The N250 Brain Potential to Personally Familiar and Newly Learned Faces and Objects

Pierce, Lara Justine; Scott, Lisa; Boddington, Sophie; Droucker, Danielle; Curran, Tim; Tanaka, Jim

doi:10.3389/fnhum.2011.00111

ORIGINAL RESEARCH article

Front. Hum. Neurosci., 31 October 2011
Sec. Sensory Neuroscience
volume 5 - 2011 | https://doi.org/10.3389/fnhum.2011.00111

The N250 brain potential to personally familiar and newly learned faces and objects

Lara J. Pierce¹ Lisa S. Scott² Sophie Boddington³ Danielle Droucker⁴ Tim Curran³* James W. Tanaka⁵*

¹ Department of Psychology, McGill University, Montreal, QC, Canada
² Department of Psychology, University of Massachusetts Amherst, Amherst, MA, USA
³ Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
⁴ Department of Applied Psychology, University of Calgary, Calgary, AB, Canada
⁵ Department of Psychology, University of Victoria, Victoria, BC, Canada

Studies employing event-related potentials have shown that when participants are monitoring for a novel target face, the presentation of their own face elicits an enhanced negative brain potential in posterior channels approximately 250 ms after stimulus onset. Here, we investigate whether the own face N250 effect generalizes to other highly familiar objects, specifically, images of the participant’s own dog and own car. In our experiments, participants were asked to monitor for a pre-experimentally unfamiliar target face (Joe), a target dog (Experiment 1: Joe’s Dog) or a target car (Experiment 2: Joe’s Car). The target face and object stimuli were presented with non-target foils that included novel face and object stimuli, the participant’s own face, their own dog (Experiment 1), and their own car (Experiment 2). The consistent findings across the two experiments were the following: (1) the N250 potential differentiated the target faces and objects from the non-target face and object foils and (2) despite being non-targets, the own face and own objects produced an N250 response that was equal in magnitude to the target faces and objects by the end of the experiment. Thus, as indicated by its response to personally familiar and recently familiarized faces and objects, the N250 component is a sensitive index of individuated representations in visual memory.

Introduction

Successful face recognition depends on our ability to quickly and accurately individuate a particular face (e.g., our roommate, spouse, best friend) from the hundreds of faces that we encounter every day. The rapid face identification of people at the individual level is the hallmark of human face recognition processes (Tanaka, 2001). Amongst all the familiar faces that we individuate, perhaps, no face is as familiar or as relevant to us as our own face. In addition to its extensive familiarity, the own face is uniquely salient because it references one’s self-identity (Keenan et al., 2001). However, personal individuation is not unique to face recognition. A similar kind of individuation occurs when we reach for our favorite coffee mug in the kitchen cupboard or try to locate our car in a crowded parking lot. Whether the perception and identification of these highly familiar, personal objects recruits similar neural processes as the recognition of one’s own face is still an open question. Using event-related potentials (ERPs), we will compare brain activity to the participant’s own face and other personal objects (i.e., participant’s own dog and own car). We will further compare the brain activity to the participant’s own face and own objects to newly familiarized faces and objects that are individuated by a name label.

Studies measuring adult ERPs have shown that faces are differentiated from non-face objects by a larger negative potential recorded over posterior electrode locations, approximately 170 ms (N170) after stimulus onset (Bentin et al., 1996; Rossion et al., 2003). Traditionally, the N170 has not been found to distinguish familiar from unfamiliar faces (e.g., celebrities, politicians) or to be sensitive to memory related factors (Bentin and Deouell, 2000; Eimer, 2000; Schweinberger et al., 2002; Tanaka et al., 2006). However, recent investigations, incorporating adaptation techniques or other various individuation tasks have found N170 effects for repeated or familiar stimuli (Jemel et al., 2005, 2009; Jacques and Rossion, 2006; Kovacs et al., 2006; Caharel et al., 2009; Keyes et al., 2010), suggesting that the N170’s sensitivity to face familiarity may be task dependent.

In addition to being sensitive to the task, the N170 has also been found to distinguish among other important non-face objects present in the environment. For example, the N170 is larger in response to birds relative to dogs in bird experts, and to dogs relative to birds in dog experts (Tanaka and Curran, 2001). Moreover, training novices with cars or birds leads to increased N170 responses post-training relative to pre-training (Scott et al., 2006, 2008). Combined, these results suggest that the N170, traditionally thought to be part of a system involved in the initial early coding of face and face-like stimuli, is modulated by familiarity and experience for both faces and objects.

The N250 component, also recorded over posterior electrode locations, peaks approximately 250 ms after stimulus onset and, unlike the N170, is consistently found to index face familiarity and repetition (Schweinberger et al., 2002, 2004). For example, priming experiments have shown that repeated presentations of a familiar politician or celebrity elicit a larger N250 than repeated presentations of novel faces (Schweinberger et al., 2002, 2004). The N250 component is also sensitive to novel faces familiarized under laboratory training conditions (Tanaka et al., 2006) and to the presentation of a familiar person across multiple viewpoints (Kaufmann et al., 2009)¹. These results indicate that the N250 component indexes perceptual memory representations for faces at the level of the individual.

However, the N250 familiarity effect is not specific to faces, but can be elicited by familiar objects after expertise training (e.g., cars, birds; Scott et al., 2006, 2008). For example, participants trained to identify birds or cars at the subordinate-level (e.g., Snowy Owl, Subaru Outback) exhibit an enhanced N250 to subordinate-level trained birds or cars relative to individuals trained at the basic level (e.g., Owl, Sedan). This kind of subordinate-level expertise is also present when viewing a single, personalized object (Sugiura et al., 2005; Miyakoshi et al., 2007). For example, Miyakoshi et al. (2007) asked participants to passively view cups, shoes, hand bags, and umbrellas that were: (1) personal items belonging to the participant, (2) generically familiar items that were pre-experimentally known, but not personal items, or (3) novel items not known to the participants. The results showed a left-lateralized N250 component that distinguished personally familiar and generically familiar objects from novel and unfamiliar objects, suggesting that items previously known to participants accessed stored representations in visual memory.

Previous research suggests that the N250 differentiates objects of expertise and personally familiar objects from unfamiliar objects. However, the results do not address whether the N250 differentially modulates highly familiar faces from highly familiar objects. More specifically, to date no experiments have compared the N250 in response to the participant’s own face to the N250 in response to other highly familiar objects. Arguably, one’s own face is the definitive marker of self-identity and has been hypothesized to be our most distinctive physical feature (Tsakiris, 2008). It has been demonstrated that one’s own face is identified more quickly in a visual search task (Tong and Nakayama, 1999), shows greater hemispheric specialization (Keenan et al., 2003) and elicits enhanced fusiform gyrus activity (Kircher et al., 2001). It has also been hypothesized that one’s own face captures attentional resources (Brédart et al., 2006). For example, in a flanker task when participants were asked to judge whether two flanking digits were both even or odd, performance was significantly disrupted when the own face was centrally presented as a to-be-ignored stimulus (Devue and Bredart, 2008). Thus, the own face is a prepotent stimulus that seems to automatically grab the observer’s attention (for a revised account see Devue et al., 2009).

In the current study, we adapted a “Joe/No Joe” task previously used to test own face recognition, to examine the processing of highly familiar personal objects (Tanaka et al., 2006). In the “Joe/No Joe” task, participants are asked to actively monitor for a target face (“Joe”) that is sequentially presented along with two types of non-target faces: completely novel faces and the participant’s own face. It was found that despite its non-target status, the participant’s own face generated a robust N250 component equivalent to the target Joe face suggesting that the participant’s own face obligatorily activates a pre-existing representation (Tanaka et al., 2006). In the current study, participants were asked to monitor for a target face (Joe) and a target object (Joe’s dog or Joe’s car) that were shown among other novel faces, novel objects, the participant’s own face and a personally familiar object (Experiment 1: the participant’s own dog; Experiment 2: the participant’s own car). The primary objectives of this study were to test whether personally familiar objects elicit an obligatory N250 response similar to the N250 response produced by one’s own face and to compare the N250 response to the own face and own-object to the N250 response to the recently familiarized and task-relevant face (Joe) and object (Joe’s Dog, Joe’s Car).

Experiment 1

In Experiment 1, participants were asked to monitor for a novel face and a novel dog target that were serially presented among their own face and dog and novel face and dog stimuli.

Materials and Methods

Participants

Participants included 12 (3 male, 9 female) undergraduate students recruited from the University of Victoria, aged 22–40 years (mean = 27.25). Participants were right-handed and had normal or corrected-to-normal vision. All participants gave informed consent to participate in this study. Participants were pre-screened to ensure that they were not familiar with any of the other subjects in the study.

Each participant completed two sessions on different days. During the first session, pictures of the participants and their dogs were taken. During the second session ERPs and behavioral responses were recorded while participants completed a target-detection task. Participation in session two took approximately 2 h. Participants were paid $30 for their time.

Stimuli

Stimuli included full color photographs of 12 faces and 12 dogs. Photographs of faces and dogs were taken with a digital camera in a well-lit room under similar conditions and were equated for size, luminance, and contrast using Adobe Photoshop. All images were cropped to show only the face or dog stimuli and were placed on a gray background. The assignment of stimuli to each experimental condition (Joe, Own, Other) was counterbalanced across participants so that each participant was exposed to each face and dog equally, and each face/dog appeared in each condition. All stimuli were 270 × 360 pixels and were presented at a visual angle of 9.03° horizontal and 11.95° vertical. Images were presented on a computer monitor.

General procedure

All procedures were approved by the Institutional Review Board at the University of Victoria and were conducted in accordance with this approval. After digital photographs of participants’ own dog and face were taken, they returned on a different day to complete the Joe/No Joe task while both ERPs and behavioral measures of accuracy were recorded.

In the Joe/No Joe task (see Figure 1), participants were introduced to a face and dog target (e.g., “Joe”) and then viewed and responded to face or car stimuli that included pictures of their own face or dog, the “Joe” target face or dog and novel faces or dogs. After viewing each stimulus, participants were prompted to determine whether each face or dog was “Joe” or “not Joe” using two separate response buttons. Females saw six female “Jane” faces and males saw six male “Joe” faces including their own face, as well as the six dogs owned by the corresponding people. Each trial included the presentation of a fixation cross (500 ms), followed by the face or dog image (500 ms), followed by a blank screen for 1000 ms, followed by a response prompt which remained on the screen until a response was made, up to 3000 ms. Participants were instructed to respond only when prompted so that exposure and response were separated by a 1000-ms interval. Each participant completed 35 blocks of trials with self-paced rest breaks in between. Each block contained 24 trials; 2 presentations of each of the 6 faces and 6 dogs. Eight-hundred forty trials were completed in total.

FIGURE 1

Figure 1. Stimuli presentation; images presented for 500 ms followed by a “Joe?/Joe’s Dog?” forced choice response (duration 3000 ms). All images were presented subsequent to a fixation.

Electrophysiological procedure

Scalp voltages were collected with a 41-channel Easy Cap using Brain Vision Recorder software (Version 1.3, Brain Products, GmbH, Munich, Germany). Amplified analog voltages (Quick Amp, Brain Products, GmbH, Munich, Germany; 0.017–67.5 Hz bandpass, 90 dB octave roll off) were digitized at 250 Hz and collected continuously. Filter cutoffs during recording have cutoff frequencies defined at −3 dB amplitude reduction. Electrode impedances were kept below 10 kΩ throughout the experiment and eye movements were measured using electrodes placed on the left and right canthi and below the right eye. Offline, the EEG data were filtered at 0.1–40 Hz passband. High and low cutoff filters reduced amplitude by 3 dB at their cutoff frequencies, corresponding to a half power reduction. EEG data were re-referenced to combined left and right earlobes (Joyce and Rossion, 2005; Luck, 2005; similar to Tanaka and Pierce, 2008). Ocular artifacts were corrected using an algorithm (Gratton et al., 1983) and an artifact rejection was used to remove trials with a change in voltage of 35 μV or greater. 1000 ms segments of the EEG were extracted around the stimulus presentation (−200 to 800 ms) for each trial and participant. ERPs were baseline-corrected with respect to a 100-ms pre-stimulus interval. Data were then averaged across conditions (face/dog × Joe/own/other), and participants.

Statistical analyses

Accuracy in each condition was at ceiling and thus no analyses were conducted using measures of accuracy. Reaction times were recorded but were not considered informative due to the delayed nature of the paradigm in which participants were instructed not to respond until the prompt.

Electrophysiological analyses of each component of interest (N170; N250) were analyzed separately. The channels were selected by identifying the electrode locations in the right and left hemisphere with the largest N170 and N250 across all conditions (channels P07 and P08). For the N170 peak amplitude was determined by finding the latency of the maximum peak within a window of 110–190 ms. In order to minimize selection bias, peak times and channels were determined from ERPs that were averaged across all conditions. Mean amplitude was then calculated in a window ± 1 SD from average peak latency: 142–183 ms. For each participant, maximum (negative) peak amplitude and peak latency were calculated within the window of interest for the N170. Average latency values for peak amplitude were in turn used to determine the time window for the N170 mean amplitude calculation. Mean amplitude was calculated within the window of interest for the N250 based on visual inspection and previous research (235–335 ms; Scott et al., 2006, 2008; Tanaka et al., 2006), rather than the peak latency approach used for the N170, because N250 peaks are difficult to reliably measure in individual subjects². Statistical analyses were conducted on these mean amplitudes. Average amplitudes were submitted to a 2 Stimulus Type (face, car) × 3 Condition (Joe, own, other) × 2 Experimental half (first half, second half) × 2 Hemisphere (left, right) repeated measures ANOVA. Bonferroni corrected paired t-tests were conducted to follow-up significant effects, however uncorrected values are also shown below in order to elucidate some of the significant interactions.

Results and Discussion

Electrophysiological results

N170. Repeated measures ANOVA analyses revealed a main effect of stimulus type, due to a greater mean amplitude N170 to faces relative to dogs [F(1, 11) = 9.35, p < 0.05]. No other significant main effects were found (Figures 2A,B, 4, and 5). There was a significant interaction between stimulus type and hemisphere [F(1, 11) = 10.71, p < 0.01], and a significant experimental half by hemisphere interaction [F(1, 11) = 5.94, p < 0.05], which were qualified by a significant interaction between stimulus type, experimental half, and hemisphere [F(1, 11) = 4.66, p = 0.05]. This three-way interaction was due to the fact that the difference between faces and dogs occurred within the right hemisphere only, with greater amplitude N170s for faces relative to dogs (p < 0.01). While N170 amplitude for dogs was equal across hemispheres over time, from the first to the second half (p > 0.05), there was a marginal trend for faces to show greater N170 amplitude in the left hemisphere as compared to the right hemisphere, in the second half only (p = 0.10).

FIGURE 2

Figure 2. Comparison of mean amplitude of the N170 to Own, Target, and Other conditions across the first and second experimental halves for (A) Experiment 1 faces, (B) Experiment 1 dogs, (C) Experiment 2 faces, and (D) Experiment 2 cars. Error bars represent 95% confidence intervals. Experiment 1 electrode sites: average P07, P08; Experiment 2 electrode sites: Mean of electrodes in the left hemisphere (58, 59, 64, 65, and 70) and right (92, 97, 91, 96, 90, and 95) hemispheres, corresponding to regions between standard locations and O1/O2 and T5/T6.

A repeated measures ANOVA conducted on latency values with the factors stimulus type (face, dog), condition (own, Joe, other), and half (first, second) showed that the latencies were significantly longer for dogs (MN = 162.6 ms) than faces (MN = 149.1 ms), [F(1,11) = 39.93, p < 0.001].

N250. A significant main effect of condition [F(2, 22) = 19.12, p < 0.001] was found due to a greater (more negative) amplitude N250 to own stimuli and target stimuli relative to other stimuli (p < 0.01; Figures 3A,B, 4, and 5). There were significant interactions between condition and experimental half [F(2, 22) = 4.87, p < 0.05], and between condition and hemisphere [F(2, 22) = 5.78, p < 0.05]. Greater N250 amplitude was seen to both own and target stimuli when compared to other stimuli in the first and second halves of the experiment (all p < 0.01). N250 amplitude to own stimuli was equivalent to target stimuli across experimental halves. While N250 amplitude was equivalent for both own and target stimuli across hemispheres, greater N250 amplitude was observed for other stimuli in the left hemisphere when compared to the right (p < 0.01; see topographic maps in Figures 6 and 7).

FIGURE 3

Figure 3. Comparison of mean amplitude of the N250 to Own, Target, and Other conditions across the first and second experimental halves for (A) Experiment 1 faces, (B) Experiment 1 dogs, (C) Experiment 2 faces, and (D) Experiment 2 cars. Error bars represent 95% confidence intervals. Experiment 1 electrode sites: average P07, P08; Experiment 2 electrode sites: Mean of electrodes in the left hemisphere (58, 59, 64, 65, and 70) and right (92, 97, 91, 96, 90, and 95) hemispheres, corresponding to regions between standard locations and O1/O2 and T5/T6. *p < 0.05, ⁺p = 0.07.

FIGURE 4

Figure 4. Comparison of ERP waveforms from stimulus onset to Own, Target, and Other conditions for Experiment 1 faces (A) first half left hemisphere, (B) second half left hemisphere, (C) first half right hemisphere, and (D) second half right hemisphere. Left hemisphere electrode: P07; Right hemisphere electrode: P08.

FIGURE 5

Figure 5. Comparison of ERP waveforms from stimulus onset to Own, Target, and Other conditions for Experiment 1 dogs (A) first half left hemisphere, (B) second half left hemisphere, (C) first half right hemisphere, and (D) second half right hemisphere. Left hemisphere electrode: P07; Right hemisphere electrode: P08.

FIGURE 6

Figure 6. Topographical maps for Experiment 1 faces showing the difference in amplitude between Own and Joe, Joe and Other, and Own and Other conditions during the first and second half of the experiment. Time points were selected as the average latency where differences across conditions were maximal.

FIGURE 7

Figure 7. Topographical maps for Experiment 1 dogs showing the difference in amplitude between Own and Joe, Joe and Other, and Own and Other conditions during the first and second half of the experiment. Time points were selected as the average latency where differences across conditions were maximal.

Although the stimulus type × condition × half interaction was not significant, pair-wise comparisons indicate different patterns of results for faces and dogs (Figures 3A,B for significance of pair-wise comparisons). Starting with the dogs, we found that both the own and target dogs elicited a more negative N250 than the other dogs in both the first and second halves of the experiment (p < 0.05 first half, p < 0.01 second half, uncorrected), with no differences between the own and target conditions (p > 0.10). Faces showed a similar pattern with own face eliciting a more negative N250 than other face (p < 0.001), a marginally significant difference between own and target faces (p < 0.07), and a significant difference between target and other faces (p < 0.01) in the first half. By the second half, own face and the target face were similar (p > 0.10), and both were more negative than other face (p < 0.001). By itself, this single marginal difference does not constitute much of a distinction between faces and dogs, but we point it out here because it was significantly replicated in Experiment 2.

Experiment 1 was designed to test the N250 familiarity effect shown in previous studies (e.g., Tanaka et al., 2006) both by replicating effects seen to own and experimentally familiarized faces, and investigating whether this process generalizes to own and experimentally familiarized non-face objects (i.e., dogs). With respect to the earlier N170 component, a face N170 effect was observed in which the N170 to faces was faster and greater than the N170 to dogs (e.g., Carmel and Bentin, 2002). Other differences were found between the N170 to faces and dogs. The N170 to faces was greatest over the right hemisphere whereas no hemisphere differences were observed for dogs. Both the face and dog N170 was not sensitive to familiarity to the extent that no within-category differences were observed between the own, Joe and other conditions for dogs or faces.

In contrast to the N170, the N250 showed sensitivity to familiarity, demonstrated by differences between the own, target, and other conditions. Both faces and dogs showed more negative N250s in response to the own and target conditions relative to the other condition. These results are similar to those previously reported by Tanaka et al. (2006), except that the previous experiment indicated that differences between the target and other conditions did not emerge until the second half – suggesting that learning the target face over the course of the experiment made the target familiarity effect slower to emerge than the immediate familiarity effect observed for the own face. However, consistent with Tanaka et al. (2006), the present experiment indicated a trend toward differences between the own and target faces in the first half of the experiment. Conversely, the own and target dog conditions showed absolutely no differences. Thus, the temporal dynamics of the own versus target familiarity effects may differ between dogs and faces, for reasons that will be examined in the General Discussion. Overall, these results suggest that increased N250 amplitude to familiar stimuli is not limited to human faces, as similar results were observed for both dogs and faces. Despite monitoring for the other target face and object stimuli, participants demonstrated a robust N250 to their own face and the face of their own dog. Experiment 2 was designed to determine whether this result is specific to living objects, such as human and animal faces or whether a self-relevance bias generalizes to non-living objects, such as one’s own car.

Experiment 2

In Experiment 2, participants were asked to monitor for novel face and car targets that were presented serially among images of their own face, their own car and other novel car and face stimuli.