient in our study displayed semantic errors (likely because the physical attributes of the actual tools and recipient often prevent the execution of semantically related actions, e.g., hammering with a screwdriver). Although following the original description of the test (Goldenberg and Spatt 2009), hesitant actions were awarded only one point for the calculation of the ToolUse subscore, they were not considered for the distinction between content and movement errors as they could not be assigned unequivocally to either category. Thus, while hesitation due to impaired action retrieval would be considered a content error, hesitation resulting from damaged action engrams or from difficulties with adapting the movement to the physical properties of tool and recipient would be regarded as movement error. Lastly, hesitation may sometimes reflect a state of generally reduced cognitive processing speed rather than a specific apraxic error. For further analyses, ToolUseContent and ToolUseMovement subscores were defined as the number of correct items in each category (e.g., if a patient displayed content errors during the use of 2 of 5 tools, the ToolUseContent score was 3).

Inter-rater reliability in terms of rank correlations (Kendall's τ) was good to excellent for ToolComplete and ToolSelect (τ = 0.921 for either score), ToolUse (τ = 0.888), ToolUseContent (τ = 0.869), and ToolUseMovement (τ = 0.801).

Additional Tests

Additional tests included the Corsi block tapping test for short-term and working memory (Kessels et al. 2000, 2008) and 3 paper-based neglect tests, that is, the Bells test (Gauthier et al. 1989), Albert's line cancellation test (Albert 1973), and the Ota test (Ota et al. 2001). For all tests, the center of cancellation score (CoC) (Rorden and Karnath 2010) was calculated to objectify the severity of disregard of the right hemispace (http://www.mccauslandcenter.sc.edu/CRNL/tools/cancel/). The score was considered pathological when greater than −0.086 (Suchan et al. 2012). When patients showed signs of neglect, it was ensured that they perceived all the recipients mounted on the rack, for example, by moving the rack slightly to the left or by actively directing patients’ attention to the right hemifield. Out of 136 patients, 122 completed the Token Test of the Aachen Aphasia Battery (Huber et al. 1984); out of the remaining 14 patients, 3 were non-German native speakers and 6 were unable to complete testing due to severe deficits. The remaining 5 were not tested due to various reasons including rapid discharge. For patients without Token Test, routine non-standardized logopedic assessments were reviewed.

Magnetic Resonance Imaging

For a detailed description of the number and modality of images obtained, see Supplementary Material. In sum, lesions were mapped on MRI scans obtained on average 2.6 days after symptom onset (SD 2.9, min 0 max 9 days). MRI scans were obtained on either a 3T Trio scanner or a 1.5T Avanto scanner (Siemens, Germany). For the diffusion-weighted imaging (DWI) obtained in 135/136 patients, we used a standard sequence (23 slices, matrix = 128 × 128 pixel, voxel size = 1.8 × 1.8 × 5 mm, repetition time = 3.1 s, echo time = 79 ms, flip angle = 90, 6 diffusion-encoding gradient directions with a b-factor of 1000 s/mm2). All patients additionally received FLAIR (fluid attenuated inversion recovery) images (repetition time = 9000 ms, echo time = 93.0 ms, flip angle = 140°, matrix 200 × 256 pixel, voxel size = 0.94 × 0.94 × 5.00 mm, 23 slices). As a prerequisite for spatial normalization, a high-resolution T1 anatomical scan was obtained from 129 patients (repetition time = 2200 ms, echo time = 2.15 ms, flip angle = 12°, matrix = 256 × 256 pixel, voxel size = 1 × 1 × 1 mm, 176 slices).

Lesion Analysis

Lesion analysis was performed as described previously (Hoeren et al. 2014). Briefly, lesions visible on the diffusion-weighted images were roughly delineated using a customized region-of-interest toolbox implemented in SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8) and subsequently inspected and manually adjusted using MRIcron (http://www.mccauslandcenter.sc.edu/mricro/mricron/). In one case in which no diffusion-weighted image was available, the lesion was drawn directly onto a FLAIR image.

For spatial normalization of the lesion maps, the underlying DWI scan (or FLAIR image) was coregistered to the anatomical T1 scan (n = 129). Following segmentation of the T1 images, deformation field parameters for nonlinear normalization into the stereotactic Montreal Neurological Institute (MNI) standard space were then computed using the DARTEL (diffeomorphic anatomical registration through exponentiated lie algebra; Ashburner 2007) approach implemented in the VBM8 toolbox (r435; http://dbm.neuro.uni-jena.de/vbm/download/). When T1 scans were unavailable, parameters for normalization were obtained using FLAIR images (n = 7) which proved sufficiently detailed for the calculation of deformation field parameters. Normalization quality of lesion maps was visually checked by MH.

Voxel-based lesion-symptom (VLSM) analyses were calculated using the nonparametric statistics implemented in MRIcron (version 12/12/2012) (Rorden et al. 2007). We performed the Brunner–Munzel test, a rank test for continuous behavioral variables and binary images to identify lesioned voxels associated with deficits in specific tests. The resulting maps display voxels with a significant difference in the distribution of the behavioral measure depending on whether the voxel was lesioned. Only voxels affected in at least 7 patients (5% of patients) were analyzed.

Separate Brunner–Munzel analyses were performed for the overall score (ToolComplete) and each of the different subscores. To single out regions specifically associated with ToolUse versus ToolSelect deficits, and ToolUseContent versus ToolUseMovement deficits, we employed the same strategy as previously (Hoeren et al. 2014). First, separate logistic regression analyses were computed for these 2 subscore pairs using 1 score as predictor variable and the other score as covariate and vice versa. This approach allows for the analysis of the variance in 1 score while controlling for the variance in another score. Secondly, for a more direct exploration in which voxels damage predicts a significant difference between subscores, Brunner–Munzel analyses were performed using the score differences ToolUse-ToolSelect and ToolUseContent-ToolUseMovement and vice versa, respectively. Given the differences in the distribution of ToolSelect and ToolUse scores (see results), differences were calculated after transforming the different scores to z-scores. Lastly, to account for a possible effect of the infarct size, separate logistic regression analyses were performed for each subscore using lesion volume as a covariate. As ToolUse impairments may possibly occur secondary to a general loss of object knowledge (as indicated by recipient selection deficits), the VLSM analysis for ToolUse was repeated across the subgroup of patients with intact ToolSelect.

In line with previous studies (Goldenberg 2009), we report results below a false discovery rate (FDR) corrected statistical threshold of P = 0.05; 1 exception was made for the results of the analyses exploring regions differentially involved in ToolSelect versus ToolUse which were additionally shown at P < 0.05 uncorrected to further assess the lack of regions specifically associated with ToolUse (see Fig. 4 and Discussion). For each statistical results map, we expressed the lesion volume within each region of the Automatic Anatomical Labelling (AAL) atlas (Tzourio-Mazoyer et al. 2002) as a percentage of the total volume of the significant voxels within the results map, and as a percentage of the AAL region. Volumes were determined with MRIcron.

Moreover, to further explore regions with specific relevance to ToolSelect or TooUse, the lesions of the patients with dissociations (and, for completeness, associations) between these scores were created.

Results are displayed on an in-house average template of 50 nonlinearly normalized T1 scans from a sample of healthy subjects who had participated in other studies in our lab (age, mean ± SD 47 ± 20.75, range 22–84 years; 25 male).

Results

Demographic and Behavioral Results

Demographic and behavioral data of the included patients are given in Table 2. Only 4 patients were diagnosed with neglect at the time of testing for apraxia.

Table 2

Demographic data and general clinical scores

 Mean SD Min Max 
Age (years) 65 15 36 85 
Sex (female/male) 53/83 
Infarct volume (mL) 26.5 35.0 0.3 244.9 
NIHSS on admission 7.4 6.1 24 
NIHSS on discharge 2.8 4.1 15 
Right arm motor NIHSS on testing 0.6 1.2 
mRS on discharge 2.0 1.2 
Barthel index on discharge 82.9 28.2 −25 100 
Thrombolysis (none/iv/bridging or mechanical) 75/45/16 
Apraxia test scores 
 ToolComplete 17.4 4.3 20 
 ToolSelect 8.2 2.8 10 
 ToolUse 9.2 1.7 10 
 ToolUseContenta 4.8 0.7 
 ToolUseMovementa 4.8 0.5 
Other test scores 
 Corsi span forward 4.7 1.1 
 Corsi span backwards 4.5 1.5 
 Token test percentile rankb 79.8 30.5 99 
 Aphasia (yes/no)c 69/67 
 Mean SD Min Max 
Age (years) 65 15 36 85 
Sex (female/male) 53/83 
Infarct volume (mL) 26.5 35.0 0.3 244.9 
NIHSS on admission 7.4 6.1 24 
NIHSS on discharge 2.8 4.1 15 
Right arm motor NIHSS on testing 0.6 1.2 
mRS on discharge 2.0 1.2 
Barthel index on discharge 82.9 28.2 −25 100 
Thrombolysis (none/iv/bridging or mechanical) 75/45/16 
Apraxia test scores 
 ToolComplete 17.4 4.3 20 
 ToolSelect 8.2 2.8 10 
 ToolUse 9.2 1.7 10 
 ToolUseContenta 4.8 0.7 
 ToolUseMovementa 4.8 0.5 
Other test scores 
 Corsi span forward 4.7 1.1 
 Corsi span backwards 4.5 1.5 
 Token test percentile rankb 79.8 30.5 99 
 Aphasia (yes/no)c 69/67 

Note: an = 134 of 136 patients.

bn = 122 of 136 patients (see Materials and Methods for details). ToolComplete, overall score for use of common tools (max. 20 points); ToolSelect and ToolUse, subscores for selecting the matching recipient and executing the action, respectively (max. 10 points each); ToolUseContent and ToolUseMovement, subscores for content and movement errors during the execution of the tool-associated action (max. 5 points each).

cAccording to non-standardized logopedic assessment as documented in patient files. mRs, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale.

Use of Common Tools

See Table 3 for a detailed overview of the numbers of patients with errors. ToolSelect scores were significantly lower compared with ToolUse scores (Wilcoxon Signed-Rank test, P < 0.001, see Table 2). Out of patients with deficits, 21 had combined ToolSelect and ToolUse deficits, 15 and 4 had isolated ToolSelect and ToolUse deficits, respectively. Dissociations with impaired ToolSelect and preserved ToolUse tended to be more pronounced with 9/15 patients scoring markedly below cutoff in ToolSelect (<6/10), while the reverse dissociations were less distinctive with all 4 patients' ToolUse scores just below the normal range (scores = 8/10).

Table 3

Number of patients with errors

Score Cutoff scores N assessed N with errors N below cutoff 
ToolSelect 8/10 136 60 (47/13) 36 (34/2) 
ToolUse 9/10 136 34 (26/8) 25 (23/2) 
 ToolUseContent 5/5 134 14 (14/0) 14 (14/0) 
  Semantic    
  Unrecognizable   13 (13/0)  
  Perplexity   2 (2/0)  
 ToolUseMovement 4/5 134 18 (12/6) 9 (7/2) 
  Configuration   1 (1/0)  
  Orientation   8 (5/3)  
  Movement   13 (10/3)  
ToolComplete 18/20 136 61 (47/14) 40 (36/4) 
Score Cutoff scores N assessed N with errors N below cutoff 
ToolSelect 8/10 136 60 (47/13) 36 (34/2) 
ToolUse 9/10 136 34 (26/8) 25 (23/2) 
 ToolUseContent 5/5 134 14 (14/0) 14 (14/0) 
  Semantic    
  Unrecognizable   13 (13/0)  
  Perplexity   2 (2/0)  
 ToolUseMovement 4/5 134 18 (12/6) 9 (7/2) 
  Configuration   1 (1/0)  
  Orientation   8 (5/3)  
  Movement   13 (10/3)  
ToolComplete 18/20 136 61 (47/14) 40 (36/4) 

Note: In parentheses, number of aphasic/non-aphasic patients.

For all patients with at least 1 ToolUse error for whom videos were available (33/35), ToolUse errors were further classified as either movement or content (see Materials and Methods). Out of these, 6 patients displayed both movement and content errors; 8 and 12 had only content or movement errors, respectively. In 11 patients who performed 1 or 2 movements only hesitatingly, errors could not be classified as movement or content.

For correlations between scores, see Table 4.

Table 4

Rank correlations between test scores (Kendall's τ)

 ToolComplete ToolSelect ToolUse ToolUseContent ToolUseMovement 
ToolComplete 0.945** 0.713** 0.518** 0.443** 
ToolSelect 0.945** 0.627** 0.487** 0.354** 
ToolUse 0.713** 0.627** 0.679** 0.668** 
ToolUseContent 0.518** 0.487** 0.679** 0.287** 
ToolUseMovement 0.443** 0.354** 0.668** 0.287** 
 ToolComplete ToolSelect ToolUse ToolUseContent ToolUseMovement 
ToolComplete 0.945** 0.713** 0.518** 0.443** 
ToolSelect 0.945** 0.627** 0.487** 0.354** 
ToolUse 0.713** 0.627** 0.679** 0.668** 
ToolUseContent 0.518** 0.487** 0.679** 0.287** 
ToolUseMovement 0.443** 0.354** 0.668** 0.287** 

Note: **P < 0.01.

Correlations with Clinical and Demographic Data

See Table 5 for rank correlations between test performances and possible confounding factors. On the whole, there were weak to moderate correlations of test scores with infarct volume, measures of global impairment (e.g., modified Rankin scale [mRS] and National Institutes of Health Stroke Scale [NIHSS] scores) as well as working memory and language scores. There were no sex differences for tool use scores (Mann-–Whitney U tests, P > 0.61).

Table 5

Rank correlations between test scores, and demographic and clinical data (Kendall's τ)

 ToolComplete ToolSelect ToolUse ToolUseContent ToolUseMovement 
Infarct volume −0.478** −0.479** −0.393** −0.282** −0.252** 
Age −0.110 −0.117 −0.072 −0.023 −0.123 
NIHSS on admission −0.373** −0.397** −0.193** −0.193** −0.102 
NIHSS on discharge −0.375** −0.386** −0.303** −0.265** −0.180* 
mRS on discharge −0.406** −0.396** −0.357** −0.295** −0.229** 
Barthel score on discharge 0.448** 0.436** 0.378** 0.341** 0.260** 
Right arm motor NIHSS −0.293** −0.274** −0.286** −0.288** −0.213** 
Token Test percentile rank 0.521** 0.542** 0.372** 0.385** 0.162* 
Corsi span forward 0.307** 0.328** 0.181* 0.231** 0.097 
Corsi span backwards 0.288** 0.284** 0.248** 0.163* 0.221** 
 ToolComplete ToolSelect ToolUse ToolUseContent ToolUseMovement 
Infarct volume −0.478** −0.479** −0.393** −0.282** −0.252** 
Age −0.110 −0.117 −0.072 −0.023 −0.123 
NIHSS on admission −0.373** −0.397** −0.193** −0.193** −0.102 
NIHSS on discharge −0.375** −0.386** −0.303** −0.265** −0.180* 
mRS on discharge −0.406** −0.396** −0.357** −0.295** −0.229** 
Barthel score on discharge 0.448** 0.436** 0.378** 0.341** 0.260** 
Right arm motor NIHSS −0.293** −0.274** −0.286** −0.288** −0.213** 
Token Test percentile rank 0.521** 0.542** 0.372** 0.385** 0.162* 
Corsi span forward 0.307** 0.328** 0.181* 0.231** 0.097 
Corsi span backwards 0.288** 0.284** 0.248** 0.163* 0.221** 

Note: mRs, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale.

*P < 0.05.

**P < 0.01.

Compared with ToolUseMovement, ToolUseContent scores were more strongly correlated with ToolSelect scores (Table 4), worse NIHSS scores on admission (Table 5), as well as lower Token Test percentile ranks. Conversely, the correlations with infarct volume seemed comparable. Testing the groups of patients with only content errors (n = 8) versus patients with only movement errors (n = 12) revealed no significant differences with respect to infarct size (Mann–Whitney U tests, P = 0.270) or measures of global impairment (NIHSS scores, mRS, Barthel scores, P > 0.427); however, patients with only content errors scored lower on ToolSelect (P = 0.003, 2.75 ± 1.91 vs. 7.17 ± 2.82), on ToolUse (P = 0.001, 5.38 ± 2.88 vs. 8.33 ± 0.49), and on the Token Test (P = 0.020, percentile 25.83 ± 33.37 vs. 74.91 ± 39.16). These results indicate, first, that content errors compared with movement errors during action execution are more closely related to recipient selection errors and aphasic deficits. Second, the distinction between content and movement errors cannot simply be explained by larger lesions or larger overall impairment. Third, content errors had a more detrimental effect on the overall performance of tool-associated actions than movement errors.

With respect to dissociations between tool use and language deficits, there were 2 patients each with ToolUse (Patient 1: 2 orientation errors; Patient 2: 2 errors of the movement dynamics) and ToolSelect deficits without aphasia, and 33 patients with aphasia without any tool use deficit (see Supplementary Fig. 2 for lesion overlap images).

Patients who used the left hand (n = 47) scored significantly worse compared with right-hand users (n = 89) for ToolSelect (Mann–Whitney U tests, P = 0.001; mean scores ± SD, 6.8 ± 3.3 vs. 8.9 ± 2.3) and ToolUse (P = 0.045; 8.6 ± 2.5 vs. 9.6 ± 1.0), but not for ToolUseContent (P = 0.268) and ToolUseMovement (P = 0.086). Patients who used the left hand had more extensive infarcts (P = 0.046) and were more impaired with respect to right upper extremity motor function (P < 0.001), as well as overall (P < 0.001 for NIHSS on admission and discharge, and mRS on discharge). In accordance with previous work (Hoeren et al. 2014), these results suggest that left hand use due to a motor deficit of the right hand was not a source of errors per se, but rather an indicator of greater overall disability and lesion size that was, in turn, also associated with lower performance.

Lesion Analysis

Lesion Distribution

Figure 1 shows the overlap of the binary normalized lesions maps. The maximum lesion overlap (40/136) localized to single voxels within the insula cortex, lateral basal ganglia, and periventricular caudate nucleus. Lesion density within inferior frontal and parietal regions was similar. One hundred and six patients had strokes involving cortical areas; 30 lesions affected subcortical structures only (mainly striatocapsular infarcts). The distribution of the lesion sizes is shown in Figure 2. The large range of lesion sizes resulted from the inclusion of consecutive patients without a predefined volume threshold.

Figure 1.

Overlap of the binarized lesions of the 136 patients included in the analysis. The color bar indicates the degree of overlap of lesions, for example, bright yellow values indicate that in 40 out of 136 subjects, tissue was affected by stroke.

Figure 1.

Overlap of the binarized lesions of the 136 patients included in the analysis. The color bar indicates the degree of overlap of lesions, for example, bright yellow values indicate that in 40 out of 136 subjects, tissue was affected by stroke.

Figure 2.

Lesion sizes of the 136 patients included in the study.

Figure 2.

Lesion sizes of the 136 patients included in the study.

Tool Use Deficits

Overall tool use deficits (ToolComplete) were mainly associated with lesions to the inferior parietal and temporal lobes, with additional involvement of subcortical, frontal, and occipital regions (Fig. 3 and see Supplementary Table 1). Nearly the same pattern was observed for the recipient selection (ToolSelect); the confirmatory analysis with ToolSelect scores after removing the distinction between “trial and error” and complete selection failure gave virtually identical results (not shown). In contrast, the extent of damage associated with errors during the application of the tool (ToolUse) was markedly smaller for frontal and temporal lobes.

Figure 3.

Results for tool use. VLSM maps for the combined score (ToolComplete, A), as well as subscores for the matching of tools to their typical recipients (ToolSelect, B), and for the application of tool (ToolUse, C). Color bars indicate z-scores. Reported results are thresholded at P < 0.05, FDR corrected (red to yellow scale); the z-scores corresponding to this threshold are indicated on the color bars. Voxels not surviving this threshold are not shown.

Figure 3.

Results for tool use. VLSM maps for the combined score (ToolComplete, A), as well as subscores for the matching of tools to their typical recipients (ToolSelect, B), and for the application of tool (ToolUse, C). Color bars indicate z-scores. Reported results are thresholded at P < 0.05, FDR corrected (red to yellow scale); the z-scores corresponding to this threshold are indicated on the color bars. Voxels not surviving this threshold are not shown.

The logistic regression for ToolSelect with ToolUse as covariate, as well as the voxel-wise Brunner–Munzel analysis using the difference between the z-transformed scores of ToolSelect and ToolUse further highlighted the specific importance of the anterior parts of middle and superior temporal gyri, the region around the posterior middle temporal gyrus (pMTG), anterior IFG, anterior insula cortex, and subcortical regions including extreme capsule and uncinated fascicle for ToolSelect (Fig. 4 and see Supplementary Table 2). In addition to these ventral stream regions, significant voxels were detected within the caudal middle frontal gyrus/inferior frontal junction zone. No regions were found to be significantly associated with ToolUse versus ToolSelect deficits at an FDR corrected threshold of P < 0.05. At a threshold of P < 0.05 uncorrected, a possible specific role of mainly the IPL and IPS emerged. At this lower threshold, the results of the VLSM analysis for ToolUse across the subgroup of patients with intact ToolSelect performances also indicated that posterior parietal lesions (mainly SMG, IPS, and SPL) may lead to ToolUse deficits independent of recipient selection deficits (Fig. 4E).

Figure 4.

Areas specifically associated with recipient selection (ToolSelect) deficits. VLSM maps for the regression analysis for ToolSelect scores with ToolUse scores as covariate and vice versa (A,B), and for the Brunner–Munzel analysis with the subscore difference ToolSelect-ToolUse (C) and ToolUse-ToolSelect (D). Color bars indicate z-scores. Reported results are thresholded at P < 0.05, FDR corrected (red to yellow scale); the z-scores corresponding to this threshold are indicated on the color bars. In addition, to explore potential subthreshold effects, voxels not meeting this criterion but surviving the less stringent threshold of P < 0.05 uncorrected are shown in blue.

Figure 4.

Areas specifically associated with recipient selection (ToolSelect) deficits. VLSM maps for the regression analysis for ToolSelect scores with ToolUse scores as covariate and vice versa (A,B), and for the Brunner–Munzel analysis with the subscore difference ToolSelect-ToolUse (C) and ToolUse-ToolSelect (D). Color bars indicate z-scores. Reported results are thresholded at P < 0.05, FDR corrected (red to yellow scale); the z-scores corresponding to this threshold are indicated on the color bars. In addition, to explore potential subthreshold effects, voxels not meeting this criterion but surviving the less stringent threshold of P < 0.05 uncorrected are shown in blue.

According to the subscore analyses for ToolUseContent and ToolUseMovement (Fig. 5 and see Supplementary Tables 3 and 4), content errors were mainly associated with damage to the lower half of the supramarginal gyrus (SMG) and to the superior temporal gyrus. In contrast, movement errors arose from lesions within mainly the anterior lateral bank of the intraparietal sulcus. These differences were even more pronounced in the logistic regression analyses using 1 score as covariate. The Brunner–Munzel analyses using score differences between ToolUseContent and ToolUseMovement, as well as the analyses with distinct error types (e.g., configuration errors alone) yielded no significant results.

Figure 5.

Areas associated with content and movement errors. VLSM maps for the Brunner–Munzel analyses with movement (A) and content (B) scores alone, and for the regression analyses for each score using the other score as covariate (C, red–yellow and blue–green: areas specifically related to movement and content errors, respectively). Color bars indicate z-scores. Reported results are thresholded at P < 0.05, FDR corrected; the z-scores corresponding to this threshold are indicated on the color bars. Voxels not surviving this threshold are not shown.

Figure 5.

Areas associated with content and movement errors. VLSM maps for the Brunner–Munzel analyses with movement (A) and content (B) scores alone, and for the regression analyses for each score using the other score as covariate (C, red–yellow and blue–green: areas specifically related to movement and content errors, respectively). Color bars indicate z-scores. Reported results are thresholded at P < 0.05, FDR corrected; the z-scores corresponding to this threshold are indicated on the color bars. Voxels not surviving this threshold are not shown.

The lesion overlaps of patients with different combinations of ToolSelect and ToolUse deficits (Fig. 6) largely confirmed the results of the VLSM analyses.

Figure 6.

Overlap of the lesions of patients with isolated ToolUse (A) or ToolSelect (B) deficits, combined ToolSelect and ToolUse impairments (C), and patients without tool use deficits (D).

Figure 6.

Overlap of the lesions of patients with isolated ToolUse (A) or ToolSelect (B) deficits, combined ToolSelect and ToolUse impairments (C), and patients without tool use deficits (D).

Lastly, given that the probability of damage to a task-relevant region increases with lesion volume, and, thus, lesion volume is significantly correlated with behavioral performance (Table 5), no significant results were found in the logistic regression analyses with lesion size as a covariate. This negative finding is in line with previous studies where either the results also did not survive the correction for lesion size (Kümmerer et al. 2013; Hoeren et al. 2014), or no such analyses were reported (Goldenberg and Spatt 2009; Karnath et al. 2011; Watson and Buxbaum 2015). Thus, while lesion volume may explain a significant fraction of the behavioral variance, it cannot account for the differences between regions associated with distinct scores (Figs 4 and 5).

Discussion

Using voxel-based lesion-symptom mapping, we aimed to clarify the involvement of dorsal and ventral streams in conceptual and production-related components of tool-associated actions as defined by Heilman, Ochipa, and others (Ochipa et al. 1992; Heilman et al. 1997). Accordingly, impairments affecting tool-recipient relationships (e.g., choosing the nail when handed a hammer; ToolSelect) and errors reflecting impaired tool-action associations (content errors during action performance, e.g., helpless perplexity resulting from an inability to retrieve the suitable action) were regarded as indicators of damage to the conceptual system. Conversely, spatio-temporal errors during action performance were aligned with a dysfunction of the production component (see Table 1 for an overview of the scores obtained).

Using advanced neuroimaging methods that have become available only fairly recently, our study extends efforts to map neuropsychological concepts developed largely on the basis of behavioral examinations onto the functional anatomy of the brain, in particular in relation to different ventral and dorsal streams (Daprati and Sirigu 2006; Buxbaum and Kalénine 2010; Hoeren et al. 2014). Our aim was, therefore, not to modify or replace cognitive models of apraxia (Rothi et al. 1991; Heilman et al. 1997), but rather to use these models as valuable guidance for the further anatomical refinement of the concept that distinct cognitive motor functions rely on different ventral and dorsal processing streams.

To our knowledge, we here report the largest cohort of stroke patients with systematic and reliable assessments of the ability to use actual tools. Moreover, also for the first time, we provide data on actual tool use from patients examined in the acute period after stroke. In contrast to the majority of lesion studies that were conducted with stroke patients in the chronic phase (Goldenberg and Spatt 2009; Buxbaum et al. 2014), investigations with acute stroke patients offer a set of methodological particularities (Hoeren et al. 2014). Thus, in the acute phase, the effect of some lesions may be overestimated due to a temporary dysfunction of regions connected to the damaged areas (diaschisis) (von Monakow 1985; Saur et al. 2006; Kümmerer et al. 2013; Weiller, Vry et al. 2015). However, as these effects are likely confined to a network of functionally related areas (Price et al. 2001), the detection of areas unrelated to the task is unlikely. Moreover, patients' performances are less likely to be stable and more susceptible to unspecific effects of fatigue or impaired attention (Hoeren et al. 2014). Conversely, examining patients in the acute phase offers 2 in our view highly relevant advantages. First, the effects of compensatory brain reorganization that may obscure relationships between lesions and functional deficits in the chronic phase can be minimized; thus, the results obtained in the acute phase may better reflect the networks active in healthy brains. Secondly, especially when MR images are used, the lesions can be more accurately delineated as unlike in the chronic phase, the structural anatomy is not yet as much altered by distortions ensuing tissue loss (e.g., enlargement of the ventricles after subcortical ischemia, see Supplementary Fig. 1 for more examples).

Our study has a similar design as a previous study by Goldenberg and Spatt (2009), but somewhat divergent results. In contrast to the previous study, we demonstrated a specific importance of ventral stream regions for tool-recipient associations (ToolSelect, Fig. 4) as well as a dissociation of lesion locations related to content and movement errors during the actual performance of tool actions (Fig. 5). In the previous study (Goldenberg and Spatt 2009), no clear differences between regions associated with ToolSelect and ToolUse were detected, and errors during ToolUse were not further classified. The differences may mainly be due to methodological reasons. Our study included a larger number of patients (136 vs. 38), the stroke etiology was homogeneous (only ischemic vs. mixed ischemic and hemorrhagic), and all patients were examined within the first 10 days post stroke (vs. within 3–100 weeks post stroke). Moreover, we used only MRI for lesion delineation and performed the statistical analyses with an updated version of the nonparametric mapping software for voxel-wise Brunner–Munzel testing that does not produce inflated z-scores in rarely affected voxels (Medina et al. 2010). A further interesting difference was that in the previous study by Goldenberg and Spatt (2009), all patients were aphasic, whereas presently, 4 patients with deficits in the tool task were not aphasic (see Supplementary Fig. 2). Aphasia without tool use deficits (n = 33) was associated with frontal and posterior superior temporal lesions. Conversely, selective ToolUse (n = 2) and ToolSelect (n = 2) deficits were associated with lesions to the SMG and the frontal lobe, respectively. Our data do not allow for a further in-depth discussion of this highly interesting topic, a more detailed analysis of regions differentially relevant for aphasia and tool use should be targeted in future studies (see also Mengotti et al. 2013; Weiss et al. 2014; Goldenberg and Randerath 2015).

The Ventro-Dorsal Stream Is Involved in Both Recipient Selection and Action Execution

The involvement of mainly ventro-dorsal stream areas in ToolUse (Figs 3 and 6) is in accordance with proposals suggesting that the typical use of common tools relies on stored motor programs acquired by experience (see, Binkofski and Buxbaum 2013 for review). In particular, the IPL may be crucial for maintaining “visuokinesthetic engrams” specifying the invariant spatio-temporal features of skilled movements that facilitate the performance of learned actions (Heilman et al. 1982; synonymously used terms include motor or movement engram, stored action representation and action blueprint, Rijntjes et al. 1999; Buxbaum et al. 2007; Vingerhoets 2008; Vingerhoets et al. 2009; Buxbaum and Kalénine 2010; Mengotti et al. 2013; Brandi et al. 2014; Niessen et al. 2014; van Elk et al. 2014a; 2014b). Together with other sources that provide information on actions not pertaining to the motor repertoire (e.g., visual memories) (Calvo-Merino et al. 2006), the sensorimotor engrams are also thought to contribute to more abstract knowledge of how objects are manipulated (manipulation knowledge), needed, for example, for sorting objects according to their mode of use (Boronat et al. 2005; Canessa et al. 2008; Chen et al. 2015). Alternatively, the IPL may support tool use by mechanical problem solving (Osiurak et al. 2011; Goldenberg 2014), by providing mechanical knowledge about, for example, gravity or lever (Goldenberg 2013; Osiurak and Lesourd 2014), or by maintaining spatial relations between body parts, tools, and objects (Goldenberg 2009). The markedly weaker association of dorso-dorsal stream lesions with ToolUse deficits may partly be due to the less extensive lesion coverage within dPMC and SPL (n = 10, see Fig. 1) compared with the IPL, which may have decreased the power for detecting a significant association. However, as SPL lesions were strongly associated with impaired imitation of meaningless gestures in a recent study with a similar dorso-dorsal lesion density (Hoeren et al. 2014), the limited involvement of SPL and dPMC may rather be in accordance with the view that routine use of common tools and objects largely relies on stored action representations as these provide an advantage over alternative strategies like mechanical reasoning and reduce the need for online feedback-driven control mechanisms (Hermsdörfer et al. 2013; Hermsdörfer 2014).

However, contrary to our expectation that ventro-dorsal lesions would impact ToolUse more than ToolSelect, ventro-dorsal lesions on the whole affected both subscores equally (Figs 3 and 6). Our hypothesis had been based on studies on patients with corticobasal degeneration (Hodges et al. 1999) and fronto-parietal strokes (Buxbaum, Veramonti et al. 2000; Buxbaum and Saffran 2002; Garcea et al. 2013) as well as on investigations on healthy subjects with virtual IPL lesions caused by TMS (Ishibashi et al. 2011) that described impaired tool manipulation knowledge despite relatively preserved performance in various other semantic tool tasks (i.e., matching tools to recipients and typical locations Hodges et al. 1999 or associating functionally or contextually similar tools, Buxbaum, Veramonti et al. 2000; Buxbaum and Saffran 2002; Ishibashi et al. 2011; Garcea et al. 2013). Consistently, fMRI studies requiring subjects to match tools according to their manipulation (e.g., typewriter and piano) or their function (e.g., vacuum cleaner and carpet beater) demonstrated higher activation within the posterior parietal lobule during the manipulation compared with the function condition (Kellenbach et al. 2003; Boronat et al. 2005; Canessa et al. 2008; Chen et al. 2015).

The absence of a stronger association between ventro-dorsal damage and ToolUse may be explained by weaker demands of ToolUse or, alternatively, by an increased reliance of ToolSelect on the ventro-dorsal stream compared with the tasks employed in these previous studies. In line with the first possibility, patients' performance of actual tool use is more robust than other tests involving tool-associated actions (Hermsdörfer et al. 2013; Baumard et al. 2014) as the visual and tactile cues provided by the tool facilitate the retrieval of the appropriate action (Hermsdörfer et al. 2006) and reduce the dependence on stored motor programs by allowing inferences on the tool's use based on its structural properties (Buxbaum, Johnson-Frey et al. 2005). Consequently, the ToolUse condition may have been relatively insensitive for the detection of more subtle tool manipulation deficits, and, therefore, our study may have been underpowered for the detection of areas more important for tool manipulation compared with recipient selection. This view was corroborated by re-examining the results of the analyses aimed at finding regions differentially involved in ToolUse versus ToolSelect at a lowered threshold of P < 0.05 uncorrected (Fig. 4), by performing a VLSM analysis for ToolUse only across the patients with intact ToolSelect performances (Fig. 4E), and by overlapping the lesions of the 4 patients with isolated ToolUse deficits (Fig. 6A). In line with our original hypothesis, these additional results indicated that a specific role of the IPL, as well as the IPS and SPL (i.e., the putative ventro-dorsal and dorso-dorsal correlates for action engrams and on-line motor control, respectively) for ToolUse may emerge more clearly if the number of patients with lesions in these regions was raised (Kimberg et al. 2007) or if a more sensitive test for ToolUse deficits was employed.

On the other hand, the recipient selection task used in our study may have drawn on stored action representations to a greater extent compared with other tasks for conceptual tool knowledge. Thus, for several tools, the appropriate recipient could not be identified based on contextual or functional knowledge. For example, possible recipients for the hammer included a nail, a screw, and a bolt. As these objects are all used in similar settings and are all driven into a piece of wood or a wall, decision-making may have required knowing that they differ in the manner they are operated on (e.g., only a nail is hammered upon). In addition, the marked impact of IPL lesions on ToolSelect may have resulted from a greater susceptibility to disrupted executive control processes compared with ToolUse. In particular, lesions to the angular gyrus and intraparietal sulcus regions (areas adjacent and therefore frequently co-affected with manipulation-specific regions like the SMG) may have caused difficulties with coordinating the selection and retrieval of task-relevant content from semantic memory (Noonan et al. 2013, e.g., in the example above, evoking knowledge about the manipulation and not about the typical context of use).

Importantly, an (although weaker) involvement of the ventro-dorsal stream was evident in tasks probing functional or contextual knowledge even in functional imaging studies that highlighted the relatively greater importance of these regions for manipulation knowledge (Kellenbach et al. 2003; Boronat et al. 2005; Canessa et al. 2008). These results are consistent with data demonstrating that tool knowledge processed within the dorsal stream informs categorical decisions about tools (Almeida et al. 2008) particular during explicit semantic processing (Noppeney et al. 2006), and that manipulation knowledge modulates object recognition (Helbig et al. 2006; Mahon et al. 2007; Campanella and Shallice 2011; Yee et al. 2013; Sim et al. 2014). Together with these studies, our results suggest that sensorimotor action representations stored within the ventro-dorsal stream may be a relevant constituent of object concepts for tools, possibly as tools are largely defined by their mode of use rather than perceptual features like color shape or texture (Warrington and Shallice 1984; Chao et al. 1999; Chao and Martin 2000; Noppeney et al. 2006; Mahon et al. 2007; see also Mahon and Caramazza 2008 for a more detailed discussion). However, tool concepts may require only a relatively gross representation of the action typically performed with the tool, whereas tasks specifically probing manipulation knowledge may often necessitate the retrieval of more detailed spatio-temporal movement characteristics and, therefore, may be relatively more susceptible to ventro-dorsal lesions. As suggested previously (Garcea et al. 2013), further research is needed to elucidate whether the dissociations between manipulation and other types of tool knowledge described in single cases (Buxbaum, Veramonti et al. 2000; Garcea et al. 2013) can be generalized across different tasks (Noppeney et al. 2006) and to larger cohorts of patients with circumscript brain lesions, or, as may be suggested by our results, occur only in a rare subset of patients.

The Ventral Stream Is More Important for Recipient Selection than Action Execution

The greater association of ToolSelect compared with ToolUse deficits with lesions affecting ATL, pMTG, anterior IFG, as well as fiber connections toward the anterior and inferior IFG along extreme capsule and uncinated fascicle confirms the specific importance of the ventral stream for conceptual components of tool use (Fig. 4 and see Supplementary Table S2). Underscored by the considerable number of patients with (near-) flawless ToolUse performance despite markedly impaired recipient selection (Fig. 6), the results show that the behavioral pattern of selectively impaired conceptual tool knowledge despite a relatively spared ability to manipulate tools can be observed not only in single cases with temporal damage (Sirigu et al. 1991; Negri et al. 2007), but that this finding is statistically significant across a large sample of stroke patients.

The association between ATL damage and recipient selection deficits is in accord with the selective disturbance of function relative to manipulation knowledge after transcranial magnetic stimulation to this region (Ishibashi et al. 2011) and with the specific activation observed in the ATL during an fMRI task involving tool function knowledge (Canessa et al. 2008). The relevance of ATL lesions supports the hypothesis that conceptual tool knowledge, like other types of semantic knowledge, relies on the ATL as a “hub” connecting different types of modality-specific information to form transmodal object representations (Patterson et al. 2007; Lambon Ralph 2014; van Elk et al. 2014a).

The pMTG region may be dedicated specifically to tool-related semantic processing (Chao et al. 1999; Mahon et al. 2007; Martin et al. 2014), as the left pMTG was associated with integrating semantic knowledge with movement representations (Willems et al. 2009; Kalénine et al. 2010) and with the naming of manipulable versus non-manipulable objects (Brambati et al. 2006; Campanella et al. 2010). Alternatively, the impact of lesions to pMTG, as well as to caudal MFG, anterior IFG and fibers connecting the IFG to temporal and parietal regions (i.e., uncinate fascicle and extreme capsule) may have resulted from disrupted semantic control processes (Noonan et al. 2013). Supporting the latter view, these areas were shown to be involved in semantic decision-making (Noonan et al. 2013), access to semantic representations (Badre et al. 2005; Badre and Wagner 2007) as well as conflict resolution and task switching (Derrfuss et al. 2005).

Partial Dissociation of Lesion Locations Associated with Movement and Content Errors

The partial overlap of the voxels associated with movement and content errors within the middle SMG suggests that both error types may be caused by different extents of damage to the action engram; however, the additional more dorsally and ventrally situated areas exclusively associated with movement and content errors, respectively, point to the existence of further dissociable mechanisms specifically related to either error category (Fig. 5). Our findings complement our recent report on pantomimed tool use where a specific lesion site was found only for content, but not movement errors (Hoeren et al. 2014). Possibly, movement errors can be more reliably assessed during tool use compared with pantomime where movement errors could quite frequently be observed even in healthy subjects (Hoeren et al. 2014).

Neuropsychological considerations as well as the observed lesions locations are consistent with 3 possibly sometimes coexisting causes for movement errors. First, damage to action engrams likely stored within the more anterior part of the IPL (Binkofski and Buxbaum 2013; Orban and Caruana 2014) may have affected particularly those action aspects that cannot be readily deduced from the physical properties of the tools and objects, for example, the orientation of the hammer head. Secondly, movement errors may have resulted from deficits affecting mechanisms necessary to implement movement engrams according to the variable physical constraints provided by the actual tools and objects, such as the ability to adapt the grasp to the shape of the tool's handle (Brandi et al. 2014; Hoeren et al. 2014). Affected regions linked to structure-dependent movement aspects include aIP and other intraparietal sulcus regions, as well as SPL (for review, see, Binkofski and Buxbaum 2013; Orban and Caruana 2014). Third, given that the cluster of significant voxels (Fig. 5A) extended into the subcortical white matter (i.e., into the SLF), a disconnection of parietal action representations with the frontal motor areas may have impaired the programming of the movements (Heilman et al. 1982; Garcea and Mahon 2014).

Conversely, content errors may have been caused by more severe damage to the motor engram or, alternatively, by an impairment of the ability to retrieve and select between different actions. Consistent with the first hypothesis, the extent of significant voxels within the lower SMG (i.e., around the area considered specific to human tool use by Peeters et al. 2009) was considerably higher for content compared with movement errors, encompassing 60% versus 9%, respectively, of the SMG as defined in the AAL atlas (approximately the ventral two-thirds of the anterior inferior parietal lobe between the sylvian fissure and the intraparietal sulcus) (see Supplementary Table 3). Of note, this difference cannot be explained by an overall larger lesion size for content errors, as even though a statistically nonsignificant tendency for a greater lesion extent was observed for patients with only content errors (n = 8) in comparison to patients with only movement errors (n = 12), the ranges of lesion sizes largely overlapped (57.5 ± 32.9 vs. 40.0 ± 23.4 cc, Mann–Whitney U test, P = 0.270; see Results). Retrieval deficits, on the other hand, may have resulted from severed fronto-parietal association tracts such as the EmC (Vry et al. 2012, 2015; Hoeren et al. 2013). Alternatively, damage affecting temporo-parietal connections (Zhong and Rockland 2003) or ventral or ventro-dorsal areas itself may have prevented the successful integration of object knowledge processed in the ventral stream with action representations largely stored within the ventro-dorsal stream (Buxbaum 2001; Buxbaum, Kyle et al. 2005; Milner and Goodale 2008; Almeida et al. 2013; Garcea and Mahon 2014).

Limitations

Given the lack of appropriate tests, we cannot with certainty exclude that ToolSelect impairments associated with ventral stream lesions (Figs 3 and 4) were caused by an isolated deficit of tool-related semantic knowledge or object agnosia. However, as outlined above, the well-documented role of the anterior temporal lobe as well as IFG and pMTG in domain-general semantic processing (Rijntjes et al. 2012; Lambon Ralph 2014) makes a general semantic deficit that extends to tool knowledge a likely explanation. Thus, contrary to divergent proposals (Martin et al. 2014), our results corroborate that similarly to other semantic categories, tool- and action-related semantic knowledge relies on the ATL (van Elk et al. 2014a). Conversely, as the common tools and objects are easily recognizable and, moreover, the regions critical for the higher order visual processing of shapes and textures (e.g., bilateral LOC and V3A [Cavina-Pratesi et al. 2010; Barton 2011]), or object categories (e.g., fusiform gyrus; Chao et al. 1999; Mahon et al. 2007; Mahon et al. 2013) were not among the regions associated with deficits, a significant role of perceptual deficits seems less probable.

Moreover, it remains uncertain to what extent ToolUse performance was driven by stored action knowledge versus compensatory mechanisms for inferring potential modes of use purely from physical object attributes either by deliberate analysis (mechanical/technical reasoning; Goldenberg and Hagmann 1998; Goldenberg and Spatt 2009; Osiurak et al. 2013) or by more automatic association (affordances; Hodges et al. 2000; Orban and Caruana 2014). However, as the functional grips used to hold different tools (e.g., scissors) as well as the spatio-temporal characteristics (e.g., correct orientation and dynamics of hammering) cannot readily be deduced from the physical structure of tools and objects (Hodges et al. 2000), we would have expected to note at minimum some score reduction due to trial and error or hesitation in patients relying heavily on compensatory strategies when using tools. More probably, structure-based inferences in patients with degraded action knowledge resulted in content errors, that is, categorically wrong actions such as pulling out the thread after fixating it between the scissor blades or trying to separate the screw from the rack with a scraping movement of the screwdriver (Table 1). Similarly to the study by Goldenberg and Spatt (2009), future studies should include additional tests for technical problem solving as well as a more specific test for stored manipulation knowledge, for example, a picture-based task (Buxbaum and Saffran 2002) to further elucidate the relative contributions of stored motor engrams and compensatory mechanisms to tool-associated actions in stroke patients.

Lastly, comprising only 5 items, our actual tools test provided only a limited amount of data for each subject. While the brevity of the examination may have reduced the influence of fatigue (which may be particularly relevant in the acute phase), future tests should comprise a larger number of tools to improve the reliability of the test, to increase the sensitivity for more fine-grained action execution deficits, and to allow for more detailed analyses of recipient selection errors (e.g., particular susceptibility for selecting functionally, contextually, or visually similar recipients).

Conclusion

Our results further specify the contributions of dorsal and ventral streams to conceptual and production-related aspects of tool use as defined in the models by Heilman et al. (1997). Lesions within the ventro-dorsal stream mainly resulted in combined impairments of recipient selection and action performance. Conversely, ventral stream damage had a more significant effect on recipient selection. The dissociation between the temporo-parietal and the more dorsally situated posterior parietal areas found to be associated with content and movement errors during action performance, respectively, highlights that the transition from conceptual to production-related action components involves several behaviorally and anatomically distinct processes along parallel streams that now can be anatomically validated.

Supplementary Material

Supplementary material can be found at: http://www.cercor.oxfordjournals.org/.

Funding

This work was supported by the BrainLinks-BrainTools Cluster of Excellence funded by the German Research Foundation (DFG, grant #EXC1086).

Notes

We thank Professor Georg Goldenberg for providing help with the tool use test. We thank Hansjörg Mast for assistance in data acquisition. We thank Gabriele Lind, Sarah Höfer, Cornelia Pietschmann, Ursula Kücking, and Susanne Karn for conducting the neuropsychological testing; without their careful examinations, this study would not have been possible. Conflict of Interest: None declared.

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Author notes

Markus Martin was formerly known as Markus Hoeren.