Differential cortical processing of local and global motion information in biological motion: An event-related potential study

Abstract

To reveal the neural dynamics underlying biological motion processing, we introduced a novel golf-swing point-light motion (PLM) stimulus with an adaptation paradigm and measured event-related potentials (ERPs). In the adaptation phase, PLM and scrambled PLM (sPLM) stimuli were presented; a static point-lights stimulus was also presented as a control condition. In the subsequent test phase, PLM or sPLM stimuli were presented. We measured ERPs from the onset of the test phase. Two negative components were observed and modulated differently: the amplitude of the N1 component was significantly attenuated by PLM and sPLM adaptation stimuli compared with the static point-light adaptation stimulus, whereas the amplitude of the N2 component in response to the PLM test stimulus was significantly attenuated only by the PLM adaptation stimulus. The amplitude of the N2 component in response to the PLM test stimulus was significantly larger than that in response to the sPLM test stimulus when a sPLM or static adaptation stimulus was used. These findings indicate that the N1 component is sensitive to local motion information while the N2 component is sensitive to the presence of a coherent form conveyed by global motion.

Introduction

Our visual system can extract much information on human actions from very limited cues. Biological motion (BM) is the phenomenon whereby one can perceive vivid actions with only several point-lights attached to the joints (Johansson, 1973). Interestingly, we can extract rich information from point-lights motion, such as identifying an individual (Cutting & Kozlowski, 1977), gender (Kozlowski & Cutting, 1977) or emotion (Dittrich, 1993). Recent behavioral studies have reported an adaptation effect on performance in a gender discrimination task using a point-light walker (Jordan, Fallah, & Stoner, 2006; Troje, Sadr, Geyer, & Nakayama, 2006). In these studies, participants were required to judge whether the presented neutral point-light walker was male or female after viewing the gait of one gender. Participants' judgments of gender based on gait were biased toward the opposite gender. This biased judgment implies that the adaptation effect was not simply due to local features of the stimuli, but instead relied upon the global motion of the figures. 

The roles of local and global motion information in BM processing have been previously discussed (Chang & Troje, 2008; Mather, Radford, & West, 1992; Shipley, 2003; Troje & Westhoff, 2006). For example, Mather et al. (1992) reported that performances on coherence and direction discrimination tasks were reliable only when the inter-frame interval and frame increments of the point-light stimulus were short. Interestingly, in recent behavioral studies, observers could reliably extract directional information even when the spatial structure of point-lights was distorted (Troje & Westhoff, 2006). We can also detect animacy and direction from local motion cues (Chang & Troje, 2008). Sensitivity to local motion information was also reported in four-day-old infants (Méary, Kitromilides, Mazens, Graff, & Gentaz, 2007). 

The role of global motion information has also been pointed out in neuropsychological studies (McLeod, Dittrich, Driver, Perrett, & Zihl, 1996; Schenk & Zihl, 1997a, 1997b; Vaina, Lemay, Bienfang, Choi, & Nakayama, 1990) and behavioral and neuroimaging studies (Beintema & Lappe, 2002; Bertenthal & Pinto, 1994; Michels, Lappe, & Vaina, 2005). For example, Vaina et al. (1990) reported that a patient who suffered from bilateral motion impairment and could not solve basic motion tasks could still perceive BM. Other behavioral studies also suggested a role for global pattern point-light motion rather than local motion information in BM perception (Beintema & Lappe, 2002). Michels et al. (2005) also found that the neuronal networks involved in BM perception are similar to those involved in the processing of BM stimuli without local motion, but that the latter type of stimulus was more strongly manifested in form-processing areas than motion-processing areas. These findings imply that not only local motion information, but also global motion pattern information, plays an important role in the processing of BM. 

Troje (2008) pointed out that although proponents for local or global processing argue for very different mechanisms, they share in common the assumption that BM perception is a unitary phenomenon. He proposed multi-level BM processing, including life detection, structure-from-motion, action recognition and style recognition (Troje, 2008). Such a multi-level view of BM processing motivated us to test for the existence of distinct neural mechanisms underlying local motion processing and global motion processing for BM perception. Previous ERP studies have detected two negative components at around 200 ms (N1) and 240–400 ms (N2) after the onset of a point-light walker stimulus in the bilateral occipitotemporal region (around T5 and T6 electrodes of the International 10–20 System) (Hirai, Fukushima, & Hiraki, 2003; Hirai, Senju, Fukushima, & Hiraki, 2005; Jokisch, Daum, Suchan, & Troje, 2005). The results of these studies demonstrated that the amplitude of the N1 component of the response to an upright point-light walker stimulus was significantly larger than that of the response to scrambled and inverted point-light walker stimuli. On the other hand, the amplitude of the N2 component of the responses to upright and inverted point-light walker stimulus was significantly larger than that of the response to a scrambled point-light walker stimulus. The authors of these studies proposed that the first component might reflect the processing of general motion information or the ‘pop-out’ effect of a moving dot pattern representing the highly familiar form of a human figure, and that the second component might be related to the specific analysis of biologically relevant information or form-from-motion processing. These ERP findings imply that at least two distinct processing events are involved in point-light walker perception within 400 ms of onset. 

However, it remained unclear if stimuli representing other kinds of action would also induce the two negative ERP response components: that is, if the two negative components were ‘specific’ to point-light walker perception or not. Moreover, because the visual stimuli were simply presented in previous ERP studies, it is hard to specify precisely the amount by which the visual stimulus modulates each ERP component. 

Therefore, we introduced (1) a novel action of point-light stimulus and (2) an adaptation paradigm to investigate the function of each component. Adaptation is the phenomenon in which the firing rates of responsive neurons and blood oxygen level-dependent (BOLD) signals are reduced when a particular stimulus is presented repetitively (Grill-Spector, Henson, & Martin, 2006; Krekelberg, Boynton, & van Wezel, 2006). The advantage of introducing an adaptation paradigm is that it enables the functional properties of cortical neurons to be probed in two stages, (adaptation and test phases) (Grill-Spector & Malach, 2001): if the signal remains adapted in the test phase despite a change of stimulus, it will indicate that the neurons are invariant to that attribute; if, however, the signal recovers in the test phase from the adapted state, it would imply that the neurons are sensitive to the property that was altered. Recent studies have revealed an adaptation effect not only for basic low-level visual dimensions, such as motion, orientation, spatial frequency or texture (Anstis, Verstraten, & Mather, 1998; Clifford, 2002; Durgin & Proffitt, 1996), but also for high-level visual processing, such as that of faces (Leopold, O'Toole, Vetter, & Blanz, 2001; Webster, Kaping, Mizokami, & Duhamel, 2004) or body parts (Kovács et al., 2006). This adaptation paradigm has also intensively introduced into ERP studies of motion perception (Heinrich, van der Smagt, Bach, & Hoffmann, 2004; Hoffmann, Unsöld, & Bach, 2001). It has been demonstrated that a negative deflection with a latency of around 150–200 ms (the N2 component in these studies) reflects cortical motion processing in humans (Bach & Ullrich, 1994; Heinrich et al., 2004; Hoffmann, Dorn, & Bach, 1999; Kubová, Kuba, Spekreijse, & Blakemore, 1995; Probst, Plendl, Paulus, Wist, & Scherg, 1993) and that this component is very susceptible to motion adaptation (Bach & Ullrich, 1994; Göpfert, Müller, & Hartwig, 1984; Wist, Gross, & Niedeggen, 1994). These studies demonstrated that the amplitude of the N2 component was reduced during the test phase when the motion direction of the test stimulus is identical to that of the adaptation stimulus (Hoffmann et al., 2001) or when both motion direction and velocity of the test stimulus are identical to those of the adaptation stimulus (Heinrich et al., 2004). These findings suggest that we should be able to specify the attributes of the visual stimulus that modulates the ERP component by introducing an adaptation paradigm. We presumed that if the observed components (N1 and N2) were functionally distinct, then each component would be modulated by a specific adaptation stimulus. Alternatively, if the components in the test phase functionally overlapped, the components would be equally modulated by the adaptation stimulus. In this study, we used an adaptation paradigm to reveal how both local and global motion information modulates each component. We used thee adaptation stimuli: point-light motion (PLM), scrambled PLM (sPLM) and a static point-light stimulus. For the sPLM stimulus, the number of point-lights and the velocity vectors of point-lights were identical to those of the PLM stimulus, but the initial starting positions were randomized. For the static point-light stimulus, the initial frame of the adaptation stimuli was presented during the adaptation phase. In the test phase, we used identical PLM and sPLM stimuli to those in the adaptation phase (for precise experimental settings, see below) and investigated how local and global motion information affects the neural responses to the test stimuli. 

Prior to the experiment, we hypothesized that if either component (N1 or N2) was sensitive to local motion information, the component observed in the test phase would be equally attenuated by both PLM and sPLM adaptation stimuli, because both stimuli had the same number of point-lights and identical velocity vectors. On the other hand, if either component was sensitive to global motion pattern information during the test phases, the component would be attenuated only when both adaptation and test stimuli were identical (that is, sPLM-sPLM or PLM-PLM). Furthermore, if either component was sensitive to the presence of a coherent form conveyed by global motion during the test phases, the component would be attenuated only when both adaptation and test stimuli were the PLM stimulus. 

Experiment 1

Methods

Participants

ERPs were recorded from 11 neurologically healthy human observers (Mean age = 28.5, SD = 3.2 years) with normal or corrected-to-normal visual acuity. All participants provided informed consent for the experimental protocol, which was approved by the Ethics Committee of the National Institute for Physiological Sciences. 

Experimental stimuli and task

Stimuli

We used two kinds of point-light motion stimuli ( Figure 1A): (1) a point-light motion (PLM) stimulus and (2) a scrambled point-light motion (sPLM) stimulus. The PLM (basic stimulus) was generated from a motion-captured stimulus that was available on the Internet. In the initial stimulus there were 26 point-lights; we reduced the number of point-lights to 13. The point-lights were attached to the head and major joints, and the animation looked like an individual performing a golf swing. The length of the animation was edited to 990 ms. This produced an animation in which a golf swing was immediately obvious to participants. In this experiment, the frame duration was 33 ms, which produced a smooth animation. 

Figure 1

 

(A) Example of the point-light motion (PLM) stimulus and scrambled point-light motion (sPLM) stimulus. To understand the stimulus more easily, the static noise point-lights are not presented in this figure. (B) To present a smooth animation, we superimposed four kinds of static point-lights on the PLM and sPLM animations: static point-lights of the initial and final frames of PLM and sPLM stimuli. As a result, participants could perceive a smoothly repeated point-light action, as if the point-lights appeared and disappeared among crowded static point-lights (see Figure 2D). In the actual stimulus, static noise dots were superimposed on the stimulus (see Figure 2D and text). In both PLM and sPLM stimuli, the number of point-lights and the velocity vector of each point were identical, but the initial positions of point-lights were different.

For the sPLM animation, the number of point-lights and their velocity vectors were identical to those in the PLM stimulus, but the initial position of each point-light was randomized, as used in previous studies (Grossman & Blake, 2002; Hirai et al., 2003; Jokisch et al., 2005). Thus, the participants perceived neither a human figure nor a global direction change, but only a swaying point-light motion. In a preliminary experiment, all participants (N = 11) correctly reported the golf-swing action from the PLM stimulus, However, no one reported such an action from the sPLM stimulus, but reported only swaying point-lights. We used six different kinds of sPLM stimuli: the initial positions of point-lights were different in each sPLM stimulus. In the sPLM adaptation condition, an identical pattern of sPLM stimulus was used during the adaptation and test phases (The effect of the initial position of point-lights was also confirmed in Experiment 2). 

In the present experiment, we adopted an adaptation paradigm as in previous motion ERP studies (Heinrich et al., 2004; Hoffmann et al., 2001). Thus, during the adaptation period, we presented the PLM or sPLM stimulus repeatedly. Because neither PLM nor sPLM stimuli were periodic actions, like the point-light walker developed by Cutting (1978), the positions of the point-lights in the initial frame were quite different from the positions of the point-lights in the end frame. Thus, we cannot present the animation smoothly when the stimulus is simply presented. To present a smooth animation, we superimposed four kinds of static point-lights on the PLM or sPLM animation (Figure 1B): static point-lights of the initial and final frames of PLM and sPLM stimuli. As a result, participants could smoothly perceive the repeated point-light action, as if the point-lights appeared and disappeared among crowded static point-lights (Figure 2D, Movie 1). Since we superimposed the static point-lights on the point-light motion stimulus, it was hard for participants to distinguish the PLM stimulus from the sPLM stimulus at the presentation of the initial frame of the point-light stimulus. Consequently, the total number of point-lights was 65, including the point-light motion stimulus (PLM or sPLM stimulus). The spatial distribution of point-lights in the initial frame was identical across conditions. 

Figure 2

 

Experimental procedure. (A) In the PLM adaptation condition, the adaptation stimulus was the PLM stimulus. (B) In the sPLM adaptation condition, the adaptation stimulus was the sPLM stimulus. (C) In the static adaptation condition, the adaptation stimulus was the static point-lights (four kinds of static point-lights were superimposed on the stimulus: static point-lights of the initial and final frames of PLM and sPLM stimuli). The alignment of point-lights in the initial frames of PLM and sPLM conditions was identical. In all conditions, both PLM and sPLM stimuli were presented equally frequently during the test phase. ERPs were recorded during the test phase. Note: to understand the stimulus more easily, the background static dots are not shown here in the adaptation phases shown in (A) and (B), or in the test phase. However, in the actual experiment, the background static dots were superimposed on the point-light motion stimulus in both adaptation and test phases, as shown in (D). These static point-lights were always presented except during the fixation period. Participants perceived a point-light animation appearing from white point-light dots and disappearing to leave white point-light dots. Due to the presence of background static point-light dots, participants could perceive a smooth point-light animation in the adaptation phase.

 

Movie 1A

 

Movie 1B

 

Movie 1C

 

Movie 1D

 

Movie 1E

 

Movie 1F

 

Movie 1. This movie shows examples of the six conditions that we used in Experiment 1 demonstrating how the point-lights were moving. (A) PLM (adaptation phase)-PLM (test phase), (B) PLM-sPLM, (C) sPLM-PLM, (D) sPLM-sPLM, (E) Static-PLM, and (F) Static-sPLM conditions.

Stimuli were generated by custom-made programs running on PC-DOS ver 6.0, and were presented on a 20-inch CRT display at a viewing distance of 150 cm. Stimuli were displayed subtending a visual angle of 3 × 3°. The size of the visual stimulus was smaller than the receptive field size in the middle temporal area (Kastner et al., 2001; Yoshor, Bosking, Ghose, & Maunsell, 2007). All points were white (1.6 cd/m²) against a black background (0.4 cd/m²). A red fixation point was presented at the center of the screen throughout the experiment. 

Procedure

The experiment consisted of three experimental conditions: a PLM adaptation condition, a sPLM adaptation condition and a static adaptation condition ( Figure 2). In the PLM adaptation condition, the adaptation stimulus was the PLM stimulus, after which the PLM or sPLM stimulus was presented during the test phase. In the sPLM adaptation condition, the adaptation stimulus was the sPLM stimulus, after which the PLM or sPLM stimulus was presented during the test phase. For the static adaptation condition, the adaptation stimulus was the static point-light stimulus, after which the PLM or sPLM stimulus was presented during the test phase. ERPs were recorded during the test phase in all conditions. 

In a trial, stimuli were presented in a cyclic design. A stimulus trial of a total duration was about 9–10 sec. The experimental procedure consisted of five epochs, as shown in Figure 2: fixation (1120–1920 ms); static stimulus (320 ms); adaptation stimulus (PLM or sPLM or static stimulus; 2970 ms); static stimulus (512 ms); test stimulus (PLM or sPLM stimulus; 990 ms). During this 990-ms test epoch, ERPs were recorded. The test stimuli were presented randomly. 

The whole experiment consisted of three blocks. Each block was assigned a given experimental condition; within one block, the same adaptation stimulus was presented. A block consisted of four sessions. In one session, both PLM and sPLM test stimuli were presented 18 times. As a result, both PLM and sPLM test stimuli were presented 72 times respectively in a block. We randomized the order of the three adaptation blocks across participants. One block took about 20 minutes to complete. The entire experiment took about 1.5 hours, including experimental preparation, instruction and recording. 

Task

In order to attend participants' attention to the stimulus, participants were required to report whether the test stimulus was identical to the adaptation stimulus in both PLM and sPLM conditions. For the static adaptation condition, participants were required to report whether the test stimulus was identical to the test stimulus that was presented in a previous trial. To prevent contamination from motor-related responses, participants were required to press the button when the test stimulus had disappeared. 

EEG recording

Electroencephalograms (EEGs) were recorded with Ag/AgCl disk electrodes placed on the scalp at 20 locations: C3, C4, P3, P4, O1, O2, T3, T4, T5, T6, Fz, Cz, Pz, A1, A2, Nz, T5′, T6′, VEOG, and HEOG according to the International 10–20 System. T5′ and T6′ were located 2 cm below T5 and T6, as in our previous studies (Watanabe, Kakigi, & Puce, 2003). The impedance was maintained at less than 5 kΩ. All of the EEG signals were collected on a signal processor (EEG-1100, Nihon-Kohden, Tokyo, Japan). The bandpass filter was set at 0.1–100 Hz. 

All recordings were initially referenced to C3 and C4 (based on system settings) and later to the tip of the nose, as in a previous ERP study (Jokisch et al., 2005). The electrical potential was digitized at a 1000-Hz sampling rate, and data were stored on a computer disk for offline analysis. Vertical and horizontal electrooculograms (EOG) were recorded to monitor eye movements. 

Data analysis

In the off-line analysis of the EEG recordings, a 0.1 to 30 Hz bandpass filter (24 dB/octave) was applied to the data. Trials in which the EEG or EOG signal variation exceeded ±50 μV were discarded. The analysis window was extended for 990 ms following the onset of each test stimulus. The mean amplitude of 200 ms before the stimulus was used as the baseline (static point-lights period). The grand mean of the waveform was then calculated for each adaptation condition. 

We mainly focused on the two components (N1, N2) that were observed at the T5, T6, T5′, and T6′ electrodes, as in previous studies (Hirai et al., 2003; Jokisch et al., 2005). Each negative component was determined by a time frame. For N1, the time frame was set between 150 and 300 ms from the onset of the test stimulus presentation, while for N2 the time frame was between 300 and 450 ms from the onset of the test stimulus presentation, based on the preliminary experiment. We regarded the prominent negative peak response during each time window to represent the N1 and N2 ERP response components. In the experiment, we could not obtain clear ERP components from one participant; data from that participant was excluded from further analysis. 

Statistical analysis

For behavioral data, the correct rate was analyzed with a one-way analysis of variance (ANOVA) with adaptation condition (PLM, sPLM and static adaptation condition) as a factor. For ERP data, the peak amplitude and latency of both N1 and N2 components were subjected to a three-way ANOVA with hemisphere (left or right hemisphere), type of adaptation stimulus (PLM, sPLM or static), and type of test stimulus (PLM or sPLM) as factors. The analysis was performed for pairs of T5′/T6′ and T5/T6 electrodes separately. 

If the sphericity assumption was violated in Mauchly's sphericity test, then the Greenhouse-Geisser correction coefficient epsilon was used to correct the degrees of freedom, and then the F and P values were recalculated. We considered statistical significance as p < 0.05. 

Results

Behavior performance

Participants were required to report whether the test stimulus was identical to the adaptation stimulus in both PLM and sPLM conditions. In the static adaptation condition, participants were required to report whether the test stimulus was identical to the test stimulus that was presented in a previous trial. The rates of correct responses (means ± SE) were as follows: PLM adaptation condition, 98.6 ± 0.6%; sPLM adaptation condition, 93.4 ± 3.9%; static adaptation condition, 98.7 ± 0.5%. In statistical analysis, no significant effect of adaptation condition was observed [ F(2,18) = 1.8, p = 0.19]. 

ERP data

Grand-averaged ERP waveforms are shown in Figure 3. At T5′/T6′ electrodes, two negative components (N1 and N2) were prominent. We applied statistical analysis to both N1 and N2 components as described below. 

Figure 3

 

Grand-averaged ERP waveforms (N = 10) at the T5/T6 (upper panel) and T5′/T6′ electrodes (bottom panel) in each experimental condition. In the adaptation phase, three kinds of stimuli (PLM or sPLM or static stimulus) were presented. In the test phase, two kinds of visual stimuli (PLM or sPLM) were presented. Two negative components were dominantly observed at the T5′/T6′ electrodes.

N1 component

T5′/T6′ electrodes

For the N1 amplitude, main effects of hemisphere [ F(1,9) = 11.6, p < 0.01] and adaptation stimulus [ F(2,18) = 16.4, p < 0.01] were significant ( Figure 4). Specifically, the N1 amplitude in the right hemisphere was significantly larger than that in the left hemisphere (−3.0 ± 0.3 vs. −3.9 ± 0.5 μV; mean ± SE). The N1 amplitude in response to the static adaptation stimulus was also significantly larger than those in response to the PLM adaptation stimulus (−4.7 ± 0.3 vs. −2.8 ± 0.4 μV, p < 0.01) and the sPLM adaptation stimulus (−4.7 ± 0.3 vs. −2.9 ± 0.5 μV, p < 0.01). 

Figure 4

 

The N1 and N2 amplitudes at the T5′/T6′ (left panel) and T5/T6 (right panel) electrodes. The top panel shows the N1 amplitudes and the bottom panel shows the N2 amplitudes. The thick lines indicate the PLM test stimulus and the dashed lines indicate the sPLM test stimulus. Error bars indicate the standard error (SE). * p < 0.05; ** p < 0.01. ( Note: the amplitude of the N2 component of the responses to static and sPLM adaptation stimuli at the T5′/T6′ electrodes was significantly larger than that of the responses to the PLM adaptation stimulus only in response to the PLM test stimulus; statistical significance is represented with a square.)

For the N1 latency, no significant effect was observed ( Fs < 1.8, ps > 0.19). 

T5/T6 electrodes

For the N1 amplitude, the interaction between adaptation stimulus and test stimulus was significant [ F(2,18) = 4.0, p < 0.05] ( Figure 4). Subsequent analysis revealed that the N1 amplitude in response to the PLM test stimulus was significantly larger than that in response to the sPLM test stimulus when the adaptation stimulus was static (−5.4 ± 0.5 vs. −4.1 ± 3.8 μV, p < 0.01). Moreover, the N1 amplitude in response to the static adaptation stimulus was significantly larger than those in response to the PLM and sPLM adaptation stimuli when the test stimulus was the PLM stimulus (static vs. PLM: −5.4 ± 0.5 vs. −2.6 ± 0.5 μV, p < 0.01; static vs. sPLM: −5.4 ± 0.5 vs. −3.1 ± 0.6 μV, p < 0.01) or the sPLM test stimulus (static vs. PLM: −4.1 ± 0.4 vs. −2.7 ± 0.4 μV, p < 0.01; static vs. sPLM: − 4.1 ± 0.4 vs. −2.4 ± 0.5 μV, p < 0.01). 

For the N1 latency, a three-way interaction (hemisphere, adaptation stimulus and test stimulus) was observed [ F(2,18) = 3.9, p < 0.05] ( Figure 5). We then carried out two 2-way ANOVAs for each hemisphere. In the left hemisphere (T5), the N1 latency in response to the PLM test stimulus was significantly delayed compared with that in response to the sPLM test stimulus when the adaptation stimulus was the sPLM stimulus (245 ± 16.2 vs. 207.6 ± 16.0 ms, p < 0.01). Moreover, the N1 latency in response to the sPLM adaptation stimulus was significantly shorter than those in response to the PLM adaptation stimulus (207.6 ± 16.0 vs. 235.1 ± 14.8 ms, p < 0.01) and the static adaptation stimulus (207.6 ± 16.0 vs. 241.5 ± 11.6 ms, p < 0.01) when the test stimulus was the sPLM stimulus. In the right hemisphere (T6), the main effect of adaptation stimulus was significant [ F(2,18) = 3.6, p < 0.05]. Subsequent analysis revealed that the N1 latency in response to the static adaptation stimulus was significantly delayed compared with that in response to the sPLM adaptation stimulus (233.0 ± 10.8 vs. 217.7 ± 12.5 ms, p < 0.05). 

Figure 5

 

The N1 and N2 latencies at T5′/T6′ (left panel) and T5/T6 (right panel) electrodes. The top panel shows the N1 latencies and the bottom panel shows the N2 latencies. The thick lines indicate the PLM test stimulus and the dashed lines indicate the sPLM test stimulus. Error bars indicate the standard error ( SE). * p < 0.05; ** p < 0.01. ( Note: the latencies of the responses to the PLM and static adaptation stimuli at the T5′/T6 electrodes were significantly delayed compared with that in response to the sPLM adaptation stimulus only with the sPLM test stimulus; statistical significance is represented with a triangle.)

N2 component

T5′/T6′ electrodes

For the N2 amplitude, the interaction between adaptation stimulus and test stimulus was significant [ F(2,18) = 16.3, p < 0.01]. Moreover, the interaction between hemisphere and test stimulus was significant [ F(2,18) = 6.3, p < 0.05] ( Figure 4). Subsequent analysis revealed that the N2 amplitude in response to the PLM test stimulus was significantly larger than that in response to the sPLM test stimulus when the adaptation stimulus was the sPLM stimulus (−5.1 ± 0.7 vs. −2.2 ± 0.6 μV, p < 0.01) or the static stimulus (−5.3 ± 0.6 vs. −3.3 ± 0.7 μV, p < 0.01). Moreover, the N2 amplitudes in response to the static adaptation stimulus and sPLM adaptation stimulus were significantly larger than that in response to the PLM adaptation stimulus when the test stimulus was the PLM stimulus (static vs. PLM: −5.3 ± 0.6 vs. −3.1 ± 0.5 μV, p < 0.01; sPLM vs. PLM: −5.1 ± 0.7 vs. −3.1 ± 0.5 μV, p < 0.01). The N2 amplitude in response to the PLM test stimulus was significantly larger than that in response to the sPLM test stimulus in both hemispheres (LH: −4.1 ± 0.4 vs. −2.9 ± 0.6 μV, p < 0.01; RH: −4.9 ± 0.4 vs. −2.8 ± 0.5 μV, p < 0.01). 

For the N2 latency, no significant effect was observed ( Fs < 2.8, ps > 0.13). 

T5/T6 electrodes

For the N2 amplitude, the interaction between adaptation stimulus and test stimulus was significant [ F(2,18) = 7.9, p < 0.01] ( Figure 4). Subsequent analysis revealed that the N2 amplitude in response to the PLM test stimulus was significantly larger than that in response to the sPLM test stimulus when the adaptation stimulus was the sPLM stimulus (−3.2 ± 0.7 vs. −1.0 ± 0.5 μV, p < 0.01) or the static stimulus (−2.2 ± 0.7 vs. −1.2 ± 0.9 μV, p < 0.05). 

For the N2 latency, the main effect of adaptation stimulus was significant [ F(2,18) = 5.0, p < 0.05] ( Figure 5). Subsequent analysis revealed that the N2 latency in response to the static adaptation stimulus was significantly delayed compared with that in response to the sPLM adaptation stimulus (419.2 ± 15.4 vs. 374.2 ± 23.7 ms, p < 0.05). 

Discussion

The results of Experiment 1 can be summarized as follows. For the N1 component, (1) the peak amplitudes did not differ much between the PLM adaptation and sPLM adaptation conditions, while the N1 amplitude under PLM and sPLM adaptation conditions was much smaller than that following adaptation with static point-light displays, and (2) the difference in the N1 amplitudes at the T5′/T6′ electrodes induced by PLM and sPLM test stimuli was small, and did not reach significance. For the N2 component, the amplitude of the response to the PLM test stimulus was significantly larger than that of the response to the sPLM test stimulus when the adaptation stimulus was sPLM or static ( Figure 4). Additionally, the N2 amplitude in response to the PLM test stimulus was significantly modulated by adaptation stimulus, but that in response to the sPLM test stimulus was not significantly modulated by adaptation stimulus at T5′/T6′ electrodes ( Figure 4). That is, the N2 amplitude in response to the PLM test stimulus was significantly attenuated in the PLM adaptation stimulus condition compared with the sPLM and static adaptation stimulus conditions. Contrary to the PLM test stimulus, no significant attenuation was observed with the sPLM test stimulus. This is probably because the response to the sPLM test stimulus was weak compared with that to the PLM test stimulus; thus, there is no room for an adaptation effect in this N2 component. These findings imply that the N1 component is related to the processing of local motion information and that the N2 component is sensitive to the presence of form coherence, which is inherent in global motion (for further discussion, see General discussion). 

In Experiment 1, because we used identical adaptation and test stimuli in some conditions (PLM adaptation with the PLM test condition and sPLM adaptation with the sPLM test condition), the modulated neural activities in the test phase might be due to the initial location of point-light motion. To verify this possibility, we conducted Experiment 2. 

Experiment 2

In this experiment, we tried to clarify whether the initial location of the point-light stimulus in the adaptation and test phases would modulate the two ERP components in the test phase. 

Methods

Participants

In Experiment 2, eight participants (six of whom took part in Experiment 1 and two of whom were new) were enrolled (mean age = 28.5, SD = 3.4). 

Experimental stimuli and task

Stimuli

The stimuli and apparatus were identical to those described for Experiment 1. 

Procedure

The additional experiment consisted of three conditions: the sPLM-same adaptation condition, the sPLM-diff adaptation condition and the sPLM-PLM adaptation condition ( Movie 2). For the sPLM-same adaptation condition, the adaptation stimulus was a sPLM stimulus; then, the identical sPLM stimulus was presented during the test phase. For the sPLM-diff adaptation condition, the adaptation stimulus was a sPLM stimulus; then, a different pattern of sPLM stimulus was presented during the test phase. For the sPLM-PLM adaptation condition, the adaptation stimulus was a sPLM stimulus; then, a PLM stimulus was presented during the test phase as in Experiment 1. In the test phase, an identical sPLM stimulus was presented in sPLM-same and sPLM-diff conditions. 

 

Movie 2A

 

Movie 2B

 

Movie 2C

 

Movie 2. This movie shows examples of the three conditions that we used in Experiment 2 demonstrating how the point-lights were moving. (A) sPLM-same, (B) sPLM-diff, and (C) sPLM-PLM conditions.

In a trial, stimuli were presented in a cyclic design as mentioned in Experiment 1. The whole experiment consisted of six sessions. In one session, each set of stimuli was presented 12 times; thus, each sPLM test stimuli was presented 72 times during the experiment. One session took about 5 minutes to complete. The entire experiment took about one hour, including experimental preparation, instruction and recording. 

Task

In Experiment 2, as in Experiment 1, participants were required to report whether the test stimulus was identical to the adaptation stimulus in all experimental conditions. 

EEG recording and data analysis

EEG recording was identical to that described for Experiment 1 except for the location of the electrodes. In Experiment 2, we focused on the activities at the bilateral occipitotemporal electrodes. We placed electrodes at 11 locations: C3, C4, T5, T6, A1, A2, Nz, T5′, T6′, VEOG and HEOG). In the present analysis, we focused on the neural activities at the T5′/T6′ electrodes, because we found a clear adaptation effect at these electrodes in Experiment 1. In the following analysis, we analyzed only the T5′/T6′ electrodes. 

Statistical analysis

For behavioral data, the correct rate was analyzed with a one-way analysis of variance (ANOVA) with adaptation condition (sPLM-same, sPLM-diff and sPLM-PLM adaptation conditions) as factors. For ERP data, the peak amplitudes and latencies of both N1 and N2 components were subjected to two-way ANOVAs with hemisphere (left or right hemisphere) and type of adaptation stimulus (sPLM-same, sPLM-diff and sPLM-PLM) as factors. 

Results

Behavioral performance

Participants were required to report whether the test stimulus was identical to the adaptation stimulus in all conditions. The rates of correct responses (means ± SE) were as follows: sPLM-same condition, 97.3 ± 3.7%; sPLM-diff condition, 97.7 ± 2.5%; sPLM-PLM condition, 99.0 ± 2.6%. In statistical analysis, no significant effect of adaptation condition was observed [ F(2,12) = 1.0, p = 0.38]. 

ERP data

Grand-averaged ERP waveforms are shown in Figure 6. In Experiment 1, we observed an adaptation effect at the T5′/T6′ electrodes; thus, we focused on these electrodes in the analysis. At these electrodes, two negative components (N1 and N2) were prominent, as in the main experiment. We applied statistical analysis to both peak amplitudes and latencies of N1 and N2 components, as in the above experiment. 

Figure 6

 

(A) Grand-averaged ERP waveforms (N = 7) at the T5′/T6′ electrodes. The thick line indicates the sPLM-PLM condition, the dashed line indicates the sPLM-same condition and the thin line indicates the sPLM-diff condition. Two negative components were dominantly observed. (B) The bar graph indicates the N1 amplitudes (left panel) and N2 amplitudes (right panel). (C) The bar graph indicates the N1 latencies (left panel) and N2 latencies (right panel). Error bars indicate the standard error (SE). * p < 0.05; ** p < 0.01.

We could not obtain a clear ERP component from one participant; thus, data from that participant has excluded from further analysis. For the N1 amplitude, the main effect of hemisphere was significant [ F(1,6) = 7.9, p < 0.01], suggesting that the N1 amplitudes were greater in the right hemisphere than in the left (left hemisphere: −1.7 ± 0.5 vs. −2.6 ± 0.5 μV). For the N1 latency, no significant effect was observed ( Fs < 2.1, ps > 0.17). For the N2 amplitude, the interaction between hemisphere and condition was significant [ F(2,12) = 5.4, p < 0.05], suggesting that the N2 amplitude in the right hemisphere was significantly larger than that in the left hemisphere (−4.5 ± 1.0 vs. −2.9 ± 1.2 μV, p < 0.01) in the sPLM-PLM condition and that the amplitude induced by the PLM stimulus was significantly larger than those induced by the sPLM stimulus conditions (sPLM-PLM vs. sPLM-same, −4.5 ± 1.0 vs. −0.78 ± 0.8 μV, p < 0.05; sPLM-PLM vs. sPLM-diff, −4.5 ± 1.0 vs. −0.68 ± 0.8 μV, p < 0.05), in the right hemisphere. For latency, no significant effect was observed ( Fs < 0.8, ps > 0.47). 

Discussion

The results of Experiment 2 revealed that neither N1 nor N2 amplitude was affected by the initial position of point-lights in either the sPLM-same or sPLM-diff condition ( Figure 6A). As in Experiment 1, the N2 amplitude induced by the PLM stimulus was significantly larger than that induced by the sPLM stimulus. This suggests that the modulation of the N1 component was not simply due to information regarding the locations of point-lights, but also to the motion of each point-light. Moreover, the N2 component was not significantly modulated by the initial position of point-lights in either the sPLM-same or sPLM-diff condition, implying indirectly that a difference in the locations of the initial point-lights would not contribute to the modulation of the N2 component observed in Experiment 1. 

General discussion

In the present experiment, we elucidated the functional dissociation between N1 and N2 component by using an adaptation paradigm. We introduced a novel point-light motion stimulus (golf-swing point-light motion) and confirmed two negative components as in previous ERP studies using a point-light walker stimulus (Hirai et al., 2003; Jokisch et al., 2005). The results suggested that the two observed negative components are not exclusively evoked by the point-light walker stimulus, but that other kinds of point-light motion can elicit them. Moreover, we also found that the N1 component seems to be sensitive to local motion information (Experiment 1) and the N2 component seems to be sensitive to the presence of a coherent form conveyed by global motion (Experiment 1). Further, neither component appears to be sensitive to the initial locations of point-lights (Experiment 2). 

For the N1 component, the effect of test stimulus was not significant at the T5′/T6′ electrodes, but the adaptation stimulus significantly affected the component: the amplitude of the response to the static adaptation stimulus was significantly larger than that of the responses to the PLM and sPLM adaptation stimuli. This implies that when the adaptation stimulus contains motion information, irrespective of global motion pattern information, the N1 amplitude in response to the test stimulus is attenuated. The result of the subsequent experiment ( Experiment 2) suggested that the N1 amplitude was not simply modulated by the initial positions of point-lights ( Figure 6A). This suggests that the N1 component is not modulated by the initial location of each point-light, but by the local motion of each point-light. This result seems to support our hypothesis that the first component is sensitive to local motion information. This finding seems to also be consistent with previous motion adaptation ERP studies. It has been reported that the negative component observed at around 200 ms is attenuated when the adaptation stimulus is a motion stimulus rather than a static stimulus (‘baseline condition’ in that study) (Heinrich et al., 2004; Hoffmann et al., 2001). At the T5/T6 electrodes, in addition to the significant effect of the adaptation stimulus, the interaction between adaptation stimulus and test stimulus was also significant: the N1 amplitude in response to the PLM test stimulus was significantly larger than that in response to the sPLM test stimulus when the adaptation stimulus was static. This implies that the N1 component is modulated by global motion pattern information only when the adaptation stimulus is static. This result also seems to be consistent with previous ERP studies (Hirai et al., 2003; Jokisch et al., 2005). In these ERP studies, the amplitude of the first negative component in response to a point-light walker stimulus was significantly larger than that in response to a scrambled point-light walker stimulus. In these studies, a blank screen was preceded by the point-light or scrambled point-light walker stimulus. Based on their results, these authors hypothesized that the N1 component would reflect not only the processing of general motion information, but also the ‘pop-out’ effect of a moving dot pattern representing the highly familiar form of a human figure, because the amplitude of the response to the upright point-light walker stimulus was significantly larger than that of the response to inverted- and scrambled- point-light walker stimuli (Jokisch et al., 2005). This implies that the global pattern of point-light information that represents a human figure would also modulate the N1 component when the preceding stimulus is static. Thus, the N1 component might be partly related to the processing of human body shape, as reported in previous ERP studies (Peelen & Downing, 2007; Stekelenburg & de Gelder, 2004). The results from T5′/T6′ and T5/T6 electrodes suggest that the N1 component is sensitive to local motion information when the adaptation stimulus contains motion information, but that it would also be sensitive to global motion pattern information when the preceding stimulus is static at particular electrodes. 

It should be noted that the size of the visual stimulus in the present experiment was 3 × 3°. The size of the visual stimulus was much smaller than the receptive field size in the higher visual areas, such as the middle temporal region (Kastner et al., 2001; Yoshor et al., 2007). Thus, we presumed that the difference in the initial positions of point-lights between PLM and sPLM stimuli would not have a significant effect in the present experiment. 

Thus, is the N1 component specific to biological motion or does it represent a general response to visual motion? We cannot directly answer this question from our present results; however, we can consider the possibility of the modulation of this component by the characteristic of local motion of point-lights. That is, this N1 component was modulated by motion information such as direction (Hoffmann et al., 2001) or both motion direction and velocity (Heinrich et al., 2004). Therefore, it is possible that the differential characteristics of local motion information, such as motion velocity or direction, modulate this component, implying that differential modulation of the component might be observed between responses to biological motion stimuli and non-biological motion. Further studies should address this issue, but we should pay attention to differences in the characteristics of point-light stimuli. In a previous behavioral experiment, Mather et al. (1992) pointed out the importance of ankle motion for biological motion: the performances on coherence and direction discrimination tasks were affected by the omission of wrist and ankle dots. More recently, Troje and Westhoff (2006) reported that observers can correctly detect the direction of point-light motion even when the spatial structure of point-light was scrambled. In their findings, the directional information can be carried by the motion of a human's or animal's foot or wrist. These findings imply that the characteristics of point-lights representing feet or wrists might be different from those of point-lights representing other body sites. In future studies, we should also investigate the relationship between the modulation of the N1 component and this characteristic of point-lights. 

For the N2 component, the amplitude of the response to the PLM test stimulus was significantly larger than that of the response to the sPLM test stimulus when the adaptation stimulus was sPLM or static. Additionally, the N2 amplitude in response to the PLM test stimulus was significantly modulated by adaptation stimulus: the N2 amplitude in response to the PLM test stimulus was significantly attenuated in the PLM adaptation stimulus condition compared with the sPLM and static adaptation stimulus conditions. Moreover, no significant attenuation of N2 amplitude was observed in response to the sPLM test stimulus. These findings imply that the N2 component is sensitive to the presence of form coherence, which is inherent in global motion information. Contrary to the PLM test stimulus, no significant attenuation of the N2 amplitude was observed in response to the sPLM test stimulus; this is probably because the response to the sPLM stimulus was weak compared with that to the PLM test stimulus; thus, we might not be able to detect a significant effect of the adaptation stimulus. 

In the present experiment, however, because a PLM test stimulus is followed by the same PLM adaptation stimulus, it is possible that the N2 component was also attenuated by identical local motion information. In previous ERP and magnetoencephalography (MEG) studies of motion perception (Heinrich et al., 2004; Hoffmann et al., 2001; Lam et al., 2000), a prominent single peak component was observed at around 200 ms. Contrary to these findings, the latency of the N2 component here was delayed about 150–200 ms compared with earlier results, thus the effect of local motion information might be minimized in this time period. However, if the adaptation weakens the magnitude of the local signals that feed into the global motion process, then the attenuation of N2 component might be observed. For now, we cannot completely rule out the possibility of the contribution of local motion information to the N2 component, further studies are needed to address this issue. 

One might also think that the attenuation of the N2 component might be due to attentional modulation, as previously reported (Hirai et al., 2005). However, it is hard to presume an effect of visual attention, in part because the correct rate was not significantly different across all blocks. In the present task, participants were required to attend to the point-light motion patterns, so we presume that participants equally attended to the stimulus across blocks. 

The distinct processing of BM would seem to be consistent with previous neuropsychological studies. It has been reported that patients with severe loss of motion perception retain intact BM perception (McLeod et al., 1996; Schenk & Zihl, 1997a, 1997b; Vaina et al., 1990). These findings imply that the mechanism underlying BM processing is different from that underlying motion processing. Other behavioral studies also suggested a role for global patterns of point-light motion rather than local motion information in BM perception (Beintema & Lappe, 2002). These findings seem to support our present findings, specifically, that a distinct process from motion processing would exist in BM processing. Moreover, the present finding seems to be compatible with the multi-level view proposed by Troje (2008). 

Our present result contributes to investigations of the neural mechanisms underlying the effect of adaptation on the responses to BM stimuli, which have been reported in several behavioral studies (Jordan et al., 2006; Troje et al., 2006). According to these studies, the global pattern of point-light motion would also affect subsequent neutral BM processing. In the light of the present result, the N2 component might be modulated by the adaptation stimulus. 

In the present experiment, we used a novel point-light motion stimulus (golf-swing action) and observed differential modulation in the N1 and N2 components. It should also be clarified whether the adaptation effect would occur irrespective of action category. If the N2 component was sensitive to ‘general’ human actions, the component would be attenuated irrespective of action category in the adaptation phase. On the other hand, if the N2 component was sensitive to ‘specific’ human action, the component would be attenuated when the point-light stimuli in the adaptation phase and test phase were identical. Moreover, we should also focus on the differential scalp topography pattern across categories. Further studies are necessary to clarify these points. 

Acknowledgments

We thank two anonymous reviewers for suggestions. We thank Mr. Y. Takeshima and Ms. M. Teruya for technical support. We thank Dr. Matsuda at Iwate prefectural university for providing the motion-captured data. M.H. was supported by a Grant-in-Aid for JSPS Fellows No. 18-11826 from the Ministry of Education, Science, Sports, and Culture, Japan. 

Commercial relationships: none. 

Corresponding author: Masahiro Hirai. 

Email: [e-mail]. 

Address: Department of Integrative Physiology, National Institute for Physiological Sciences, 38 Nishigonaka, Myoudaiji, Okazaki, 444-8585, Japan.