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Available online at www.sciencedirect.com
www.elsevier.com/locate/brainres
Research Report
Spatial auditory regularity encoding and prediction: Human middle-latency and long-latency auditory evoked potentials M. Cornellaa,b, A. Bendixenc,d, S. Grimma,b,c, S. Leunga,b, E. Schro¨gerc, C. Esceraa,b,n a
Institute for Brain, Cognition and Behavior (IR3C), University of Barcelona, Catalonia, Spain Cognitive Neuroscience Research Group, Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Catalonia, Spain c Institute of Psychology, University of Leipzig, Leipzig, Germany d Auditory Psychophysiology Lab, Department of Psychology, Cluster of Excellence “Hearing4all”, European Medical School, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany b
art i cle i nfo
ab st rac t
Article history:
By encoding acoustic regularities present in the environment, the human brain can
Accepted 11 April 2015
generate predictions of what is likely to occur next. Recent studies suggest that deviations
Available online 22 April 2015
from encoded regularities are detected within 10–50 ms after stimulus onset, as indicated
Keywords:
by electrophysiological effects in the middle latency response (MLR) range. This is
Middle latency response
upstream of previously known long-latency (LLR) signatures of deviance detection such
Long latency response
as the mismatch negativity (MMN) component. In the present study, we created pre-
Prediction
dictable and unpredictable contexts to investigate MLR and LLR signatures of the encoding
Auditory regularity
of spatial auditory regularities and the generation of predictions from these regularities. Chirps were monaurally delivered in an either regular (predictable: left–right–left–right) or a random (unpredictable left/right alternation or repetition) manner. Occasional stimulus omissions occurred in both types of sequences. Results showed that the Na component (peaking at 34 ms after stimulus onset) was attenuated for regular relative to random chirps, albeit no differences were observed for stimulus omission responses in the same latency range. In the LLR range, larger chirp-and omission-evoked responses were elicited for the regular than for the random condition, and predictability effects were more prominent over the right hemisphere. We discuss our findings in the framework of a hierarchical organization of spatial regularity encoding. This article is part of a Special Issue entitled SI: Prediction and Attention. & 2015 Elsevier B.V. All rights reserved.
n Corresponding author at: Cognitive Neuroscience Research Group, Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Catalonia, Spain. Fax: þ34 93 4021584. E-mail address: [email protected] (C. Escera).
http://dx.doi.org/10.1016/j.brainres.2015.04.018 0006-8993/& 2015 Elsevier B.V. All rights reserved.
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1.
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Introduction
The brain constantly needs to encode the dynamic information present in the environment to make predictions about occurrences of future events, as well as to rapidly respond to unexpected events taking place. In the auditory domain this is done by encoding regularities from the mix of auditory information that surrounds us (Winkler et al., 2009), and by using the probabilistic information to predict what is likely to occur next (Schröger et al., 2014). Auditory events that do not match the current predictions elicit a frontocentrally negative event-related potential component termed mismatch negativity (MMN) (Näätänen et al., 2007). MMN occurs at about 150–200 ms after deviation onset, and is automatically generated by violations of auditory regularities that range from simple stimulus repetitions in oddball or roving standard paradigms (e.g., Haenschel et al., 2005) to complex statistical structures (Garrido et al., 2013), or even abstract sequence-based rules (e.g., Bendixen and Schröger, 2008; Tervaniemi et al., 1994). Therefore, the elicitation of MMN indirectly implies that the regularities present in the environment have been encoded (Schröger, 2007).The amplitude of the MMN is often interpreted as the magnitude of the prediction error signal which is the output from a comparison between the incoming information and a prediction based on recent stimulus history (Baldeweg, 2007; Friston, 2005; Garrido et al., 2009; Winkler, 2007). A more direct approach to examine the electrophysiological correlates of prediction is to use unexpected stimulus omissions (Bendixen et al., 2009; Hughes et al., 2001; Raij et al., 1997; Todorovic et al., 2011; Wacongne et al., 2011). This way, in the absence of a physical deviant stimulus it is possible to examine correlates of endogenous expectations once the regularity has been encoded. Omissions generate a response that resembles the actual stimulus evoked response, with sources located in similar regions as those activated when the acoustic stimulus was presented, suggesting the pre-activation of neural circuits needed to process the actual physical inputs (Hughes et al., 2001; Raij et al., 1997; SanMiguel et al., 2013; Wacongne et al., 2011). A striking feature of the ERP signatures of automatic auditory predictions is that they occur fast, within the first 80 ms after the expected stimulus onset (Bendixen et al., 2009; Winkler et al., 2009). Early cortical auditory evoked potentials (AEPs) correspond to the middle latency response (MLR), a series of components (P0, Na, Pa and Nb) that occur from 10 to 60 ms after stimulus onset (Picton et al., 1974) and are thought to originate in primary and secondary auditory areas (Yvert et al., 2001). Recent studies have shown that one or more components of the MLR can be modulated by deviant stimuli in oddball paradigms (Althen et al., 2011; Grimm et al., 2011; Recasens et al., 2014; Slabu et al., 2010), or by unexpected changes of single features like frequency or location in complex paradigms (Cornella et al., 2012; Leung et al., 2012). These findings suggest that the detection of auditory regularity violations, at least for simple regularities (i.e. stimulus or feature repetitions), takes place at earlier latencies than those corresponding to the MMN. Current theoretical frameworks emphasize that regularity encoding (and deviance
detection) develops in a hierarchical manner (for a review, see Escera and Malmierca (2014)). The present study aimed at examining ERP correlates of regularity encoding and stimulus predictions in the MLR and LLR ranges by using a more complex regularity than stimulus repetition. We designed two conditions differing in their degree of predictability with respect to stimulus location (Fig. 1). In the first condition, the stimuli were presented monaurally in a strictly alternating fashion (left–right–left– right–…) so that it was possible to predict the location of the next stimulus. In a second condition, the stimuli were randomly repeating or alternating (e.g., left–left–right–left–right– right–right–left–…), so that it was not possible to predict whether the next input would be presented from the left or the right. Additionally, we introduced rare omissions to probe correlates of stimulus prediction (i.e., auditory activity without tone input) in both the MLR and LLR ranges.
2.
Results
2.1.
Predictability effects in the MLR range
MLR analyses were confined to the Na component, as this was previously reported to be involved in location deviance detection (Cornella et al., 2012; Grimm et al., 2012; Sonnadara et al., 2006). The Na component amplitude elicited by the chirps at the midline electrode Fz (32–36 ms window) did not differ as a function of predictability (regular versus random condition) [t(20)¼ 1.277, p¼ 0.216] when keeping stimulus history identical across conditions (i.e., analyzing only alternation trials from the random condition). The omission responses were not dependent on predictability either when measured in the same time window [t(20) ¼0.661, p¼ 0.516] (Fig. 2). In order to investigate whether effects of predictability would be present at more lateral electrode sites, effects of lateralization on the chirp-evoked responses were examined in a repeated-measures analysis of variance (rm-ANOVA) with the factors stimulus location (left, right), hemisphere (F7, F8) and predictability (random, regular). Note that the same analysis was not possible for the omission-evoked responses due to low signal-to-noise ratio when splitting the omission trials by side of presentation. In the chirp-
Fig. 1 – Experimental design. Schematic representation of the random and regular conditions. Chirps delivered to the left are represented by the letter “L” and chirps delivered to the right are represented by the letter “R”. Omissions are shown in gray; in the regular condition they indicate the expected location of the stimulus.
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Fig. 2 – Middle latency response (MLR) to chirps and omissions. AEP waveforms in the MLR range elicited by chirps (solid lines) and omissions (dashed lines) for both the regular (gray) and the random (black) conditions at the Fz electrode.
evoked responses, a main effect of predictability [F(1,20)¼ 6.034, p¼ 0.023, η2p ¼ 0.232] was observed, with larger Na mean amplitudes elicited in the random condition (Fig. 3). There were no main effects of hemisphere or stimulus location [F (1,20)o1.616, p¼ 0.218, η2p ¼0.075], but we found a Stimulus location Hemisphere interaction [F(1,20)¼8.245, p¼ 0.009, η2p ¼0.292]. This interaction was caused by the elicitation of larger responses on the right hemisphere for stimuli occurring on the left (mean¼ 0.253 mV, SEM¼ 0.059 mV) as compared to stimuli occurring on the right (mean¼ 0.163 mV, SEM¼0.06 mV) [t(20) ¼ 2.871, p¼ 0.028], without such differences on the left hemisphere between stimuli occurring to either left or right sides [t(20) ¼ 0.252 p¼ 0.404]. We found neither a Stimulus location Predictability interaction, nor a Hemisphere Predictability interaction (F's o0.839, p's40.05, η2po0.40), nor an interaction of these three factors [F(1,20)¼ 0.701, p¼ 0.412, η2p ¼ 0.034].
2.2.
Predictability effects in the LLR range
When comparing chirp-evoked responses between regular and random conditions at the midline electrode Fz (90– 130 ms window), no main effect of predictability was found [t(20)¼ 0.097, p ¼0.924]. There was, however, a significant effect of predictability on the omission-evoked responses [t(20)¼ 3.175, p¼ 0.005], with larger amplitudes elicited by omissions in the regular condition (mean¼ 0.864 mV, SEM¼0.1125 mV) than by omissions in the random condition (mean¼ 0.497 mV, SEM¼0.098 mV) (Fig. 4). We examined the effects of lateralization for chirp-evoked responses by performing an rm-ANOVA with the factors stimulus location (left, right), hemisphere (F7, F8) and predictability (random, regular). There were no main effects of stimulus location, hemisphere or predictability [F'so2.282, p's40.05, η2p o0.102] but there was an Hemisphere Predictability interaction [F(1,20)¼ 14.629, p ¼0.001, η2p ¼0.422] (Fig. 5). This interaction was caused by the elicitation of larger responses on the right than on the left hemisphere when the stimuli were presented in the regular context
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[t(20)¼ 3.015, p¼ 0.007]; but not when they were presented in the random context [t(20)¼ 0.151, p ¼0.882]. Furthermore, we examined the effects of predictability on the omission-evoked responses at lateral electrodes (Fig. 6). An rm-ANOVA with the factors expected stimulus location (left, right), hemisphere (F7,F8) and predictability (random, regular) was conducted. For both conditions, the factor stimulus expectation was derived based on the location of the previous stimulus. For example, an “expected right” location would mean that the preceding stimulus was presented on the left in both regular and random conditions. (Note that this reflects a veridical expectation in the regular condition, but a pseudo-assignment of trials with the same immediate stimulus history in the random condition). The rm-ANOVA revealed a main effect of hemisphere [F(1,20)¼ 4.778, p¼ 0.041, η2p ¼ 0.193] with larger responses elicited on the right hemisphere. Also, the effect of predictability [F(1,20)¼7.884, p ¼0.011, η2p ¼0.283] was significant, with larger amplitudes elicited by the omissions occurring in the regular context. No effect of expected stimulus location was observed [F(1,20)¼1.007, p¼ 0.328, η2p ¼ 0.048]. There was an Expected location Predictability interaction [F(1,20)¼ 1.141, p¼ 0.048, η2p ¼ 0.181], with significant differences between regular and random contexts for stimuli expected to occur on the left [t (20)¼ 2.919, p¼ 0.008], but not for stimuli expected to occur on the right [t(20) ¼ 0.682, p¼ 0.503]. We also observed an Expected location Hemisphere interaction [F(1,20)¼ 6.750, p¼ 0.017, η2p ¼ 0.252], with significant expected location differences observed on the right hemisphere (F8 expected left versus F8 expected right, t(20)¼ 2.636, p¼ 0.016), but not on the left hemisphere (F7 expected left versus F7 expected right, t(20)¼ 0.425, p¼ 0.676). There was no Hemisphere Predictability interaction [F(1,20)¼ 0.938 p¼ 0.344, η2p ¼0.045] nor a Predictability Hemisphere Expected location interaction [F (1,20)¼0.584, p¼ 0.452, η2p ¼ 0.029].
3.
Discussion
In the present study, we investigated regularity encoding and the generation of auditory predictions at early processing stages of the cortical auditory hierarchy. In the MLR range, we found an attenuation of the Na component's amplitude elicited by chirps whose location was predictable (based on regular alternation) as compared to chirps with unpredictable locations (i.e., in the random condition). Brain responses elicited by the omission of stimuli with predictable or unpredictable location did not start to differ until the LLR range. While in the MLR range, regularity-dependent modulations were found bilaterally, in the LLR range regularity effects and predictability-dependent responses were more prominent over the right hemisphere. These findings speak for a hierarchical configuration of complex spatial regularity encoding. In the MLR range, we observed an attenuation of the Na component's amplitude to the regular alternation of chirps as compared to the random sequence. Previous studies that were designed to reveal effects of spatial deviance detection in the MLR range also reported modulations of the Na component to deviant sounds differing in their perceived location, suggesting the involvement of the Na component in the encoding of auditory
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Fig. 3 – Laterality effects in the MLR range. AEP waveforms in the MLR range obtained at lateral electrodes (F7 and F8). (A) Laterality effects for stimuli delivered to the left ear. Chirp-evoked responses are depicted in dark blue for the random condition and light blue for the regular condition. Bar graphs show mean amplitudes and error bars (standard error of mean) at the Na component (mean window 32–36 ms). Scalp topographies on the right are shown for the same time window for each condition. (B) Laterality effects for stimuli delivered to the right ear. Chirp-evoked responses are shown in red for the random condition and in orange for the regular condition. Bar graphs show mean amplitudes and error bars at the Na component (mean window 32–36 ms). Topographies on the right are shown for the same time window for each condition. regularities in space (Cornella et al., 2012; Grimm et al., 2012; Sonnadara et al., 2006). However, the spatial regularities of these studies were based on either stimulus or single feature (i.e. perceived location) repetitions. Here, we were able to demonstrate that the Na component of the MLR was sensitive to more complex spatial sequences (i.e., regular alternation). Our findings
thus shed further light on the role of the Na component in spatial auditory regularity encoding. Previous MLR studies that examined the encoding of nonspatial complex regularities, such as tones alternating in frequency or complex pattern rules, did not find modulations of any component of the MLR (Cornella et al., 2012; Recasens
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Fig. 4 – Long-latency responses (LLR) to chirps and omissions. AEP waveforms in the LLR range elicited by chirps (solid lines) and omissions (dashed lines) for both the regular (gray) and the random (black) conditions at the Fz electrode. Note that the early difference between the ERPs elicited by chirps in the regular and random conditions was not significant as shown by a post-hoc dependent samples t-test in the 15–55 ms interval [t(20)¼ 1.862, p ¼0.077]. et al., 2014). However, these studies were designed to examine deviance-related effects in complex sequences, and did not specifically control for stimulus history effects resulting from the sequence regularity. In order to control for such effects, here we compared only those stimuli that were preceded by a stimulus in the alternate location in either condition. This way we could disregard that our effects were due to the immediate stimulus history, which in the random condition would include stimulus repetition in the same location. Therefore, the Na suppression in the regular sequence is likely to result from the fact that the system was sensitive to the global structure of the sound sequence. The Na attenuation to the regular sequence parallels findings from animal studies when manipulating frequency deviants. By using intra- and extracellular recordings, Yaron et al. (2012) showed that standards in periodic (i.e., regular) oddball sequences elicited smaller responses than standards in random sequences, with effects observed as early as in the primary auditory cortex. The authors argued that these effects could not be due to the immediate stimulus history, but to the global structure of the sequence. Our findings are thus in line with those of Yaron et al., and argue for the system's sensitivity to complex statistical regularities that can be observed at the early MLR time ranges. When examining omission-evoked responses in the MLR range, we did not find any differences between the regular and random conditions. As the omission-evoked responses are usually interpreted as direct correlates of the prediction (Bendixen et al., 2009; Hughes et al., 2001; Raij et al., 1997; Todorovic et al., 2011; Wacongne et al., 2011), the fact that we failed to observe any predictability effects on the omission responses might suggest that predictions about the location of upcoming sounds were not induced at lower stages in the auditory hierarchy. However, other explanations cannot easily be ruled out: due to the decrease of the signal-
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to-noise ratio when splitting the trials by the location in which they were expected to occur, it was not possible to analyze the laterality effects to omitted stimuli in the regular sequence as we did in the LLR range. Another alternative explanation for the lack of predictability effects on the omission responses in the MLR range could be that, with the present design, local probability transitions were not strong enough to generate a differential predictive response. That is, in the random condition there was still a 50% chance of a stimulus to occur either to the left or to the right. Therefore, while the differences between the regular and random conditions were sufficient for analyzing chirp-evoked responses, they might not have been large enough to observe differences in the omission-evoked responses. Overall, we found an interesting dissociation: whereas the auditory system is sensitive to the location regularity in the MLR range when a physical stimulus is present (i.e., chirpevoked responses), no differential predictive responses are observed in the absence of physical input (i.e., omissionevoked responses). This would mean that the system has the information about the regularity available at early latency ranges, but predictions can only be generated or validated in the presence of an auditory stimulus. When a physical stimulus is present, the system is sensitive to the difference between regular and random sequences, and the attenuated responses can be interpreted as a reduction of the prediction error (Friston, 2005). These early modulations are important in that they can help in creating object representations, in detecting the most salient source of acoustic information, or in separating between streams of information that may belong to different sound sources (Bendixen, 2014; Bregman, 1990; Schröger et al., 2014; Winkler et al., 2009). In the LLR range, we did not find sequence-related differences between click-evoked responses in the regular or random conditions at central electrodes, but we did find an effect of predictability on the right hemisphere. These findings are in agreement with the right-hemisphere specialization in processing auditory information in space (Chennu et al., 2013; Dietz et al., 2014; Kaiser et al., 2000). When examining omission-evoked responses in the LLR range, we found larger response amplitudes in the regular sequence as compared to the random sequence at both central and lateral electrodes. The larger (i.e., more negative) omission responses that were elicited in the regular sequence can be explained by the increased neural activity due to a larger omission MMN or prediction error (Todorovic et al., 2011) when the stimulus with a stronger expectation did not occur (Friston, 2005). Both types of omission-evoked responses elicited a large positivity at about 250 ms after stimulus onset. When examining the effect of predictability at lateral electrodes in more detail, it was not possible to exclude confounding effects of stimulus history, since most effects occurred similarly for predictable sequences (where the location of the upcoming stimulus could be expected on the basis of the preceding stimulus) and random sequences (where stimuli were arbitrarily grouped into expected-left versus expected-right on the basis of the preceding stimulus). At lateral electrodes the predictability effect was restricted to omitted stimuli expected to occur on the left, without a clear explanation as to why stimuli expected to occur on the right
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Fig. 5 – Laterality effects in the LLR range. AEP waveforms in the LLR range obtained at lateral electrodes (F7 and F8) for chirpevoked stimuli. (A) Laterality effects for stimuli delivered to the left ear. Chirp-evoked responses are depicted in dark blue for the random condition and light blue for the regular condition. Bar graphs show mean amplitudes and error bars (standard error of mean; mean window 85–125 ms). Scalp topographies on the right are shown for the same time window for each condition. (B) Laterality effects for stimuli delivered to the left ear. Chirp-evoked responses are shown in red for the random condition and in orange for the regular condition. Bar graphs show mean amplitudes and error bars (mean window 85– 125 ms). Topographies on the right are shown for the same time window for each condition.
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Fig. 6 – Laterality effects for omissions in the regular and random conditions. AEP waveforms in the LLR range obtained at lateral electrodes (F7 and F8) for (A) regular and (B) random omission-evoked responses. Bar graphs show mean amplitudes and standard errors of mean measured in the 85–125 ms time window.
should not show a similar pattern. Speculatively, a predominantly contra-lateral processing of monaural stimuli combined with stronger modulations of activity in the right hemisphere could cause such a pattern. In line with that, the processing of spatial regularity showed a right-hemispheric dominance – as did the omission processing in general. Further examination of effects at lateral electrodes revealed that omitted stimuli which were expected to occur on the left side elicited larger right-hemispheric activations than stimuli expected on the right side. However, it was not possible to exclude a confounding influence of stimulus history, since this effect occurred similarly for predictable sequences (where the location of the upcoming stimulus could be expected on the basis of the preceding stimulus) and random sequences (where stimuli were arbitrarily grouped into expected-left versus expected-right on the basis of the preceding stimulus). It is possible that the lack of clear differential predictability responses is due to the design of our random condition, which still may have induced some form of predictability (i.e., there were only two alternatives). Recent studies have offered converging evidence that the auditory system works in a hierarchical and predictive manner, in agreement with the predictive-coding account (Friston, 2005). Interest has been put on the dissociation between mismatch negativity and the later P3 component, with sources expanding over prefrontal and parietal cortices (Bekinschtein et al., 2009; Wacongne et al., 2011). In our study, we focused on earlier cortical stages of auditory regularity encoding and deviance detection, operating at earlier time scales than those
To summarize, we were able to demonstrate that complex spatial sequences modulate the Na component of the MLR, suggesting that predictions about the structure of complex sequences can be generated at about 34 ms after stimulus onset in the presence of physical input. In the LLR range, predictions additionally exerted an effect on the processing of sound omissions. Our findings speak for a hierarchical predictive organization of early auditory regularity encoding.
4.
Experimental procedure
4.1.
Participants
Twenty-seven healthy female students of the university of Leipzig participated in the experiment (age range 19–36, mean¼ 22.95, SD¼ 3.97). Participants reported no hearing impairment and no history of psychiatric or neurological disease. All participants gave informed consent and received monetary compensation or course credit for participating in the experiment. The experiment was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). From the initial 27 participants that were recorded, 21 were finally used for analysis, since the data of 6 participants showed either poor signal-to-noise ratio or contamination by post-auricular muscle response (PAM), a large positive dip (circa 5 μV) occurring at about 15 ms after stimulus onset which changes the morphology of the MLR (Bell et al., 2004).
corresponding to the MMN and with sources located to primary and secondary auditory cortices (Yvert et al., 2001). In view of the present results, the MLR responses seem to be modulated by the complex statistical structure of sound sequences, while a higher-order regularity encoding system may be needed so that further computations about the stimulus identity and predictions can be generated and refined at later processing stages (Wacongne et al., 2011).
4.2.
Stimuli and procedure
Stimuli consisted of 16.7 ms up-chirps, which were generated by adding up harmonic series of cosine waveforms that ranged from 50 to 8000 Hz and by using the phase delays reported in Elberling et al. (2007) obtained from data by Don et al. (2007). Such chirp stimuli activate different regions
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of the basilar membrane simultaneously, so that larger brainstem and MLR responses are generated (Bell et al., 2002; Dau et al., 2000), thus providing higher signal-to-noise ratio than clicks (Elberling et al., 2007). Stimuli were delivered monaurally via headphones (Sennheiser HD 25-1) either to the left or the right ear with an intensity of 70 dB SPL. The experiment consisted of two conditions: regular and random (Fig. 1). In the regular condition, stimuli strictly alternated in location (left–right–left–right…) and occasional omissions occurred equiprobably to the expected right or left locations, with a total probability of 8% (4% to the left and 4% to the right). In the random condition, location repetition or alternation were randomly chosen, hence it was not possible to predict whether the next stimulus would appear to the right or the left ear. As in the regular condition, occasional omissions were presented with a probability of 8%. For each condition (regular and random), there were a total of 1344 omissions and after each omission, at least four stimuli needed to be presented before the next omission would occur. In both conditions stimuli were delivered with a constant stimulus onset asynchrony (SOA) of 125 ms. Stimulus presentation was controlled with MATLAB, using the Psychophysics Toolbox extensions (Brainard, 1997; Pelli, 1997). During recording, participants sat in an electricallyshielded and sound-attenuated room and were asked to watch a silent movie with subtitles and to ignore the acoustic stimuli. Both conditions were presented in 14 blocks (7 blocks for each condition) with alternating order, with the starting condition counterbalanced across participants. Each block consisted of 3000 trials and had a duration of ca. 6 min.
4.3.
EEG data acquisition
EEG data were recorded using BioSemi amplifiers (BioSemi, Amsterdam, The Netherlands) and were digitized with a sampling rate of 1024 Hz. A total of 128 scalp electrodes organized according to the ABC BioSemi layout system (http://www.biosemi.com) were used. In addition to the scalp electrodes, the vertical and horizontal electrooculograms (EOG) were recorded by electrodes placed above and below the right eye as well as lateral to the outer canthi of both eyes. Additionally, two electrodes were placed on the left and right mastoids (M1 and M2), and an electrode was placed on the tip of the nose which served as offline reference.
4.4.
Analysis
EEG data were referenced offline to the signal recorded at the nose electrode. Data recorded at the four ocular channels were bipolarized to yield vertical and horizontal EOG channels. All further preprocessing parameters were separately optimized for the MLR and LLR analyses. For the MLR analysis, data were filtered between 15 and 200 Hz using a band-pass FIR filter (Kaiser window, filter order¼1238). Data were re-referenced to the average of the potentials recorded at the mastoids. Epochs of 150 ms were used, including a period of 50 ms before stimulus onset which was used for baseline correction. Epochs with amplitude deviations larger than 120 mV at any channel were rejected.
In order for the participants to be included in the analysis, more than 60% of the epochs (795 epochs for omission trials) had to be artifact-free according to this rejection criterion. Individual mean amplitudes were extracted from a 4 ms window (32–36 ms) centered around the grand average peak latency of the Na component of the MLR, a component which was previously reported to be involved in location deviance detection (Cornella et al., 2012; Grimm et al., 2012; Sonnadara et al., 2006). One should note that up-chirps created a latency increase of about 10 ms in the MLR due to the compensation for the place-frequency mapping in the human cochlea (Bell et al., 2002; Leung et al., 2013). Omission responses were analyzed in the same window as the one used for the Na component. For the LLR range, data were downsampled to 512 Hz and filtered using a band-pass FIR filter from 1 to 30 Hz (Kaiser window, filter order¼ 9274). For both chirp- and omissionevoked responses, a 40-ms window around the mean grandaverage peak latency obtained for chirp-and omission-evoked responses in the two conditions (over left and right hemisphere) was used. Individual mean amplitudes were extracted from a window that ranged from 90 to 130 ms at the Fz electrode. In order to address laterality effects at F7 and F8 electrodes, this window ranged from 85 to 125 ms. For both the MLR and LLR ranges, only those stimuli in the random condition that were preceded by a stimulus occurring in the opposite location were kept. This was done to ensure the same stimulus history in both regular and random conditions. Moreover, in both conditions, the first 3 stimuli occurring after each omission were excluded from statistical analysis. In the MLR and LLR ranges, the overall effects of predictability were analyzed by performing two-tailed t tests for dependent samples between chirp-evoked responses elicited in the regular and random conditions, as well as between the omission-evoked responses elicited in the regular and random conditions. This initial comparison allowed us to better examine the ERPs elicited by omitted stimuli in the MLR range, as a high signal-to-noise ratio was needed in order to reliably detect the presence of omission evoked responses. In order to examine laterality effects, a 2 2 2 repeated measures ANOVA with the factors stimulus location (left,right), hemisphere (F7, F8) and predictability (random, regular) was conducted. Finally, in the LLR range the effects of predictability on the omitted stimuli were analyzed by conducting a 2 2 2 rm-ANOVA with the factors expected stimulus location (left, right), hemisphere (F7, F8), and predictability (random, regular). The factor expected stimulus location was derived based on the location of the previous stimulus (left or right) so that we could control for the effects of the previous stimulus processing, but it only reflected a veridical expectation in the regular condition. For all comparisons, post-hoc t tests for dependent samples were performed when appropriate. Effect sizes (partial eta squared, η2p) are reported in addition to F and p values.
Acknowledgments This work was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft [DFG]: Reinhart-Koselleck grant DFG SCH 375/20-1 to Erich Schröger, DFG BE 4284/2-1 to
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Alexandra Bendixen, DFG Cluster of Excellence 1077 “Hearing4all”), by the Spanish Ministry of Economy and Knowledge (PSI2012-37174), a grant from the Catalan Government (SGR2014-177), and the ICREA Academia Distinguished Professorship awarded to Carles Escera. The authors wish to thank Susann Duwe and Julia Steinbrück for their assistance in data acquisition.
r e f e r e n c e s
Althen, H., Grimm, S., Escera, C., 2011. Fast detection of unexpected sound intensity decrements as revealed by human evoked potentials. PLoS One 6, e28522, http://dx.doi. org/10.1371/journal.pone.0028522. Baldeweg, T., 2007. ERP repetition effects and mismatch negativity generation. J. Psychophysiol. 21, 204–213, http://dx. doi.org/10.1027/0269-8803.21.34.204. Bekinschtein, T.A., Dehaene, S., Rohaut, B., Tadel, F., Cohen, L., Naccache, L., 2009. Neural signature of the conscious processing of auditory regularities. Proc. Natl. Acad. Sci. USA 106, 1672–1677, http://dx.doi.org/10.1073/pnas.0809667106. Bell, S.L., Allen, R., Lutman, M.E., 2002. An investigation of the use of band-limited chirp stimuli to obtain the auditory brainstem response. Int. J. Audiol. 41, 271–278. Bell, S.L., Smith, D.C., Allen, R., Lutman, M.E., 2004. Recording the middle latency response of the auditory evoked potential as a measure of depth anaesthesia. A technical note. Br. J. Anaesth. 92, 442–445. Bendixen, A., 2014. Predictability effects in auditory scene analysis: a review. Front. Neurosci. 8, 60, http://dx.doi.org/ 10.3389/fnins.2014.00060. Bendixen, A., Schro¨ger, E., 2008. Memory trace formation for abstract auditory features and its consequences in different attentional contexts. Biol. Psychol. 78, 231–241, http://dx.doi. org/10.1016/j.biopsycho.2008.03.005. Bendixen, A., Schro¨ger, E., Winkler, I., 2009. I heard that coming: event-related potential evidence for stimulus-driven prediction in the auditory system. J. Neurosci. 29, 8447–8451, http://dx.doi.org/10.1523/JNEUROSCI.1493-09.2009. Brainard, D.H., 1997. The Psychophysics Toolbox. Spat. Vis. 10, 433–436. Bregman, A., 1990. Auditory Scene Analysis: The Perceptual Organization of Sound. MIT Press, Bradford, Cambridge, MA. Chennu, S., Noreika, V., Gueorguiev, D., Blenkmann, A., Kochen, S., Iba´n˜ez, A., Owen, A.M., Bekinschtein, T.A., 2013. Expectation and attention in hierarchical auditory prediction. J. Neurosci. 33, 11194–11205, http://dx.doi.org/10.1523/ JNEUROSCI.0114-13.2013. Cornella, M., Leung, S., Grimm, S., Escera, C., 2012. Detection of simple and pattern regularity violations occurs at different levels of the auditory hierarchy. PLoS One 7, e43604, http://dx. doi.org/10.1371/journal.pone.0043604. Dau, T., Wegner, O., Mellert, V., Kollmeier, B., 2000. Auditory brainstem responses with optimized chirp signals compensating basilar-membrane dispersion. J. Acoust. Soc. Am. 107, 1530–1540. Dietz, M.J., Friston, K.J., Mattingley, J.B., Roepstorff, A., Garrido, M. I., 2014. Effective connectivity reveals right-hemisphere dominance in audiospatial perception: implications for models of spatial neglect. J. Neurosci. 34, 5003–5011, http://dx. doi.org/10.1523/JNEUROSCI.3765-13.2014. Don, M., Kwong, B., Tanaka, C., 2007. An alternative diagnostic test for active Me´nie`re’s disease and cochlear hydrops using high-pass noise masked responses: the complex amplitude ratio. Audiol. Neurotol. 12, 359–370, http://dx.doi.org/10.1159/ 000106479.
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Elberling, C., Don, M., Cebulla, M., Stu¨rzebecher, E., 2007. Auditory steady-state responses to chirp stimuli based on cochlear traveling wave delay. J. Acoust. Soc. Am. 122, 2772–2785, http: //dx.doi.org/10.1121/1.2783985. Escera, C., Malmierca, M.S., 2014. The auditory novelty system: an attempt to integrate human and animal research. Psychophysiology 51, 111–123, http://dx.doi.org/10.1111/ psyp.12156. Friston, K., 2005. A theory of cortical responses. Philos. Trans. R. Soc. Lond. B.: Biol. Sci. 360, 815–836, http://dx.doi.org/10.1098/ rstb.2005.1622. Garrido, M.I., Kilner, J.M., Stephan, K.E., Friston, K.J., 2009. The mismatch negativity: a review of underlying mechanisms. Clin. Neurophysiol. 120, 453–463, http://dx.doi.org/10.1016/j. clinph.2008.11.029. Garrido, M.I., Sahani, M., Dolan, R.J., 2013. Outlier responses reflect sensitivity to statistical structure in the human brain. PLoS Comput. Biol. 9, e1002999, http://dx.doi.org/10.1371/ journal.pcbi.1002999. Grimm, S., Escera, C., Slabu, L., Costa-Faidella, J., 2011. Electrophysiological evidence for the hierarchical organization of auditory change detection in the human brain. Psychophysiology 48, 377–384, http://dx.doi.org/10.1111/ j.1469-8986.2010.01073.x. Grimm, S., Recasens, M., Althen, H., Escera, C., 2012. Ultrafast tracking of sound location changes as revealed by human auditory evoked potentials. Biol. Psychol. 89, 232–239, http: //dx.doi.org/10.1016/j.biopsycho.2011.10.014. Haenschel, C., Vernon, D.J., Dwivedi, P., Gruzelier, J.H., Baldeweg, T., 2005. Event-related brain potential correlates of human auditory sensory memory-trace formation. J. Neurosci. 25, 10494–10501, http://dx.doi.org/10.1523/JNEUROSCI.122705.2005. Hughes, H.C., Darcey, T.M., Barkan, H.I., Williamson, P.D., Roberts, D.W., Aslin, C.H., 2001. Responses of human auditory association cortex to the omission of an expected acoustic event. NeuroImage 13, 1073–1089, http://dx.doi.org/10.1006/ nimg.2001.0766. Kaiser, J., Lutzenberger, W., Preissl, H., Ackermann, H., Birbaumer, N., 2000. Right-hemisphere dominance for the processing of sound-source lateralization. J. Neurosci. 20, 6631–6639. Leung, S., Cornella, M., Grimm, S., Escera, C., 2012. Is fast auditory change detection feature specific? An electrophysiological study in humans. Psychophysiology 49, 933–942, http://dx.doi. org/10.1111/j.1469-8986.2012.01375.x. Leung, S., Recasens, M., Grimm, S., Escera, C., 2013. Electrophysiological index of acoustic temporal regularity violation in the middle latency range. Clin. Neurophysiol. 124, 2397–2405, http://dx.doi.org/10.1016/j.clinph.2013.06.001. Na¨a¨ta¨nen, R., Paavilainen, P., Rinne, T., Alho, K., 2007. The mismatch negativity (MMN) in basic research of central auditory processing: a review. Clin. Neurophysiol. 118, 2544–2590, http://dx.doi.org/10.1016/j.clinph.2007.04.026. Pelli, D.G., 1997. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat. Vis. 10, 437–442. Picton, T.W., Hillyard, S.A., Krausz, H.I., Galambos, R., 1974. Human auditory evoked potentials. I. Evaluation of components. Electroencephalogr. Clin. Neurophysiol. 36, 179–190. Raij, T., McEvoy, L., Ma¨kela¨, J.P., Hari, R., 1997. Human auditory cortex is activated by omissions of auditory stimuli. Brain Res. 745, 134–143. Recasens, M., Grimm, S., Capilla, A., Nowak, R., Escera, C., 2014. Two sequential processes of change detection in hierarchically ordered areas of the human auditory cortex. Cereb. Cortex 24, 143–153, http://dx.doi.org/10.1093/cercor/ bhs295.
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SanMiguel, I., Widmann, A., Bendixen, A., Trujillo-Barreto, N., Schro¨ger, E., 2013. Hearing silences: human auditory processing relies on preactivation of sound-specific brain activity patterns. J. Neurosci. 33, 8633–8639, http://dx.doi.org/ 10.1523/JNEUROSCI.5821-12.2013. Schro¨ger, E., 2007. Mismatch negativity: a microphone into auditory memory. J. Psychophysiol. 21, 138–146, http://dx.doi. org/10.1027/0269-8803.21.34.138. Schro¨ger, E., Bendixen, A., Denham, S.L., Mill, R.W., Bo˝hm, T.M., Winkler, I., 2014. Predictive regularity representations in violation detection and auditory stream segregation: from conceptual to computational models. Brain Topogr. 27, 565–577, http://dx.doi.org/10.1007/s10548-013-0334-6. Slabu, L., Escera, C., Grimm, S., Costa-Faidella, J., 2010. Early change detection in humans as revealed by auditory brainstem and middle-latency evoked potentials. Eur. J. Neurosci. 32, 859–865, http://dx.doi.org/10.1111/j.14609568.2010.07324.x. Sonnadara, R.R., Alain, C., Trainor, L.J., 2006. Occasional changes in sound location enhance middle latency evoked responses. Brain Res. 1076, 187–192, http://dx.doi.org/10.1016/j. brainres.2005.12.093. Tervaniemi, M., Maury, S., Na¨a¨ta¨nen, R., 1994. Neural representations of abstract stimulus features in the human
brain as reflected by the mismatch negativity. NeuroReport 5, 844–846. Todorovic, A., van Ede, F., Maris, E., de Lange, F.P., 2011. Prior expectation mediates neural adaptation to repeated sounds in the auditory cortex: an MEG study. J. Neurosci. 31, 9118–9123, http://dx.doi.org/10.1523/JNEUROSCI.1425-11.2011. Wacongne, C., Labyt, E., van Wassenhove, V., Bekinschtein, T., Naccache, L., Dehaene, S., 2011. Evidence for a hierarchy of predictions and prediction errors in human cortex. Proc. Natl. Acad. Sci. USA 108, 20754–20759, http://dx.doi.org/10.1073/ pnas.1117807108. Winkler, I., 2007. Interpreting the mismatch negativity. J. Psychophysiol. 21, 147–163, http://dx.doi.org/10.1027/02698803.21.34.147. Winkler, I., Denham, S.L., Nelken, I., 2009. Modeling the auditory scene: predictive regularity representations and perceptual objects. Trends Cogn. Sci. 13, 532–540, http://dx.doi.org/ 10.1016/j.tics.2009.09.003. Yaron, A., Hershenhoren, I., Nelken, I., 2012. Sensitivity to complex statistical regularities in rat auditory cortex. Neuron 76, 603–615, http://dx.doi.org/10.1016/j.neuron.2012.08.025. Yvert, B., Crouzeix, A., Bertrand, O., 2001. Multiple supratemporal sources of magnetic and electric auditory evoked middle latency components in humans. Cereb. Cortex 11, 411–423.
Available online at www.sciencedirect.com
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Research Report
Spatial auditory regularity encoding and prediction: Human middle-latency and long-latency auditory evoked potentials M. Cornellaa,b, A. Bendixenc,d, S. Grimma,b,c, S. Leunga,b, E. Schro¨gerc, C. Esceraa,b,n a
Institute for Brain, Cognition and Behavior (IR3C), University of Barcelona, Catalonia, Spain Cognitive Neuroscience Research Group, Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Catalonia, Spain c Institute of Psychology, University of Leipzig, Leipzig, Germany d Auditory Psychophysiology Lab, Department of Psychology, Cluster of Excellence “Hearing4all”, European Medical School, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany b
art i cle i nfo
ab st rac t
Article history:
By encoding acoustic regularities present in the environment, the human brain can
Accepted 11 April 2015
generate predictions of what is likely to occur next. Recent studies suggest that deviations
Available online 22 April 2015
from encoded regularities are detected within 10–50 ms after stimulus onset, as indicated
Keywords:
by electrophysiological effects in the middle latency response (MLR) range. This is
Middle latency response
upstream of previously known long-latency (LLR) signatures of deviance detection such
Long latency response
as the mismatch negativity (MMN) component. In the present study, we created pre-
Prediction
dictable and unpredictable contexts to investigate MLR and LLR signatures of the encoding
Auditory regularity
of spatial auditory regularities and the generation of predictions from these regularities. Chirps were monaurally delivered in an either regular (predictable: left–right–left–right) or a random (unpredictable left/right alternation or repetition) manner. Occasional stimulus omissions occurred in both types of sequences. Results showed that the Na component (peaking at 34 ms after stimulus onset) was attenuated for regular relative to random chirps, albeit no differences were observed for stimulus omission responses in the same latency range. In the LLR range, larger chirp-and omission-evoked responses were elicited for the regular than for the random condition, and predictability effects were more prominent over the right hemisphere. We discuss our findings in the framework of a hierarchical organization of spatial regularity encoding. This article is part of a Special Issue entitled SI: Prediction and Attention. & 2015 Elsevier B.V. All rights reserved.
n Corresponding author at: Cognitive Neuroscience Research Group, Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Catalonia, Spain. Fax: þ34 93 4021584. E-mail address: [email protected] (C. Escera).
http://dx.doi.org/10.1016/j.brainres.2015.04.018 0006-8993/& 2015 Elsevier B.V. All rights reserved.
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1.
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Introduction
The brain constantly needs to encode the dynamic information present in the environment to make predictions about occurrences of future events, as well as to rapidly respond to unexpected events taking place. In the auditory domain this is done by encoding regularities from the mix of auditory information that surrounds us (Winkler et al., 2009), and by using the probabilistic information to predict what is likely to occur next (Schröger et al., 2014). Auditory events that do not match the current predictions elicit a frontocentrally negative event-related potential component termed mismatch negativity (MMN) (Näätänen et al., 2007). MMN occurs at about 150–200 ms after deviation onset, and is automatically generated by violations of auditory regularities that range from simple stimulus repetitions in oddball or roving standard paradigms (e.g., Haenschel et al., 2005) to complex statistical structures (Garrido et al., 2013), or even abstract sequence-based rules (e.g., Bendixen and Schröger, 2008; Tervaniemi et al., 1994). Therefore, the elicitation of MMN indirectly implies that the regularities present in the environment have been encoded (Schröger, 2007).The amplitude of the MMN is often interpreted as the magnitude of the prediction error signal which is the output from a comparison between the incoming information and a prediction based on recent stimulus history (Baldeweg, 2007; Friston, 2005; Garrido et al., 2009; Winkler, 2007). A more direct approach to examine the electrophysiological correlates of prediction is to use unexpected stimulus omissions (Bendixen et al., 2009; Hughes et al., 2001; Raij et al., 1997; Todorovic et al., 2011; Wacongne et al., 2011). This way, in the absence of a physical deviant stimulus it is possible to examine correlates of endogenous expectations once the regularity has been encoded. Omissions generate a response that resembles the actual stimulus evoked response, with sources located in similar regions as those activated when the acoustic stimulus was presented, suggesting the pre-activation of neural circuits needed to process the actual physical inputs (Hughes et al., 2001; Raij et al., 1997; SanMiguel et al., 2013; Wacongne et al., 2011). A striking feature of the ERP signatures of automatic auditory predictions is that they occur fast, within the first 80 ms after the expected stimulus onset (Bendixen et al., 2009; Winkler et al., 2009). Early cortical auditory evoked potentials (AEPs) correspond to the middle latency response (MLR), a series of components (P0, Na, Pa and Nb) that occur from 10 to 60 ms after stimulus onset (Picton et al., 1974) and are thought to originate in primary and secondary auditory areas (Yvert et al., 2001). Recent studies have shown that one or more components of the MLR can be modulated by deviant stimuli in oddball paradigms (Althen et al., 2011; Grimm et al., 2011; Recasens et al., 2014; Slabu et al., 2010), or by unexpected changes of single features like frequency or location in complex paradigms (Cornella et al., 2012; Leung et al., 2012). These findings suggest that the detection of auditory regularity violations, at least for simple regularities (i.e. stimulus or feature repetitions), takes place at earlier latencies than those corresponding to the MMN. Current theoretical frameworks emphasize that regularity encoding (and deviance
detection) develops in a hierarchical manner (for a review, see Escera and Malmierca (2014)). The present study aimed at examining ERP correlates of regularity encoding and stimulus predictions in the MLR and LLR ranges by using a more complex regularity than stimulus repetition. We designed two conditions differing in their degree of predictability with respect to stimulus location (Fig. 1). In the first condition, the stimuli were presented monaurally in a strictly alternating fashion (left–right–left– right–…) so that it was possible to predict the location of the next stimulus. In a second condition, the stimuli were randomly repeating or alternating (e.g., left–left–right–left–right– right–right–left–…), so that it was not possible to predict whether the next input would be presented from the left or the right. Additionally, we introduced rare omissions to probe correlates of stimulus prediction (i.e., auditory activity without tone input) in both the MLR and LLR ranges.
2.
Results
2.1.
Predictability effects in the MLR range
MLR analyses were confined to the Na component, as this was previously reported to be involved in location deviance detection (Cornella et al., 2012; Grimm et al., 2012; Sonnadara et al., 2006). The Na component amplitude elicited by the chirps at the midline electrode Fz (32–36 ms window) did not differ as a function of predictability (regular versus random condition) [t(20)¼ 1.277, p¼ 0.216] when keeping stimulus history identical across conditions (i.e., analyzing only alternation trials from the random condition). The omission responses were not dependent on predictability either when measured in the same time window [t(20) ¼0.661, p¼ 0.516] (Fig. 2). In order to investigate whether effects of predictability would be present at more lateral electrode sites, effects of lateralization on the chirp-evoked responses were examined in a repeated-measures analysis of variance (rm-ANOVA) with the factors stimulus location (left, right), hemisphere (F7, F8) and predictability (random, regular). Note that the same analysis was not possible for the omission-evoked responses due to low signal-to-noise ratio when splitting the omission trials by side of presentation. In the chirp-
Fig. 1 – Experimental design. Schematic representation of the random and regular conditions. Chirps delivered to the left are represented by the letter “L” and chirps delivered to the right are represented by the letter “R”. Omissions are shown in gray; in the regular condition they indicate the expected location of the stimulus.
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Fig. 2 – Middle latency response (MLR) to chirps and omissions. AEP waveforms in the MLR range elicited by chirps (solid lines) and omissions (dashed lines) for both the regular (gray) and the random (black) conditions at the Fz electrode.
evoked responses, a main effect of predictability [F(1,20)¼ 6.034, p¼ 0.023, η2p ¼ 0.232] was observed, with larger Na mean amplitudes elicited in the random condition (Fig. 3). There were no main effects of hemisphere or stimulus location [F (1,20)o1.616, p¼ 0.218, η2p ¼0.075], but we found a Stimulus location Hemisphere interaction [F(1,20)¼8.245, p¼ 0.009, η2p ¼0.292]. This interaction was caused by the elicitation of larger responses on the right hemisphere for stimuli occurring on the left (mean¼ 0.253 mV, SEM¼ 0.059 mV) as compared to stimuli occurring on the right (mean¼ 0.163 mV, SEM¼0.06 mV) [t(20) ¼ 2.871, p¼ 0.028], without such differences on the left hemisphere between stimuli occurring to either left or right sides [t(20) ¼ 0.252 p¼ 0.404]. We found neither a Stimulus location Predictability interaction, nor a Hemisphere Predictability interaction (F's o0.839, p's40.05, η2po0.40), nor an interaction of these three factors [F(1,20)¼ 0.701, p¼ 0.412, η2p ¼ 0.034].
2.2.
Predictability effects in the LLR range
When comparing chirp-evoked responses between regular and random conditions at the midline electrode Fz (90– 130 ms window), no main effect of predictability was found [t(20)¼ 0.097, p ¼0.924]. There was, however, a significant effect of predictability on the omission-evoked responses [t(20)¼ 3.175, p¼ 0.005], with larger amplitudes elicited by omissions in the regular condition (mean¼ 0.864 mV, SEM¼0.1125 mV) than by omissions in the random condition (mean¼ 0.497 mV, SEM¼0.098 mV) (Fig. 4). We examined the effects of lateralization for chirp-evoked responses by performing an rm-ANOVA with the factors stimulus location (left, right), hemisphere (F7, F8) and predictability (random, regular). There were no main effects of stimulus location, hemisphere or predictability [F'so2.282, p's40.05, η2p o0.102] but there was an Hemisphere Predictability interaction [F(1,20)¼ 14.629, p ¼0.001, η2p ¼0.422] (Fig. 5). This interaction was caused by the elicitation of larger responses on the right than on the left hemisphere when the stimuli were presented in the regular context
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[t(20)¼ 3.015, p¼ 0.007]; but not when they were presented in the random context [t(20)¼ 0.151, p ¼0.882]. Furthermore, we examined the effects of predictability on the omission-evoked responses at lateral electrodes (Fig. 6). An rm-ANOVA with the factors expected stimulus location (left, right), hemisphere (F7,F8) and predictability (random, regular) was conducted. For both conditions, the factor stimulus expectation was derived based on the location of the previous stimulus. For example, an “expected right” location would mean that the preceding stimulus was presented on the left in both regular and random conditions. (Note that this reflects a veridical expectation in the regular condition, but a pseudo-assignment of trials with the same immediate stimulus history in the random condition). The rm-ANOVA revealed a main effect of hemisphere [F(1,20)¼ 4.778, p¼ 0.041, η2p ¼ 0.193] with larger responses elicited on the right hemisphere. Also, the effect of predictability [F(1,20)¼7.884, p ¼0.011, η2p ¼0.283] was significant, with larger amplitudes elicited by the omissions occurring in the regular context. No effect of expected stimulus location was observed [F(1,20)¼1.007, p¼ 0.328, η2p ¼ 0.048]. There was an Expected location Predictability interaction [F(1,20)¼ 1.141, p¼ 0.048, η2p ¼ 0.181], with significant differences between regular and random contexts for stimuli expected to occur on the left [t (20)¼ 2.919, p¼ 0.008], but not for stimuli expected to occur on the right [t(20) ¼ 0.682, p¼ 0.503]. We also observed an Expected location Hemisphere interaction [F(1,20)¼ 6.750, p¼ 0.017, η2p ¼ 0.252], with significant expected location differences observed on the right hemisphere (F8 expected left versus F8 expected right, t(20)¼ 2.636, p¼ 0.016), but not on the left hemisphere (F7 expected left versus F7 expected right, t(20)¼ 0.425, p¼ 0.676). There was no Hemisphere Predictability interaction [F(1,20)¼ 0.938 p¼ 0.344, η2p ¼0.045] nor a Predictability Hemisphere Expected location interaction [F (1,20)¼0.584, p¼ 0.452, η2p ¼ 0.029].
3.
Discussion
In the present study, we investigated regularity encoding and the generation of auditory predictions at early processing stages of the cortical auditory hierarchy. In the MLR range, we found an attenuation of the Na component's amplitude elicited by chirps whose location was predictable (based on regular alternation) as compared to chirps with unpredictable locations (i.e., in the random condition). Brain responses elicited by the omission of stimuli with predictable or unpredictable location did not start to differ until the LLR range. While in the MLR range, regularity-dependent modulations were found bilaterally, in the LLR range regularity effects and predictability-dependent responses were more prominent over the right hemisphere. These findings speak for a hierarchical configuration of complex spatial regularity encoding. In the MLR range, we observed an attenuation of the Na component's amplitude to the regular alternation of chirps as compared to the random sequence. Previous studies that were designed to reveal effects of spatial deviance detection in the MLR range also reported modulations of the Na component to deviant sounds differing in their perceived location, suggesting the involvement of the Na component in the encoding of auditory
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Fig. 3 – Laterality effects in the MLR range. AEP waveforms in the MLR range obtained at lateral electrodes (F7 and F8). (A) Laterality effects for stimuli delivered to the left ear. Chirp-evoked responses are depicted in dark blue for the random condition and light blue for the regular condition. Bar graphs show mean amplitudes and error bars (standard error of mean) at the Na component (mean window 32–36 ms). Scalp topographies on the right are shown for the same time window for each condition. (B) Laterality effects for stimuli delivered to the right ear. Chirp-evoked responses are shown in red for the random condition and in orange for the regular condition. Bar graphs show mean amplitudes and error bars at the Na component (mean window 32–36 ms). Topographies on the right are shown for the same time window for each condition. regularities in space (Cornella et al., 2012; Grimm et al., 2012; Sonnadara et al., 2006). However, the spatial regularities of these studies were based on either stimulus or single feature (i.e. perceived location) repetitions. Here, we were able to demonstrate that the Na component of the MLR was sensitive to more complex spatial sequences (i.e., regular alternation). Our findings
thus shed further light on the role of the Na component in spatial auditory regularity encoding. Previous MLR studies that examined the encoding of nonspatial complex regularities, such as tones alternating in frequency or complex pattern rules, did not find modulations of any component of the MLR (Cornella et al., 2012; Recasens
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Fig. 4 – Long-latency responses (LLR) to chirps and omissions. AEP waveforms in the LLR range elicited by chirps (solid lines) and omissions (dashed lines) for both the regular (gray) and the random (black) conditions at the Fz electrode. Note that the early difference between the ERPs elicited by chirps in the regular and random conditions was not significant as shown by a post-hoc dependent samples t-test in the 15–55 ms interval [t(20)¼ 1.862, p ¼0.077]. et al., 2014). However, these studies were designed to examine deviance-related effects in complex sequences, and did not specifically control for stimulus history effects resulting from the sequence regularity. In order to control for such effects, here we compared only those stimuli that were preceded by a stimulus in the alternate location in either condition. This way we could disregard that our effects were due to the immediate stimulus history, which in the random condition would include stimulus repetition in the same location. Therefore, the Na suppression in the regular sequence is likely to result from the fact that the system was sensitive to the global structure of the sound sequence. The Na attenuation to the regular sequence parallels findings from animal studies when manipulating frequency deviants. By using intra- and extracellular recordings, Yaron et al. (2012) showed that standards in periodic (i.e., regular) oddball sequences elicited smaller responses than standards in random sequences, with effects observed as early as in the primary auditory cortex. The authors argued that these effects could not be due to the immediate stimulus history, but to the global structure of the sequence. Our findings are thus in line with those of Yaron et al., and argue for the system's sensitivity to complex statistical regularities that can be observed at the early MLR time ranges. When examining omission-evoked responses in the MLR range, we did not find any differences between the regular and random conditions. As the omission-evoked responses are usually interpreted as direct correlates of the prediction (Bendixen et al., 2009; Hughes et al., 2001; Raij et al., 1997; Todorovic et al., 2011; Wacongne et al., 2011), the fact that we failed to observe any predictability effects on the omission responses might suggest that predictions about the location of upcoming sounds were not induced at lower stages in the auditory hierarchy. However, other explanations cannot easily be ruled out: due to the decrease of the signal-
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to-noise ratio when splitting the trials by the location in which they were expected to occur, it was not possible to analyze the laterality effects to omitted stimuli in the regular sequence as we did in the LLR range. Another alternative explanation for the lack of predictability effects on the omission responses in the MLR range could be that, with the present design, local probability transitions were not strong enough to generate a differential predictive response. That is, in the random condition there was still a 50% chance of a stimulus to occur either to the left or to the right. Therefore, while the differences between the regular and random conditions were sufficient for analyzing chirp-evoked responses, they might not have been large enough to observe differences in the omission-evoked responses. Overall, we found an interesting dissociation: whereas the auditory system is sensitive to the location regularity in the MLR range when a physical stimulus is present (i.e., chirpevoked responses), no differential predictive responses are observed in the absence of physical input (i.e., omissionevoked responses). This would mean that the system has the information about the regularity available at early latency ranges, but predictions can only be generated or validated in the presence of an auditory stimulus. When a physical stimulus is present, the system is sensitive to the difference between regular and random sequences, and the attenuated responses can be interpreted as a reduction of the prediction error (Friston, 2005). These early modulations are important in that they can help in creating object representations, in detecting the most salient source of acoustic information, or in separating between streams of information that may belong to different sound sources (Bendixen, 2014; Bregman, 1990; Schröger et al., 2014; Winkler et al., 2009). In the LLR range, we did not find sequence-related differences between click-evoked responses in the regular or random conditions at central electrodes, but we did find an effect of predictability on the right hemisphere. These findings are in agreement with the right-hemisphere specialization in processing auditory information in space (Chennu et al., 2013; Dietz et al., 2014; Kaiser et al., 2000). When examining omission-evoked responses in the LLR range, we found larger response amplitudes in the regular sequence as compared to the random sequence at both central and lateral electrodes. The larger (i.e., more negative) omission responses that were elicited in the regular sequence can be explained by the increased neural activity due to a larger omission MMN or prediction error (Todorovic et al., 2011) when the stimulus with a stronger expectation did not occur (Friston, 2005). Both types of omission-evoked responses elicited a large positivity at about 250 ms after stimulus onset. When examining the effect of predictability at lateral electrodes in more detail, it was not possible to exclude confounding effects of stimulus history, since most effects occurred similarly for predictable sequences (where the location of the upcoming stimulus could be expected on the basis of the preceding stimulus) and random sequences (where stimuli were arbitrarily grouped into expected-left versus expected-right on the basis of the preceding stimulus). At lateral electrodes the predictability effect was restricted to omitted stimuli expected to occur on the left, without a clear explanation as to why stimuli expected to occur on the right
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Fig. 5 – Laterality effects in the LLR range. AEP waveforms in the LLR range obtained at lateral electrodes (F7 and F8) for chirpevoked stimuli. (A) Laterality effects for stimuli delivered to the left ear. Chirp-evoked responses are depicted in dark blue for the random condition and light blue for the regular condition. Bar graphs show mean amplitudes and error bars (standard error of mean; mean window 85–125 ms). Scalp topographies on the right are shown for the same time window for each condition. (B) Laterality effects for stimuli delivered to the left ear. Chirp-evoked responses are shown in red for the random condition and in orange for the regular condition. Bar graphs show mean amplitudes and error bars (mean window 85– 125 ms). Topographies on the right are shown for the same time window for each condition.
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Fig. 6 – Laterality effects for omissions in the regular and random conditions. AEP waveforms in the LLR range obtained at lateral electrodes (F7 and F8) for (A) regular and (B) random omission-evoked responses. Bar graphs show mean amplitudes and standard errors of mean measured in the 85–125 ms time window.
should not show a similar pattern. Speculatively, a predominantly contra-lateral processing of monaural stimuli combined with stronger modulations of activity in the right hemisphere could cause such a pattern. In line with that, the processing of spatial regularity showed a right-hemispheric dominance – as did the omission processing in general. Further examination of effects at lateral electrodes revealed that omitted stimuli which were expected to occur on the left side elicited larger right-hemispheric activations than stimuli expected on the right side. However, it was not possible to exclude a confounding influence of stimulus history, since this effect occurred similarly for predictable sequences (where the location of the upcoming stimulus could be expected on the basis of the preceding stimulus) and random sequences (where stimuli were arbitrarily grouped into expected-left versus expected-right on the basis of the preceding stimulus). It is possible that the lack of clear differential predictability responses is due to the design of our random condition, which still may have induced some form of predictability (i.e., there were only two alternatives). Recent studies have offered converging evidence that the auditory system works in a hierarchical and predictive manner, in agreement with the predictive-coding account (Friston, 2005). Interest has been put on the dissociation between mismatch negativity and the later P3 component, with sources expanding over prefrontal and parietal cortices (Bekinschtein et al., 2009; Wacongne et al., 2011). In our study, we focused on earlier cortical stages of auditory regularity encoding and deviance detection, operating at earlier time scales than those
To summarize, we were able to demonstrate that complex spatial sequences modulate the Na component of the MLR, suggesting that predictions about the structure of complex sequences can be generated at about 34 ms after stimulus onset in the presence of physical input. In the LLR range, predictions additionally exerted an effect on the processing of sound omissions. Our findings speak for a hierarchical predictive organization of early auditory regularity encoding.
4.
Experimental procedure
4.1.
Participants
Twenty-seven healthy female students of the university of Leipzig participated in the experiment (age range 19–36, mean¼ 22.95, SD¼ 3.97). Participants reported no hearing impairment and no history of psychiatric or neurological disease. All participants gave informed consent and received monetary compensation or course credit for participating in the experiment. The experiment was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). From the initial 27 participants that were recorded, 21 were finally used for analysis, since the data of 6 participants showed either poor signal-to-noise ratio or contamination by post-auricular muscle response (PAM), a large positive dip (circa 5 μV) occurring at about 15 ms after stimulus onset which changes the morphology of the MLR (Bell et al., 2004).
corresponding to the MMN and with sources located to primary and secondary auditory cortices (Yvert et al., 2001). In view of the present results, the MLR responses seem to be modulated by the complex statistical structure of sound sequences, while a higher-order regularity encoding system may be needed so that further computations about the stimulus identity and predictions can be generated and refined at later processing stages (Wacongne et al., 2011).
4.2.
Stimuli and procedure
Stimuli consisted of 16.7 ms up-chirps, which were generated by adding up harmonic series of cosine waveforms that ranged from 50 to 8000 Hz and by using the phase delays reported in Elberling et al. (2007) obtained from data by Don et al. (2007). Such chirp stimuli activate different regions
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of the basilar membrane simultaneously, so that larger brainstem and MLR responses are generated (Bell et al., 2002; Dau et al., 2000), thus providing higher signal-to-noise ratio than clicks (Elberling et al., 2007). Stimuli were delivered monaurally via headphones (Sennheiser HD 25-1) either to the left or the right ear with an intensity of 70 dB SPL. The experiment consisted of two conditions: regular and random (Fig. 1). In the regular condition, stimuli strictly alternated in location (left–right–left–right…) and occasional omissions occurred equiprobably to the expected right or left locations, with a total probability of 8% (4% to the left and 4% to the right). In the random condition, location repetition or alternation were randomly chosen, hence it was not possible to predict whether the next stimulus would appear to the right or the left ear. As in the regular condition, occasional omissions were presented with a probability of 8%. For each condition (regular and random), there were a total of 1344 omissions and after each omission, at least four stimuli needed to be presented before the next omission would occur. In both conditions stimuli were delivered with a constant stimulus onset asynchrony (SOA) of 125 ms. Stimulus presentation was controlled with MATLAB, using the Psychophysics Toolbox extensions (Brainard, 1997; Pelli, 1997). During recording, participants sat in an electricallyshielded and sound-attenuated room and were asked to watch a silent movie with subtitles and to ignore the acoustic stimuli. Both conditions were presented in 14 blocks (7 blocks for each condition) with alternating order, with the starting condition counterbalanced across participants. Each block consisted of 3000 trials and had a duration of ca. 6 min.
4.3.
EEG data acquisition
EEG data were recorded using BioSemi amplifiers (BioSemi, Amsterdam, The Netherlands) and were digitized with a sampling rate of 1024 Hz. A total of 128 scalp electrodes organized according to the ABC BioSemi layout system (http://www.biosemi.com) were used. In addition to the scalp electrodes, the vertical and horizontal electrooculograms (EOG) were recorded by electrodes placed above and below the right eye as well as lateral to the outer canthi of both eyes. Additionally, two electrodes were placed on the left and right mastoids (M1 and M2), and an electrode was placed on the tip of the nose which served as offline reference.
4.4.
Analysis
EEG data were referenced offline to the signal recorded at the nose electrode. Data recorded at the four ocular channels were bipolarized to yield vertical and horizontal EOG channels. All further preprocessing parameters were separately optimized for the MLR and LLR analyses. For the MLR analysis, data were filtered between 15 and 200 Hz using a band-pass FIR filter (Kaiser window, filter order¼1238). Data were re-referenced to the average of the potentials recorded at the mastoids. Epochs of 150 ms were used, including a period of 50 ms before stimulus onset which was used for baseline correction. Epochs with amplitude deviations larger than 120 mV at any channel were rejected.
In order for the participants to be included in the analysis, more than 60% of the epochs (795 epochs for omission trials) had to be artifact-free according to this rejection criterion. Individual mean amplitudes were extracted from a 4 ms window (32–36 ms) centered around the grand average peak latency of the Na component of the MLR, a component which was previously reported to be involved in location deviance detection (Cornella et al., 2012; Grimm et al., 2012; Sonnadara et al., 2006). One should note that up-chirps created a latency increase of about 10 ms in the MLR due to the compensation for the place-frequency mapping in the human cochlea (Bell et al., 2002; Leung et al., 2013). Omission responses were analyzed in the same window as the one used for the Na component. For the LLR range, data were downsampled to 512 Hz and filtered using a band-pass FIR filter from 1 to 30 Hz (Kaiser window, filter order¼ 9274). For both chirp- and omissionevoked responses, a 40-ms window around the mean grandaverage peak latency obtained for chirp-and omission-evoked responses in the two conditions (over left and right hemisphere) was used. Individual mean amplitudes were extracted from a window that ranged from 90 to 130 ms at the Fz electrode. In order to address laterality effects at F7 and F8 electrodes, this window ranged from 85 to 125 ms. For both the MLR and LLR ranges, only those stimuli in the random condition that were preceded by a stimulus occurring in the opposite location were kept. This was done to ensure the same stimulus history in both regular and random conditions. Moreover, in both conditions, the first 3 stimuli occurring after each omission were excluded from statistical analysis. In the MLR and LLR ranges, the overall effects of predictability were analyzed by performing two-tailed t tests for dependent samples between chirp-evoked responses elicited in the regular and random conditions, as well as between the omission-evoked responses elicited in the regular and random conditions. This initial comparison allowed us to better examine the ERPs elicited by omitted stimuli in the MLR range, as a high signal-to-noise ratio was needed in order to reliably detect the presence of omission evoked responses. In order to examine laterality effects, a 2 2 2 repeated measures ANOVA with the factors stimulus location (left,right), hemisphere (F7, F8) and predictability (random, regular) was conducted. Finally, in the LLR range the effects of predictability on the omitted stimuli were analyzed by conducting a 2 2 2 rm-ANOVA with the factors expected stimulus location (left, right), hemisphere (F7, F8), and predictability (random, regular). The factor expected stimulus location was derived based on the location of the previous stimulus (left or right) so that we could control for the effects of the previous stimulus processing, but it only reflected a veridical expectation in the regular condition. For all comparisons, post-hoc t tests for dependent samples were performed when appropriate. Effect sizes (partial eta squared, η2p) are reported in addition to F and p values.
Acknowledgments This work was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft [DFG]: Reinhart-Koselleck grant DFG SCH 375/20-1 to Erich Schröger, DFG BE 4284/2-1 to
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Alexandra Bendixen, DFG Cluster of Excellence 1077 “Hearing4all”), by the Spanish Ministry of Economy and Knowledge (PSI2012-37174), a grant from the Catalan Government (SGR2014-177), and the ICREA Academia Distinguished Professorship awarded to Carles Escera. The authors wish to thank Susann Duwe and Julia Steinbrück for their assistance in data acquisition.
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