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Early cortical response to behaviorally relevant absence of anticipated outcomes: A human event-related potential study
www.elsevier.com/locate/ynimg NeuroImage 35 (2007) 1348 – 1355
Early cortical response to behaviorally relevant absence of anticipated outcomes: A human event-related potential study Armin Schnider, a,⁎ Christine Mohr, a,b,c Stéphanie Morand, a and Christoph M. Michel b a
Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, University Hospital Geneva, Av. de Beau-Séjour 26, CH-1211 Geneva 14, Switzerland b Functional Brain Mapping Laboratory, Division of Neurology, University Hospital Geneva, Micheli-du-Crest 24, CH-1211 Geneva 14, Switzerland c Department of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol BS8 1TU, UK Received 6 October 2006; revised 13 January 2007; accepted 19 January 2007 Available online 13 February 2007 Animals with lesions of the orbitofrontal cortex (OFC) have an extinction and reversal learning deficit. Humans with OFC lesions have similar deficits and often continue to act according to currently inappropriate memories. We tested when the human brain distinguishes between confirmed and negated outcomes of anticipations. Eleven participants predicted behind which one of two rectangles an object drawing was hidden while their cerebral activity was recorded from 123 surface electrodes. We found that absence of the predicted outcome induced specific electrical field topographies between 190 ms– 300 ms and 380 ms–600 ms. Behaviorally irrelevant deviation from predicted outcomes did not induce these alterations. Distributed linear inverse solutions indicated that the source of the early electric field topography after negated predictions differed by additional left ventrolateral prefrontal activation. The late differences in electrical field topographies were characterized by the selective absence of a processing stage in response to negated predictions. The study indicates early, specific cortical processing of behaviorally relevant absence of predicted outcomes. © 2007 Elsevier Inc. All rights reserved. Keywords: Anticipation; Outcome processing; Reality monitoring; Orbitofrontal cortex; Evoked potentials; Brain mapping; Imaging
Introduction The ability to adapt behavior when anticipated outcomes do not occur is crucial for flexible, goal-directed behavior. Human and animal studies point to an outstanding role of the orbitofrontal cortex (OFC) for this capacity (Dias et al., 1996; Rolls, 2000; Schoenbaum et al., 2000). Animals with OFC lesions fail to extinguish previously rewarded behavior and to adopt new behavior when stimulus⁎ Corresponding author. Service de Neurorééducation, Hôpitaux Universitaires de Genève, Av. de Beau-Séjour 26, CH-1211 Geneva 14, Switzerland. Fax: +41 22 372 3705. E-mail address: [email protected] (A. Schnider). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2007.01.047
outcome contingencies change (Bohn et al., 2003; Butter, 1969; Iversen and Mishkin, 1970). Patients suffering from OFC damage fail to disengage from previously correct, but currently incorrect behavior in reversal learning paradigms (Fellows and Farah, 2003; Rolls, 2000). In gambling tasks, patients with OFC lesions may continue to choose cards initially providing big gains, but eventually yielding big losses (Anderson et al., 1999; Bechara et al., 1994, 2000; Eslinger and Damasio, 1985; Price et al., 1990). Similar dysfunction may underlie certain forms of psychopathy (Blumer and Benson, 1975; Damasio, 1994), acquired sociopathy (Eslinger and Damasio, 1985; Price et al., 1990), or drug addiction (Volkow et al., 1991). These patient populations reveal impairments in reversal learning (Mitchell et al., 2002; Newman et al., 1987; Rahman et al., 1999; Rolls et al., 1994) and gambling (Anderson et al., 1999; Bechara, 2003; Bechara et al., 1996; Grant et al., 2000; Mitchell et al., 2002; Rahman et al., 1999) paradigms. Acute OFC lesions may profoundly impair the ability to adapt behavior and thought to ongoing reality: the patients act according to memories that do not pertain to current reality, a disorder called spontaneous confabulation (Schnider, 2003; Schnider and Ptak, 1999). These observations indicate that the OFC has a crucial role in the monitoring of anticipated outcomes and redirection of behavior when contingencies change. Accordingly, imaging studies with healthy participants showed activation of the OFC in gambling and reversal learning tasks (Critchley et al., 2001; Elliott et al., 1997, 1999, 2000; Fellows and Farah, 2003; O'Doherty et al., 2001; Rogers et al., 1999). However, the OFC also seems to monitor outcomes when there is no expectation of tangible reward. The simple confirmation that one is “right” activates the OFC, particularly when the outcome is uncertain (Elliott et al., 2000). In a recent PET study, OFC activation was observed when healthy subjects anticipated and monitored the outcome following simple predictions, although they had no perspective of receiving “reward”, not even in the form of a score or a comment (Schnider et al., 2005). While these functional imaging studies provided valuable information about the brain regions processing anticipation and outcomes,
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they did not reveal when and how rapidly the brain processes outcomes. In the present study, we aimed to explore when the healthy human brain distinguishes between confirmation and absence of anticipated outcomes, which are either behaviorally relevant or irrelevant, but which have no intrinsic value. We used a similar paradigm to a previous PETstudy (Schnider et al., 2005) but recorded brain activity with high-resolution event related potentials (ERP), which were analyzed using spatio-temporal mapping procedures. Methods Subjects Eleven right-handed, healthy participants (7 men, age range 20– 31 years) gave written, informed consent to participate in the study. The Ethical Committee of the University Hospital of Geneva approved the study. Anticipation task The task was adapted from the one used in our previous PET study (Schnider et al., 2005). Trials had the following general design (Fig. 1): First, a red and a green rectangle appeared on the screen with their position (left or right) varying randomly. Subjects then predicted behind which one of the two rectangles the line drawing of an object (Snodgrass and Vanderwart, 1980) was hidden by pressing with the index or middle finger of the right hand the button on the side of the chosen rectangle. Immediately after the button press, a fixation cross appeared in the center of the chosen rectangle for 700 ms. Then, feedback was provided for 1500 ms by presentation of an object drawing, indicating correct prediction, or a grid, indicating absence (and implicitly, change of position) of the object.
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After an inter-trial interval of 700 ms with white screen, the next trial started. Subjects were instructed to base their prediction on the previous trial and to refrain from guessing. They were told that the “object” would normally stay behind the same rectangle and only occasionally change position. In this case, a grid would signal the absence of the object behind the predicted rectangle. To ensure that participants really associated the object with a colored rectangle and thus performed experience-based anticipations rather than guesses, the same object was presented at least twice in succession behind the same colored rectangle (RepTrials, Fig. 1A). On subsequent trials, the probability of the object being present behind the same rectangle declined to 80%, 50%, 20%, and finally 0%. The subsequent presentation of the grid, which signaled the absence of the object behind the predicted rectangle, indicated that the object had changed its position (Fig. 1C). As the absence of an expected outcome resembles the absence of a predicted reward in animal studies, this condition was termed “Extinction” trials (ExtTrial). Following an ExtTrial, the object drawing had a 98% probability of appearing when the rectangle with the other color was selected on the next trial (Fig. 1D). This color change (NewCol) condition – that is, the first trial after change of the correct color – was separately analyzed to dissociate the learning of a new color-object association from experience-based anticipation behavior. In 2%, a second ExtTrial followed (ExtTrial2) with the intention of increasing attention and to decrease color-guided automatic responding. To evaluate the effect of unexpected outcomes having no behavioral relevance but inducing surprise, an additional condition was included. In this condition, the color of the correct rectangle was maintained but the object was different from the previous one. Thus, the trial was correct, as the “object” – albeit different from the previous one – was indeed “behind” the chosen rectangle. This condition with behaviorally irrelevant
Fig. 1. Task design. Sequential order of trials in the course of the experiment demonstrating the different outcome types. (A) A typical trial of the experiment consists of three steps: two differently colored rectangles are presented and subjects had to predict by button press (left black horizontal arrow) behind which one of the two rectangles an object is “hidden”. After the choice, a cross appears on the respective rectangle, then the object (correct choice) is presented. The curved flash on the side indicates that these three steps are repeated (RepTrial) up to four times before changing to another task condition (B and C). (B) In the object change condition (ObjChange), the choice of the correct rectangle results in the presentation of another object. (C) In an “Extinction” trial (ExtTrial), a grid indicating absence of the object is presented and finally, (D) First trial after an ExtTrial, that is, the first trial having a new color-object association (NewCol).
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changes of the object was called the object change condition (ObjChange; Fig. 1B). Subjects performed five blocks with 20 ObjChange, 20 ExtTrials, 2 ExtTrial2, and 20 NewCol (following ExtTrials) and approximately 94 RepTrials (total, approx. 781 trials). Trials with unprovoked errors were repeated until correct responses were obtained.
NewCol (task condition) as within-subject factors. For predetermined time windows, the number of time points during which cluster maps appeared was used to compare the different task conditions. Post-hoc single comparisons were conducted using Newman–Keuls statistics correcting for multiple comparisons.
EEG recording and averaging
Distributed linear inverse solution based on a Local AutoRegressive Average (LAURA) model (Grave de Peralta Menendez et al., 2001, 2004) was applied to estimate the sources of the cluster maps (Michel et al., 2004). This linear distributed inverse solution is capable of simultaneously dealing with multiple active sources of a priori unknown location (Michel et al., 2004). The lead field was calculated on a realistic head model that included 4024 nodes, selected from a 6 × 6 × 6 mm grid equally distributed within the gray matter of the average brain provided by the Montreal Neurological Institute (MNI).
Subjects were seated 140 cm from the computer screen. EEG was continuously recorded from 123 electrodes at a sampling rate of 500 Hz during the task (Electrical Geodesics Inc., Eugene, OR, USA). Electrical impedance was below 50 kΩ for all electrodes in accordance with systems specification (Tucker, 1993), filters were set at 0.1 and 100 Hz with the vertex electrode (Cz) as a reference. After the task, the EEG was recomputed off-line to the average reference. Stimuli were presented with e-prime (©Psychology Software Tools), which sends coded trigger pulses to the EEG system to mark stimulus onset. EEG was visually inspected off-line to reject epochs distorted by artifacts (eye blinks, body or eye movements). Data were digitally filtered between 1 and 30 Hz and averaged (ERPs) over 800 ms from − 200 ms to +600 ms relative to the onset of the presentation of the outcome stimulus (object or grid). No pre-stimulus baseline correction was applied. ERPs were realigned to the time point of maximum global field power of the P100 (Murray et al., 2004). Spatio-temporal analysis We applied spatio-temporal ERP analysis using a modified spatial k-means cluster analysis to determine the most dominant electrocortical map configurations (Michel et al., 2001; PascualMarqui et al., 1995). The optimal number of clusters was determined with a modified cross-validation criterion described in detail in Pascual-Marqui et al. (1995). Statistical smoothing was used to eliminate temporally isolated maps with low strength (Besag, 1986; Pascual-Marqui et al., 1995). As an additional constraint a given scalp topography had to be present for at least 10 consecutive data points (≥ 20 ms). This approach allows summarizing ERP data into a limited number of electrocortical map configurations and identifying time periods during which different experimental conditions evoke different maps (Michel et al., 2001). The spatial cluster analysis was applied to the four grand average ERPs of the four stimulus conditions over the time period between − 200 ms and 600 ms. For statistical analysis, we tested the appearance of the different cluster maps in the individual ERPs of each task condition by means of strength-independent spatial correlation. That is, the cluster maps were compared with the voltage topography of each time point of each individual ERP during the time period defined by the grand mean analysis, and labeled with the cluster map it best correlated with. This analysis yielded the number of time points a cluster map was present in the individual data for each task condition separately (Pegna et al., 1997). These values (the presence of each cluster map in the individual data) were then used for statistical analysis. Statistical analyses We used repeated measures ANOVAs to analyze temporal differences in the ERPs of the ExtTrial, RepTrial, ObjChange and
Source localization
Waveform analysis In order to allow comparison with traditional EEG analysis, amplitude differences of ERP traces at nine electrode positions over anterior, central, and posterior regions of both hemispheres and the midline (approx. corresponding to AF8, AFz, AF7, T10, Cz, T9, P10, Oz, P7) were examined. The potentials were averaged over periods of interest determined by the spatial cluster analysis described above. ANOVAs were used to compare the mean amplitudes between conditions within these windows. Results Task performance Over all trials, the error rate (excluding ExtTrials) was low, 4.9 ± 2.2%, confirming that the task was easy. An ANOVA on reaction times (anticipation response) with task condition as the repeated measure revealed a significant main effect [F(3,30) = 7.26; P = 0.0008]. Consistent with previous findings that response latencies were increased after error trials, response latencies were longest in the NewCol (693 ± 193 ms) as compared to the RepTrial (647 ± 144 ms, P= 0.04), the ObjChange (630 ± 149 ms, P= 0.02) and the ExtTrial (595 ± 143 ms, P= 0.0005). Response latencies did not differ between the RepTrial, the ObjChange, and the ExtTrial (all P-values > 0.05). Event-related potentials Spatio-temporal analysis Spatial cluster analysis applied to the ERPs of the four task conditions revealed a total of nine different cluster maps, which best explained the whole data set (Fig. 2, middle part). The first two maps appeared between 200 ms prior to and 190 ms after the presentation of the outcome, independent of whether an object drawing or grid was shown (Fig. 2, cluster maps 1 and 2). Although the grand mean analysis suggested that map 1 might be more present in the ObjChange and the NewCol conditions and map 2 in the RepTrial and the ExtTrial conditions, the interaction was not significant. Between 190 ms and 300 ms after presentation of the outcome, ExtTrials induced a significantly different electrocortical response
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Fig. 2. Functional cluster analysis and distributed inverse solution. In the middle, the sequence of the nine cluster maps that had been determined from the grand mean of all subjects between − 200 ms and 600 ms after outcome presentation are displayed for each task condition. The amplitude of the curves reflects the global field power. For cluster maps with significant differences between task conditions, the electrocortical map configuration (nose upward, right ear on the right side) and inverse solutions are presented to the right and left of the functional cluster analyses.
than all other conditions: map 6 dominated in ExtTrials, while map 5 dominated in all other conditions (Fig. 2). There was a significant interaction between maps 5 and 6 and task conditions [F3.30 = 28.02, P < 0.0001]. Map 6 was present more often (longer) in ExtTrials and map 5 in all other conditions (all P-values < 0.002, Fig. 3). The sources associated with the maps as estimated by LAURA are illustrated in Fig. 2 (left). While both maps reflected occipito-temporal activation, map 6 reflected additional left ventrolateral prefrontal (lateral orbitofrontal) activation. Between 300 ms and 380 ms after outcome presentation, two different maps appeared: map 7 in RepTrial and NewCol trials, and map 3 in ObjChange and ExtTrial trials (Fig. 2). However, when the frequency was analyzed with which these maps were present in
the ERPs of the individual subjects, the interaction was not significant. Between 380 ms and 600 ms, confirmed anticipations (RepTrial, ObjChange, NewCol) first induced map 8, followed by map 9 (Fig. 2). In contrast, ExtTrial only induced map 9 in this period. The ANOVA on the frequency with which map 8 and 9 appeared, showed a significant interaction [F3.30 = 8.30, P= 0.0004]. In ExtTrials, map 9 was more frequently present in the ERPs of the individual subjects than map 8 (P= 0.003, Fig. 3). In addition, map 9 was more frequently present in the ExtTrial than the NewCol trials (P= 0.03). LAURA revealed for map 9 a bilateral ventrolateral prefrontal (lateral orbitofrontal) and right antero-medial temporal activation. For map 8, in contrast, the inverse solution showed
Fig. 3. Mean data points (moment-by-moment) with which the cluster maps determined from the group-averaged ERPs appeared in the individual ERPs. Presented are scalp configurations of significant differences between task conditions; (A) cluster map 5 and 6 (see Fig. 2) during the early time period between 190 ms and 300 ms. (B) Frequency of cluster map 8 and 9 during the later time period between 380 ms and 600 ms after stimulus onset. Vertical lines indicate standard deviations. a: Map 5: ExtTrial against all other task conditions, all P-values < 0.0006; b: Map 6: ExtTrial against all other task conditions, all P-values < 0.0006; c: ExtTrial: Map 8 against map 9, P = 0.003; d: Map 9: ExtTrial against NewColor, P = 0.03. Abbreviations: RepT = RepTrial; ObjC = ObjChange; ExtT = ExtTrials; NewC = NewColor.
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bilateral inferior temporo-occipital activation. Thus, the electrocortical response in ExtTrials skips one processing stage (map 8) and directly proceeds to the stage common to all conditions (map 9).
confirmed significant amplitude differences at electrodes AF8, AF7, T10, Cz, T9, and Oz (Fig. 4).
Waveform analysis Amplitude differences of ERP traces at the nine electrode positions (approx. corresponding to AF8, AFz, AF7, T10, Cz, T9, P10, Oz, P7) were examined in the two windows that showed significant differences in the cluster analyses, i.e. between 190– 300 ms and 380–600 ms. In the first time window, strongest amplitude differences were found between the ExtTrial and all other conditions (Fig. 4). ExtTrials elicited a persisting positivity over the frontal electrodes and a negativity over the posterior (left and midline) electrodes. An ANOVA comparing the mean individual amplitudes for each task condition over the nine electrode positions in the period between 190 ms and 300 ms showed significant effects (P < 0.01, Neuman–Keuls corrected) at electrodes AF8, AFz, AF7, P7, and Oz (Fig. 4). In the second time window (380–600 ms), a late positive deflection over bilateral temporal electrodes was evoked by all but the ExtTrial condition. Conversely, a positive deflection was seen on Cz in ExtTrials, but not the other conditions. The ANOVA
This study demonstrates early (190–300 ms) and late (400– 600 ms) differences between electrocortical responses to the appearance and the absence of predicted outcomes, although these outcomes offered no prospect of a tangible reward or punishment, a win or loss. Most remarkably, absence of predicted outcomes (ExtTrials) induced an electrocortical response, which differed from all other task conditions. Similarly surprising and rare, but behaviorally irrelevant deviations from the predicted outcome (condition ObjChange) did not induce these electrocortical potential changes. Thus, the observed differences appear to be specific for the processing of behaviorally pertinent absence of predicted outcomes. The time range of the early specific response to ExtTrials corresponds to the so-called feedback-related negativity (FRN), also called medial frontal negativity (Gehring and Willoughby, 2002). This potential normally peaks about 250 ms after negative feedback indicating a loss in gambling tasks (Gehring and Willoughby, 2002; Hajcak et al., 2006; Yasuda et al., 2004). It has also been demonstrated in a choice-reaction task
Discussion
Fig. 4. Evoked potential curves. In the center of the figure, the arrangement of all 123 electrodes is presented. The black dots indicate electrode positions of the displayed waveform. The short vertical black bar in each graph indicates stimulus onset. A single bold star shows significant differences between task conditions during the time period between 190 ms and 300 ms, two stars between 380 ms and 600 ms. The empty graph on the lower left indicates the time scale and potential amplitudes (in μV).
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with delayed feedback (Luu et al., 2003) and a time-estimation task with feedback about the correctness of the estimation (Miltner et al., 1997). By contrast, when feedback about the correctness of a response was necessary for the learning of stimulus values, this potential did not differ between correct and error trials (Frank et al., 2005), indicating that its modulation depends on the precise task context and the behavioral significance of the feedback. The ExtTrials in our task diverge from these experiments in that subjects were asked to base anticipations on the previous trial, that is, not to guess. In that sense, an error was not to be considered “their fault” and had no negative consequence (no loss, no negative comment, no change of a score). The absence of the object at the anticipated position simply indicated a position change of the object requiring the adaptation of the choice in the next trial. Despite temporal coincidence, the electrocortical response to ExtTrials at 190–300 ms markedly differed from the typical FRN in several respects. The response was strongly positive at frontal leads (Fig. 4), whereas the FRN (or medial frontal negativity) is strongly negative at frontal positions (Gehring and Willoughby, 2002). In addition, inverse solutions indicated an anterior cingulate source of the FRN (Luu et al., 2000, 2003; Gehring and Willoughby, 2002). This area seems to be important for the detection of self-generated errors (Hester et al., 2005). By contrast, the source of the activity in response to ExtTrials in our task differed from confirmed trials (RepTrials) by a ventrolateral prefrontal (lateral OFC) activity (Fig. 2, map 6); there was no evidence of an anterior cingulate generator of this activity. It thus appears that, in a task in which subjects respond according to clear rules (according to the outcome of the last trial) and which provides no expectation of a win or loss, the behaviorally relevant absence of anticipated outcomes induces an electrocortical response which is different from guessing tasks involving rewards. We found a second time period between 400 and 600 ms, in which event-related potentials in response to absence of predicted outcomes differed from all other task conditions. In this period, ExtTrials led to the absence of a processing stage (Fig. 2, map 8) that was common to all other conditions. This late specific response to ExtTrials (400–600 ms) occurred in a period in which a late P300 might be seen. This potential has been reported to signal error trials and might relate to conscious awareness of the error (Frank et al., 2005). However, the configuration of the potential found in the present study does not correspond to a typical P300, as it was characterized by a central positivity (Fig. 4), rather than negativity (Donchin et al., 1978; Spencer et al., 2001). In addition, source analysis indicated a left superior parietal generator of the P300 (Pae et al., 2003), which is markedly different from the activity associated with the late electrocortical configuration dominating ExtTrials in the present study (Fig. 2, map 9). It is conceivable that the differences at the beginning of the time period between 400 and 600 ms (map 8, bitemporal activation) reflect the encoding of the continued validity of stimulus–response associations and of behavioral adaptation to the stimulus–response association (cluster map 9, immediate frontal activity in response to ExtTrials). This interpretation is compatible with our earlier study showing significant amplitude modulation at about 400– 600 ms associated with learning and recognition (Schnider et al., 2002). The interpretation is also compatible with earlier studies showing specific ERP components after 350 ms, which reflected cognitive processes such as recognition, source memory, recollection, and updating of working memory (Cycowicz et al., 2001; Duzel et al., 2001; Eimer, 2000; Halgren et al., 2002; Wilding and Rugg, 1996).
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In previous functional imaging studies, the suppression of previously correct responses (Elliott et al., 2000) as well as the update, in particular the reversal, of stimulus–response associations was associated with activity of the OFC (Fellows and Farah, 2003; Rolls, 2000). In our recent PET study using a similar paradigm as in the present study, we found left medial OFC activation indicating that the human OFC monitors outcomes irrespective of explicit reward (Schnider et al., 2005). OFC activation was considerably more extended, involving the OFC on both sides, when subjects were asked to guess (Schnider et al., 2005). The difference between the present study indicating left ventrolateral prefrontal activation in response to absence of anticipated outcomes (ExtTrials) and the more medial OFC activation obtained with PET may have different reasons. It is possible that electrical source analysis, with its relatively low spatial resolution, underestimated concurrent OFC activation. But it appears even more likely that PET, with its temporal resolution of approximately 45 s, reflected activation during many more components of the task, including decision making and the phase of anticipation (2.5 s), whereas transient influences on cortical activity, as found in the present study, were probably too discrete to induce significant alterations of brain metabolism as measured by PET. The two studies complement each other, in that one – PET – provided information about brain regions active over the whole task, and the other – ERP – providing temporal specifics regarding single outcome processing. In any case, the present study shows that the processing of behaviorally significant absence of an anticipated outcome in a task, which activates the OFC in PET, is associated with temporally discrete, but specific phasic alteration of electrocortical activity. In summary, this study shows that the human brain processes behaviorally relevant absence of predicted outcomes in a markedly different way than the confirmation of predicted outcomes. This difference has an early cortical expression around 200–300 ms, presumably indicating the suppression (extinction) of a previously valid memory (prediction), and a late component around 400– 600 ms, possibly reflecting behavioral adaptation. Acknowledgments This work was supported by The Swiss National Science Foundation grant no. 3200B0-100152 and 32000-113436 to A.S. We thank Denis Brunet, Stephanie Ortigue, Rolando Grave de Peralta Menendez and Sara Andino Gonzalez for their help, Lillian Zamorra and Toby Elliman for editorial assistance. References Anderson, S.W., Bechara, A., Damasio, H., Tranel, D., Damasio, A.R., 1999. Impairment of social and moral behavior related to early damage in human prefrontal cortex. Nat. Neurosci. 2, 1032–1037. Bechara, A., 2003. Risky business: emotion, decision-making, and addiction. J. Gambl. Stud. 19, 23–51. Bechara, A., Damasio, A.R., Damasio, H., Anderson, S.W., 1994. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50, 7–15. Bechara, A., Tranel, D., Damasio, H., Damasio, A.R., 1996. Failure to respond autonomically to anticipated future outcomes following damage to prefrontal cortex. Cereb. Cortex 6, 215–225. Bechara, A., Damasio, H., Damasio, A.R., 2000. Emotion, decision making and the orbitofrontal cortex. Cereb. Cortex 10, 295–307. Besag, J., 1986. On the statistical analysis of dirty pictures. J. R. Stat. Rev. 53, 259–302.
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Early cortical response to behaviorally relevant absence of anticipated outcomes: A human event-related potential study Armin Schnider, a,⁎ Christine Mohr, a,b,c Stéphanie Morand, a and Christoph M. Michel b a
Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, University Hospital Geneva, Av. de Beau-Séjour 26, CH-1211 Geneva 14, Switzerland b Functional Brain Mapping Laboratory, Division of Neurology, University Hospital Geneva, Micheli-du-Crest 24, CH-1211 Geneva 14, Switzerland c Department of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol BS8 1TU, UK Received 6 October 2006; revised 13 January 2007; accepted 19 January 2007 Available online 13 February 2007 Animals with lesions of the orbitofrontal cortex (OFC) have an extinction and reversal learning deficit. Humans with OFC lesions have similar deficits and often continue to act according to currently inappropriate memories. We tested when the human brain distinguishes between confirmed and negated outcomes of anticipations. Eleven participants predicted behind which one of two rectangles an object drawing was hidden while their cerebral activity was recorded from 123 surface electrodes. We found that absence of the predicted outcome induced specific electrical field topographies between 190 ms– 300 ms and 380 ms–600 ms. Behaviorally irrelevant deviation from predicted outcomes did not induce these alterations. Distributed linear inverse solutions indicated that the source of the early electric field topography after negated predictions differed by additional left ventrolateral prefrontal activation. The late differences in electrical field topographies were characterized by the selective absence of a processing stage in response to negated predictions. The study indicates early, specific cortical processing of behaviorally relevant absence of predicted outcomes. © 2007 Elsevier Inc. All rights reserved. Keywords: Anticipation; Outcome processing; Reality monitoring; Orbitofrontal cortex; Evoked potentials; Brain mapping; Imaging
Introduction The ability to adapt behavior when anticipated outcomes do not occur is crucial for flexible, goal-directed behavior. Human and animal studies point to an outstanding role of the orbitofrontal cortex (OFC) for this capacity (Dias et al., 1996; Rolls, 2000; Schoenbaum et al., 2000). Animals with OFC lesions fail to extinguish previously rewarded behavior and to adopt new behavior when stimulus⁎ Corresponding author. Service de Neurorééducation, Hôpitaux Universitaires de Genève, Av. de Beau-Séjour 26, CH-1211 Geneva 14, Switzerland. Fax: +41 22 372 3705. E-mail address: [email protected] (A. Schnider). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2007.01.047
outcome contingencies change (Bohn et al., 2003; Butter, 1969; Iversen and Mishkin, 1970). Patients suffering from OFC damage fail to disengage from previously correct, but currently incorrect behavior in reversal learning paradigms (Fellows and Farah, 2003; Rolls, 2000). In gambling tasks, patients with OFC lesions may continue to choose cards initially providing big gains, but eventually yielding big losses (Anderson et al., 1999; Bechara et al., 1994, 2000; Eslinger and Damasio, 1985; Price et al., 1990). Similar dysfunction may underlie certain forms of psychopathy (Blumer and Benson, 1975; Damasio, 1994), acquired sociopathy (Eslinger and Damasio, 1985; Price et al., 1990), or drug addiction (Volkow et al., 1991). These patient populations reveal impairments in reversal learning (Mitchell et al., 2002; Newman et al., 1987; Rahman et al., 1999; Rolls et al., 1994) and gambling (Anderson et al., 1999; Bechara, 2003; Bechara et al., 1996; Grant et al., 2000; Mitchell et al., 2002; Rahman et al., 1999) paradigms. Acute OFC lesions may profoundly impair the ability to adapt behavior and thought to ongoing reality: the patients act according to memories that do not pertain to current reality, a disorder called spontaneous confabulation (Schnider, 2003; Schnider and Ptak, 1999). These observations indicate that the OFC has a crucial role in the monitoring of anticipated outcomes and redirection of behavior when contingencies change. Accordingly, imaging studies with healthy participants showed activation of the OFC in gambling and reversal learning tasks (Critchley et al., 2001; Elliott et al., 1997, 1999, 2000; Fellows and Farah, 2003; O'Doherty et al., 2001; Rogers et al., 1999). However, the OFC also seems to monitor outcomes when there is no expectation of tangible reward. The simple confirmation that one is “right” activates the OFC, particularly when the outcome is uncertain (Elliott et al., 2000). In a recent PET study, OFC activation was observed when healthy subjects anticipated and monitored the outcome following simple predictions, although they had no perspective of receiving “reward”, not even in the form of a score or a comment (Schnider et al., 2005). While these functional imaging studies provided valuable information about the brain regions processing anticipation and outcomes,
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they did not reveal when and how rapidly the brain processes outcomes. In the present study, we aimed to explore when the healthy human brain distinguishes between confirmation and absence of anticipated outcomes, which are either behaviorally relevant or irrelevant, but which have no intrinsic value. We used a similar paradigm to a previous PETstudy (Schnider et al., 2005) but recorded brain activity with high-resolution event related potentials (ERP), which were analyzed using spatio-temporal mapping procedures. Methods Subjects Eleven right-handed, healthy participants (7 men, age range 20– 31 years) gave written, informed consent to participate in the study. The Ethical Committee of the University Hospital of Geneva approved the study. Anticipation task The task was adapted from the one used in our previous PET study (Schnider et al., 2005). Trials had the following general design (Fig. 1): First, a red and a green rectangle appeared on the screen with their position (left or right) varying randomly. Subjects then predicted behind which one of the two rectangles the line drawing of an object (Snodgrass and Vanderwart, 1980) was hidden by pressing with the index or middle finger of the right hand the button on the side of the chosen rectangle. Immediately after the button press, a fixation cross appeared in the center of the chosen rectangle for 700 ms. Then, feedback was provided for 1500 ms by presentation of an object drawing, indicating correct prediction, or a grid, indicating absence (and implicitly, change of position) of the object.
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After an inter-trial interval of 700 ms with white screen, the next trial started. Subjects were instructed to base their prediction on the previous trial and to refrain from guessing. They were told that the “object” would normally stay behind the same rectangle and only occasionally change position. In this case, a grid would signal the absence of the object behind the predicted rectangle. To ensure that participants really associated the object with a colored rectangle and thus performed experience-based anticipations rather than guesses, the same object was presented at least twice in succession behind the same colored rectangle (RepTrials, Fig. 1A). On subsequent trials, the probability of the object being present behind the same rectangle declined to 80%, 50%, 20%, and finally 0%. The subsequent presentation of the grid, which signaled the absence of the object behind the predicted rectangle, indicated that the object had changed its position (Fig. 1C). As the absence of an expected outcome resembles the absence of a predicted reward in animal studies, this condition was termed “Extinction” trials (ExtTrial). Following an ExtTrial, the object drawing had a 98% probability of appearing when the rectangle with the other color was selected on the next trial (Fig. 1D). This color change (NewCol) condition – that is, the first trial after change of the correct color – was separately analyzed to dissociate the learning of a new color-object association from experience-based anticipation behavior. In 2%, a second ExtTrial followed (ExtTrial2) with the intention of increasing attention and to decrease color-guided automatic responding. To evaluate the effect of unexpected outcomes having no behavioral relevance but inducing surprise, an additional condition was included. In this condition, the color of the correct rectangle was maintained but the object was different from the previous one. Thus, the trial was correct, as the “object” – albeit different from the previous one – was indeed “behind” the chosen rectangle. This condition with behaviorally irrelevant
Fig. 1. Task design. Sequential order of trials in the course of the experiment demonstrating the different outcome types. (A) A typical trial of the experiment consists of three steps: two differently colored rectangles are presented and subjects had to predict by button press (left black horizontal arrow) behind which one of the two rectangles an object is “hidden”. After the choice, a cross appears on the respective rectangle, then the object (correct choice) is presented. The curved flash on the side indicates that these three steps are repeated (RepTrial) up to four times before changing to another task condition (B and C). (B) In the object change condition (ObjChange), the choice of the correct rectangle results in the presentation of another object. (C) In an “Extinction” trial (ExtTrial), a grid indicating absence of the object is presented and finally, (D) First trial after an ExtTrial, that is, the first trial having a new color-object association (NewCol).
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changes of the object was called the object change condition (ObjChange; Fig. 1B). Subjects performed five blocks with 20 ObjChange, 20 ExtTrials, 2 ExtTrial2, and 20 NewCol (following ExtTrials) and approximately 94 RepTrials (total, approx. 781 trials). Trials with unprovoked errors were repeated until correct responses were obtained.
NewCol (task condition) as within-subject factors. For predetermined time windows, the number of time points during which cluster maps appeared was used to compare the different task conditions. Post-hoc single comparisons were conducted using Newman–Keuls statistics correcting for multiple comparisons.
EEG recording and averaging
Distributed linear inverse solution based on a Local AutoRegressive Average (LAURA) model (Grave de Peralta Menendez et al., 2001, 2004) was applied to estimate the sources of the cluster maps (Michel et al., 2004). This linear distributed inverse solution is capable of simultaneously dealing with multiple active sources of a priori unknown location (Michel et al., 2004). The lead field was calculated on a realistic head model that included 4024 nodes, selected from a 6 × 6 × 6 mm grid equally distributed within the gray matter of the average brain provided by the Montreal Neurological Institute (MNI).
Subjects were seated 140 cm from the computer screen. EEG was continuously recorded from 123 electrodes at a sampling rate of 500 Hz during the task (Electrical Geodesics Inc., Eugene, OR, USA). Electrical impedance was below 50 kΩ for all electrodes in accordance with systems specification (Tucker, 1993), filters were set at 0.1 and 100 Hz with the vertex electrode (Cz) as a reference. After the task, the EEG was recomputed off-line to the average reference. Stimuli were presented with e-prime (©Psychology Software Tools), which sends coded trigger pulses to the EEG system to mark stimulus onset. EEG was visually inspected off-line to reject epochs distorted by artifacts (eye blinks, body or eye movements). Data were digitally filtered between 1 and 30 Hz and averaged (ERPs) over 800 ms from − 200 ms to +600 ms relative to the onset of the presentation of the outcome stimulus (object or grid). No pre-stimulus baseline correction was applied. ERPs were realigned to the time point of maximum global field power of the P100 (Murray et al., 2004). Spatio-temporal analysis We applied spatio-temporal ERP analysis using a modified spatial k-means cluster analysis to determine the most dominant electrocortical map configurations (Michel et al., 2001; PascualMarqui et al., 1995). The optimal number of clusters was determined with a modified cross-validation criterion described in detail in Pascual-Marqui et al. (1995). Statistical smoothing was used to eliminate temporally isolated maps with low strength (Besag, 1986; Pascual-Marqui et al., 1995). As an additional constraint a given scalp topography had to be present for at least 10 consecutive data points (≥ 20 ms). This approach allows summarizing ERP data into a limited number of electrocortical map configurations and identifying time periods during which different experimental conditions evoke different maps (Michel et al., 2001). The spatial cluster analysis was applied to the four grand average ERPs of the four stimulus conditions over the time period between − 200 ms and 600 ms. For statistical analysis, we tested the appearance of the different cluster maps in the individual ERPs of each task condition by means of strength-independent spatial correlation. That is, the cluster maps were compared with the voltage topography of each time point of each individual ERP during the time period defined by the grand mean analysis, and labeled with the cluster map it best correlated with. This analysis yielded the number of time points a cluster map was present in the individual data for each task condition separately (Pegna et al., 1997). These values (the presence of each cluster map in the individual data) were then used for statistical analysis. Statistical analyses We used repeated measures ANOVAs to analyze temporal differences in the ERPs of the ExtTrial, RepTrial, ObjChange and
Source localization
Waveform analysis In order to allow comparison with traditional EEG analysis, amplitude differences of ERP traces at nine electrode positions over anterior, central, and posterior regions of both hemispheres and the midline (approx. corresponding to AF8, AFz, AF7, T10, Cz, T9, P10, Oz, P7) were examined. The potentials were averaged over periods of interest determined by the spatial cluster analysis described above. ANOVAs were used to compare the mean amplitudes between conditions within these windows. Results Task performance Over all trials, the error rate (excluding ExtTrials) was low, 4.9 ± 2.2%, confirming that the task was easy. An ANOVA on reaction times (anticipation response) with task condition as the repeated measure revealed a significant main effect [F(3,30) = 7.26; P = 0.0008]. Consistent with previous findings that response latencies were increased after error trials, response latencies were longest in the NewCol (693 ± 193 ms) as compared to the RepTrial (647 ± 144 ms, P= 0.04), the ObjChange (630 ± 149 ms, P= 0.02) and the ExtTrial (595 ± 143 ms, P= 0.0005). Response latencies did not differ between the RepTrial, the ObjChange, and the ExtTrial (all P-values > 0.05). Event-related potentials Spatio-temporal analysis Spatial cluster analysis applied to the ERPs of the four task conditions revealed a total of nine different cluster maps, which best explained the whole data set (Fig. 2, middle part). The first two maps appeared between 200 ms prior to and 190 ms after the presentation of the outcome, independent of whether an object drawing or grid was shown (Fig. 2, cluster maps 1 and 2). Although the grand mean analysis suggested that map 1 might be more present in the ObjChange and the NewCol conditions and map 2 in the RepTrial and the ExtTrial conditions, the interaction was not significant. Between 190 ms and 300 ms after presentation of the outcome, ExtTrials induced a significantly different electrocortical response
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Fig. 2. Functional cluster analysis and distributed inverse solution. In the middle, the sequence of the nine cluster maps that had been determined from the grand mean of all subjects between − 200 ms and 600 ms after outcome presentation are displayed for each task condition. The amplitude of the curves reflects the global field power. For cluster maps with significant differences between task conditions, the electrocortical map configuration (nose upward, right ear on the right side) and inverse solutions are presented to the right and left of the functional cluster analyses.
than all other conditions: map 6 dominated in ExtTrials, while map 5 dominated in all other conditions (Fig. 2). There was a significant interaction between maps 5 and 6 and task conditions [F3.30 = 28.02, P < 0.0001]. Map 6 was present more often (longer) in ExtTrials and map 5 in all other conditions (all P-values < 0.002, Fig. 3). The sources associated with the maps as estimated by LAURA are illustrated in Fig. 2 (left). While both maps reflected occipito-temporal activation, map 6 reflected additional left ventrolateral prefrontal (lateral orbitofrontal) activation. Between 300 ms and 380 ms after outcome presentation, two different maps appeared: map 7 in RepTrial and NewCol trials, and map 3 in ObjChange and ExtTrial trials (Fig. 2). However, when the frequency was analyzed with which these maps were present in
the ERPs of the individual subjects, the interaction was not significant. Between 380 ms and 600 ms, confirmed anticipations (RepTrial, ObjChange, NewCol) first induced map 8, followed by map 9 (Fig. 2). In contrast, ExtTrial only induced map 9 in this period. The ANOVA on the frequency with which map 8 and 9 appeared, showed a significant interaction [F3.30 = 8.30, P= 0.0004]. In ExtTrials, map 9 was more frequently present in the ERPs of the individual subjects than map 8 (P= 0.003, Fig. 3). In addition, map 9 was more frequently present in the ExtTrial than the NewCol trials (P= 0.03). LAURA revealed for map 9 a bilateral ventrolateral prefrontal (lateral orbitofrontal) and right antero-medial temporal activation. For map 8, in contrast, the inverse solution showed
Fig. 3. Mean data points (moment-by-moment) with which the cluster maps determined from the group-averaged ERPs appeared in the individual ERPs. Presented are scalp configurations of significant differences between task conditions; (A) cluster map 5 and 6 (see Fig. 2) during the early time period between 190 ms and 300 ms. (B) Frequency of cluster map 8 and 9 during the later time period between 380 ms and 600 ms after stimulus onset. Vertical lines indicate standard deviations. a: Map 5: ExtTrial against all other task conditions, all P-values < 0.0006; b: Map 6: ExtTrial against all other task conditions, all P-values < 0.0006; c: ExtTrial: Map 8 against map 9, P = 0.003; d: Map 9: ExtTrial against NewColor, P = 0.03. Abbreviations: RepT = RepTrial; ObjC = ObjChange; ExtT = ExtTrials; NewC = NewColor.
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bilateral inferior temporo-occipital activation. Thus, the electrocortical response in ExtTrials skips one processing stage (map 8) and directly proceeds to the stage common to all conditions (map 9).
confirmed significant amplitude differences at electrodes AF8, AF7, T10, Cz, T9, and Oz (Fig. 4).
Waveform analysis Amplitude differences of ERP traces at the nine electrode positions (approx. corresponding to AF8, AFz, AF7, T10, Cz, T9, P10, Oz, P7) were examined in the two windows that showed significant differences in the cluster analyses, i.e. between 190– 300 ms and 380–600 ms. In the first time window, strongest amplitude differences were found between the ExtTrial and all other conditions (Fig. 4). ExtTrials elicited a persisting positivity over the frontal electrodes and a negativity over the posterior (left and midline) electrodes. An ANOVA comparing the mean individual amplitudes for each task condition over the nine electrode positions in the period between 190 ms and 300 ms showed significant effects (P < 0.01, Neuman–Keuls corrected) at electrodes AF8, AFz, AF7, P7, and Oz (Fig. 4). In the second time window (380–600 ms), a late positive deflection over bilateral temporal electrodes was evoked by all but the ExtTrial condition. Conversely, a positive deflection was seen on Cz in ExtTrials, but not the other conditions. The ANOVA
This study demonstrates early (190–300 ms) and late (400– 600 ms) differences between electrocortical responses to the appearance and the absence of predicted outcomes, although these outcomes offered no prospect of a tangible reward or punishment, a win or loss. Most remarkably, absence of predicted outcomes (ExtTrials) induced an electrocortical response, which differed from all other task conditions. Similarly surprising and rare, but behaviorally irrelevant deviations from the predicted outcome (condition ObjChange) did not induce these electrocortical potential changes. Thus, the observed differences appear to be specific for the processing of behaviorally pertinent absence of predicted outcomes. The time range of the early specific response to ExtTrials corresponds to the so-called feedback-related negativity (FRN), also called medial frontal negativity (Gehring and Willoughby, 2002). This potential normally peaks about 250 ms after negative feedback indicating a loss in gambling tasks (Gehring and Willoughby, 2002; Hajcak et al., 2006; Yasuda et al., 2004). It has also been demonstrated in a choice-reaction task
Discussion
Fig. 4. Evoked potential curves. In the center of the figure, the arrangement of all 123 electrodes is presented. The black dots indicate electrode positions of the displayed waveform. The short vertical black bar in each graph indicates stimulus onset. A single bold star shows significant differences between task conditions during the time period between 190 ms and 300 ms, two stars between 380 ms and 600 ms. The empty graph on the lower left indicates the time scale and potential amplitudes (in μV).
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with delayed feedback (Luu et al., 2003) and a time-estimation task with feedback about the correctness of the estimation (Miltner et al., 1997). By contrast, when feedback about the correctness of a response was necessary for the learning of stimulus values, this potential did not differ between correct and error trials (Frank et al., 2005), indicating that its modulation depends on the precise task context and the behavioral significance of the feedback. The ExtTrials in our task diverge from these experiments in that subjects were asked to base anticipations on the previous trial, that is, not to guess. In that sense, an error was not to be considered “their fault” and had no negative consequence (no loss, no negative comment, no change of a score). The absence of the object at the anticipated position simply indicated a position change of the object requiring the adaptation of the choice in the next trial. Despite temporal coincidence, the electrocortical response to ExtTrials at 190–300 ms markedly differed from the typical FRN in several respects. The response was strongly positive at frontal leads (Fig. 4), whereas the FRN (or medial frontal negativity) is strongly negative at frontal positions (Gehring and Willoughby, 2002). In addition, inverse solutions indicated an anterior cingulate source of the FRN (Luu et al., 2000, 2003; Gehring and Willoughby, 2002). This area seems to be important for the detection of self-generated errors (Hester et al., 2005). By contrast, the source of the activity in response to ExtTrials in our task differed from confirmed trials (RepTrials) by a ventrolateral prefrontal (lateral OFC) activity (Fig. 2, map 6); there was no evidence of an anterior cingulate generator of this activity. It thus appears that, in a task in which subjects respond according to clear rules (according to the outcome of the last trial) and which provides no expectation of a win or loss, the behaviorally relevant absence of anticipated outcomes induces an electrocortical response which is different from guessing tasks involving rewards. We found a second time period between 400 and 600 ms, in which event-related potentials in response to absence of predicted outcomes differed from all other task conditions. In this period, ExtTrials led to the absence of a processing stage (Fig. 2, map 8) that was common to all other conditions. This late specific response to ExtTrials (400–600 ms) occurred in a period in which a late P300 might be seen. This potential has been reported to signal error trials and might relate to conscious awareness of the error (Frank et al., 2005). However, the configuration of the potential found in the present study does not correspond to a typical P300, as it was characterized by a central positivity (Fig. 4), rather than negativity (Donchin et al., 1978; Spencer et al., 2001). In addition, source analysis indicated a left superior parietal generator of the P300 (Pae et al., 2003), which is markedly different from the activity associated with the late electrocortical configuration dominating ExtTrials in the present study (Fig. 2, map 9). It is conceivable that the differences at the beginning of the time period between 400 and 600 ms (map 8, bitemporal activation) reflect the encoding of the continued validity of stimulus–response associations and of behavioral adaptation to the stimulus–response association (cluster map 9, immediate frontal activity in response to ExtTrials). This interpretation is compatible with our earlier study showing significant amplitude modulation at about 400– 600 ms associated with learning and recognition (Schnider et al., 2002). The interpretation is also compatible with earlier studies showing specific ERP components after 350 ms, which reflected cognitive processes such as recognition, source memory, recollection, and updating of working memory (Cycowicz et al., 2001; Duzel et al., 2001; Eimer, 2000; Halgren et al., 2002; Wilding and Rugg, 1996).
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In previous functional imaging studies, the suppression of previously correct responses (Elliott et al., 2000) as well as the update, in particular the reversal, of stimulus–response associations was associated with activity of the OFC (Fellows and Farah, 2003; Rolls, 2000). In our recent PET study using a similar paradigm as in the present study, we found left medial OFC activation indicating that the human OFC monitors outcomes irrespective of explicit reward (Schnider et al., 2005). OFC activation was considerably more extended, involving the OFC on both sides, when subjects were asked to guess (Schnider et al., 2005). The difference between the present study indicating left ventrolateral prefrontal activation in response to absence of anticipated outcomes (ExtTrials) and the more medial OFC activation obtained with PET may have different reasons. It is possible that electrical source analysis, with its relatively low spatial resolution, underestimated concurrent OFC activation. But it appears even more likely that PET, with its temporal resolution of approximately 45 s, reflected activation during many more components of the task, including decision making and the phase of anticipation (2.5 s), whereas transient influences on cortical activity, as found in the present study, were probably too discrete to induce significant alterations of brain metabolism as measured by PET. The two studies complement each other, in that one – PET – provided information about brain regions active over the whole task, and the other – ERP – providing temporal specifics regarding single outcome processing. In any case, the present study shows that the processing of behaviorally significant absence of an anticipated outcome in a task, which activates the OFC in PET, is associated with temporally discrete, but specific phasic alteration of electrocortical activity. In summary, this study shows that the human brain processes behaviorally relevant absence of predicted outcomes in a markedly different way than the confirmation of predicted outcomes. This difference has an early cortical expression around 200–300 ms, presumably indicating the suppression (extinction) of a previously valid memory (prediction), and a late component around 400– 600 ms, possibly reflecting behavioral adaptation. Acknowledgments This work was supported by The Swiss National Science Foundation grant no. 3200B0-100152 and 32000-113436 to A.S. We thank Denis Brunet, Stephanie Ortigue, Rolando Grave de Peralta Menendez and Sara Andino Gonzalez for their help, Lillian Zamorra and Toby Elliman for editorial assistance. References Anderson, S.W., Bechara, A., Damasio, H., Tranel, D., Damasio, A.R., 1999. Impairment of social and moral behavior related to early damage in human prefrontal cortex. Nat. Neurosci. 2, 1032–1037. Bechara, A., 2003. Risky business: emotion, decision-making, and addiction. J. Gambl. Stud. 19, 23–51. Bechara, A., Damasio, A.R., Damasio, H., Anderson, S.W., 1994. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50, 7–15. Bechara, A., Tranel, D., Damasio, H., Damasio, A.R., 1996. Failure to respond autonomically to anticipated future outcomes following damage to prefrontal cortex. Cereb. Cortex 6, 215–225. Bechara, A., Damasio, H., Damasio, A.R., 2000. Emotion, decision making and the orbitofrontal cortex. Cereb. Cortex 10, 295–307. Besag, J., 1986. On the statistical analysis of dirty pictures. J. R. Stat. Rev. 53, 259–302.
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