hazardous tools: the emergence of reasoning in human tool use

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Psychological Research https://doi.org/10.1007/s00426-020-01466-2

ORIGINAL ARTICLE

Hazardous tools: the emergence of reasoning in human tool use

Giovanni Federico1 · François Osiurak2,3 · Maria A. Brandimonte4

Received: 31 August 2020 / Accepted: 14 December 2020 © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021

AbstractHumans are unique in the way they understand the causal relationships between the use of tools and achieving a goal. The idea at the core of the present research is that tool use can be considered as an instance of problem-solving situations sup-ported by technical reasoning. In an eye-tracking study, we investigated the fixation patterns of participants (N = 32) looking at 3D images of thematically consistent (e.g., nail–steel hammer) and thematically inconsistent (e.g., scarf–steel hammer) object-tool pairs that could be either “hazardous” (accidentally electrified) or not. Results showed that under thematically consistent conditions, participants focused on the tool’s manipulation area (e.g., the handle of a steel hammer). However, when electrified tools were present or when the visual scene was not action-prompting, regardless of the presence of elec-tricity, the tools’ functional/identity areas (e.g., the head of a steel hammer) were fixated longer than the tools’ manipulation areas. These results support an integrated and reasoning-based approach to human tool use and document, for the first time, the crucial role of mechanical/semantic knowledge in tool visual exploration.

Introduction

Tool use, alongside language and bipedal locomotion, is a characterising ability of human beings. While non-human primates can manipulate tools (e.g., Baber, 2003), the main differences between human and non-human tool use can be traced in the evolutionary discontinuities related to hand–eye coordination, social learning and intelligence, teaching, lan-guage, function representation, executive functioning and, most importantly, causal reasoning (Vaesen, 2012). Indeed, humans appear to be unique in the way they understand the causal relationships between the use of tools and achiev-ing a goal (Povinelli et al., 2000). Such a noticeable dif-ferentiation becomes particularly apparent if one considers how individuals spontaneously and frequently use tools to solve everyday-life problems, in common (e.g., pounding a nail using a hammer) and uncommon (e.g., screwing a

screw using a knife) ways, according to their goals (e.g., hang a picture on the wall) and intentions (e.g., furnish the living room). Indeed, tool use can be easily considered as an instance of problem-solving situations sustained by technical reasoning (Osiurak & Badets, 2016; see also: Beck, Apperly, Chappell, Guthrie, & Cutting, 2011).

When considering such a kind of reasoning-centred abili-ties, the emphasis on motor aspects given by “manipula-tion-based” theories of human tool use seems quite pecu-liar (e.g., Thill, Caligiore, Borghi, Ziemke, & Baldassarre, 2013; but see Malafouris, 2013; Gallagher, 2017). By echo-ing the embodied-cognition account (Barsalou, 2008), the manipulation-knowledge hypothesis put in the foreground the role of the sensorimotor knowledge in tool use: humans manipulate tools and, consequently, they store information regarding how to manipulate them. The corollary idea is that, when we perceive a tool, we automatically activate motor simulations of actions that are associated with the tool. In this way, the notion of “affordance” (Gibson, 1977) has become highly (ab)used in the field of tool use, on the presumptive basis that the ecological approach is limpidly embodied (i.e., perception for action).1 Notwithstanding, it

* Giovanni Federico [email protected] IRCCS SDN, Via Emanuele Gianturco, 113, 80143 Naples,

Italy2 Laboratoire d’Etude des Mécanismes Cognitifs, Université de

Lyon, Lyon, France3 Institut Universitaire de France, Paris, France4 Laboratory of Experimental Psychology, Suor Orsola

Benincasa University, Naples, Italy

1 For the majority of the manipulation-based theorists, when we see a tool, we automatically activate two kinds of motor representa-tions: How to grasp it (i.e., “structural affordances”) and How to use it (i.e., “functional affordances”; Buxbaum & Kalénine, 2010; Thill et al., 2013; Bach, Nicholson, & Hudson, 2014; Kourtis & Vinger-hoets, 2015; Kourtis, Vandemaele, & Vingerhoets, 2018). By positing

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Psychological Research

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should be noted how, for Gibson (1977) himself, an affor-dance is not a form of knowledge at all, and even less it is a kind of sensorimotor knowledge. Instead, Gibson’s ecologi-cal account highlighted the systemic nature of affordances by considering them as properties that emerge from the mutuality between an organism and its interactive/environ-mental context. Such opportunities for action may provide information about functional properties of objects without calling for recognition and/or retrieval of declarative knowl-edge (Gibson, 1977; see Osiurak, Rossetti, & Badets, 2017 for a comprehensive review of the multitude of meanings associated with the term "affordance”). Having said that, it should be noted how a reasonable scientific question could be asking whether any embodied and/or ecological concept of affordance is sufficient per se to incorporate the cognitive foundations of human tool use. In fact, although stressing the role of the object-provided motor affordances can be an effective way to understand the prehensile mechanisms and the associative-learning skills implicated in how chim-panzees use objects (Orban & Caruana, 2014), the manip-ulation-based approach might not be as much adequate to fully understand the “cognitive magnitude” associated with human tool use. Hence, recent evidence has started to high-light the involvement of higher-order cognitive processes in such a characterising human ability, particularly emphasis-ing the crucial role of technical reasoning and of semantic processing in human tool use (e.g., Federico & Brandimonte, 2020; Osiurak, Lesourd, Navarro, & Reynaud, 2020; Osi-urak & Badets, 2016; see also: Goldenberg, 2013).

Within a “reasoning-based perspective”, humans are not seen as manipulators. Instead, they are considered as problem solvers who can transform their physical environ-ment according to their goals (Osiurak et al., 2020). Tool use is thereby incorporated in a wider cognitive framework that emphasises reasoning on the basis of the so-called mechanical knowledge, that is, a non-declarative form of knowledge associated with tools and objects that contains

abstract information about mechanical actions.2 Thus, when we see a screwdriver on the table, we do not automatically activate manipulation knowledge to use it. Rather, based on the physical problem we intend to solve, we use mechani-cal knowledge to reason about how to use the screwdriver with an appropriate object (e.g., screw). Hence, it is thereby expected a kind of mechanical-to-motor “cascade” mecha-nism through which an agent, in a recursive way, first gen-erates the mechanical actions to be executed, then places constraints on the motor actions that should be selected by the motor-control system to actualise the action. This mecha-nism is substantiated by the multiplicity of neurocognitive systems involved in tool use (e.g., Reynaud, Lesourd, Nav-arro, & Osiurak, 2016; Orban & Caruana, 2014). In particu-lar, mechanical knowledge (i.e., the ventro-dorsal system) seems to be a kind of bridge system between the semantic system associated with tools’ identity and functions (i.e., the ventral system) and the motor-control system (i.e., the dorso-dorsal system; Osiurak et al., 2017).

The effects of the interaction between the aforementioned neurocognitive systems on tool visual exploration have been recently explored by Federico and Brandimonte (2020). By comparing an implicit motoric task with an explicit rec-ognition task, in two eye-tracking experiments the authors investigated how the visuoperceptual context and the goal of the task influenced the visual-attentional processing of tools that were part of object-tool pairs. The first key result was that, within the first 500 ms of visual exploration, par-ticipants focused on the tools’ functional areas in any experi-mental condition. In contrast, when participants looked at the scene in a natural way and a longer time window of analysis was considered (1000 ms), the fixation pattern focused on the tool’s manipulation area (e.g., the handle of a screwdriver) under thematically consistent conditions (e.g., screw-screwdriver) and on the tool’s functional area (e.g., the head of a screwdriver) under thematically inconsistent conditions (e.g., nut-screwdriver). Crucially, looking at the

2 With the term “mechanical knowledge” (within this paper, syno-nym of “technical reasoning”) we considered a form of knowledge about physical principles. Such a non-declarative kind of knowledge may be considered as abstract because physical and technical reali-ties do not overlap. Hence, a single physical matter (e.g., glass) can have distinct properties (e.g., hardness, sharpness, transparency). Conversely, distinct physical matters (e.g., metal or plastic) can have the same single property (e.g., hardness). Additionally, as happens in by-analogy problem solving situations, we are able to quickly transfer the mechanical principles we learned through a specific tool or in a specific circumstance to another (e.g., a knife may be used to screw by transferring the function usually associated with a screwdriver to the knife). Crucially, one of the peculiarities of human tool use lies exactly in transfer skills (e.g., Penn, Holyoak, & Povinelli, 2008). Further discussions on these aspects may be found in Osiurak and Badets (2016).

Footnote 1 (continued)the automatic activation of motor representations associated with the tool’s usual function (i.e., How to use it), the so-called automatic acti-vation hypothesis of functional affordances becomes a crucial aspect of many embodied approaches to human tool use (e.g., Bach et al., 2014; Buxbaum, 2001; Gonzalez Rothi, Ochipa, & Heilma, 1991; van Elk, van Schie, & Bekkering, 2014). Please note that the terms “ges-ture engram” (Buxbaum, 2001), “visuokinesthetic motor engram” (Heilman, Gonzalez Rothi, & Valenstein, 1982), “spatial–temporal movement representation” (Heilman & Watson, 2008), “manipula-tion knowledge” (Bach et al., 2014; van Elk et al., 2014) or “repre-sentation of motor programs for acquired tool use skills” (Johnson-Frey, Newman-Norlund, & Grafto, 2005), as well as many others, are generally used as synonyms of functional affordances. Thus, while it differs from the initial conceptualisation made by Gibson (1977) and despite its polysemic nature, the concept of functional affordance remains univocally meaningful.



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tools to recognise them, generated longer fixations on the tools’ functional areas, irrespective of thematic consistency. Thus, when the visuoperceptual context prompts high action readiness, the easiest resolution of the cascade mechanism is reflected in a visual-attentional pattern that emphasises the tool’s manipulative part to actualise the action. Conversely, when the visual scene is not prompting action readiness or when there is an explicit non-motoric goal, individuals do not proceed toward motor processing. These results were interpreted by the authors as indicating a mechanism of “action reappraisal”, that is, a reasoning-based multidimen-sional cognitive process through which—using multiple sources of information and distinct neurocognitive systems (e.g., semantic knowledge, mechanical knowledge, sensori-motor knowledge)—people may exploit the environment in terms of action.

The action-reappraisal concept—far from being consid-ered as an automatic and motor-centric process—implies, on the one hand, that the action possibilities are "caught" by the individual, based on her goals and, on the other hand, that the individual’s action propensity may be influenced by the environmental context, by previous knowledge, and by the individual’s experience (Federico & Brandimonte, 2019, 2020). The action reappraisal idea overcomes the the-oretical dichotomy between embodied and non-embodied approaches by positing how, in tool-use contexts, the human mind can rely on technical reasoning and semantic knowl-edge, alongside processing sensorimotor information (e.g., affordance perception). Importantly, the authors underline how semantic knowledge, despite neither necessary nor suf-ficient to actually use tools, can be indispensable to create abstract and generalisable concepts associated with tools and objects (e.g., Lambon Ralph, Jefferies, Patterson, & Rog-ers, 2017; Wurm & Caramazza, 2019; see also: Rogers & McClelland, 2004; Bar et al., 2006). Hence, within such an integrated framework, semantic knowledge is considered as a complementary addendum to construct object-related action representations. Such representations can be usable in everyday life by a reasoning-based agent, in the context of a cognitive-oriented functioning (Federico & Brandimonte, 2020).

In the present study, we moved a step further and devised a task that enables technical reasoning only if it is based on the understanding of classical Physics principles. To date, electrical conductivity is a measure of the ability of a sub-stance to conduct an electric current. Metals are capable of conducting electricity so that no one would touch a metal tool if it were electrified. Hence, a steel hammer seen next to a nail, with both objects placed on a steel tray, would be seen less graspable if a stripped electrical cable was plugged in the power line and its stripped part was accidentally in contact with the tray. In such a situation, an agent should prevent herself from using the electrified tool as an effect

of an inferential process. Consequently, we should expect a fixation pattern that, despite the higher action readiness prompted by the thematic consistency of the visual scene (Federico & Brandimonte, 2019), does not favour the tool’s manipulation area. In other words, by following the inte-grated perspective of action reappraisal, we hypothesised that participants’ affordance-based visual exploratory behav-iour (i.e., affordance perception) should be modulated by both semantic and mechanical knowledge (i.e., recognising a power cable, understanding how its wiring signals that a given object is electrified, hence reasoning about the associ-ated potential risk). Based on our best knowledge, no other study investigated such a specific hypothesis. Therefore, in the present study, we analysed by eye-tracking the fixation patterns of participants looking at 3D colour images repro-ducing thematically consistent (e.g., nail–steel hammer) and thematically inconsistent (e.g., scarf–steel hammer) object-tool pairs that could be electrified or not (Fig. 1). We pos-ited that, as an effect of the action reappraisal mechanism, tools that were part of thematically consistent and electri-fied object-tool pairs should be looked at their manipula-tive area less than their correspondent non-electrified pairs. Conversely, electricity should not produce any effect under thematically inconsistent conditions, given the lower action readiness produced by the visual scene. Hence, in these con-trol conditions, we expected a pattern that did not favour the tool’s manipulative part, regardless of the presence of electricity.

Methods

Participants

Thirty-two right-handed participants (22 females; mean age = 25.69 years, SD = 4.19) engaged in the experiment. All had a normal vision and no history of psychiatric/neurologi-cal disorders. Written informed consent was obtained from all participants involved in the experiment. The sample size was calculated on the basis of similar studies (Federico & Brandimonte, 2019, 2020) and by performing a power analy-sis (Faul, Erdfelder, Lang, & Buchner, 2007) to detect a small effect size ( !2

p = 0.10) within a repeated-measures

ANOVA, with a power of 0.95 and an alpha level of 0.05.

Materials

We used twenty 3D computer-graphics generated colour images as stimuli for the experiment. Stimuli were divided into four different groups. The first two groups of images (Fig. 1a, b) represented object-tool pairs that were themati-cally consistent (a tool made of steel on the right—e.g., steel



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whip—and an object on the left, e.g., a bowl). The objects were placed on a steel tray that was located on a table in close proximity to the observer, within the participant’s peri-personal space. For each group, there were the following five object-tool pairs: nail–steel hammer, bowl–steel whip, bot-tle–steel bottle opener, salami–steel knife, coffee cup–steel teaspoon. The first group of stimuli (Fig. 1a) presented a stripped power cord that was plugged in the power line on the wall, with the stripped part of the cable accidentally in contact with the steel tray, while the second group (Fig. 1b) showed the same stripped power cord unplugged from the power line. The third and fourth group of stimuli (Fig. 1c, d) depicted pairs of thematically inconsistent objects (a tool made of steel on the right—e.g., a steel teaspoon—and an object on the left, e.g., a cap). The pairs appeared arranged on a steel tray that was placed on a table, within the peri-personal space of participants. Both groups com-prised five object-tool pairs: scarf–steel hammer, women shoe–steel whip, alarm clock–steel bottle opener, nut–steel knife, cap–steel teaspoon. Once again, the third (Fig. 1c) and fourth (Fig. 1d) group of stimuli showed one of two scenarios with either plugged or unplugged power cords. In all experimental conditions, the object-tool pairs appeared placed directly on the steel tray located on the table. The mean perceived centre-to-centre distance between the tool and the object was about 25 cm, with an angle of approxi-mately 180° (taking the horizontal line of the table as a refer-ence). Some examples of the stimuli used in the experiment are shown in Fig. 1.

Procedure

The experiment was performed in the Laboratory of Experi-mental Psychology of the Suor Orsola Benincasa University

of Naples (Italy). All procedures were in accordance with the ethical standards of the 1964 Helsinki Declaration. The Ethics Committee of the Suor Orsola Benincasa Univer-sity approved the study. Before starting with the experi-ment, written informed consent was obtained from each participant. Then, participants were asked to self-report the absence of any psychiatric/neurological diseases, their adequate visual acuity and their right-handedness. The participants were seated on a chair, with a headrest used to limit their head movements to permit an accurate eye-tracking data recording. Participants were positioned at a distance of 54 cm from a 23-inches monitor. They were then asked to keep their hand motionless on the desk. The right hand was resting on the right side of the monitor, hence being peripherally visible. Then, the experimental instruc-tions were provided. Participants completed an eye-tracking software calibration procedure. Subsequently, participants were asked to "observe what appeared on the screen in the most natural way as possible" and the experiment began. For each experimental condition, five images were adminis-tered. Thus, being the design of a within-participants design, twenty images were randomly presented to each participant, in accordance with the experimental visual flow (Fig. 2). A fixation point (i.e., a white cross positioned in the centre of a black screen) appeared for 500 ms before each stimulus. Then, the stimulus was shown for 5000 ms. A black screen appeared for 4000 ms after each stimulus to allow partici-pants’ eyes to relax. Each stimulus presentation lasted 9.5 s (500 ms + 5000 ms + 4000 ms) whereas the overall stimuli presentation lasted 190 s (9500 ms × 20 stimuli). Then, par-ticipants were asked to perform a reachability task using the same stimuli as those used during the experiment. Par-ticipants were asked to indicate if both the objects of the pairs were graspable with their right hand. All participants

Fig. 1 Example of stimuli used in the experiment. a Electrified, thematically consistent, object-tool pair (nail–steel hammer). b Non-electrified, thematically consistent, object-tool pair (nail–steel hammer). c Electri-fied, thematically inconsistent, object-tool pair (scarf–steel hammer). d Non-electrified, thematically inconsistent, object-tool pair (scarf–steel hammer)



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reported that they were reachable. Most importantly, in the thematically consistent condition, tools were reported as potentially usable on the objects (e.g., the steel knife was considered effectively usable on the salami) only when the tools were considered not electrified by the presence of the plugged-in stripped power cord placed in contact with the steel tray, whereas, in the thematically inconsistent condi-tion, tools and objects were considered not properly usable with each other (e.g., the steel hammer was not considered usable on the scarf), regardless of the presence of electricity. For each participant, the experiment lasted about 20 min. All participants were debriefed about the aims of the research. None of the participants was excluded from the sample.

Apparatus

The eye-tracking data were collected through a Full-HD Webcam (Logitech HD Pro C920, with a sampling rate of 60 Hz). RealEye.io platform (RealEye sp. z o. o.) was used to manage the experiment and to acquire gaze-behaviour data. The eye-tracking technologies at the core of the plat-form we used are based on WebGazer (Papoutsaki et al., 2016). A 23-inches monitor was used to show the stimuli at a resolution of 1920 × 1080 px. The experimental software and scripts were executed on an Apple Mac Mini (2018) running macOS Catalina (version 10.15).

Eye-tracking data

We analysed the participants’ visual-attentional patterns by considering the mean fixation time (milliseconds) on differ-ent Areas of Interest (AOIs) of the tools. In particular, we defined two different AOIs (Fig. 3): the manipulation part of the tool (i.e., the middle-bottom area where to put the hand to use the tool) and the functional part of the tool (i.e., middle-top area through which it is possible to understand the identity/function of the tool). The AOIs considered in the study are shown in Fig. 3. To overcome the technical limita-tions of the eye-tracking technology used here (Papoutsaki et al., 2016), we increased the perimeter of the AOIs by

64 pixels in all directions. The mean fixation time to the AOIs was averaged for each condition. Eye-tracking data related to the first 250 ms of each stimulus were excluded to reduce the error produced by the initial fixation point in participants’ visual-exploration patterns. For each stimulus, we considered only the first 2000 ms of visual-exploration data. According to previous pilot studies, we chose such a time-window of analysis to decrease data dispersal effects due to participants’ visual-scene exploration (fixations not useful for the purposes of the analysis; e.g., fixations to the table, the wall, the edges of the scene, etc.). Preliminary qualitative indications of differences in participants’ visual-attentional patterns may be appreciated by looking at the fixation heatmaps (Fig. 4).

Data analyses

We analysed how participants looked at the tools as the visuoperceptual context changed by performing a 2 × 2 × 2 repeated-measure ANOVA with AOIs (functional vs. manipulative part of the tool), Thematic Consistency (the-matically consistent vs. thematically inconsistent object-tool pairs), and Electricity (electrified vs. non-electrified tools)

Fig. 2 Experimental flow. A fixation point appeared for 500 ms before each trial, then an object-tool pair appeared for 5000 ms. Such a pair could be electrified or not, thematically consistent or not. Every pair was followed by a black screen that appeared for 4000 ms to allow participants’ eyes to relax

Fig. 3 Areas of interest analysed in the experiment. The AOIs ana-lysed in the experiment were the functional area (highlighted in blue, labelled as “F”) and the manipulation area (highlighted in red, labelled as “M”) of the tool



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as 2-level factors on tools’ fixation time (milliseconds). An alpha level of 0.05 was used for all the analyses. For multi-ple comparisons, we used the Tukey HSD test. We used the open-source software “R” and the graphical user interface “Jamovi” (both for Apple macOS operating system) to per-form all the statistical analyses.

Results

Eye-tracking data related to the temporal allocation of vis-ual-spatial attention (i.e., mean fixation time) to the tools’ function and manipulation AOIs are synthesised in Table 1.

A repeated-measure analysis of variance revealed a main effect of AOIs on tools’ mean fixation time, F(1, 31) = 128.34, p < 0.001, !2

p = 0.81. This main effect was due

to a longer fixation duration for the tool’s functional area (M = 361 ms, SD = 187) than the tool’s manipulation area (M = 144 ms, SD = 158). A main effect of Electricity was also found, F(1, 31) = 4.15, p = 0.05, !2

p = 0.12. This main

effect was due to a longer fixation duration for Non-Electri-fied tools (M = 264 ms, SD = 187) than Electrified tools (M = 241 ms, SD = 217). Three statistically significant inter-actions were found: (1) AOIs × Electricity, F(1, 31) = 39.61, p < 0.001, !2

p = 0.56; (2) AOIs × Thematic Consistency, F(1,

31) = 68.65, p < 0.001, !2p = 0.69; (3) AOIs × Electricity ×

Thematic Consistency, F(1, 31) = 35.14, p < 0.001, !2p = 0.53.

We restricted the description of results to the three-way interaction “AOIs × Thematic Consistency × Electricity” to simplify the pattern of results. Hence, post-hoc pairwise

comparisons revealed that, for the thematically consistent object-tool pairs, the tool’s manipulation area was fixated longer than the tool’s functional area in the non-electrified condition (p < 0.05), whereas, in the Electrified condition, the visuo-attentional pattern was reversed, with tools fixated longer in their functional area (p < 0.001). In addition, the manipulation area of tools that were part of thematically consistent object-tool pairs obtained longer fixation time in the non-electrified condition as compared to the remaining conditions (all with p < 0.001). Conversely, the tool’s func-tional area was fixated longer than the manipulation area in the thematically inconsistent conditions, regardless of the presence of electricity (all with p < 0.001). Finally, tools of thematically consistent pairs were fixated longer in their functional area in Electrified condition (p < 0.001). The three-way interaction effect reported here is shown in Fig. 5. No main effect of Thematic Consistency was found.

Fig. 4 Visual-scene explora-tion heatmaps. Examples of heatmaps associated with the way participants explored the visual scene. a A heatmap of an electrified, thematically consist-ent, object-tool pair (nail–steel hammer). b A heatmap of a non-electrified, thematically consistent, object-tool pair (nail–steel hammer). c A heat-map of an electrified, themati-cally inconsistent, object-tool pair (scarf–steel hammer). d A heatmap of a non-electrified, thematically inconsistent, object-tool pair (scarf–steel hammer). The time window of the eye-tracking analysis for a, b, c, d was 2000 ms

Table 1 Tool’s manipulation and functional AOIs: mean fixation time

Areas of interest (mean fixation time − mean and SD)Manipulation AOI Functional AOI

Thematically consistent object-tool pairs Electrified 86 ms (89) 389 ms (221) Not electrified 320 ms (186) 214 ms (115)

Thematically inconsistent object-tool pairs Electrified 85 ms (100) 403 ms (165) Not electrified 85 ms (88) 437 ms (149)



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Discussion

In the present eye-tracking3 study, we investigated the impact of inferential technical reasoning on the tool’s visual-atten-tional patterns of participants engaged in a free-to-look-at task in which stimuli composed by 3D images of themati-cally consistent (nail–steel hammer) and thematically incon-sistent (scarf–steel hammer) object-tool pairs were randomly

administered. These pairs could appear as electrified or not by means of a stripped power cord that could be plugged in or unplugged from the electrical line. In all experimental conditions, the stripped part of the cable was placed acci-dentally in contact with a steel tray upon which the objects were located (Fig. 1).

Results showed that under the thematically consistent, non-electrified condition, the mechanical knowledge issue (How to use the tool with the object?) was presumably easily solved so that the mechanical-to-motor cascade mechanism could proceed fast (Federico & Brandimonte, 2019). This was reflected in a fixation pattern (Figs. 4, 5) that focused on the manipulative part of the tool, to actualise the action (i.e., using the tool with the object). However, such a vis-ual-attentional pattern is far from suggesting an automatic motor engagement. In fact, as soon as the same consistent pairs appeared electrified, the manipulation-centred pat-tern disappeared and was replaced by an opposite pattern in which the tools’ functional areas were fixated longer than the tools’ manipulation areas. Therefore, it appears that reasoning about the electricity circumstance inhibited par-ticipants from proceeding toward the motor processing of the visual scene. In other words, the mechanical-to-motor cascade mechanism was not finalised as participants lingered in technical reasoning. Interestingly, the same fixation pat-tern was obtained—regardless of the presence of electric-ity—when the visual scene was not action-prompting “by default”. Namely, in the control condition with thematically

Fig. 5 Visual exploration of the tools. Three-way interaction between AOIs, thematic consistency and electricity. When object-tool pairs were thematically consistent, but not electrified, the tool’s manipula-tion area was fixated longer than the tool’s functional area. Crucially, when objects were electrified, an inverse visual-attentional pattern was registered, with the tool’s functional area fixated longer than the

tool’s manipulation area. Analogously, fixation of the functional area was longer when object-tool pairs were thematically inconsistent, irrespective of the presence of electricity. Vertical bars denote 0.95 confidence intervals, computed by adopting a simpler solution to Lof-tus and Masson (1994) provided by Cousineau (2005)

3 Given the background of the study, one might wonder why we pre-ferred to study oculomotor behaviour rather than actual tool manip-ulation behaviour (e.g., motor preparation of grasps or other typical affordance-related experimental tasks). Alongside the relevant eye-hand coordination issues we introduced above, here it may be use-ful to remind that the basic assumption of the direct-visual-route-to-action view is that vision guides action (Milner & Goodale, 2008). In particular, it has been repeatedly suggested in the literature how the “implicit recognition of action-related object attributes [affordances] can bias object competition—and visual spatial attention” so that “the motor affordance of an object must first be recognized, a pro-cess that likely involves attention to specific object features” (Handy, Grafton, Shroff, Ketay, & Gazzaniga, 2003, p. 424–425). Therefore, the temporal allocation of visuo-spatial attention reflects visually guided behaviour. If an affordance associated with a tool is perceived, the fixation pattern of the tool will be mostly focused on its action-relevant parts (Handy et al., 2003; Land, 2006; Roberts & Hum-phreys, 2011; Natraj, Pella, Borghi, & Wheaton, 2015; Ambrosini & Costantini, 2017). Consistently with that, the temporal allocation of visuo-spatial attention to specific areas of tools (e.g., the handle of a hammer) can be effectively used as an indirect index of affordance perception (see Federico & Brandimonte, 2019 for a detailed discus-sion).



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inconsistent pairs, participants explored the visual scene in a reasoning-based way, with motor processing and elec-tricity being no longer relevant. Finally, tools were fixated longer under non-electrified than electrified conditions, as evidenced by the main effect of electricity.

The involvement of reasoning processes in tool visual exploration makes the present results very difficult to interpret within a manipulation-centred framework (e.g., Buxbaum, 2001; Buxbaum & Kalénine, 2010; Thill et al., 2013). Participants appeared to be able to implicitly dis-tinguish the “opportunities for action” (Gibson, 1977) prompted by the visual scene on the basis of an inferential process (i.e., understanding the hazardousness elicited by the visual scene) supported by technical reasoning, which, in turn, was made possible through the knowledge of a prin-ciple of Physics (i.e., electrical conductivity). These results may help understand how a reasoning-based agent can use tools by processing and integrating multiple types of infor-mation through distinct neurocognitive systems. Such an integrated perspective has been recently proposed by Fed-erico and Brandimonte (2020) by introducing the concept of “action reappraisal” as a way to conceptualise human tool use as the product of dynamic interactions between semantic knowledge, mechanical knowledge, and the motor-control system. Therefore, we endorsed a perspective that assumes the centrality of action within a cognitive-centred perim-eter. In so doing, we adopted the concept of action reap-praisal (Federico & Brandimonte, 2019, 2020) to highlight how humans construct and use tools to deal with everyday circumstances, hence acquiring, updating and, most impor-tantly, reasoning about the most appropriate use of tools in a specific context, rather than to passively learn and actualise actions that can be executed with them.

The flexible interactions between neurocognitive sys-tems we outlined here are well testified by the wide and composite interplay of frontoparietal and occipitotemporal brain networks involved in human tool use (e.g., Reynaud et al., 2016, 2019; Orban & Caruana, 2014). In particu-lar, mechanical knowledge appears to be stored within the cytoarchitectonic “PF” area (Caspers et al., 2006, 2008) of the supramarginal gyrus (SMG), in the left inferior pari-etal cortex. Such a neurocognitive system seems to act as a bridge between the tools’ function knowledge (i.e., seman-tic knowledge associated with tools’ identity and functions; Garcea & Mahon, 2012) and the motor-control system (Osi-urak et al., 2017). These latter two systems have specific neural correlates. Indeed, the function knowledge produces sparse activations in the left temporal cortex, in the lateral occipital complex and in the left posterior middle temporal gyrus (Reynaud et al., 2016; see also: Boronat et al., 2005; Canessa et al., 2008; Goldenberg; 2013; Orban & Caruana, 2014; Roux-Sibilon, Kalénine, Pichat, & Peyrin; 2018). The bilateral superior parietal cortex and the intraparietal sulcus

(the anterior dorsal IPS and the putative human anterior intraparietal sulcus area) appear to be the neural substrates associated with the motor-control system (Reynaud et al., 2016; see also: Chao & Martin, 2000; Johnson-Frey, 2004; Goldenberg & Spatt, 2009). Most importantly, the left ante-rior portion of the SMG, extending to the cytoarchitectonic “PFt” area of the SMG appears to be an area that integrates information between mechanical knowledge and the motor-control system (Reynaud et al., 2016; Caspers et al., 2006, 2008). Thus, when an agent reasons on the feasibility of an action, an initial activation of the cytoarchitectonic PF area may reflect the degree of technical-reasoning involvement in visual scene analysis. Then, it is conceivable that when the agent decides to actualise the action, as in the case of a non-electrified nail-steel hammer pair, we should expect the activation of the motor-control system (i.e., superior parietal areas such as the IPS) while looking at the handle of the tool. Conversely, lower or no activation of the same parietal areas should be expected when an agent does not decide to use a tool (i.e., when the agent does not look at the tool’s manipulation area), as in the case of electrified tools or the-matically inconsistent pairs. Currently, the present findings do not speak directly to the issue of the neural correlates of the effects reported here. Therefore, future fMRI studies should specifically test the cascade-mechanism hypothesis.

By following the neuroscientific debate, it is worth to notice how the action-reappraisal perspective might find an echo in the recent findings about the identification of cortical convergence temporo-parietal areas that combine different kinds of knowledge to construct generalisable object/action representations (e.g., Lambon Ralph et al., 2017; Chen, Gar-cea, Jacobs, & Mahon, 2018; Wurm & Caramazza, 2019; see also: Rogers & McClelland, 2004; Bar et al., 2006). Addi-tionally, if we assume the action-reappraisal perspective, the evidence of a left inferior prefrontal cortex activation in tool use (particularly in action planning and execution) appears promising (Reynaud et al., 2016). Indeed, these brain areas are actively implicated in high-level executive functions as well as in motor timing, sequencing, and simulation (Koech-lin & Summerfield, 2007; Bortoletto & Cunnington, 2010; Stadler et al., 2011). Coherently, the rostro-lateral prefron-tal cortex appears to be also involved in complex human-reasoning tasks such as relational integration, that is, when considering multiple relations simultaneously (e.g., Christoff et al., 2001). Besides, if we assume the so-called “affordance competition hypothesis” (Cisek, 2007; Cisek & Kalaska, 2010) as a different version of the cascade mechanism, the frontal-lobes involvement might also reflect an inhibitory mechanism that select only the affordances that are con-sistent with the individual’s intentions, from the multiple environment-available ones. In brief, whereas the complex-ity of integration processes involving temporoparietal brain areas has been increasingly investigated in the specialised



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tool-use literature, the frontal-areas involvement did not get the same popularity. This is probably due to the absence of a clear-cut neuropsychological correlation between tool-use impairments and frontal lesions (but see: Bakheit, Bren-nan, Gan, Green, & Roberts, 2013; Lagarde et al., 2013; Lhermitte, Pillon, & Serdaru, 1986; Lhermitte, 1986). That notwithstanding, those areas might actively take part in the action-reappraisal mechanism and, therefore, they may deserve further consideration in future studies.

To sum up, our results clearly support a reasoning-based and integrated approach to human tool use by highlighting, for the first time, the role of both semantic and mechani-cal knowledge in tool visual exploration. As we discussed before, an important limitation of the mainstream embodied approach is that it might induce us to under-intellectualise the cognitive bases of human tool use, thereby leading us to pay attention mainly to the manipulative component (Osi-urak et al., 2020). This limitation is not specific to the cogni-tive science literature and can also be found in other domains such as in archaeology or anthropology (for discussion, see Osiurak & Reynaud, 2019). In contrast, it has been repeat-edly shown that people may focus on the goal component of the action more than on its manipulative component (e.g., Massen & Prinz, 2007; Osiurak & Badets, 2014). This pat-tern has also been found in observational studies in which participants looked at a model using a tool (e.g., Decroix & Kalénine, 2018, 2019; Naish, Reader, Houston-Price, Bremner, & Holmes, 2013; Nicholson, Roser, & Bach, 2017; van Elk, van Schie, & Bekkering, 2008). Interestingly, the goal component explored in those different studies generally refers to the mechanical action involving the functional part of the tool and its associated object. Nevertheless, the results are frequently interpreted within the embodied-cognition framework, perhaps because of the absence of an alternative comprehensive framework. In this context, the reasoning-based framework (Osiurak et al., 2020), as well as relevant associated concepts as the action reappraisal idea (Federico & Brandimonte, 2019, 2020), might be useful to generate alternative predictions. Hopefully, this line of research might help open new avenues toward a better understanding of the neurocognitive bases of human tool use.

Conclusion

Tool use is a fundamental characteristic of human beings. Current theories of human tool use can be divided into two distinct approaches: mainstream “manipulation-based” the-ories which, by echoing the embodied-cognition account, consider tool use as deriving from past sensorimotor experi-ences, and “reasoning-based” theories, which explain tool use as an instance of problem-solving situations based on

technical reasoning. Our study provides answers related to the crucial role of both semantic and mechanical knowl-edge in the elaboration of the causal relationship between tools and goal achievement. In particular, by analysing the visual-attentional patterns associated with object-tool pairs, we found that participants focused on the tool’s manipula-tion area under thematically consistent conditions. Crucially, when tools appeared electrified or when the visuo-perceptual context was not action-prompting (i.e., thematically incon-sistent conditions), the tools’ functional areas were fixated longer than the tools’ manipulation areas, regardless of the presence of electricity. The results presented here suggest that an integrated approach, which incorporates reasoning-based, semantic and mechanical knowledge, as well as the concept of action reappraisal, may lead to a better under-standing of the mechanisms at the roots of human tool use.

Author contributions GF and MAB conceived and designed the study and the experiment. GF developed the experimental software, con-ducted the experiment, analysed the data, prepared the figures, and wrote the paper. MAB and FO revised the manuscript and provided critical comments and theoretical contribution. All authors approved the final version of the manuscript for submission.

Funding No funding was received.

Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability Software code and scripts are available on reasonable request to the corresponding author.

Compliance with ethical standards

Conflict of interest The authors declare that they have no conflict of interest.

Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. The Ethics Committee of the Suor Orsola Benincasa University approved the study.

Consent to participate Informed consent was obtained from all indi-vidual participants included in the study.

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