Is neural adaptation of the N170 category-specific? Effects of adaptor stimulus duration and interstimulus interval

https://doi.org/10.1016/j.ijpsycho.2015.02.030Get rights and content

Highlights

  • Neural adaptation of the N170 was not stimulus category-specific.

  • Category adaptation effects were also found for the visual P1 component.

  • Adapting stimulus duration modulated N170 amplitudes evoked by test stimuli.

Abstract

Neural adaptation paradigms have been used in the electrophysiological and neuroimaging literature to characterise neural populations underlying face and object perception. It was recently reported by Nemrodov and Itier (2012) that adaptation of the N170 event-related potential (ERP) component is not stimulus category-specific over rapid adapting stimulus durations (S1 durations) and interstimulus intervals (ISIs). We therefore tested the category-specificity of adaptation over a range of S1 durations and ISIs. Faces and chairs were presented at S1 (for 200, 500 or 1000 ms) and S2 (for 200 ms), over a variable ISI (200 or 500 ms). Mean amplitudes of the P1, N170 and P2 visual ERP components were measured following S1 and S2 stimuli. Faces at S1 led to the smallest (i.e., most adapted) N170 amplitudes to both faces and chairs at S2, more than chairs at S1. N170s at S2 were smallest after a 500 ms S1 duration; but N170 amplitude did not vary over ISI. Effects were also seen for the two surrounding positive components, the P1 and P2. Presenting faces at S1 led to enhanced P1 amplitudes evoked by S2 chair stimuli. The P2 showed the smallest amplitudes following the shorter 200 ms ISI. These results indicate that adaptation of the N170 is not actually category-specific but instead dependent on the S1 category (regardless of S2 category), and may also be influenced by earlier effects at the P1 (i.e., not specific to the N170). This challenges the assumption that N170 category adaptation indexes effects on distinct neural populations that differ between faces and non-face objects.

Introduction

Human observers are highly proficient at recognising visual objects as abstract categories (e.g., faces, chairs, houses) and individual exemplars within a category (e.g., the face of a friend or one's own house). A long line of research has investigated how category and exemplar information is processed in the visual system. Neuroimaging experiments have identified a distributed network of face and object-selective areas in the ventral temporal cortex (Kanwisher and Yovel, 2006, Haxby et al., 2001, Malach et al., 1995; for a review see Grill-Spector and Weiner, 2014). Event-related potential (ERP) investigations have examined the time course of face and object perception through investigating face-sensitive ERP components such as the N170 (Bentin et al., 1996).

Researchers have utilised neural adaptation to characterise neuronal populations involved in visual processing (Grill-Spector and Malach, 2001, Koutstaal et al., 2001, Andrews and Ewbank, 2004). Neural adaptation, also called repetition suppression, refers to a reduction in neural population response to repetitions of the same or similar stimuli (for reviews see Grill-Spector et al., 2006, Henson, 2003). In the commonly used Adaptor-level Manipulation paradigm, an adapting stimulus (S1) and a subsequent test stimulus (S2) are presented within a trial. By presenting the same stimulus at S2 and manipulating the preceding S1 stimulus along a dimension of interest (e.g., stimulus category), one can assess whether differences along that dimension cause varying degrees of neural adaptation at S2; implying sensitivity to that dimension in the measured neuronal population. For example, if different stimulus categories at S1 cause varying degrees of neural response reduction at S2, this implies sensitivity to stimulus category in the neuronal population of interest.

Investigations of the N170 have varied stimulus categories at S1 and S2 to test for stimulus category-specific adaptation. The N170 is thought to index multiple sources of neural activity, including structural encoding of faces and objects, and integration of visual features into a meaningful percept (Bentin et al., 1996, Eimer, 2000, Jacques and Rossion, 2009, Rossion et al., 2000). Since the findings of category-specific adaptation for face and hand stimuli by Kovács et al. (2006), most N170 adaptation experiments have presented face and nonface object categories at S1, followed by faces at S2. In these experiments face-specific adaptation is defined as smaller N170s when S2 faces are preceded by S1 faces, compared to other S1 categories. Such an approach relies on the assumption that if stimulus categories other than faces were presented at S2 they would be maximally adapted by S1 stimuli of the same category (Nemrodov and Itier, 2012). This approach also assumes adaptation of distinct neural populations that differ between faces and non-face objects.

Following the study of Kovács et al. (2006) others have not reported category-specific adaptation for non-face objects at S2. Recent evidence from rapid adaptation experiments instead suggests that N170 adaptation is not category-specific. A series of experiments by Nemrodov and Itier, 2011, Nemrodov and Itier, 2012 presented face and non-face object categories (houses, cars and chairs) at S1 and S2. They found that the extent of N170 amplitude reduction at S2 depended on the stimulus category at S1. Importantly, these S1 category effects did not interact with S2 category, and therefore were not category-specific (for similar results see Eimer et al., 2010, Eimer et al., 2011).

Effects specific to S1 category, but not S2 category, challenge assumptions of adaptation of distinct neural populations for different stimulus categories. However, it is unclear whether this S1 category-dependent effect is particular to the rapid 200 ms S1 presentation durations and 200–250 ms ISIs used in experiments that reported these results (Nemrodov and Itier, 2011, Nemrodov and Itier, 2012, Eimer et al., 2010, Eimer et al., 2011). Whether S1 duration and ISI affect the specificity of category adaptation is unclear, as these experimental factors have not been systematically studied.

In addition to the N170, the P1 and P2 visual ERP components also show stimulus repetition effects to faces and non-face objects. P1 amplitude has been shown to differ by S1 category, and is typically enhanced for S2 stimuli following S1 faces (e.g., Kovács et al., 2006, Nemrodov and Itier, 2012, Xu et al., 2012). Adaptation during the time range of the P2 is sensitive to face identity (Schweinberger et al., 2004, Schweinberger et al., 2002, Xu et al., 2012) although identity-specific N170 adaptation has also been reported following long (3-second) S1 durations (Jacques et al., 2007, Caharel et al., 2009, Caharel et al., 2011).

The obvious step to determine whether category-specific adaption does operate, as captured by ERPs, is to systematically vary S1 and ISI durations. Varying S1 duration will identify whether adaptation is influenced by prolonged stimulus processing, as is the case in the auditory system (Lanting et al., 2013); while varying ISI will index the speed of recovery from adaptation. Therefore we systematically tested for differences in adaptation across S1 duration and ISI following faces and non-face objects. As the neural mechanisms of adaptation are currently unresolved (Grill-Spector et al., 2006, Gotts et al., 2012) identifying conditions under which category-specific adaptation occurs is necessary to validate category adaptation paradigms.

In addition to the N170 we measured the P1 and P2 visual ERP components to assess whether category adaptation effects are specific to the N170. We expected to find S1 category-dependent effects over rapid (200 ms) S1 and ISI durations, and category-specific N170 adaptation following longer (500 ms and 1000 ms) S1 durations.

Section snippets

Participants

Twenty people participated in this experiment. One participant was excluded from analyses due to poor task performance (correct responses to < 70% of target trials) and 3 others were excluded due to excessive EEG artefacts. The remaining 16 participants (6 males) were 20–35 years old (mean age 25.5 ± 4.6 years). All participants had normal or corrected-to-normal vision. Fifteen were right-handed and 1 was left-handed as assessed by the Flinders Handedness Survey (Nicholls et al., 2013). This study

Task performance

Overall task performance was 92.2% ± 6.5%. Mean response time was 482 ms ± 77 ms.

S1 stimulus analyses

Grand average waveforms to face and chair S1 stimuli are displayed in Fig. 2. For P1 mean amplitudes no main effects or interactions reached alpha-corrected significance. N170s evoked by faces were larger (more negative) than those evoked by chairs [main effect of S1 category, F(1,15) = 20.35, p < .001]. Analyses of P2 mean amplitudes revealed a main effect of hemisphere, showing larger P2 amplitudes in the right hemisphere

Discussion

We demonstrated the dynamic nature of neural adaptation by testing for stimulus category-specific effects while systematically varying S1 duration and ISI. Our N170 findings indicate that adaptation in vision is not category-specific over the tested S1 durations and ISIs; as faces at S1 adapted responses to both chairs and faces at S2. This also suggests that the category-specificity of adaptation is critically dependent on the S1 duration, and may be category-specific only after long (5-s) S1

Acknowledgements

We thank Ms. Lisa Kurylowicz for assistance with data collection. HADK was funded by a NHMRC Early Career Fellowship (GNT568890).

References (56)

  • W. Koutstaal et al.

    Perceptual specificity in visual object priming: Functional magnetic resonance imaging evidence for a laterality difference in fusiform cortex

    Neuropsychologia

    (2001)
  • G. Kovács et al.

    Adaptation duration affects the spatial selectivity of facial aftereffects

    Vis. Res.

    (2007)
  • L.K. Kuehl et al.

    Exploring the time course of N170 repetition suppression: a preliminary study

    Int. J. Psychophysiol.

    (2013)
  • D. Nemrodov et al.

    Is the rapid adaptation paradigm too rapid? Implications for face and object processing

    Neuroimage

    (2012)
  • M.F. Neumann et al.

    N250r and N400 ERP correlates of immediate famous face repetition are independent of perceptual load

    Brain Res.

    (2008)
  • M.E. Nicholls et al.

    The Flinders Handedness survey (FLANDERS): A brief measure of skilled hand preference

    Cortex

    (2013)
  • H. Sawamura et al.

    Selectivity of neuronal adaptation does not match response selectivity: a single-cell study of the FMRI adaptation paradigm

    Neuron

    (2006)
  • S. Schinkel et al.

    Modulation of the N170 adaptation profile by higher level factors

    Biol. Psychol.

    (2014)
  • S.R. Schweinberger et al.

    Event-related brain potential evidence for a response of inferior temporal cortex to familiar face repetitions

    Brain Res. Cogn. Brain Res.

    (2002)
  • C. Walther et al.

    Neural correlates of priming and adaptation in familiar face perception

    Cortex

    (2013)
  • C.L. Wiggs et al.

    Properties and mechanisms of perceptual priming

    Curr. Opin. Neurobiol.

    (1998)
  • I. Amihai et al.

    Neural adaptation is related to face repetition irrespective of identity: a reappraisal of the N170 effect

    Exp. Brain Res.

    (2011)
  • Y. Benjamini et al.

    Controlling the false discovery rate: a practical and powerful approach to multiple testing

    J. R. Stat. Soc. Ser. B Methodol.

    (1995)
  • S. Bentin et al.

    Electrophysiological studies of face perception in humans

    J. Cogn. Neurosci.

    (1996)
  • R. Desimone et al.

    Stimulus-selective properties of inferior temporal neurons in the macaque

    J. Neurosci.

    (1984)
  • M. Eimer

    The face-specific N170 component reflects late stages in the structural encoding of faces

    Neuroreport

    (2000)
  • M. Eimer et al.

    Response profile of the face-sensitive N170 component: a rapid adaptation study

    Cereb. Cortex

    (2010)
  • F. Fang et al.

    Duration-dependent FMRI adaptation and distributed viewer-centered face representation in human visual cortex

    Cereb. Cortex

    (2007)
  • Cited by (0)

    View full text