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Neuroscience and Biobehavioral Reviews 35 (2011) 452–461

Contents lists available at ScienceDirect

Neuroscience and Biobehavioral Reviews

journa l homepage: www.e lsev ier .com/ locate /neubiorev

eview

neurophysiological evaluation of a cognitive cycle in humans

arlos M. Gómez ∗, Angelica Floresab. of Human Psychobiology, Department of Experimental Psychology, University of Sevilla, c/Camilo Jose Cela s/n, 41010 Sevilla, Spain

r t i c l e i n f o

rticle history:eceived 9 February 2010eceived in revised form 25 May 2010ccepted 27 May 2010

a b s t r a c t

The present review describes and analyzes several recent papers in which the processes of prepara-tion, evaluation and changing a cue’s predictive value on a trial-by-trial basis conform a cycle thatpermits behavior to be constantly updated. This approach is an extension of Joaquin Fuster’s proposalof a “perception–action” cycle in which executive networks are constantly updated as a function of thetrials’ outcome. The presented results can also be considered in relation to the computational Bayesian

eywords:reparationvaluationrial-by-trial learningNV3a

brain framework proposed by Friston (2009). The present approach is based on human electrophysiolog-ical studies of Posner’s central cue paradigm, which provides the possibility to dissociate the followingprocessing steps: (i) preparation for certain stimuli, (ii) evaluation of the validity or invalidity of thepreparatory state, and (iii) the feedback cycling of the information extracted from one trial to the next.This trial-by-trial learning would be a potential basis for organism adaptation.

3bayesian brain

© 2010 Elsevier Ltd. All rights reserved.

ontents

1. Rational for a cognitive cycle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4522. The preparatory phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4543. Perception and evaluation of S2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4554. Transfer of information to next trial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4575. Developmental studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4586. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 460References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 460

. Rational for a cognitive cycle

In daily life, humans continuously monitor their actions tonsure that they are appropriate for the environment. In a nat-ralistic perspective, the “perception–action cycle” concept was

ntroduced by Fuster (2003, 2004) to highlight the continuous inter-lay between the outcomes of perceptual and executive networks.

n this neurocognitive model, the sensory and executive networksnteract continuously at different levels of the processing hier-rchy. One major consequence of such interaction would be the

credibility that they can assign to those inputs. After encounterswith real stimuli the neural nets change the synaptic weights inorder to make better predictions of the environment in the nextfuture (Friston, 2009, 2010).

The purpose of this review is to present information obtained inthe past years from our group and others about how brain systemsare able to predict in a short-term, certain characteristics about sub-sequent incoming stimuli. As a consequence of this prediction, theactual stimuli must be evaluated. Consequently, brain responsesindexing the validity or invalidity of predictions in the current trial

bility to monitor appropriateness between perception and action.n computational terms these ideas are embedded in the Bayesianomputational framework proposed by Friston (2009), in whicheural networks establish predictions about sensory inputs and the

∗ Corresponding author. Tel.: +34 954557800.E-mail address: cgomez@us.es (C.M. Gómez).

149-7634/$ – see front matter © 2010 Elsevier Ltd. All rights reserved.oi:10.1016/j.neubiorev.2010.05.005

will be discussed. Finally, the brain response which represents thesignature of previous trial information being incorporated in theprocessing of the subsequent trial (inter-trial validity/invalidity

effect) will be also presented.

The aim of attention and its motor counterpart, intention ofmovement, is to bias the selection of relevant stimuli and appropri-ate responses that a subject makes at a given moment in relation tothe evaluation of cues and context. For instance, a red traffic light

d Biobehavioral Reviews 35 (2011) 452–461 453

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Fig. 1. Scheme of the cognitive cycle. A certain cue S1 provides information aboutthe features of S2 and induces a task-specific preparatory state, which facilitatesthe perception and responses of S2. In addition, the subjects assign a certain cred-ibility value to the cue (the conditional a priori probability P(S2/S1)). When the

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C.M. Gómez, A. Flores / Neuroscience an

ells you to stop, but once you have stopped, the red light couldlso be considered as a signal for the upcoming green light, cueinghe adequate responses for accelerating. Selecting an appropriateesponse to a stimulus is not an easy task when there are sev-ral similar options. Stimulus saliency and low threshold responsesue to implicitly consolidated stimulus–response habits are wayso partially overcome the problem. However, in new and com-lex tasks, in which there is no certainty about the nature of thetimuli and/or responses, these mechanisms would not be able toroduce an adequate selection of pairs of stimuli and responses,iven the non-consolidated habits and the similar energetic val-es of different stimuli. Preparatory activity, as a function of ariori probabilities generated in previous similar situations, couldertainly bias the selection of stimuli and appropriate actions. How-ver, preparation can be correct (valid) or incorrect (invalid) as aunction of the real stimulus, which may or may not match thexpectations.

As a global consideration in view of our previous results, we willut forth the idea of a simple cognitive act in which preparation forertain stimuli is followed by the perception–evaluation and cor-esponding action. The evaluation of the stimulus is important inrder to assign credibility to the cues. More formally P(S2/S1) ishe a priori conditional probability, which is the probability that an2 occurs given that a certain S1 has occurred. The final point ofhis review pertains to the idea that the information obtained by

eans of the evaluation in a given trial (a posteriori probabilities) ismmediately incorporated and taken into account for the process-ng of next trial. Therefore, the a posteriori probability of the currentrial becomes the a priori probability of next trial. These ideas areummarised in Fig. 1.

S1 is the presented cue, which includes some information about

he possible characteristics of the S2 stimulus (p(S2/S1)). S2 trig-ers the response to the information conveyed by the actual targettimulus S2, but during the evaluation process, S2 can be consideredalid or invalid to the extent that it fulfils or not the expectationsreated by the S1. Finally a response is executed. In Fig. 1 the idea

ig. 2. Sequence of two trials in Posner’s central cue paradigm. A directional cue indicaterial can be valid or invalid depending on whether the cue has predicted the target stimunfluence on the next trial. In Fig. 2 appear the possible sequences of the two trials. The pn the ERPs by the CNV component. The evaluation phase is indexed by the P3 componenext was evaluated in the P3 corresponding to the target of the second trial (trial N + 1) o

n the lower part of Fig. 2 (This image is extracted from Gómez et al., 2009).

target stimulus is presented, the S2 is evaluated, and depending on the outcome ofthe trial (valid or invalid), conditional probabilities are modified, transferring thisinformation to the processing of the following trial.

that the outcome of the trial feedbacks to the brain in order to incor-porate the outcome of the trial is marked by the red and blue lines,which suggest possible re-entering of information from the percep-tual, evaluative, motor and/or propioceptive systems in the brain.This feedback would change the value assigned to the a priori con-ditional probability relating S1 and S2 (p(S2/S1)). However, for thesake of this review and given the complexity of that matter, onlythe role of feedback, not the origin, will be taken into account.

One type of stimulus sequence that seems particularly wellsuited for testing congruency between expected and current stim-uli is Posner’s central cue paradigm (Posner, 1980). In this paradigm,the central cue may validly (V trials) or invalidly (I trials) indicatethe spatial position of an upcoming target (Fig. 2). If the cue is a

valid predictor of the target, there is a benefit in the RT with respectto neutral cues. However, if the target is incorrectly cued, a costoccurs in the RT with respect to neutral cues (Posner, 1980). In theseries of experiments from our group we review here, no neutral

s the probable location of a target with certain validity, typically around 80%. Thelus correctly or incorrectly. The outcome of a trial would be expected to have somereparation phase is evaluated in the period between cue and target. It is reflected

t induced by each target stimulus. The transfer of information from one trial to thef the two-trial sequence. The temporal sequence of stimulus presentation appears

4 d Biobehavioral Reviews 35 (2011) 452–461

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Fig. 3. Reaction times during three experiments of Posner’s central cue paradigm.Experiment 1 (Gómez et al., 2008a,b) corresponds to a central cue paradigm withvertical cues and targets in young adults. Experiment 2 corresponds to a similar typeof experiment but with horizontal cues (Digiacomo et al., 2008) in young adults.Experiment 2 (Ch.) corresponds to the same type of experiment as experiment 2 inchildren (non-published data). VV: valid–valid sequence of trials; IV: invalid–valid;II: invalid–invalid; VI: valid–invalid. YA: young adults, Ch: children. Please noticethat when the target of the second trial in the sequence is Valid (VV and IV) theRTs are shorter than when the target is Invalid (II and VI). The pattern of RTs V < I

54 C.M. Gómez, A. Flores / Neuroscience an

ues were used to improve the signal to noise ratio of the V andtrials.

The Bayesian brain perspective is particularly relevant in theontext of the present discussion because it entails the update ofeliefs about subsequent targets based upon cues in the current andrevious trials. Technically, this Bayesian updating is usually imple-ented with some form of Kalman filtering and leads to predictive

oding schemes when considered in a neurobiological context. Thiss potentially important, because predictive coding depends uponhe suppression of prediction errors thought to originate in therincipal (superficial pyramidal) cells originating forward connec-ions in the brain (Friston, 2010). Crucially, these cells are thoughto be the major contributors to ERPs, which we will discuss exten-ively below.

In what follows, we will look at the electrophysiological cor-elates of violations, in terms of a validity/invalidity effects onvoked responses. In the next section, we will consider the trans-er of information from one trial to the next. With respect to thenderlying neural mechanisms, we will consider how within-trialontext is represented by neuronal activity and how this is reflectedn observed brain responses. This can be regarded as optimisingeuronal states (activity) during perceptual inference. In the nextection, we will consider perceptual learning of the associationsetween cues and the probabilistic outcomes they predict. Oneight suppose that this learning or association is encoded in con-

ection strengths in the brain (possibly by short-term changes inynaptic efficacy—plasticity). Having said this, both optimisationf neuronal activity and connectivity are closely linked becausehe latter depends upon the former through activity-dependenthanges in synaptic strength.

The general idea that we will put forward is that there shouldxist neural signatures of (1) task-related neural set preparationinduced by the orientation cue), (2) the perceptive–evaluativerocess in which the validity or invalidity of the trial should bebserved, and (3) the transfer of information obtained in the currentrial to the next. These phases are marked in Fig. 1.

. The preparatory phase

The preparatory phase in the brain has a characteristic neu-ophysiological signature called the contingent negative variationCNV) component. The CNV is observed in situations of expectancynduced by a warning stimulus (S1) providing pertinent informa-ion about the occurrence of a second stimulus (S2), the so-calledmperative, executive, or target stimulus. The preparation for S2nduced by the warning is what generates the change in corti-al activity seen in the CNV (Walter et al., 1964; Rockstroh et al.,982). The CNV comprises at least two different phases: an earlyhase related to stimulus orientation, and a late phase related toreparation for motor response (Loveless and Sanford, 1974). Someeports also suggest participation of sites responsible for sensoryrocessing in the genesis of the CNV (Brunia, 1999; Gómez et al.,001, 2003). It has been proposed that S1 acts as a warning stimulushat activates areas needed for the subsequent processing of the S2timulus (Brunia, 1999). How task-specific the cortical activation isuring the preparatory period and how it influences the subsequent

mperative stimulus is a subject of much debate (i.e. Frith, 2001;natsakanian and Tarkka, 2002; Gómez et al., 2001, 2003, 2004).

ll these activations of the neural set related to the processing of thepcoming target could be attentionally controlled through fronto-

arietal networks (Corbetta and Shulman, 2002; Hopfinger et al.,000; Gómez et al., 2007). This fronto-parietal network may acti-ate the contralateral extrastriate cortex which has been observedo be active during the preparation phase induced by the cue inMRI experiments (Hopfinger et al., 2000).

corresponds to the cost–benefit pattern described by Posner (1980). The pattern ofRTs VV < IV < II < VI corresponds to the inter-trial validity–invalidity effect describedby Jongen and Smulders (2007).

Using directional central cues, two studies have shown waves(CNV) that could represent the pre-activation of sensory cortices,suggesting that the CNV could have a sensory component (Deeckeet al., 1984; Harter et al., 1989). Electrophysiological recordings ofsingle neurons in animals and fMRI studies in humans (Requin etal., 1990; Luck et al., 1997; Kastner et al., 1999; Lee et al., 1999)support the activation of frontal, striate and extrastriate corticesduring preparatory periods while visual stimulation is delivered.Based on these observations, one could postulate that the neuralpreparatory activity in primary motor (Cui et al., 2000; Gómez etal., 2003) and posterior sites (Gómez et al., 2001, 2003) anticipatesthe activation of these same areas, which are needed for the actualprocessing of the imperative stimulus. One clear example of thisappears in an experiment where a central light cues for the presen-tation of a peripheral light. In this experiment, in addition to theactivation of the prefrontal and cingulate cortices, there is an acti-vation of the primary motor cortex contralateral to the hand to beused, indicating that the areas that are needed for processing theupcoming stimulus are pre-activated (Gómez et al., 2003).

Going back to the problem of specific preparation occurringafter the cue during Posner’s central cue paradigm, our proposalis that the task-specific preparation, indexed by the CNV, is thecause of the cost–benefit pattern occurring during Posner’s centralcue paradigm (Posner and Cohen, 1984) (Fig. 3). The same proposalhas previously been made based on fMRI data by Hopfinger et al.(2000). In a Posner-type experiment (Gómez et al., 2004) where adirectional central arrow indicates in which ear an imperative stim-ulus will be presented (validity of the cue 84%), the activation of theprimary auditory cortex contralateral to the cued side and the cor-responding primary motor cortex was observed by analyzing thecontingent magnetic variation (CMV). This pattern of neural acti-vation could explain the cost–benefit pattern of the RTs observedin Posner-type central cue experiments: benefit when the centralarrow allows the activation of the cortex that would process thestimulus and produce the response, and cost when the incorrectsensory and motor cortices are activated and a reorientation ofattention must occur.

In the same sense, in a classical visual central cue Posnerparadigm, a clear sensory CNV possibly originating in the visualextrastriate cortex appeared in both children and adults (Floreset al., 2009) (Fig. 4, top). The extrastriate origin of these poste-

C.M. Gómez, A. Flores / Neuroscience and Biobehavioral Reviews 35 (2011) 452–461 455

Fig. 4. Topography of the different components used to evaluate the cognitive cycle. Top: Posterior sensory CNV indicating the activation of the occipital cortex contralateralto the cue (extracted from Flores et al., 2009). Middle: Evaluation of the outcome of a trial by means of the P3 component. An invalid trial induces a P3a-like component( t in thv matioo ls mina

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middle left) and a P3b-like component (middle right) which are particularly evidenalid) (extracted from Gómez et al., 2008a). Below: To show the transfer of the inforf the P3 component in trial N + 1 is represented. The difference wave of P3 of IV triamplitude of IV trials with respect to VV trials (extracted from Gómez et al., 2009).

ior negativities was supported by a dipole analysis. This patternf activation in the occipital scalp of the hemisphere contralateralo the cue gives additional support to the idea of a task-specificattern of activation in the CNV (Gómez et al., 2004), and confirmslectrophysiologically previous studies using fMRI (Hopfinger et al.,000).

Therefore, when a directional cue indicates the probable loca-ion of a target stimulus, a task-specific sensory–motor neural set isctivated in order to facilitate the processing of the probable incom-ng stimulus. The CNV and CMV (contingent magnetic variation)licited after the appearance of the cue are the electrophysiolog-cal signatures of this preparation (Gómez et al., 2004; Flores etl., 2009), which can also be observed in hemodynamic studiesHopfinger et al., 2000).

The presence of a task-specific cortical network has also beenetected in the differential topographies of the negative slow wavesegistered during retrieval of different items during a memory taskRösler et al., 1995). In a review, Brunia and Van Boxtel (2001)ointed out the possibility that cortically generated slow negativeotentials index the preparatory processes dealing with selection.runia’s functional interpretation of these negativities is based onhe proposal that they are a consequence of the tonic depolarizationf apical dendrites in the cortex, which would allow a state of ele-ated excitability so the firing threshold can be reached (Rockstroht al., 1982). Preparatory activity would certainly bias the selectionf stimuli and appropriate action.

. Perception and evaluation of S2

The aim of this section is to establish which neural patternsre activated for S2 target stimuli as a function of being validly or

e P3 Current Source density maps and in the voltage difference maps (invalid minusn obtained by the outcome of trial N (valid or invalid) to trial N + 1, the topographyus VV trials shows a small but statistically significant increase in the P3 component

invalidly cued. The early sensory and late endogenous componentsare modulated by the valid/invalid nature of S2. The spatial cue-ing effects on the attentional sensory processing have previouslybeen evaluated by analyzing the modulation of the ERPs to validand invalid cues (Eimer, 1993; Mangun and Hillyard, 1991; Perchetand García-Larrea, 2000; Perchet et al., 2001). The general resultobtained was an increase in P1 and N1 and a decrease in posteriorP3 components in validly cued trials with respect to invalid ones.The P1 component is the earliest ERP component modulated byattention (Fig. 5) and it is considered to reflect the cost of payingattention to unattended locations (Anllo-Vento, 1995; Coull, 1998;Luck et al., 1990; Mangun and Hillyard, 1991; Mangun et al., 1993;Talsma et al., 2005). The increase of the N1 component reflects notonly the benefit of paying attention to attended locations, but alsothe starting point of discriminative processes, which are increasedat the spatially attended locations. The activation of the extrastri-ate cortex contralateral to the cue, occurring prior to the occurrenceof S2, is probably the neural mechanism promoting increased pro-cessing at attended locations (Hopfinger et al., 2000; Gómez et al.,2004; Flores et al., 2009). Therefore, the neural set whose activityhas been attentionally biased during the preparatory period couldbe able to increase the processing level of the attentionally cuedstimuli, as indexed by the P1 and N1 components.

However, the increased P1 and N1 ERP components in validlywith respect to invalidly cued targets would also be interpreted interms of the Bayesian brain hypothesis (Friston, 2010). In terms of

predictive coding schemes for Bayesian updating one could think ofthe enhanced early components (during valid trials) as a boostingof prediction error in sensory channels whose precision (credibil-ity) is encoded in activity associated with the CNV. Probably, P1would be more related to this Bayesian scheme than the N1 com-

456 C.M. Gómez, A. Flores / Neuroscience and Biob

Fig. 5. Event-related potentials for validly and invalidly cued targets. The early P1component is increased in valid with respect to invalid conditions. The late endoge-nous P3a and P3b components present a higher amplitude in the invalid than in thevti

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when I trials were compared to V trials. A similar result was

alid condition. In this particular case he N1 component was not higher in the validhan in the invalid condition, probably due to the long duration of the P1 componentn the valid condition.

onent because it reflects the cost of paying attention to the invalidpatial target position. Additionally, late endogenous componentsave been shown to be modulated by the valid/invalid nature ofues.

Regarding the P3 component, a delay in I trials with respect totrials and to non-cue conditions has been described, suggesting a

elay in the processing time of I target stimuli (Perchet and García-arrea, 2000). An increase in posterior positivities for I as comparedo V conditions at the latency of the P3 component has also beenescribed (Mangun and Hillyard, 1991; Eimer, 1993). The increase

n the late positivity would indicate that the subjective expectancynduced by the cue was not accomplished in I trials (Mangun andillyard, 1991). Absence of P3 increase has also been reported, but

n experimental conditions differing from the previous studies inhe difficulty of the task, the time interval between the S1 and the2, and in the number of trials in which a response was requiredonly a 25%) (Talsma et al., 2005). In some recent studies (Gómezt al., 2008a; Digiacomo et al., 2008) using Posner’s central cuearadigm, an increased P3a and P3b has been obtained during Irials as compared to V trials (Fig. 4, middle; Fig. 5). The highermplitude of P3 in I than V trials has been suggested to representhe assessment of the lack of adequacy between sensory–motorreparation and sensory perception on the one hand and the actualction in response to the target stimulus on the other. It has beenuggested that the most important component of this assessments revision of the S1–S2 (cue–target) contingency value (Gómez etl., 2008a). In this approach, it is important to separate anteriornd early P3 components of ERPs (P3a-like) from posterior andate ones (P3b-like), since source localization studies and scalp cur-ent source analysis have allowed early anterior and late posteriorources to be separated under I and V conditions (Gómez et al.,008b). It must be remarked that invalid trials increase the acti-ation of current sources in the brain with respect to valid trialsy means of increasing the inter-trial coherence (Digiacomo et al.,

008).

To put these results in context we need to consider the possiblesychophysiological meaning of the P3 component. The P3a com-onent is generated as a brain response to stimuli that are novel in

ehavioral Reviews 35 (2011) 452–461

comparison to more frequent stimulation. In fact, completely novelstimuli generate a higher amplitude P3a component than deviantbut often-repeated stimuli (Escera et al., 1998; Friedman et al.,2001). A larger P3a (Friedman et al., 2001; Dien et al., 2003) wouldthus indicate that the invalidly cued target is processed as a novelstimulus. In contrast, the P3b is a late positive component with aparietal distribution and typically appears in odd-ball paradigms.It is well known that the amplitude of P3 is inversely related to theprobability of stimulus appearance (Duncan-Johnson and Donchin,1977). According to Donchin and Coles’ (1988) interpretation ofthe cognitive meaning of P3b, the higher P3b in invalid trials wouldrepresent a context-updating operation and subsequent memorystorage (Polich, 2007). An alternative interpretation of the cogni-tive meaning of P3 was suggested by Verleger et al. (2005), whoindicated that P3b is related to the neural linkage between stimu-lus perception and the response to that stimulus. A recent proposalrelates the P3b component to the neuroinhibition needed to focusattention on the relevant task, facilitating the interference-freeaction of memory systems (Polich, 2007).

There are also fMRI studies showing increased activation duringinvalid trials as compared to valid trials. The studies of Vossel et al.(2006) computed direct comparisons between Invalid and Validtargets. They obtained higher activation for invalid targets withrespect to valid targets in the right hemisphere in areas includ-ing the inferior frontal gyrus, the middle and superior temporalgyrus, the posterior part of the superior temporal sulcus and theparahippocampal gyrus, and bilateral activation in the intrapari-etal sulcus (including the right supramarginal gyrus). Moreover, theleft thalamus also showed higher activation in invalid targets withrespect to valid targets. This network should be involved, at leastin part, in generating the electrophysiological changes previouslydescribed. However, it must be remarked that given that fMRI stud-ies are not sensitive to increased activation due to phase-resettingof ongoing EEG activity, some of the potential sources produc-ing the validity–invalidity effect would not be observed in fMRIstudies (Digiacomo et al., 2008). In particular, the dorsal AnteriorCingulated Cortex (dACC) has been shown to be activated using theLORETA and dipole localization algorithms during the processing ofinvalid trials (Gómez et al., 2008b). The P3a component is generatedas a brain response to stimuli that are surprising because of theirdifference with standard stimulus (Dien et al., 2003; Friedman etal., 2001; Escera et al., 1998). From a cognitive point of view, it couldbe argued that the presence of a P3a component and the underly-ing activation of the frontal cortex in I trials would be related to thedisconfirmation of the induced contingencies between the cue andthe target in the I trials (Gómez et al., 2008a). The I target would betreated as a deviant stimulus because the endogenous expectancy(subjective probability) of the position of the target, induced bythe central cue, is validated in V trials and invalidated in I trials. Inaddition to the novelty-like treatment of the targets associated toI trials, the obtained activation in the dACC suggests that the con-flict monitoring system is activated in this type of trials, possibly totrigger compensatory actions to overcome the simultaneous activa-tion of the prepared and the executed response and/or the inducedcognitive conflict (Gehring et al., 1993; Holroyd and Coles, 2002;Botvinick et al., 2004). However, given the very different situationsin which the error-related negativity and the P3a are generated, therelationship of the obtained activation in the dorsal ACC with theconflict monitoring system would need more confirmatory studies.

As already mentioned, the study of Vossel et al. (2006), usingfMRI, showed an increased activation in the parahippocampal gyrus

obtained by Gómez et al. (2008b) using LORETA and dipole localiza-tion algorithms for the P3b during Posner’s central cue paradigm. Inthis sense, it must be remarked that the medial temporal lobe hasbeen reported as one main contributor to P3 generation (reviewed

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n Yamazaki et al. (2000)). The medial temporal lobe, includinghe hippocampus and parahippocamppal gyrus, is a key struc-ure for memory processes in the brain. The relationship of P3ith memory has been recently highlighted by Polich (2007), indi-

ating that “stimulus encoding that promotes successful memorytorage to facilitate retrieval and recognition produces increased300-like amplitude”. In this sense, the P3b would promote mem-ry operations in temporal–parietal areas. When applied to thealidity–invalidity effect, the increase of the P3b component duringtrials with respect to V trials would reflect the change in the con-itional probability P(S2/S1) involving in this operation the medialemporal lobe (Vossel et al., 2006; Gómez et al., 2008a,b). There-ore, in addition to the already described novelty detection andeorienting of attention of invalidly cued targets and based on theeuroanatomical information of the differential effects of the anal-sis of I and V targets, it can be suggested that conflict monitoringctivation (Gehring et al., 1993; Holroyd and Coles, 2002; Botvinickt al., 2004) (dACC) and working memory update (Duncan-Johnsonnd Donchin, 1977) (parahippocampal gyrus) occur during the pro-essing of I targets.

In conclusion, taking into account all the previous analyses, wean conclude that cueing produces a bias in subjective expectan-ies for targets, as it has already been demonstrated by analyzinghe CNV (Brunia and Van Boxtel, 2001; Eimer, 1993; Gómez et al.,003, 2004, 2007; Flores et al., 2009). This subjective bias induces

nvalidly cued targets to be treated in a similar manner to low fre-uency targets in odd-ball paradigms, indicated by the presence ofn increased P3a and P3b in I trials. The increased P3a (Dien et al.,003; Friedman et al., 2001) would index the processing of the I tar-et as a novel and conflict stimulus, and then according to Donchinnd Coles (1988), the increased P3b in I trials would represent theontext updating of working memory, in this case the updatingf the S1–S2 contingencies, or in a more operational form, chang-ng the a priori conditional probabilities P(S2/S1) as a function ofhe trial outcome. In terms of predictive coding, the exuberant P3esponses during invalid trials may reflect an expression of predic-ion error about the context established by the cue. Note that thisrediction error will be necessary to drive changes in associativelasticity that may mediate trial-to-trial transfer effects.

. Transfer of information to next trial

An important issue which has been scarcely studied in Pos-er’s central cue paradigm is how correct or incorrect prediction

n a given trial can induce changes in the processing of the nextrial, i.e. sequential effects. A recent behavioral report on Posner’sentral cue paradigm addresses this point (Jongen and Smulders,007). These authors found an inter-trial validity–invalidity effect:he benefit in RTs when compared to neutral cues is higher if aalid trial is preceded by a valid trial than if it is preceded by annvalid one. On the other hand, the cost of an invalid trial is greaterf it is preceded by a valid trial than by an invalid one. To ournowledge, there have been only two ERP experiments (Gómezt al., 2009; Behavioral results in Fig. 3) analyzing the sequentialffects of inter-trial validity using event-related potentials (ERPs).RP studies could elucidate the timing and neurocognitive effectsf inter-trial validity/invalidity in cueing paradigms.

Therefore, analyzing the sequential effects of valid S1–S2 centralue trials, preceded by other S1–S2s (Fig. 2), it would be possible tovaluate how the outcome of a trial affects the behavior and ERPs of

he next one. Using such an approach, two different types of effectsn the processing of a target are expected: (i) effects due to themplicit meanings of spatial cues and to the global predictive val-es of cues during the experiment (the so-called validity/invalidityffect); and (ii) local effects due to the spatial validity or invalid-

ehavioral Reviews 35 (2011) 452–461 457

ity of the previous trial (inter-trial validity/invalidity effect). Theanalysis of late positive components would allow to analyze hownovel the stimuli are considered to be (via P3a) and how much theinternal model of the current predictive value associated with thecue presented (S1–S2 contingency value) needs to be revised (viaP3b).

These experiments (Gómez et al., 2009) showed behavioralresults similar to those of Jongen and Smulders (2007), whoobtained a RT pattern of VV < IV < II < VI (Fig. 3). From the ERP results,the invalidity/validity effect already described in the previous sec-tion (increased P3a and P3b in the invalid with respect to validtrials), would account for the global and implicit meaning of thecues. On the other hand, the comparisons between the ERPs ofthe IV vs. VV would make it possible to test the local sequentialeffects. P3a showed no statistically significant differences betweenthese two conditions. However, the comparison of P3b in IV and VVshowed statistically significant differences: it was larger to validtargets preceded by an invalid trial (IV trials) than to valid targetspreceded by a valid trial (VV trials) (Fig. 4, below). These behavioraland ERP results suggested that there is a transfer of information(learning of the credibility of the cue) from trial N to trial N + 1. IVtrials present higher P3b amplitude than VV trials, because the cueneeds to regain the credibility lost in the previous trial. Therefore,P(S2/S1) needs to be revised in IV sequences while this value canremain steady in VV trials.

‘Credibility’ here simply means the probability that a stimuluswill be encountered. There is an interesting distinction betweenthe predicted value or category of a stimulus and the precisionof that prediction. If we take credibility to be an attribute of theprior probability distribution on the causes of sensory input, thenwe can associate credibility with the tightness or precision of theprior expectation. Operationally, this involves boosting sensoryinformation (or more precisely prediction error) in sensory chan-nels where precision (credibility) is expected to be high. This fitscomfortably with the notion of attentional gain and its underlyingsynaptic mechanisms. It also speaks to the ideas in Yu and Dayan(2005) about balancing the relative influence of bottom-up sen-sory information and top-down prior expectations by weightingthem according to their relative precision (credibility). Indeed, ithas been proposed that attention can be understood purely in termsof optimising the precision or credibility of representations duringhierarchical inference in the brain (Friston, 2009).

Another possible explanation of the inter-trial validity effectsobserved in the behavior and the ERPs would be in terms ofincreased control in V trials after an I trial occurred, i.e. more cogni-tive control in IV trials than in VV trials (Botvinick et al., 2001, 2004).Since the CNV represents preparation for the incoming stimulus(Eimer, 1993; Gómez et al., 2003, 2004, 2007), and comparisons ofthe CNV after valid and invalid trials yielded inconsistent resultsbetween the two experiments which assessed the inter-trial valid-ity/invalidity effect (Gómez et al., 2009), the sequential effectsobtained are probably not due to increased cognitive control in thetrial following an invalid trial (Botvinick et al., 2001, 2004). More-over, intensity effects related to the orientation of the cue shouldpredominate in the early CNV, but the early CNV did not show con-sistent modulation depending on the nature (valid or invalid) ofthe previous trial. Therefore, it was not evident that greater cogni-tive control after invalid trials explained why the RTs were longerin IV than VV trials. It must be remarked that the experiments inwhich increased cognitive control has been proposed to explainlonger RTs after incongruent trials had shorter ISIs than the central

cue experiment of Posner, and also no cue was interposed betweentwo target stimuli (Gratton et al., 1992; Stürmer et al., 2002; Kernset al., 2004; Burle et al., 2005; Notebaert et al., 2006).

Therefore, a possible explanation for the longer RTs in the IV thanthe VV condition is continuous updating of the predictive value that

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ubjects assign to the spatial cue. Yu and Dayan (2005) proposedhat Posner’s central cue paradigm is a good example of how prob-bilistic Bayesian learning occurs. In trials in which expectationsre violated, the subjects would pay less attention to top–downignals (cues) and more attention to bottom–up processes (targettimuli). In other words, the cue’s predictive value would changen a trial-by-trial basis. This value would be lower in the IV thanhe VV condition, consequently producing longer RTs in the IV con-ition than the VV condition. It must be noted that a comparisonetween the VV and the IV conditions would reflect a local effect ofhe outcome of the previous trial, superimposed on the more robustost–benefit effect because of global contingencies on the task andhe implicit spatial value of the cues (Posner, 1980).

The increase in the P3b during the IV condition with respecto the VV condition would reflect the operation of changing the

priori conditional probabilities that the subjects assign to theues (P(S2/S1)). As far as we know, there are no fMRI studies ofhe sequential effects during Posner’s central cue paradigm. Suchxperiments seem perfectly feasible, although only small effectshould be expected as the behavioral (Jongen and Smulders, 2007)nd ERPs results suggest (Gómez et al., 2009).

. Developmental studies

One important issue related to the preparation–valuation–transfer to next cycle is how it develops from childreno adults. For the preparatory phase, the CNV continues to be thendex of the activation of the neural set related to the expectedask. Few studies have addressed the course of developmentf the CNV during Posner’s central cue paradigm. Perchet andarcía-Larrea (2000, 2005) assessed the orientation of attentionnd response selection in a spatially cued motor reaction taskn children and adults. Adults showed a slow negative potentialreceding the target under valid, invalid and no cue conditions,hereas in children, this potential did not appear under the valid

nd invalid conditions, only during ‘no cue’. These differencesere interpreted as a lack of maturation for executive processes in

hildren (Perchet and García-Larrea, 2005).However, these authors used an interval between cue and tar-

et (500 ms) that was very short for a full development of theNV. Other studies have provided information about brain activ-

ty in normal children during preparatory periods using the CNV.onkman et al. (2003) performed a go-nogo task and comparedhildren (9–10 years old) with adults (20 years old). In the earlyNV in centro-parietal locations, the CNV amplitude was smaller

n children than in adults. This difference was attributed to thenefficiency of the cue-orientation processes caused by incompleterontal lobe development. Segalowitz and Davies (2004) comparedhildren (7–17 years old) with adults (19–25 years old). Theseuthors, taking account of other ERPs such as the error-related neg-tivity and the P3a to novel stimuli, proposed that the frontal lobeontinues to develop and its generators to mature during adoles-ence, in parallel with the growing amplitude of the CNV with age,ssociated with the maturation of the frontal lobe generators.

In two recent reports (Flores et al., 2009, 2010) using Posner’sentral cue paradigm, the sequence of CNV and P3 component wasbtained in children, and compared with young adults, in order tosses the perceptual-evaluative phase of the cognitive cycle. Behav-orally the children presented the validity–invalidity effect withhorter RTs in valid with respect to invalid trials.

The preparatory activation of the specific neural resources,otor and sensory, needed to complete the task was clearly

ecorded in young adults as negative components over the con-ralateral motor and sensory cortex (Fig. 6, top) while only theensory anticipation component was recorded in children. In addi-

ehavioral Reviews 35 (2011) 452–461

tion, a parietal positivity was recorded in children, suggesting apossible differential cortical engagement of brain resources in chil-dren and adults for accomplishing the task.

In conclusion, no clear preparatory activity over motor areas wasobtained in children, but only preparatory sensory activation wasobserved. These results conform the results of Bender et al. (2005),using auditory cues and targets. They found a parietal negativityin children, which could represent pre-activation of the auditorysensory signal, but motor pre-activation was only present as anevent-related desynchronization of the sensorimotor rhythm, andthe motor preparation component of the CNV did not appear in chil-dren. The early maturation of the sensory CNV is consistent withthe observed delayed maturation of premotor, motor and supple-mentary motor areas, the peak cortical thickness of which occurs at9.5–10.5 years old, while visual posterior sensory areas reach peakthickness at 8–9 years old (Shaw et al., 2008). From the point of viewof this review it can be concluded that children between 7 and 12years old are able to compute the subjective conditional probability(P(S2/S1)) as indexed by the lateralized pattern of the posterior CNVduring Posner’s central cue paradigm. Therefore, a similar patternfor the P3 to that described in adults would be expected in children.

From the same experiment, the evaluative phase was also ana-lyzed in children and young adults, comparing the amplitude of theP3 component for valid and invalid trials. Therefore, the behavioralperformance and ERPs in children and young adults who evalu-ated target stimuli previously indicated by a spatial directional cuewere analyzed (Flores et al., 2010). As found in other studies acrosslifespan, the cue direction produced a cost–benefit pattern in RTs(Posner, 1980; Perchet and García-Larrea, 2000, 2005; Brodeur andBoden, 2000). RTs were shorter in the valid condition than theinvalid condition in both age groups, indicating that children at theage of 8–13 years old have the validity–invalidity effect. This resultreflects a behavioral cost associated with an invalid cue and/or abenefit with a valid cue, probably due to the sensory attentionalallocation previously described during the CNV period.

With respect to the ERP analysis, young adults showed greateractivation in the anterior (P3a) and posterior (P3b) areas in theinvalid condition than the valid condition (Fig. 6, below). How-ever, the children showed greater activation in posterior areas (P3b)in the invalid condition than the valid condition, but no clear for-mation of the anterior P3a in the invalid condition (Fig. 6, below).These results suggested that the late maturation of the frontal lobeinfluenced the development of the P3a in children (Flores et al.,2010). In experiments in which a novel distractor is intermingledwith standard stimuli, a P3a is obtained to the distractors. Chil-dren show a P3a component to distractors in the auditory modality(Gumenyuk et al., 2004; Wetzel et al., 2006). However, for visualmodality in children, there are few studies on the P3a to distractors.Courchesne (1978) found no P3a component in children, but Stigeet al. (2007) and Thomas and Nelson (1996) found such a compo-nent. More studies are needed to understand the conditions thatallow to induce a P3a in the visual modality in children. The exper-iments presented in this review are not typically used for obtaininga P3a, although adults showed a central positivity resembling theP3a to unexpected stimuli (Digiacomo et al., 2008). As a conclusion,the absence of a P3a-like component during Posner’s central cueparadigm in children reflects an immaturity in the developmentof the frontal cortex which does not affect the behavioral perfor-mance of the subjects, suggesting that the P3a-like componentswhich appear in adults during invalid targets are related to a purecognitive evaluation of the trial.

Children and young adults showed a posterior positivity that, inview of its latency and topography, could be considered a P3b com-ponent. In both groups, the targets in the invalid condition induceda higher voltage than validly cued targets. In other studies withadult subjects, a higher amplitude of the P3b component in the

C.M. Gómez, A. Flores / Neuroscience and Biobehavioral Reviews 35 (2011) 452–461 459

Fig. 6. Topography of the different components used to evaluate the cognitive cycle, comparing children and adults. Top: Posterior sensory CNV indicating the activationof the occipital cortex contralateral to the cue (extracted from Flores et al., 2009). Notice the similar behavior in children and adults. Below: Evaluation of the outcome of at nd rowH , whil

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rial by means of the P3 component. An invalid trial yields a P3a-like component (2owever, in the children group no P3a-like component is formed (1st row of maps)

nvalid condition than the valid condition has been observed, possi-ly because of incorrect preparation of the attentional set (Mangunnd Hillyard, 1991; Eimer, 1993; Gómez et al., 2008a; Digiacomot al., 2008). In children, a delayed P3 and a higher late positivelow wave in invalid than valid trials has been reported, but no dif-erence in P3 amplitude (Perchet and García-Larrea, 2000, 2005).he differences between our data and that of Perchet and García-arrea (2000, 2005) may lie in the different categorization of lateositive components, but might in fact represent a similar type ofhenomenon.

Vossel et al. (2006), using a similar experimental paradigm indults, and Gómez et al. (2008b), using LORETA with the samearadigm, have shown a greater activation in the invalid than thealid condition in posterior areas, such as the parahippocampalyrus and the vicinity of the superior temporal sulcus. The dorsalart of the cingulate gyrus was also activated. Activation of theseosterior areas would explain the appearance of an increased P3b

n children and young adults. The earlier maturation of these pos-

erior areas than the frontal areas would explain the similaritiesetween children and young adults in the late phases of the P3or the invalid condition (Giedd et al., 1999; Giedd, 2004; Shaw etl., 2008). These posterior areas would support the renew of the(S2/S1) in children and in adults.

of maps) and a P3b-like component (4th row of maps) in the young adults group.e the P3b component fully develops (3rd row of maps) (Flores et al., 2010).

With respect to the transfer of information across trials in chil-dren, the reanalysis of the behavioral and ERP data described inthe Flores et al. report (2010), using the sequential approach, haveyielded inconsistent results (unpublished data). The RT pattern ofVV < IV < II < VI was similar to that obtained in young adults (Fig. 3),but the differences between conditions were not statistically sig-nificant. Increasing the number of subjects would be desirable forincreasing the statistical power of these comparisons.

6. Conclusions

- When a cue indicates the probable position of a target, as in Pos-ner’s central cue paradigm, a CNV-like component is generated,which indicates task-specific activation of the sensory and motorcortex related to the processing of the expected S2, but also theactivation of the attentional fronto-parietal networks (Hopfingeret al., 2000; Gómez et al., 2004, 2007; Fan et al., 2007; Flores etal., 2009) (Fig. 4, top).

- The increased P3a and P3b during I trials with respect to V trialssuggest that targets during I trials produce a novelty-like effectand a change in the conditional probabilities that the subjects giveto the sequence of stimuli S1–S2 (Gómez et al., 2008a,b; Vosselet al., 2006) (Fig. 4, middle).

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The behavioral and ERP results of the inter-trial sequences sug-gest that there is a trial-by-trial evaluation of the outcome of eachtrial, inducing a change in the a priori validity that subjects assignto the next spatial cue, which can be observed as an increase inthe P3b of IV trials with respect to VV trials (Gómez et al., 2009)(Fig. 4, below).

The results summarised here conform the ideas proposed byriston (2009, 2010) of the brain as a Bayesian inferential machine,nd suggest that the CNV component would be a component index-ng the a priori conditional probabilities, the P3a component wouldrovide a method to estimate the surprise or difference betweenhe model and the empirical encounter, and finally the P3b can beonsidered as an index of the amount of review that the model isndergoing in a given trial.

cknowledgements

I thank Dr. Mikael Roll for his interesting comments andemarks. This work was supported by the Spanish Ministry of Sci-nce and Technology Grant no. SEJ2007/60974/pSIC and by theunta de Andalucia. We also want to acknowledge the contributionf the ICSE foundation.

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