Abstract

Previous reports suggest that the internal organization of semantic memory is in terms of different “types of knowledge,” including “sensory” (information about perceptual features), “action” (motor-based knowledge of object utilization), and “functional” (abstract properties, as function and context of use). Consistent with this view, a specific loss of action knowledge, with preserved functional knowledge, has been recently observed in patients with left frontoparietal lesions. The opposite pattern (impaired functional knowledge with preserved action knowledge) was reported in association with anterior inferotemporal lesions. In the present study, the cerebral representation of action and functional knowledge was investigated using event-related analysis of functional magnetic resonance imaging data. Fifteen subjects were presented with pictures showing pairs of manipulable objects and asked whether the objects within each pair were used with the same manipulation pattern (“action knowledge” condition) or in the same context (“functional knowledge” condition). Direct comparisons showed action knowledge, relative to functional knowledge, to activate a left frontoparietal network, comprising the intraparietal sulcus, the inferior parietal lobule, and the dorsal premotor cortex. The reverse comparison yielded activations in the retrosplenial and the lateral anterior inferotemporal cortex. These results confirm and extend previous neuropsychological data and support the hypothesis of the existence of different types of information processing in the internal organization of semantic memory.

Introduction

How is semantic knowledge organized and how it is represented in the brain are central questions of cognitive neuroscience. The investigation of patients who, after a brain lesion, are affected by disorders of semantic memory, which selectively affect knowledge of living or nonliving items, has played a central role in this area of research. Although the existence of category-specific semantic impairment is relatively uncontroversial, the interpretation of the findings derived from the study of these patients remains a matter of discussion. A number of alternative hypotheses have been proposed, and the debate has been extensively reviewed in several recent publications (see, e.g., Laiacona et al. 2003; Thompson-Schill et al. 2003; Gainotti 2004, 2005). A basic distinction is between theories that propose that such category-specific impairments reflect the taxonomical, domain-specific organization of semantic memory (Caramazza and Shelton 1998) and “reductionist” interpretations, which interpret the semantic category effect as a by-product of other noncategorical aspects of conceptual representations. One of the most well-known approaches of the latter type is based on the idea that the internal organization of semantic memory is in terms of different “types of knowledge” (Warrington and Shallice 1984). These include “perceptual” (comprising information about perceptual features) and “functional” (including abstract and propositional properties, such as function, location, and context of use) knowledge. According to the original version of this model, category-specific deficits reflect the differential weighting of these types of knowledge in the semantic representations. Semantic knowledge of animals and other living things, which share a number of characteristics, relies more strongly on perceptual information, whereas knowledge of artifacts, which may share the same function despite remarkably different appearance, is primarily based on functional properties (Warrington and Shallice 1984). This “perceptual–functional” model was subsequently extended to account for a specific deficit at identifying smaller and manipulable items, such as kitchen tools, relative to larger nonmanipulable man-made objects, such as vehicles. The revised model underlined the importance of the dominant channel of experience (perceptual or motor) associated with the acquisition, storage, and retrieval of the semantic representation of a given object (Warrington and McCarthy 1987).

As to the neural correlates of semantic knowledge, “feature-based models” are usually grounded in the proposal that object concepts may be represented in the brain as distributed networks of activity in the areas involved in the processing of perceptual or functional knowledge. Indeed, an extensive literature suggests that information about different object features (i.e., different “types of knowledge”) may be stored in distinct regions of the cortex. In particular, different activations for the retrieval of functional versus perceptual knowledge (Cappa et al. 1998; Mummery et al. 1998; Thompson-Schill et al. 1999) and perceptual versus manipulative (Phillips et al. 2002) and for specific attributes (color, form, motion) (Chao et al. 1999) have been reported (see Martin and Chao 2001 and Thompson-Schill 2003, for a review).

Although the notion of perceptual features can be easily defined (see, e.g., Vinson et al. 2003), the definition of functional features has been used in a more loose way, to include widely different classes of information. Indeed, it is worth noting that the term functional does not refer exclusively to the knowledge of object's function but rather to those abstract propositional properties of concepts that do not belong to the perceptual or the motor domains (Martin and Chao 2001), for instance, the “context of use.” An important distinction to be drawn, in particular, in the case of artifacts, is between functional and action knowledge. Although these 2 types of knowledge have been often treated as a unitary concept in the past, the distinction between them has been recently supported by neuropsychological evidence. In general, the use of an object and the way it is manipulated do not bear any relationship. The distinction between these two aspects is supported by the classical neuropsychological distinction between semantic deficits and apraxia. The latter has been associated with lesions in those frontoparietal structures, which are also responsible for visuomotor transformations from objects' visual properties into actions toward them, and in the retrieval of action knowledge (Haaland et al. 2000). By definition, apraxic subjects should show preserved object identification. On the other hand, there are several reports on record of patients who show a profound impairment of object knowledge but can nonetheless gesture appropriately for objects they fail to identify, in association with anterior, inferotemporal lesions (see, e.g., Sirigu et al. 1991; Buxbaum et al. 1997; Lauro-Grotto et al. 1997; Hodges et al. 1999; Magnie et al. 1999).

The distinction between “what for” knowledge and “how” knowledge was further specified by Buxbaum and Saffran (2002; see also Buxbaum et al. 2000). These authors studied 2 subpopulations of left hemisphere–lesioned patients and observed that apraxic patients with frontoparietal lesions had a specific loss of manipulation knowledge, which was associated with impaired general knowledge about tools and body parts but preserved functional knowledge. The opposite dissociation was observed in a nonapraxics patients, with lesions confined in the temporal lobe. Spatt et al. (2002) confirmed the presence of a severe impairment in mechanical problem solving in cortico-basal degeneration, which, however, in some cases may be associated with defective conceptual knowledge, reflecting the overlap of this condition with frontotemporal dementia (Josephs et al. 2006). Moreover, Levy et al. (2004) reported a significant correlation between the extent of anterolateral temporal lesions and the severity of impaired semantic knowledge (including functional features). The site of the lesion in these patients is consistent with the results of a recent positron emission tomography (PET) study, aiming to investigate the cerebral regions recruited by the retrieval of knowledge regarding perceptual (structural and color) and functional aspects of familiar objects (Kellenbach et al. 2005). In fact, the left anterior middle/superior temporal regions and the temporal pole were activated only by the retrieval of functional knowledge, relative to both object structure and color.

The possible anatomical segregation of manipulative and functional knowledge has been already investigated in 2 imaging studies. The left posterior parietal cortex was reported to be more strongly activated by the retrieval of manipulative, compared with object's function, knowledge both by Kellenbach et al. (2003) and Boronat et al. (2005), using PET and epoch-based functional magnetic resonance imaging (fMRI), respectively. This region, together with its more occipital extension, is widely considered to be where the interface between perceptually related and action-related processes occur (Rizzolatti et al. 1997). The rostral portion of the inferior parietal lobule and the ventral premotor cortex in the left hemisphere were also activated in the same comparison in the former study. These studies, however, failed to detect cerebral regions specifically activated when retrieving functional knowledge.

In the present study, the cerebral organization of action and functional semantic representations was investigated using event-related modeling of single trials. Based on the above reviewed neuropsychological evidence, we predicted stronger anterior lateral temporal activations for the retrieval of functional knowledge relative to action knowledge and stronger frontoparietal activations in the opposite comparison.

Materials and Methods

Participants

Fifteen right-handed healthy monolingual native speakers of Italian (8 females and 7 males; mean age = 24.6 years; age range = 22–28 years) with normal vision took part in the experiment. Handedness was verified by means of the Edinburgh Inventory (Oldfield 1971). None of them had a history of neurological or psychiatric disorders. Subjects gave informed written consent to the experimental procedure, which was approved by the local Ethics Committee.

Tasks and Experimental Procedure

A semantic-decision task was used, with 2 experimental conditions. Subjects were presented with photographs showing pairs of manipulable man-made objects and asked whether the 2 objects within each pair were used with the same manipulation pattern (i.e., tongs and potato squasher; vacuum cleaner and metal detector) or not (“action knowledge” condition, A), or in the same context, based on their function (i.e., tongs and screwdriver; vacuum cleaner and carpet beater) or not (“functional knowledge” condition, F) (see Table 1 and Fig. 1).

Figure 1.

Experimental tasks. Schematic depiction of the sequence of events in a representative trial of A (on the left) and F (on the right) tasks. The numbers reported in the superior and left portion of each image represent the duration of the corresponding event and were not shown to the participants.

Figure 1.

Experimental tasks. Schematic depiction of the sequence of events in a representative trial of A (on the left) and F (on the right) tasks. The numbers reported in the superior and left portion of each image represent the duration of the corresponding event and were not shown to the participants.

Table 1

An example of the object pairs in the 2 tasks

Task First object Second object Same context? Same manipulation? 
Poultry shears Hand spiral beater Yes No 
Poultry shears Computer keyboard No No 
Poultry shears Tongs No Yes 
Poultry shears Stamp for postmark No No 
Task First object Second object Same context? Same manipulation? 
Poultry shears Hand spiral beater Yes No 
Poultry shears Computer keyboard No No 
Poultry shears Tongs No Yes 
Poultry shears Stamp for postmark No No 

The study was composed by 8 scanning periods lasting 4 min 32 s each. A blocked design for the presentation of the stimulus pairs was used, with every period comprising one A and one F block condition, each including 12 trials overall (see Fig. 1). In each trial, a pair of object was presented. Every block started with a screen alerting the subject (“Ready!,” 1000 ms), followed by a screen displaying the instructions (1500 ms), which were phrased as a question (“Same manipulation?” or “Same context of use?” for A and F tasks, respectively). All verbal instructions were presented in Italian. Instructions were followed by a screen displaying the first pair of objects, which was visible for a 4-s period during which subjects had to perform the task and prepare the answer, based on the instructions and the presented objects. These were followed by a white cross on black background, prompting subjects to answer (Yes/No). Subjects were asked to give a vocal response, which was recorded by means of a digital microphone lying outside the scanner room and connected via a plastic tube in proximity of the volunteers' mouth. A vocal, rather than a manual, response was used to reduce possible confoundings with the systems involved in the A task. The appearance of the white cross and the onset of the next trial were separated by a variable-length interval, allowing for implicit modeling of the baseline. In order to optimize statistical efficiency, interstimulus intervals between successive trials within a block were presented in different (“jittered”) durations across trials (4.8, 7.2, and 10.1 s, in the proportion of 4:2:1) (Dale 1999). Any possible priming effect within subjects was prevented for by requiring them to name all the 48 stimuli prior to scanning. Stimulus pairs were viewed via a back-projection screen located in front of the scanner and a mirror placed on the head coil. Stimulus pairs were presented, and subjects' answers and experimental timing information were recorded, using the software Presentation 9.13 (http://www.neurobs.com).

Stimuli

Forty-eight digitized color photographs of manipulable man-made objects on a white background served as stimuli. Both large and small objects were depicted as similar sizes. In the F blocks, the objects within a pair always differed in their manner of manipulation, and in the A blocks, they always differed in their context of use. The same set of photographs was used across the 2 tasks. Objects were paired so as that all the 48 stimuli were presented in each period. Therefore, none of the objects was presented more than once within each scanning period, and all were presented exactly 8 times. In both tasks, half the pairs within each block were made to cue a “yes” response, the other half to cue a “no” response. It was possible to create 4 A and 4 F blocks (see Appendix). Within the 4 A and F blocks, each object was always paired with a different object. Each of these blocks occurred twice. The left–right position of the objects within a pair was reversed at the second repetition of each block. The order of the 8 periods, and the order of all the trials within each block, were individually randomized for every subject. In order to avoid the temporal proximity of 2 blocks belonging to the same experimental condition, the order of the 2 blocks within a scanning period was always the same throughout the experiment (AF–AF for 9 subjects, FA–FA for the other 6 subjects).

The consistency with which the pairings between objects were associated with the target (yes or no) response was tested across all stimulus sets by means of a behavioral study, in which 10 subjects (5 females and 5 males who would not take part at the functional study) underwent the same experimental procedure as that described. The results showed an average agreement of 0.97 (standard deviation [SD] = 0.02; range = 0.78–1) and 0.96 (SD = 0.02; range = 0.75–1) for the A and F tasks, respectively. In order to investigate the amount of time needed to produce the response, we carried out a second behavioral study, in which the experimental procedure was slightly modified. Ten subjects (5 females and 5 males) were asked to solve the same task as above, except that they were required to respond as soon as possible. The results showed a small and not statistically significant difference between the reaction time in the tasks F (mean = 1640 ms, SD = 343 ms) and A (mean = 1718 ms, SD = 257 ms) (F(1,9) = 2.69; P > 0.05). In addition, there was no significant effect of the order of task presentation (F(7,63) = 1.654; P > 0.05) or a significant interaction between the task and the presentation order (F(7,63) = 0.506; P > 0.05).

fMRI Data Acquisition

Anatomical T1-weighted and functional T2*-weighted MR images were acquired with a 3 Tesla Philips Intera scanner (Philips Medical Systems, Best, the Netherlands), using an 8-channel Sense head coil (sense reduction factor = 2). Functional images were acquired using a T2*-weighted gradient-echo, echo-planar (EPI) pulse sequence (30 interleaved slices parallel to the anterior commissure-posterior commissure line, covering the whole brain, time repetition [TR] = 2000 ms, time echo [TE] = 30 ms, flip angle = 85°, field of view = 240 × 240 mm, no gap, slice thickness = 4 mm, in-plane resolution 2 × 2 mm). Each scanning sequence comprised 136 sequential volumes. Immediately after the functional scanning, a high-resolution T1-weighted anatomical scan (3D, spoiled-gradient-recalled sequence, 124 slices, TR = 600 ms, TE = 20 ms, slice thickness = 1 mm, in-plane resolution 1 × 1 mm) was acquired for each subject.

Data Analysis

Image preprocessing and statistical analysis were performed using SPM2 (Wellcome Department of Cognitive Neurology; http://www.fil.ion.ucl.ac.uk/spm), implemented in Matlab v6.5 (Mathworks, Inc., Sherborn, MA). The first 5 volumes of each subject were discarded to allow for T1 equilibration effects. EPI images were realigned temporally to acquisition of the middle slice, spatially realigned and unwarped, spatially normalized (voxel size: 2 × 2 × 2 mm) to the Montreal Neurological Institute (MNI) brain template (Evans et al. 1993), spatially smoothed (full-width-half-maximum Gaussian kernel: 6 × 6 × 6 mm) and globally scaled to 100. The resulting time series across each voxel were then high-pass filtered to 1/128 Hz, and serial autocorrelations were modeled as an AR(1) process.

Statistical maps were generated using a random-effect model (Friston et al. 1999), implemented in a 2-level procedure.

At the first level, single-subject fMRI responses, synchronized with the acquisition of the middle slice, were modeled as delta “stick” functions by a design matrix comprising the onset of the stimulus pair for each trial of both tasks. An additional regressor per condition was included to model the effect of the type of response (yes or no). Regressors modeling events were convolved with a canonical hemodynamic response function (HRF), along with its temporal and dispersion derivatives, and parameter estimates for all regressors were obtained by maximum-likelihood estimation.

At the second level, random-effect group analyses across the 15 subjects were computed. Statistical parametric maps for the “simple main effects” were generated by an analysis of variance incorporating the HRF and its derivatives for each condition (corrected for nonsphericity using a restricted maximum-likelihood procedure [Friston et al. 2002]). The resulting statistical maps were then used to perform a “conjunction analysis,” which tests for areas activated by both tasks, by means of inclusive masking. “Direct comparisons” between tasks were performed using paired t-tests on images of the contrasts of HRF parameter estimates, masked by the main effect of the task at P < 0.001. All the statistical maps were thresholded at P < 0.05, family-wise error corrected for multiple comparisons.

A “regions of interest (ROIs) analysis” was carried out using the Spm-toolbox Marsbar 0.40 (http://marsbar.sourceforge.net). First, we computed the percentage of blood oxygen level–dependent (BOLD) signal change during each task for the regions highlighted by the direct comparisons (see Fig. 2, top). Then, we focused on the involvement of the left occipitoparietal and inferior parietal cortices in the 2 experimental conditions, as these regions have consistently activated in related studies and are ones held to be critical for the perception–action interface. In order to investigate the differential contribution of different areas within this regions in the 2 tasks, the percentage of signal change was examined in 3 stripes of seven 6 mm radius spheres each, running in parallel from the occipital cortex to the rostral portion of the intraparietal sulcus along its fundus (ROIs 8–14) and the uppermost portions of its lateral (1–7) and medial (15–21) banks (see Fig. 3).

Figure 2.

Top: direct comparisons. Activation foci for A versus F (orange) and F versus A (light blue) tasks (P < 0.05, family-wise error corrected for multiple comparisons) superimposed on the flattened cortical surface of the left hemisphere. Major sulcal landmarks are labeled. The colored arrows link each activated cluster with a section showing the same activation superimposed on the MNI template provided with SPM2. Under each section, histograms representing the BOLD signal change percentage in both tasks are shown (red, A task; blue, F task). For each effect, standard error bars are indicated. Asterisks above histogram bars show a statistically significant effect (P < 0.05). The dashed box on the flattened surface highlights the region investigated in the ROIs analysis described in Figure 3. Bottom: conjunction analysis. Activation foci for the A task (red), the F task (blue) and both tasks as shown by the results of the conjunction analysis (violet) (P < 0.05, family-wise error corrected for multiple comparisons). Activations were superimposed on inflated cortical surfaces of the 2 hemispheres. IPS, intraparietal sulcus; POS, parieto-occipital sulcus; SFS, superior frontal sulcus; STS, superior temporal sulcus.

Figure 2.

Top: direct comparisons. Activation foci for A versus F (orange) and F versus A (light blue) tasks (P < 0.05, family-wise error corrected for multiple comparisons) superimposed on the flattened cortical surface of the left hemisphere. Major sulcal landmarks are labeled. The colored arrows link each activated cluster with a section showing the same activation superimposed on the MNI template provided with SPM2. Under each section, histograms representing the BOLD signal change percentage in both tasks are shown (red, A task; blue, F task). For each effect, standard error bars are indicated. Asterisks above histogram bars show a statistically significant effect (P < 0.05). The dashed box on the flattened surface highlights the region investigated in the ROIs analysis described in Figure 3. Bottom: conjunction analysis. Activation foci for the A task (red), the F task (blue) and both tasks as shown by the results of the conjunction analysis (violet) (P < 0.05, family-wise error corrected for multiple comparisons). Activations were superimposed on inflated cortical surfaces of the 2 hemispheres. IPS, intraparietal sulcus; POS, parieto-occipital sulcus; SFS, superior frontal sulcus; STS, superior temporal sulcus.

Figure 3.

ROIs analysis. The results of the ROIs analysis on the left occipitoparietal and inferior parietal cortices (highlighted by the dashed box in the upper part of Fig. 2) are depicted. The percentage of BOLD signal change in A (red) and F (blue) tasks and the difference between F and A (F minus A: yellow) are shown within each sphere. For each effect, standard error bars are indicated. A single asterisk above histogram bars indicates a statistically significant difference between the 2 tasks (paired t-test, P < 0.05), whereas effects approaching statistical significance are signaled by ♦; (ROI6, P = 0.063; ROI12, P = 0.055; ROI 15, P = 0.072).

Figure 3.

ROIs analysis. The results of the ROIs analysis on the left occipitoparietal and inferior parietal cortices (highlighted by the dashed box in the upper part of Fig. 2) are depicted. The percentage of BOLD signal change in A (red) and F (blue) tasks and the difference between F and A (F minus A: yellow) are shown within each sphere. For each effect, standard error bars are indicated. A single asterisk above histogram bars indicates a statistically significant difference between the 2 tasks (paired t-test, P < 0.05), whereas effects approaching statistical significance are signaled by ♦; (ROI6, P = 0.063; ROI12, P = 0.055; ROI 15, P = 0.072).

The location of the activation foci in terms of Brodmann areas was determined using the nomenclature given by Talairach and Tournoux (1988) after correcting for differences between the MNI and Talairach coordinate systems by means of a nonlinear transformation (see http://imaging.mrc-cbu.cam.ac.uk/Imaging/MniTalairach). For visualization purposes, the activated foci were superimposed on inflated or flattened cortical surfaces of the 2 hemispheres using Caret 5.4 software (http://brainmap.wustl.edu/caret.html).

Results

Behavioral results during functional scanning showed no significant difference in the percentage of correct answers between the A (mean = 0.95, SD = 0.02) and the F (mean = 0.96, SD = 0.01) tasks (F(1, 14) = 0.356, P > 0.05). Moreover, there was no significant effect of the order of task presentation throughout the 8 scanning sequences (F(7,98) = 0.898; P > 0.05) or a significant interaction between the task and the presentation order (F(7,98) = 0.400; P > 0.05).

Turning to the imaging results, the analysis of simple main effects showed comparable cerebral networks recruited in the 2 experimental conditions (see Fig. 2, bottom). Both tasks, in fact, activated bilaterally the same temporo-occipital, medial frontal and lateral frontal cerebral regions. Regions differentially activated by either task were observed as well: the left lateral anterior inferotemporal cortex was activated in the F task only, whereas the posterior parietal cortex was bilaterally activated in the A task only. No significant effect of the type of response (yes or no), or an interaction between the latter and the task, was observed. No activation was observed in the rostral portion of the inferior parietal lobule in any of the 2 tasks using a corrected statistical threshold. However, the fact that an activation in these region was predicted based on previous related findings (see Introduction) justified the use of an appropriate correction (small volume correction, SVC; Worsley et al. 1996). The procedure was applied to a 6 mm radius sphere centered on the coordinates which Grezes et al. (2003) derived by averaging the coordinates reported in 5 related studies (x = −37, y = −40, z = 44). The results showed that, with such a correction, a significant activation (P < 0.05) was observed in this region in the A, but not in the F, task.

The conjunction analysis showed the commonalities between tasks (see Fig. 2, bottom and Table 2). In the frontal lobe, common activations were observed in the precentral gyrus (Brodmann areas [BA] 6) and, in the medial wall, both in the pre–supplementary motor area (SMA) and in the proper-SMA (BA 6). In addition, the superior frontal gyrus (BA 8) was also activated, bilaterally, in both tasks. Common activations were also observed in the anterior cingulate gyrus (BA 24, 32), extending rostrally into the medial frontal gyrus (BA 10). In the temporal lobe, common activations were observed bilaterally in the posterior lateral temporal cortex and the superior temporal gyrus (BA 22) and in the anterior portion of the middle temporal gyrus (BA 21) on the left. In the occipital lobe, both tasks activated bilaterally a large occipitotemporal cluster, extending from the inferior and middle occipital gyri (BA 18, 19) through the inferior temporal and the fusiform gyrus (BA 37, 20). The precuneus (BA 31, 7) was activated as well. Finally the parieto-occipital junction, at the border between the superior occipital gyrus and the angular gyrus (BA 19), was also bilaterally activated.

Table 2

Spatial coordinates of the local maxima in the group analysis

Anatomical region MNI t-value 
x y z 
Conjunction analysis      
Inferior occipital gyrus −24 −100 −10 24.98 
Inferior occipital gyrus 14 −96 −6 17.48 
Middle occipital gyrus −30 −86 24.75 
Middle occipital gyrus 34 −94 23.61 
Fusiform gyrus −32 −46 −28 35.65 
Fusiform gyrus 34 −48 −28 35.19 
Precuneus −12 −62 18 29.74 
Precuneus 12 −62 14 30.65 
Posterior middle temporal gyrus −52 −58 10 27.47 
Posterior middle temporal gyrus 54 −54 12 19.98 
Superior temporal sulcus −54 −64 24 19.53 
Superior temporal sulcus 54 −62 16 27.93 
Superior temporal gyrus −62 −24 10 29.06 
Superior temporal gyrus 60 −26 21.57 
Middle temporal gyrus −56 −14 −24 19.30 
Superior occipital gyrus −30 −78 24 24.98 
Superior occipital gyrus 28 −72 32 26.34 
Superior parietal lobule 30 −66 52 23.61 
Ventral premotor cortex −58 −6 42 21.80 
Ventral premotor cortex 56 −10 46 18.39 
Opercular premotor cortex −60 −6 21.99 
Opercular premotor cortex 64 −2 10 28.84 
Superior frontal gyrus −18 38 46 22.02 
Superior frontal gyrus 20 26 48 17.94 
L/R Pre-SMA 10 52 24.29 
L/R SMA-Proper −4 58 36.33 
L/R Anterior cingulate gyrus −2 26 14 33.15 
Anterior cingulate gyrus 28 10 29.74 
Anterior cingulate gyrus −4 40 −2 24.75 
L/R Medial frontal gyrus −2 50 −4 23.61 
Direct comparisons      
A > F      
Intraparietal sulcus −32 −56 54 9.80 
Inferior parietal lobule −50 −30 42 8.07 
Dorsal premotor cortex −26 58 9.77 
F > A      
Lateral anterior inferotemporal cortex −54 −2 −38 11.23 
Retrosplenial cortex −6 −60 30 9.70 
Anatomical region MNI t-value 
x y z 
Conjunction analysis      
Inferior occipital gyrus −24 −100 −10 24.98 
Inferior occipital gyrus 14 −96 −6 17.48 
Middle occipital gyrus −30 −86 24.75 
Middle occipital gyrus 34 −94 23.61 
Fusiform gyrus −32 −46 −28 35.65 
Fusiform gyrus 34 −48 −28 35.19 
Precuneus −12 −62 18 29.74 
Precuneus 12 −62 14 30.65 
Posterior middle temporal gyrus −52 −58 10 27.47 
Posterior middle temporal gyrus 54 −54 12 19.98 
Superior temporal sulcus −54 −64 24 19.53 
Superior temporal sulcus 54 −62 16 27.93 
Superior temporal gyrus −62 −24 10 29.06 
Superior temporal gyrus 60 −26 21.57 
Middle temporal gyrus −56 −14 −24 19.30 
Superior occipital gyrus −30 −78 24 24.98 
Superior occipital gyrus 28 −72 32 26.34 
Superior parietal lobule 30 −66 52 23.61 
Ventral premotor cortex −58 −6 42 21.80 
Ventral premotor cortex 56 −10 46 18.39 
Opercular premotor cortex −60 −6 21.99 
Opercular premotor cortex 64 −2 10 28.84 
Superior frontal gyrus −18 38 46 22.02 
Superior frontal gyrus 20 26 48 17.94 
L/R Pre-SMA 10 52 24.29 
L/R SMA-Proper −4 58 36.33 
L/R Anterior cingulate gyrus −2 26 14 33.15 
Anterior cingulate gyrus 28 10 29.74 
Anterior cingulate gyrus −4 40 −2 24.75 
L/R Medial frontal gyrus −2 50 −4 23.61 
Direct comparisons      
A > F      
Intraparietal sulcus −32 −56 54 9.80 
Inferior parietal lobule −50 −30 42 8.07 
Dorsal premotor cortex −26 58 9.77 
F > A      
Lateral anterior inferotemporal cortex −54 −2 −38 11.23 
Retrosplenial cortex −6 −60 30 9.70 

Note: Stereotactic coordinates and t-values of the foci of maximum activation in the conjunction analysis and in the direct comparisons (P < 0.05, family-wise error corrected for multiple comparisons). Coordinates are expressed in MNI space adopted by SPM2 in terms of distance (in mm) from the anterior commissure. The foci were anatomically localized on the standard stereotactic brain atlas developed by Talairach and Tournoux (1988) after correcting for differences between the MNI and Talairach coordinate systems using a nonlinear transformation. H, hemisphere.

“Direct comparisons” highlighted the selective differences between the tasks: (see Fig. 2, top and Table 2). Compared with the F task, the A task activated the left caudal intraparietal sulcus (BA 7), the rostral portion of the inferior parietal lobule (BA 40), and the dorsal premotor cortex (BA 6). The reverse comparison revealed an activation in the lateral anterior portion of the inferior temporal gyrus (BA 20/21) as well as in the retrosplenial cortex (BA 7).

The general picture shown by the statistical maps of the main effects was confirmed by the results of the ROIs analysis on the percentage of signal change in the areas which were highlighted by the direct comparisons (see Fig. 2, top). In addition, the ROI analysis on the left occipitoparietal and inferior parietal cortices confirmed the differential involvement of these regions in the 2 tasks. For all the 3 stripes of ROIs, direct comparisons between average BOLD signal for the 2 tasks in each ROI largely confirmed the prediction. The only statistically significant differences (paired t-test, P < 0.05) between the 2 tasks were observed in the rostral ROIs (approximately in the same cerebral regions where significant differences were also highlighted in the statistical maps; see asterisks in Fig. 3). Nonetheless, a larger BOLD signal for the F, compared with A, task (as indicated by a positive difference between the respective average intensity values; see yellow columns in Fig. 3) was observed in the first 2 ROIs of each strip, located in occipital BA 18 and 19. In contrast, an increasingly larger BOLD signal for the A, compared with the F, task was observed in the more rostral ROIs, extending from occipitoparietal BA 19 through caudal (BA 7) to rostral (BA 40) inferior parietal regions. Such an increase was observed to grow constantly up to the last ROI of each strip, where the difference started to decrease. The statistical significance of this trend was assessed by means of a multiple regression on the difference between the signal intensity in the 2 tasks (A minus F), which showed a significant effect of the position of the ROI (1–7) (t(18) = 2.82; P < 0.05) and no significant effect of the stripe (1–3) (t(18) = −0.29; P > 0.05]).

Discussion

The imaging results indicated that, although the patterns of activation in the 2 tasks largely overlap, some cerebral regions are preferentially activated by each experimental condition (i.e., dependently of the specific type of knowledge retrieved). We first discuss the differential activations and then consider those that were commonly activated in the 2 tasks.

Neural System Related to Action Knowledge

Direct comparisons highlighted a left frontoparietal cerebral network, which was more strongly activated by manipulation than functional judgments, including the caudal intraparietal sulcus (BA 7), the rostral portion of the inferior parietal lobule (BA 40), and the dorsal premotor cortex (BA 6) (see Fig. 2, top). All these regions are part of the neural circuits responsible for object-related action organization and control.

The posterior parietal cortex is known to play a critical role in the sensorimotor transformations underlying action organization and objects' use. The likely involvement of this region in a direct “pragmatic” route from vision to object-directed action has been initially fueled by neuropsychological double dissociations between object use and semantic knowledge of objects (Goodale et al. 1991; Hodges et al. 1999). This view has been confirmed by recent neurophysiological data, indicating that this region consists of a mosaic of areas, each receiving specific sensory information and transforming it into information appropriate for action organization (see Rizzolatti and Luppino 2001 for a review).

The location of the 2 foci resulting from the A > F comparison is consistent with this view. The most posterior of the foci was located in the caudal portion of the intraparietal sulcus, a region that has typically been associated with observation of object-related actions in previous studies (Buccino et al. 2001, 2004a, 2004b) and explained in terms of higher order visual functions, possibly reflecting the first stages of the extraction of object affordances (Buccino et al. 2004a, 2004b). The second activated parietal focus was located in the rostral portion of the inferior parietal lobule, a region involved in computing the sensorimotor transformations necessary for grasping and manipulating objects and most likely corresponding to primate anterior intra-parietal areas. Based both on neurophysiological (Taira et al. 1990; Sakata and Taira 1994; Sakata et al. 1995) and inactivation (Gallese et al. 1994) data, it has been suggested that this area provides multiple descriptions of a three-2dimensional object, thus facilitating several different possibilities for grasping it (Gallese et al. 1997). A region with analogous properties has been described in the human brain, in the anterior part of the lateral bank of the intraparietal sulcus, approximately at the same location as that reported here (Decety et al. 1994; Bonda et al. 1996; Grafton et al. 1996a, 1996b; Binkofski et al. 1998, 1999; Krams et al. 1998; Moll et al. 2000; Perani et al. 2001; Grefkes et al. 2002; Grezes and Decety 2002; Johnson-Frey et al. 2005).

To summarize, the available evidence is in agreement with the proposed interplay between perception and action in the left occipitoparietal and posterior parietal cortices (Rizzolatti et al. 1997, 2001b). Such a view suggests that different portions of a perception-to-action system should be preferentially involved in the 2 tasks, the rostral, inferior parietal, portion being more strongly activated by manipulation, compared with functional judgments, with its caudal, occipitoparietal part being more strictly associated with the more visually demanding processing required by the F task. This hypothesis was confirmed by the results of the ROIs analysis on the percentage of BOLD signal change in these regions in the 2 tasks (see Materials and Methods and Fig. 3), which showed a statistically significant shift in the percentage of BOLD signal change from F to A task when moving from caudal to rostral ROIs. This confirms the existence of a perceptual-to-motor gradient in the activity of the left occipitoparietal and posterior parietal cortex and provides further support for the hypothesis that the cerebral regions resulting from the A > F comparison are part of a graded process, involved in the visuomotor analysis of objects' properties for their use.

A third focus selective for the A task was located in the left dorsal premotor cortex. This region is known to be involved in movement selection. Lesions in premotor cortex disrupt the selection of responses to visual cues both in monkeys (Halsband and Passingham 1985; Petrides 1987) and in patients (Halsband and Freund 1990). By using transcranic magnetic stimulation, Schluter et al. (1998) demonstrated that stimulation over the dorsal premotor cortex (mainly in the left hemisphere) can temporarily interfere with the selection of movements that are instructed by visual cues. The involvement of the dorsal premotor cortex in movement selection was further supported by the imaging data provided by Johnson et al. (2002), Grezes et al. (2003), and Choi et al. (2001).

Neural System Related to Functional Knowledge

In the complementary comparison, which failed to yield any significant results in previous studies, 2 regions were more strongly activated by functional than by manipulation judgments (see Fig. 2, top). The first is in the retrosplenial cortex. This is consistent with the results reported by Bar and Aminoff (2003), who found that observing objects with a characteristic context of use (e.g., roulette), by comparison with those that lack such a context (e.g., mobile phone), activates the parahippocampal cortex (PHC) and the retrosplenial cortex. In addition, they observed that only the latter structure is activated independently of the presence or absence of the object's typical background (e.g., a casino) and by both spatial (e.g., a kitchen) and nonspatial (e.g., a birthday) contexts. They argued that both these structures are involved in the analysis of context but with a different level of abstraction: whereas the PHC is more strictly associated with the analysis of visual properties that define a specific place, the retrosplenial cortex holds the abstract representations of an object's contextual associations, whose retrieval is essential in the current task. This might explain why only the latter was found active in the present study: subjects were presented with objects “floating” in isolation on a white background, and both objects characterized by spatial (e.g., a kitchen) and by nonspatial context (e.g., sport) might be presented within a given trial. Based on the data provided by Bar and Aminoff (2003), both these factors were likely to facilitate the activation of the retrosplenial, compared with the parahippocampal, cortex.

The second region that resulted from the F > A comparison is in the lateral anterior inferotemporal cortex. This is in excellent agreement with previous neuropsychological data showing a loss of functional knowledge, with preserved action knowledge, after a damage to this region in certain patients with semantic dementia (Buxbaum et al. 1997; Lauro-Grotto et al. 1997; Hodges et al. 1999) and herpes simplex encephalitis (Sirigu et al. 1991). Semantic dementia is typically characterized by progressive atrophy involving the anterolateral temporal cortex, particularly in the left hemisphere (Mummery et al. 2000), and herpes simplex encephalitis involves nearby areas. This fits with the suggestion of Damasio (1989, 1990) that the anterior temporal lobe is a higher order convergence zone, which integrates simple semantic features (and which would therefore include functional features) into a single object representation (see also Devlin et al. 2002 and Noppeney and Price 2002). Supporting evidence comes from neurophysiological studies on monkeys (Meunier et al. 1993; Buckley et al. 1997; Murray and Bussey 1999), imaging data in humans (Damasio et al. 1996; Gauthier et al. 1997), and lesion simulations on connectionist models by Bussey and Saksida (2002). The involvement of the anterior, inferior temporal cortex in the present study may thus be explained in terms of retrieval and integration of multiple semantic features, which are processed in different and specific cerebral regions (the retrosplenial cortex, in the case of the typical context of use).

It has been suggested that featural integration may be particularly important in the representation of stimuli in the “living” domain, which are associated with more featural overlap between category members than, say, tools (Devlin et al. 1998; Tyler et al. 2000; McRae and Cree 2002) and consequently may rely more heavily on anterior inferotemporal activity (Devlin et al. 2002). However, the processing of “living” stimuli is typically associated with activity of the more medial portions of the anterior temporal cortex (see Devlin et al. 2002). Instead, consistent with previous clinical reports (see Gainotti 2000; Mummery et al. 2000), its lateral portion was specifically activated by the retrieval of functional knowledge in the present study. This discrepancy suggests a functional specialization within this cerebral region. The medial portion of the anterior and inferior temporal cortex may be involved in the integration of perceptual features, whereas its lateral portion may be more engaged by the integration of abstract features, including those related to functional knowledge.

Common Activations

Both tasks activated bilaterally a cluster of areas extending from the inferior and middle occipital gyri (BA 18, 19) to the fusiform gyrus (BA 37, 20), corresponding to the so-called “lateral occipital complex.” This region is known to play an important role in both explicit (see Grill-Spector et al. 2001 for a review) and implicit (Pins et al. 2004) object recognition.

In the temporal lobe, the region at the border between the posterior part of the middle and the superior temporal gyrus has been extensively shown to be involved in processing objects, and actions on them, in a variety of experimental tasks in previous studies (Cappa et al. 1998; Mummery et al. 1998; Moore and Price 1999; Perani et al. 1999; Devlin et al. 2002; Phillips et al. 2002; Grezes et al. 2003; Creem-Regehr and Lee 2005; Johnson-Frey et al. 2005; see Lewis 2006 for a review), and its damage has been associated with a selective loss of knowledge about tools by Tranel et al. (1997). Based on its proximity to the MT/V5 complex, this region has been associated with processing of different features of moving stimuli (Chao et al. 1999) and in particular of nonbiological tool motion (Beauchamp et al. 2002, 2003; Kable et al. 2005). The same region as that described here was found by Ruby and Decety (2001) to be activated during mental simulation of object use, suggesting an automatic activation of implicit motion imagery by visual presentation of objects in the present study. This also fits with the activation of the medial precuneus, which has been previously involved in imagery (Fletcher et al. 1995, 1996), also in the motor domain (Bonda et al. 1995; Parsons et al. 1995; Gerardin et al. 2000; Ruby and Decety 2001; Hanakawa et al. 2003). A second temporal focus of activation was observed in the anterior portion of the left middle temporal gyrus, which, according to previous reports, is associated both with the acquisition (Maguire and Frith 2004) and the retrieval of different kinds of semantic information (Vandenberghe et al. 1996; Phillips et al. 2002).

In the precentral gyrus, the dorsal-most activation foci were located close to the hand/arm premotor cortex field, previously associated with manipulation of complex objects (Binkofski et al. 1999) and mental simulation of hand actions across different tasks (Decety et al. 1994; Parsons et al. 1995; Stephan et al. 1995; Grafton et al. 1996b; Krams et al. 1998; Ruby and Decety 2001; Grezes and Decety 2002). Activation extended caudally to the ventral premotor cortex, which has consistently been associated with perceptual and semantic tool–related tasks (Martin et al. 1996; Perani et al. 1999; Chao and Martin 2000; Devlin et al. 2002; Kellenbach et al. 2003; Fridman et al. 2006; see Lewis 2006 for a review). Noteworthily, both the dorsal and the caudal sectors of the cluster here described were found to be active also during passive object viewing by Grafton et al. (1997) and Grezes and Decety (2002) and interpreted in terms of implicit activation of motor representations by their visual presentation. This can also explain the activation in the SMA (from the rostral-most portion of the SMA-proper to the pre-SMA), which were found to be active during simple observation of objects by Grafton et al. (1997) and Grezes and Decety (2002).

A similar interpretation may be proposed for the activations in the anterior cingulate cortex (BA 24, 32), extending into the orbital portion of the medial frontal gyrus (BA 10), whose involvement has been previously interpreted in terms of inhibition of the observed actions by Decety et al. (1997) and whose damage is typically associated with the so-called “utilization behavior” (Lhermitte 1983; Lhermitte et al. 1986; Shallice et al. 1989). Instead, the activation of the dorsal portion of this medial cluster, which is located in the supracallosal portion of the anterior cingulate cortex (BA 24/32), is likely to reflect the overall change in cognitive demands over time in carrying out the tasks. Stuss et al. (2005), in fact, have recently suggested this portion of the medial frontal cortex to be critical for 3 putative components of the so-called Supervisory System of Norman and Shallice (1986): energizing (activation and energization of the neural systems required to make the decision), inhibition of wrong responses, and monitoring the level of activity of these schemata (see also Luria 1973; Drewe 1975; Plum and Posner 1980; Leimkuhler and Mesulam 1985; Alexander 2001).

However, the interpretation of the results of a conjunction analysis is not always straightforward. The involvement of the same cerebral areas in 2, or more, experimental conditions suffers from different possible interpretations. The first is the one that is most often adopted in papers, namely, that all of the contrasting theoretical processes that are being assessed separately in one of the conditions require the observed, commonly activated regions. The second arises from the so-called “switch costs,” that is, from carrying out an overall task that requires a switch in each period between 2 blocks and in each of which a different task is carried out on the same set of stimuli. Wylie and Allport (2000) used color/word Stroop and contrasted word naming with naming its color in successive alternating blocks. They found that although one of the tasks is being carried out, the other one continues to remain primed and so interferes with the first. Thus, a weaker activation related to 1 of the 2 tasks in our study may merely reflect the fact that the influence of a task in one block persists in a weaker form in the next block. Thus, in these cases observed common activations may not have been such if the study had been run on separate groups of subjects. A third possibility is that the existence of commonly activated regions and regions activated in A but not in F task derives from the lower sensitivity of the latter, compared with the former, say because of lower general attentional demands. Because, however, the 2 tasks activate occipital regions to roughly the same amount, it seems that this possibility can be discounted. Further studies are required to distinguish among these 3 possibilities.

Differences with Respect to Previous Related Studies

The involvement of the anterior inferotemporal cortex in the retrieval of functional knowledge was largely predicted based on previous neuropsychological findings. Yet, both Kellenbach et al. (2003) and Boronat et al. (2005) have failed to detect it. How to account for this discrepancy? The former study was based on a different task. Subjects were shown the picture of an object and asked whether it was used with a specific movement (e.g., with a circular motion, manipulative task) or to a specific goal (e.g., to alter the shape of another object, functional task). Hence, subjects were required to respond yes or no to a manipulative/functional feature that was already available to them, rather than to actively retrieve it. However, the anterior inferotemporal cortex has been associated with the active retrieval and linkage of semantic features, which are processed in other cortical regions (Noppeney and Price 2002). The fact that specific activations for manipulative judgments were still observed is likely to reflect the prominent role of action knowledge in the semantic representation of tools.

Instead, Boronat et al. used an identical task. However, an important difference can be found in the way single trials were statistically modeled. Whereas we analyzed single events within blocks, whole epochs were modeled by Boronat et al. Yet, based on the reaction times they report, it is likely that in each trial, subjects were engaged in the retrieval component of the task for less than half of the overall period during which activity was measured. In this kind of task, an event-related analysis, in which the hemodynamic responses to stimulus-induced neuronal transients are modeled without assuming constant within-block activity (Mechelli et al. 2003, p. 806), may capture changes in cerebral activity that cannot be accounted for by an epoch-based model.

Thus, we reanalyzed our data set using an “epoch-like” approach, modeling mini-epochs of 2500 ms (convolving the stimulus function with the canonical HRF only). Although longer than the amount of time actually needed by the subjects to respond, the length of this period is shorter than the epochs analyzed by Boronat et al. Thus, any negative result found in the former case should be valid for the latter as well. Direct comparisons between tasks showed that no cerebral region was more strongly activated by functional, compared with manipulative, knowledge at the same corrected statistical threshold as both in our primary analysis and in Boronat et al. The activation of the inferotemporal focus reported in the primary analysis was observed only at an uncorrected threshold of P < 0.001. The opposite comparison revealed an activation in the caudal portion of the left intraparietal sulcus (x = −34, y = −60, z = 54), in the region they also reported (x = 40, y = −63, z = 40). Overall, this strongly suggests that the different statistical analysis to be the most likely reason for the discrepancy between findings of Boronat et al. and our findings.

Conclusions

In conclusion, both tasks activated a set of areas that are involved in the structural analysis and recognition of objects, tool-related action processing, and mental simulation of their use. The observed pattern of activation is coherent with previous studies, indicating 2 distinct regions to be consistently and automatically activated in studies employing tools as stimuli: the posterior temporal cortex and ventrolateral premotor cortex, likely reflecting the automatic engagement of cerebral structures associated with their use. This is consistent with previous reports, suggesting that simple perception of objects affords action toward them (Grezes and Decety 2002; Johnson-Frey et al. 2005). In addition, the observation of cerebral regions that were preferentially activated in either task confirms and extends previous neuropsychological evidence, supporting the hypothesis of different types of information processing in the internal organization of semantic memory. The involvement of the frontoparietal circuits responsible for object-related actions in the retrieval of action knowledge supports the strict link between action and cognition, and the contribution of cortical motor system to cognitive tasks that do not involve motor responses, already suggested in other domains (Rizzolatti et al. 2001b). Further, functional knowledge is at least not entirely dependent on the activity of these neural circuits but rather engages anterior temporal areas related to object-specific conceptual knowledge.

Funding

This work was partially supported by a MIUR grant to S.F.C. (2005119758_001) and one to T.S.

We wish to thank B. Carsaniga and B. Torri for their help in preparing the stimuli. Thanks also to R. Alonso Clarke for his help in data collection and analysis. Conflict of Interest: None declared.

Appendix

Tables A1–A4.

Table A1
Task Response Number First object Second object 
True Steering wheel Battery clamps 
True Hockey stick Hand grippers 
True Bellows Gas lighter 
True Stretcher Sphygmomanometer 
True Hoover Carpet beater 
True Spiral beater Poultry shears 
False Rotovator Telephone keyboard 
False Nail polish Doorknob 
False Metal detector Shopping trolley 
False 10 Push-botton calculator Potato masher 
False 11 Parrot pliers Broom 
False 12 Door handle Pump horn 
True 13 Screwdriver Pencil sharpener with pencil 
True 14 Meat pounder Stamp for postmark 
True 15 Nutcrackers Pliers 
True 16 Accordion Pectoral expander 
True 17 Piano keyboard Computer keyboard 
True 18 Colander Mesh strainer 
False 19 Tongs Fly swatter 
False 20 Stapler Light bulb 
False 21 Lever for water tubes Correcting fluid 
False 22 Pruning shears Two-handled chopper 
False 23 Machine gun Fly reel 
False 24 Garden roller Electric drill 
Task Response Number First object Second object 
True Steering wheel Battery clamps 
True Hockey stick Hand grippers 
True Bellows Gas lighter 
True Stretcher Sphygmomanometer 
True Hoover Carpet beater 
True Spiral beater Poultry shears 
False Rotovator Telephone keyboard 
False Nail polish Doorknob 
False Metal detector Shopping trolley 
False 10 Push-botton calculator Potato masher 
False 11 Parrot pliers Broom 
False 12 Door handle Pump horn 
True 13 Screwdriver Pencil sharpener with pencil 
True 14 Meat pounder Stamp for postmark 
True 15 Nutcrackers Pliers 
True 16 Accordion Pectoral expander 
True 17 Piano keyboard Computer keyboard 
True 18 Colander Mesh strainer 
False 19 Tongs Fly swatter 
False 20 Stapler Light bulb 
False 21 Lever for water tubes Correcting fluid 
False 22 Pruning shears Two-handled chopper 
False 23 Machine gun Fly reel 
False 24 Garden roller Electric drill 
Table A2
Task Response Number First object Second object 
True Computer keyboard Push-botton calculator 
True Electric drill Screwdriver 
True Parrot pliers Lever for water tubes 
True Potato masher Meat pounder 
True Piano keyboard Accordion 
True Doorknob Door handle 
False Fly reel Garden roller 
False Mesh strainer Telephone keyboard 
False Pencil sharpener with pencil Colander 
False 10 Nutcrackers Nail polish 
False 11 Gas lighter Correcting fluid 
False 12 Broom Rotovator 
True 13 Hand grippers Battery clamps 
True 14 Tongs Poultry shears 
True 15 Carpet beater Fly swatter 
True 16 Two-handled chopper Steering wheel 
True 17 Hoover Metal detector 
True 18 Bellows Pruning shears 
False 19 Pump horn Stapler 
False 20 Light bulb Sphygmomanometer 
False 21 Pliers Stamp for postmark 
False 22 Hockey stick Spiral beater 
False 23 Stretcher Pectoral expander 
False 24 Shopping trolley Machine gun 
Task Response Number First object Second object 
True Computer keyboard Push-botton calculator 
True Electric drill Screwdriver 
True Parrot pliers Lever for water tubes 
True Potato masher Meat pounder 
True Piano keyboard Accordion 
True Doorknob Door handle 
False Fly reel Garden roller 
False Mesh strainer Telephone keyboard 
False Pencil sharpener with pencil Colander 
False 10 Nutcrackers Nail polish 
False 11 Gas lighter Correcting fluid 
False 12 Broom Rotovator 
True 13 Hand grippers Battery clamps 
True 14 Tongs Poultry shears 
True 15 Carpet beater Fly swatter 
True 16 Two-handled chopper Steering wheel 
True 17 Hoover Metal detector 
True 18 Bellows Pruning shears 
False 19 Pump horn Stapler 
False 20 Light bulb Sphygmomanometer 
False 21 Pliers Stamp for postmark 
False 22 Hockey stick Spiral beater 
False 23 Stretcher Pectoral expander 
False 24 Shopping trolley Machine gun 
Table A3
Task Response Number First object Second object 
True Two-handled chopper Nutcrackers 
True Pruning shears Pliers 
True Mesh strainer Metal detector 
True Steering wheel Pump horn 
True Colander Potato masher 
True Screwdriver Tongs 
False Carpet beater Accordion 
False Correcting fluid Pectoral expander 
False Hoover Lever for water tubes 
False 10 Sphygmomanometer Nail polish 
False 11 Pencil sharpener with pencil Battery clamps 
False 12 Piano keyboard Shopping trolley 
True 13 Door handle Light bulb 
True 14 Gas lighter Stapler 
True 15 Telephone keyboard Push-botton calculator 
True 16 Fly reel Spiral beater 
True 17 Rotovator Stretcher 
true 18 Hockey stick Broom 
False 19 Meat pounder Doorknob 
False 20 Hand grippers Fly swatter 
False 21 Stamp for postmark Poultry shears 
False 22 Electric drill Compute keyboard 
False 23 Parrot pliers Machine gun 
False 24 Bellows Garden roller 
Task Response Number First object Second object 
True Two-handled chopper Nutcrackers 
True Pruning shears Pliers 
True Mesh strainer Metal detector 
True Steering wheel Pump horn 
True Colander Potato masher 
True Screwdriver Tongs 
False Carpet beater Accordion 
False Correcting fluid Pectoral expander 
False Hoover Lever for water tubes 
False 10 Sphygmomanometer Nail polish 
False 11 Pencil sharpener with pencil Battery clamps 
False 12 Piano keyboard Shopping trolley 
True 13 Door handle Light bulb 
True 14 Gas lighter Stapler 
True 15 Telephone keyboard Push-botton calculator 
True 16 Fly reel Spiral beater 
True 17 Rotovator Stretcher 
true 18 Hockey stick Broom 
False 19 Meat pounder Doorknob 
False 20 Hand grippers Fly swatter 
False 21 Stamp for postmark Poultry shears 
False 22 Electric drill Compute keyboard 
False 23 Parrot pliers Machine gun 
False 24 Bellows Garden roller 
Table A4
Task Response Number First object Second object 
True Rotovator Pruning shears 
True Stapler Pencil sharpener with pencil 
True Broom Fly swatter 
True Pectoral expander Hockey stick 
True Two-handled chopper Meat pounder 
True Spiral beater Nutcrackers 
False Hoover Piano keyboard 
False Carpet beater Push-botton calculator 
False Metal detector Colander 
False 10 Poultry shears Computer keyboard 
False 11 Telephone keyboard Tongs 
False 12 Door handle Battery clamps 
True 13 Correcting fluid Nail polish 
True 14 Doorknob Lever for water tubes 
True 15 Pump horn Sphygmomanometer 
True 16 Shopping trolley Garden roller 
True 17 Parrot pliers Potato masher 
True 18 Electric drill Machine gun 
False 19 Gas lighter Screwdriver 
False 20 Stamp for postmark Hand grippers 
False 21 Pliers Light bulb 
False 22 Steering wheel Bellows 
False 23 Accordion Stretcher 
False 24 Fly reel Mesh strainer 
Task Response Number First object Second object 
True Rotovator Pruning shears 
True Stapler Pencil sharpener with pencil 
True Broom Fly swatter 
True Pectoral expander Hockey stick 
True Two-handled chopper Meat pounder 
True Spiral beater Nutcrackers 
False Hoover Piano keyboard 
False Carpet beater Push-botton calculator 
False Metal detector Colander 
False 10 Poultry shears Computer keyboard 
False 11 Telephone keyboard Tongs 
False 12 Door handle Battery clamps 
True 13 Correcting fluid Nail polish 
True 14 Doorknob Lever for water tubes 
True 15 Pump horn Sphygmomanometer 
True 16 Shopping trolley Garden roller 
True 17 Parrot pliers Potato masher 
True 18 Electric drill Machine gun 
False 19 Gas lighter Screwdriver 
False 20 Stamp for postmark Hand grippers 
False 21 Pliers Light bulb 
False 22 Steering wheel Bellows 
False 23 Accordion Stretcher 
False 24 Fly reel Mesh strainer 

References

Alexander
MP
Chronic akinetic mutism after mesencephalic-diencephalic infarction: remediated with dopaminergic medications
Neurorehabil Neural Repair
 , 
2001
, vol. 
15
 (pg. 
151
-
156
)
Andersen
RA
Asanuma
C
Essick
G
Siegel
RM
Corticocortical connections of anatomically and physiologically defined subdivisions within the inferior parietal lobule
J Comp Neurol
 , 
1990
, vol. 
296
 (pg. 
65
-
113
)
Bar
M
Aminoff
E
Cortical analysis of visual context
Neuron
 , 
2003
, vol. 
38
 (pg. 
347
-
358
)
Beauchamp
MS
Lee
KE
Haxby
JV
Martin
A
Parallel visual motion processing streams for manipulable objects and human movements
Neuron
 , 
2002
, vol. 
34
 (pg. 
149
-
159
)
Beauchamp
MS
Lee
KE
Haxby
JV
Martin
A
FMRI responses to video and point-light displays of moving humans and manipulable objects
J Cogn Neurosci
 , 
2003
, vol. 
15
 (pg. 
991
-
1001
)
Binkofski
F
Buccino
G
Posse
S
Seitz
RJ
Rizzolatti
G
Freund
H
A fronto-parietal circuit for object manipulation in man: evidence from an fMRI-study
Eur J Neurosci
 , 
1999
, vol. 
11
 (pg. 
3276
-
3286
)
Binkofski
F
Dohle
C
Posse
S
Stephan
KM
Hefter
H
Seitz
RJ
Freund
HJ
Human anterior intraparietal area subserves prehension: a combined lesion and functional MRI activation study
Neurology
 , 
1998
, vol. 
50
 (pg. 
1253
-
1259
)
Bonda
E
Petrides
M
Frey
S
Evans
A
Neural correlates of mental transformations of the body-in-space
Proc Natl Acad Sci USA
 , 
1995
, vol. 
92
 (pg. 
11180
-
11184
)
Bonda
E
Petrides
M
Ostry
D
Evans
A
Specific involvement of human parietal systems and the amygdala in the perception of biological motion
J Neurosci
 , 
1996
, vol. 
16
 (pg. 
3737
-
3744
)
Boronat
CB
Buxbaum
LJ
Coslett
HB
Tang
K
Saffran
EM
Kimberg
DY
Detre
JA
Distinctions between manipulation and function knowledge of objects: evidence from functional magnetic resonance imaging
Brain Res Cogn Brain Res
 , 
2005
, vol. 
23
 (pg. 
361
-
373
)
Buccino
G
Binkofski
F
Fink
GR
Fadiga
L
Fogassi
L
Gallese
V
Seitz
RJ
Zilles
K
Rizzolatti
G
Freund
HJ
Action observation activates premotor and parietal areas in a somatotopic manner: an fMRI study
Eur J Neurosci
 , 
2001
, vol. 
13
 (pg. 
400
-
404
)
Buccino
G
Lui
F
Canessa
N
Patteri
I
Lagravinese
G
Benuzzi
F
Porro
CA
Rizzolatti
G
Neural circuits involved in the recognition of actions performed by nonconspecifics: an FMRI study
J Cogn Neurosci
 , 
2004
, vol. 
16
 (pg. 
114
-
126
)
Buccino
G
Vogt
S
Ritzl
A
Fink
GR
Zilles
K
Freund
HJ
Rizzolatti
G
Neural circuits underlying imitation learning of hand actions: an event-related fMRI study
Neuron
 , 
2004
, vol. 
42
 (pg. 
323
-
334
)
Buckley
MJ
Gaffan
D
Murray
EA
Functional double dissociation between two inferior temporal cortical areas: perirhinal cortex versus middle temporal gyrus
J Neurophysiol
 , 
1997
, vol. 
77
 (pg. 
587
-
598
)
Bussey
TJ
Saksida
LM
The organization of visual object representations: a connectionist model of effects of lesions in perirhinal cortex
Eur J Neurosci
 , 
2002
, vol. 
15
 (pg. 
355
-
364
)
Buxbaum
LJ
Saffran
EM
Knowledge of object manipulation and object function: dissociations in apraxic and nonapraxic subjects
Brain Lang
 , 
2002
, vol. 
82
 (pg. 
179
-
199
)
Buxbaum
LJ
Schwartz
MF
Carew
TG
The role of semantic memory in object use
Cogn Neuropsychol
 , 
1997
, vol. 
14
 (pg. 
219
-
254
)
Buxbaum
LJ
Veramonti
T
Schwartz
MF
Function and manipulation tool knowledge in apraxia: knowing “what for” but not “how”
Neurocase
 , 
2000
, vol. 
6
 (pg. 
83
-
97
)
Cappa
SF
Perani
D
Schnur
T
Tettamanti
M
Fazio
F
The effects of semantic category and knowledge type on lexical-semantic access: a PET study
Neuroimage
 , 
1998
, vol. 
8
 (pg. 
350
-
359
)
Caramazza
A
Shelton
JR
Domain-specific knowledge systems in the brain: the animate-inanimate distinction
J Cogn Neurosci
 , 
1998
, vol. 
10
 (pg. 
1
-
34
)
Chao
LL
Haxby
JV
Martin
A
Attribute-based neural substrates in temporal cortex for perceiving and knowing about objects
Nat Neurosci
 , 
1999
, vol. 
2
 (pg. 
913
-
919
)
Chao
LL
Martin
A
Representation of manipulable man-made objects in the dorsal stream
Neuroimage
 , 
2000
, vol. 
12
 (pg. 
478
-
484
)
Choi
SH
Na
DL
Kang
E
Lee
KM
Lee
SW
Na
DG
Functional magnetic resonance imaging during pantomiming tool-use gestures
Exp Brain Res
 , 
2001
, vol. 
139
 (pg. 
311
-
317
)
Constantinidis
C
Steinmetz
MA
Neuronal responses in area 7a to multiple-stimulus displays: I. Neurons encode the location of the salient stimulus
Cereb Cortex
 , 
2001
, vol. 
11
 (pg. 
581
-
591
)
Creem-Regehr
SH
Lee
JN
Neural representations of graspable objects: are tools special?
Brain Res Cogn Brain Res
 , 
2005
, vol. 
22
 (pg. 
457
-
469
)
Dale
AM
Optimal experimental design for event-related fMRI
Hum Brain Mapp
 , 
1999
, vol. 
8
 (pg. 
109
-
114
)
Damasio
AR
Time-locked multiregional retroactivation: a systems-level proposal for the neural substrates of recall and recognition
Cognition
 , 
1989
, vol. 
33
 (pg. 
25
-
62
)
Damasio
AR
Category-related recognition defects as a clue to the neural substrates of knowledge
Trends Neurosci
 , 
1990
, vol. 
13
 (pg. 
95
-
98
)
Damasio
H
Grabowski
TJ
Tranel
D
Hichwa
RD
Damasio
AR
A neural basis for lexical retrieval
Nature
 , 
1996
, vol. 
380
 (pg. 
499
-
505
)
Decety
J
Grezes
J
Costes
N
Perani
D
Jeannerod
M
Procyk
E
Grassi
F
Fazio
F
Brain activity during observation of actions. Influence of action content and subject's strategy
Brain
 , 
1997
, vol. 
120
 (pg. 
1763
-
1777
Pt 10
Decety
J
Perani
D
Jeannerod
M
Bettinardi
V
Tadary
B
Woods
R
Mazziotta
JC
Fazio
F
Mapping motor representations with positron emission tomography
Nature
 , 
1994
, vol. 
371
 (pg. 
600
-
602
)
Devlin
JT
Gonnerman
LM
Andersen
ES
Seidenberg
MS
Category-specific semantic deficits in focal and widespread brain damage: a computational account
J Cogn Neurosci
 , 
1998
, vol. 
10
 (pg. 
77
-
94
)
Devlin
JT
Moore
CJ
Mummery
CJ
Gorno-Tempini
ML
Phillips
JA
Noppeney
U
Frackowiak
RS
Friston
KJ
Price
CJ
Anatomic constraints on cognitive theories of category specificity
Neuroimage
 , 
2002
, vol. 
15
 (pg. 
675
-
685
)
Drewe
EA
Go-no go learning after frontal lobe lesions in humans
Cortex
 , 
1975
, vol. 
11
 (pg. 
8
-
16
)
Evans
AC
Collins
DL
Mills
SR
Brown
ED
Kelly
RL
Peters
TM
3D Statistical neuroanatomical model from 305 MRI volumes. In: IEEE Conference Record, Nuclear Science Symposium and Medical Imaging Conference
1993
San Francisco, CA
(pg. 
1813
-
1817
Fletcher
PC
Frith
CD
Baker
SC
Shallice
T
Frackowiak
RS
Dolan
RJ
The mind's eye—precuneus activation in memory-related imagery
Neuroimage
 , 
1995
, vol. 
2
 (pg. 
195
-
200
)
Fletcher
PC
Shallice
T
Frith
CD
Frackowiak
RS
Dolan
RJ
Brain activity during memory retrieval. The influence of imagery and semantic cueing
Brain
 , 
1996
, vol. 
119
 (pg. 
1587
-
1596
Pt 5
Fridman
EA
Immisch
I
Hanakawa
T
Bohlhalter
S
Waldvogel
D
Kansaku
K
Wheaton
L
Wu
T
Hallett
M
The role of the dorsal stream for gesture production
Neuroimage
 , 
2006
, vol. 
29
 (pg. 
417
-
428
)
Friston
KJ
Holmes
AP
Worsley
KJ
How many subjects constitute a study?
Neuroimage
 , 
1999
, vol. 
10
 (pg. 
1
-
5
)
Friston
KJ
Penny
W
Phillips
C
Kiebel
S
Hinton
G
Ashburner
J
Classical and Bayesian inference in neuroimaging: theory
Neuroimage
 , 
2002
, vol. 
16
 (pg. 
465
-
483
)
Gainotti
G
What the locus of brain lesion tells us about the nature of the cognitive defect underlying category-specific disorders: a review
Cortex
 , 
2000
, vol. 
36
 (pg. 
539
-
559
)
Gainotti
G
A metanalysis of impaired and spared naming for different categories of knowledge in patients with a visuo-verbal disconnection
Neuropsychologia
 , 
2004
, vol. 
42
 (pg. 
299
-
319
)
Gainotti
G
The influence of gender and lesion location on naming disorders for animals, plants and artefacts
Neuropsychologia
 , 
2005
, vol. 
43
 (pg. 
1633
-
1644
)
Gallese
V
Fadiga
L
Fogassi
L
Luppino
G
Murata
A
Thier
P
Karnath
H-O
A parieto-frontal circuit for hand grasping movements in the monkey: evidence from reversible inactivation experiments
Parietal lobe contributions to orientation in 3D space
 , 
1997
Heidelberg, Germany
Springer-Verlag
(pg. 
255
-
270
)
Gallese
V
Murata
A
Kaseda
M
Niki
N
Sakata
H
Deficit of hand preshaping after muscimol injection in monkey parietal cortex
Neuroreport
 , 
1994
, vol. 
5
 (pg. 
1525
-
1529
)
Gauthier
I
Anderson
AW
Tarr
MJ
Skudlarski
P
Gore
JC
Levels of categorization in visual recognition studied using functional magnetic resonance imaging
Curr Biol
 , 
1997
, vol. 
7
 (pg. 
645
-
651
)
Gerardin
E
Sirigu
A
Lehericy
S
Poline
JB
Gaymard
B
Marsault
C
Agid
Y
Le Bihan
D
Partially overlapping neural networks for real and imagined hand movements
Cereb Cortex
 , 
2000
, vol. 
10
 (pg. 
1093
-
1104
)
Goodale
MA
Milner
AD
Jakobson
LS
Carey
DP
A neurological dissociation between perceiving objects and grasping them
Nature
 , 
1991
, vol. 
349
 (pg. 
154
-
156
)
Grafton
ST
Arbib
MA
Fadiga
L
Rizzolatti
G
Localization of grasp representations in humans by positron emission tomography. 2. Observation compared with imagination
Exp Brain Res
 , 
1996
, vol. 
112
 (pg. 
103
-
111
)
Grafton
ST
Fadiga
L
Arbib
MA
Rizzolatti
G
Premotor cortex activation during observation and naming of familiar tools
Neuroimage
 , 
1997
, vol. 
6
 (pg. 
231
-
236
)
Grafton
ST
Fagg
AH
Woods
RP
Arbib
MA
Functional anatomy of pointing and grasping in humans
Cereb Cortex
 , 
1996
, vol. 
6
 (pg. 
226
-
237
)
Grefkes
C
Weiss
PH
Zilles
K
Fink
GR
Crossmodal processing of object features in human anterior intraparietal cortex: an fMRI study implies equivalencies between humans and monkeys
Neuron
 , 
2002
, vol. 
35
 (pg. 
173
-
184
)
Grezes
J
Armony
JL
Rowe
J
Passingham
RE
Activations related to “mirror” and “canonical” neurones in the human brain: an fMRI study
Neuroimage
 , 
2003
, vol. 
18
 (pg. 
928
-
937
)
Grezes
J
Decety
J
Does visual perception of object afford action? Evidence from a neuroimaging study
Neuropsychologia
 , 
2002
, vol. 
40
 (pg. 
212
-
222
)
Grezes
J
Tucker
M
Armony
J
Ellis
R
Passingham
RE
Objects automatically potentiate action: an fMRI study of implicit processing
Eur J Neurosci
 , 
2003
, vol. 
17
 (pg. 
2735
-
2740
)
Grill-Spector
K
Kourtzi
Z
Kanwisher
N
The lateral occipital complex and its role in object recognition
Vision Res
 , 
2001
, vol. 
41
 (pg. 
1409
-
1422
)
Haaland
KY
Harrington
DL
Knight
RT
Neural representations of skilled movement
Brain
 , 
2000
, vol. 
123
 (pg. 
2306
-
2313
Pt 11
Halsband
U
Freund
HJ
Premotor cortex and conditional motor learning in man
Brain
 , 
1990
, vol. 
113
 (pg. 
207
-
222
Pt 1
Halsband
U
Passingham
RE
Premotor cortex and the conditions for movement in monkeys (Macaca fascicularis)
Behav Brain Res
 , 
1985
, vol. 
18
 (pg. 
269
-
277
)
Hanakawa
T
Immisch
I
Toma
K
Dimyan
MA
Van Gelderen
P
Hallett
M
Functional properties of brain areas associated with motor execution and imagery
J Neurophysiol
 , 
2003
, vol. 
89
 (pg. 
989
-
1002
)
Hodges
JR
Spatt
J
Patterson
K
“What” and “how”: evidence for the dissociation of object knowledge and mechanical problem-solving skills in the human brain
Proc Natl Acad Sci USA
 , 
1999
, vol. 
96
 (pg. 
9444
-
9448
)
Hyvarinen
J
Posterior parietal lobe of the primate brain
Physiol Rev
 , 
1982
, vol. 
62
 (pg. 
1060
-
1129
)
Johnson
SH
Rotte
M
Grafton
ST
Hinrichs
H
Gazzaniga
MS
Heinze
HJ
Selective activation of a parietofrontal circuit during implicitly imagined prehension
Neuroimage
 , 
2002
, vol. 
17
 (pg. 
1693
-
1704
)
Johnson-Frey
SH
Newman-Norlund
R
Grafton
ST
A distributed left hemisphere network active during planning of everyday tool use skills
Cereb Cortex
 , 
2005
, vol. 
15
 (pg. 
681
-
695
)
Josephs
KA
Petersen
RC
Knopman
DS
Boeve
BF
Whitwell
JL
Duffy
JR
Parisi
JE
Dickson
DW
Clinicopathologic analysis of frontotemporal and corticobasal degenerations and PSP
Neurology
 , 
2006
, vol. 
66
 (pg. 
41
-
48
)
Kable
JW
Kan
IP
Wilson
A
Thompson-Schill
SL
Chatterjee
A
Conceptual representations of action in the lateral temporal cortex
J Cogn Neurosci
 , 
2005
, vol. 
17
 (pg. 
1855
-
1870
)
Kellenbach
ML
Brett
M
Patterson
K
Actions speak louder than functions: the importance of manipulability and action in tool representation
J Cogn Neurosci
 , 
2003
, vol. 
15
 (pg. 
30
-
46
)
Kellenbach
ML
Hovius
M
Patterson
K
A pet study of visual and semantic knowledge about objects
Cortex
 , 
2005
, vol. 
41
 (pg. 
121
-
132
)
Krams
M
Rushworth
MF
Deiber
MP
Frackowiak
RS
Passingham
RE
The preparation, execution and suppression of copied movements in the human brain
Exp Brain Res
 , 
1998
, vol. 
120
 (pg. 
386
-
398
)
Laiacona
M
Capitani
E
Caramazza
A
Category-specific semantic deficits do not reflect the sensory/functional organization of the brain: a test of the “sensory quality” hypothesis
Neurocase
 , 
2003
, vol. 
9
 (pg. 
221
-
231
)
Lauro-Grotto
R
Piccini
C
Shallice
T
Modality-specific operations in semantic dementia
Cortex
 , 
1997
, vol. 
33
 (pg. 
593
-
622
)
Leimkuhler
ME
Mesulam
MM
Reversible go-no go deficits in a case of frontal lobe tumor
Ann Neurol
 , 
1985
, vol. 
18
 (pg. 
617
-
619
)
Levy
DA
Bayley
PJ
Squire
LR
The anatomy of semantic knowledge: medial vs. lateral temporal lobe
Proc Natl Acad Sci USA
 , 
2004
, vol. 
101
 (pg. 
6710
-
6715
)
Lewis
JW
Cortical networks related to human use of tools
Neuroscientist
 , 
2006
, vol. 
12
 (pg. 
211
-
231
)
Lhermitte
F
‘Utilization behaviour’ and its relation to lesions of the frontal lobes
Brain
 , 
1983
, vol. 
106
 (pg. 
237
-
255
Pt 2
Lhermitte
F
Pillon
B
Serdaru
M
Human autonomy and the frontal lobes. Part I: imitation and utilization behavior: a neuropsychological study of 75 patients
Ann Neurol
 , 
1986
, vol. 
19
 (pg. 
326
-
334
)
Luria
AR
The working brain: an introduction to neuropsychology
1973
New York
Basic Books
Magnie
MN
Ferreira
CT
Giusiano
B
Poncet
M
Category specificity in object agnosia: preservation of sensorimotor experiences related to objects
Neuropsychologia
 , 
1999
, vol. 
37
 (pg. 
67
-
74
)
Maguire
EA
Frith
CD
The brain network associated with acquiring semantic knowledge
Neuroimage
 , 
2004
, vol. 
22
 (pg. 
171
-
178
)
Martin
A
Chao
LL
Semantic memory and the brain: structure and processes
Curr Opin Neurobiol
 , 
2001
, vol. 
11
 (pg. 
194
-
201
)
Martin
A
Wiggs
CL
Ungerleider
LG
Haxby
JV
Neural correlates of category-specific knowledge
Nature
 , 
1996
, vol. 
379
 (pg. 
649
-
652
)
McRae
K
Cree
G
Forde
EME
Humphreys
GW
Factors underlying category-specific semantic deficits
Category specificity in mind and brain
 , 
2002
Sussex, UK
Psychology Press
Mechelli
A
Henson
RN
Price
CJ
Friston
KJ
Comparing event-related and epoch analysis in blocked design fMRI
Neuroimage
 , 
2003
, vol. 
18
 (pg. 
806
-
810
)
Meunier
M
Bachevalier
J
Mishkin
M
Murray
EA
Effects on visual recognition of combined and separate ablations of the entorhinal and perirhinal cortex in rhesus monkeys
J Neurosci
 , 
1993
, vol. 
13
 (pg. 
5418
-
5432
)
Moll
J
de Oliveira-Souza
R
Passman
LJ
Cunha
FC
Souza-Lima
F
Andreiuolo
PA
Functional MRI correlates of real and imagined tool-use pantomimes
Neurology
 , 
2000
, vol. 
54
 (pg. 
1331
-
1336
)
Moore
CJ
Price
CJ
A functional neuroimaging study of the variables that generate category-specific object processing differences
Brain
 , 
1999
, vol. 
122
 (pg. 
943
-
962
)
Mummery
CJ
Patterson
K
Hodges
JR
Price
CJ
Functional neuroanatomy of the semantic system: divisible by what?
J Cogn Neurosci
 , 
1998
, vol. 
10
 (pg. 
766
-
777
)
Mummery
CJ
Patterson
K
Price
CJ
Ashburner
J
Frackowiak
RS
Hodges
JR
A voxel-based morphometry study of semantic dementia: relationship between temporal lobe atrophy and semantic memory
Ann Neurol
 , 
2000
, vol. 
47
 (pg. 
36
-
45
)
Murray
EA
Bussey
TJ
Perceptual-mnemonic functions of the perirhinal cortex
Trends Cogn Sci
 , 
1999
, vol. 
3
 (pg. 
142
-
151
)
Noppeney
U
Price
CJ
A PET study of stimulus- and task-induced semantic processing
Neuroimage
 , 
2002
, vol. 
15
 (pg. 
927
-
935
)
Norman
DA
Shallice
T
Davidson
RJ
Shwartz
GE
Shapiro
D
Attention to action: willed and automatic control of behavior
Consciousness and self-regulation: advances in research and theory
 , 
1986
New York
Plenum Press
(pg. 
1
-
18
)
Oldfield
RC
The assessment and analysis of handedness: the Edinburgh Inventory
Neuropsychologia
 , 
1971
, vol. 
9
 (pg. 
97
-
113
)
Parsons
LM
Fox
PT
Downs
JH
Glass
T
Hirsch
TB
Martin
CC
Jerabek
PA
Lancaster
JL
Use of implicit motor imagery for visual shape discrimination as revealed by PET
Nature
 , 
1995
, vol. 
375
 (pg. 
54
-
58
)
Perani
D
Fazio
F
Borghese
NA
Tettamanti
M
Ferrari
S
Decety
J
Gilardi
MC
Different brain correlates for watching real and virtual hand actions
Neuroimage
 , 
2001
, vol. 
14
 (pg. 
749
-
758
)
Perani
D
Schnur
T
Tettamanti
M
Gorno-Tempini
M
Cappa
SF
Fazio
F
Word and picture matching: a PET study of semantic category effects
Neuropsychologia
 , 
1999
, vol. 
37
 (pg. 
293
-
306
)
Petrides
M
Perecman
E
Conditional learning and the primate frontal cortex
The frontal lobe revisited
 , 
1987
New York
IRBN
(pg. 
91
-
108
)
Phillips
JA
Noppeney
U
Humphreys
GW
Price
CJ
Can segregation within the semantic system account for category-specific deficits?
Brain
 , 
2002
, vol. 
125
 (pg. 
2067
-
2080
)
Pins
D
Meyer
ME
Foucher
J
Humphreys
G
Boucart
M
Neural correlates of implicit object identification
Neuropsychologia
 , 
2004
, vol. 
42
 (pg. 
1247
-
1259
)
Plum
F
Posner
JB
The diagnosis of stupor and coma
1980
Philadelphia (PA)
Davis
Rizzolatti
G
Fogassi
L
Gallese
V
Parietal cortex: from sight to action
Curr Opin Neurobiol
 , 
1997
, vol. 
7
 (pg. 
562
-
567
)
Rizzolatti
G
Fogassi
L
Gallese
V
Neurophysiological mechanisms underlying the understanding and imitation of action
Nat Rev Neurosci
 , 
2001
, vol. 
2
 (pg. 
661
-
670
)
Rizzolatti
G
Luppino
G
The cortical motor system
Neuron
 , 
2001
, vol. 
31
 (pg. 
889
-
901
)
Rorden
C
Brett
M
Stereotaxic display of brain lesions
Behav Neurol
 , 
2000
, vol. 
12
 (pg. 
191
-
200
)
Ruby
P
Decety
J
Effect of subjective perspective taking during simulation of action: a PET investigation of agency
Nat Neurosci
 , 
2001
, vol. 
4
 (pg. 
546
-
550
)
Sakata
H
Taira
M
Parietal control of hand action
Curr Opin Neurobiol
 , 
1994
, vol. 
4
 (pg. 
847
-
856
)
Sakata
H
Taira
M
Murata
A
Mine
S
Neural mechanisms of visual guidance of hand action in the parietal cortex of the monkey
Cereb Cortex
 , 
1995
, vol. 
5
 (pg. 
429
-
438
)
Schluter
ND
Rushworth
MF
Passingham
RE
Mills
KR
Temporary interference in human lateral premotor cortex suggests dominance for the selection of movements. A study using transcranial magnetic stimulation
Brain
 , 
1998
(pg. 
121
(pg. 
785
-
799
Pt 5
Shallice
T
Burgess
PW
Schon
F
Baxter
DM
The origins of utilization behaviour
Brain
 , 
1989
, vol. 
112
 (pg. 
1587
-
1598
Pt 6
Sirigu
A
Duhamel
JR
Poncet
M
The role of sensorimotor experience in object recognition. A case of multimodal agnosia
Brain
 , 
1991
, vol. 
114
 (pg. 
2555
-
2573
Pt 6
Spatt
J
Bak
T
Bozeat
S
Patterson
K
Hodges
JR
Apraxia, mechanical problem solving and semantic knowledge: contributions to object usage in corticobasal degeneration
J Neurol
 , 
2002
, vol. 
249
 (pg. 
601
-
608
)
Stephan
KM
Fink
GR
Passingham
RE
Silbersweig
D
Ceballos-Baumann
AO
Frith
CD
Frackowiak
RS
Functional anatomy of the mental representation of upper extremity movements in healthy subjects
J Neurophysiol
 , 
1995
, vol. 
73
 (pg. 
373
-
386
)
Stuss
DT
Alexander
MP
Shallice
T
Picton
TW
Binns
MA
Macdonald
R
Borowiec
A
Katz
DI
Multiple frontal systems controlling response speed
Neuropsychologia
 , 
2005
, vol. 
43
 (pg. 
396
-
417
)
Taira
M
Mine
S
Georgopoulos
AP
Murata
A
Sakata
H
Parietal cortex neurons of the monkey related to the visual guidance of hand movement
Exp Brain Res
 , 
1990
, vol. 
83
 (pg. 
29
-
36
)
Talairach
J
Tournoux
P
Co-planar stereotactic atlas of the human brain
 , 
1988
Germany: Thieme
Stuttgart
Thompson-Schill
SL
Neuroimaging studies of semantic memory: inferring “how” from “where”
Neuropsychologia
 , 
2003
, vol. 
41
 (pg. 
280
-
292
)
Thompson-Schill
SL
Aguirre
GK
D'Esposito
M
Farah
MJ
A neural basis for category and modality specificity of semantic knowledge
Neuropsychologia
 , 
1999
, vol. 
37
 (pg. 
671
-
676
)
Tranel
D
Damasio
H
Damasio
AR
A neural basis for the retrieval of conceptual knowledge
Neuropsychologia
 , 
1997
, vol. 
35
 (pg. 
1319
-
1327
)
Tyler
LK
Moss
HE
Durrant-Peatfield
M
Levy
JP
Conceptual structure and the structure of concepts: a distributed account of category-specific deficits
Brain Lang
 , 
2000
, vol. 
75
 (pg. 
195
-
231
)
Vandenberghe
R
Price
C
Wise
R
Josephs
O
Frackowiak
R
Functional anatomy of a common semantic system for words and pictures
Nature
 , 
1996
, vol. 
383
 (pg. 
254
-
256
)
Vinson
DP
Vigliocco
G
Cappa
S
Siri
S
The breakdown of semantic knowledge: insights from a statistical model of meaning representation
Brain Lang
 , 
2003
, vol. 
86
 (pg. 
347
-
365
)
Warrington
EK
McCarthy
RA
Categories of knowledge. Further fractionations and an attempted integration
Brain
 , 
1987
, vol. 
110
 (pg. 
1273
-
1296
Pt 5
Warrington
EK
Shallice
T
Category specific semantic impairments
Brain
 , 
1984
, vol. 
107
 (pg. 
829
-
854
Pt 3
Worsley
KJ
Marrett
S
Neelin
P
Vandal
AC
Friston
K
Evans
AC
A unified statistical approach for determining significant signals in images of cerebral activation
Hum Brain Mapp
 , 
1996
, vol. 
4
 (pg. 
58
-
73
)
Wylie
G
Allport
A
Task switching and the measurement of “switch costs”
Psychol Res
 , 
2000
, vol. 
63
 (pg. 
212
-
233
)