.Neuroscience of Rule-Guided Behavior Phần 9 ppt

a particular tempo ral context, thereby increasing selection demands and so requiring greater activation in left mid-VLPFC (Badre a nd Wagner, 2005). More specifically, we reasoned that the presentation of a probe, eve n in a short-term item memory test, requires assignment of the probe to a particular temporal context, such as the current trial, as opposed to the previous, trial. When encountering a probe that appeared in the previous trial, the participant retrieves irrelevant contextual information associated with that probe in the previous trial. To correctly assign the probe to the appropriate temporal con- text, the participant must select against this information, and so this selection demand elicits greater activation in left VLPFC. One distinguishing implication of this hypothesis is the prediction that it makes for positive recent trials. Positive trials, although present in the cur- Figure 16–3 A. Task schematic diagram of conditions in the short-term item rec- ognition experiment. Proactive interference is elicited by arranging an overlap of a target in trial N with a member of the memory set in trial N – 1. B. Overlap map of negative recent > negative nonrecent contrast and episodic context selection (Dobbins and Wagner, 2005). Arrows indicate the point of overlap in mid-ventrolateral prefrontal cortex (mid-VLPFC). C. Greater mid-VLPFC activation was evident for negative and positive recent trials relative to nonrecent trials. (Adapted from Badre and Wagner, Cerebral Cortex, 15, 2003–2012. Copyright Oxford University Press, 2005.) 376 Building Blocks of Rule Representation rent trial’s memory set, may also overlap with the previous trial’s memory set. Whereas this arrangement ensures that familiarity with the probe is conver- gent with the correct response, any associations with the previous trial are still irrelevant and so should increase selection demands. Such an effect would pro- duce increased activation in left VLPFC to positive recent trials. To test our hypothesis, we designed a variant of the standard short-term item memory test and tested the effects of probe recency during positive as well as negative trials. As depicted in Figure 16–3C, both negative and positive recent trials resulted in increases in left mid-VLPFC activation. Importantly, this was not simply an effect of familiarity generally, because all positive trials are familiar, having been in the current set, and there was no difference bet- ween positive and negative low-overlap trials. Following from the logic outlined earlier, one might further anticipate some convergence of mid-VLPFC and other regions observed in this task with those observed in tasks from other domai ns that require selection of details from memory to assign a probe to a given temporal context. In particular, ep- isodic memory tasks often demand precisely this type of selection. Bearing in mind the limitations inherent in such analyses, there was, indeed, a high degree of convergen ce between mid-VLPFC activation in this task and an indepen- dent episodic memory task that directly manipulated the domain-general se- lection of contextual details (Figure 16–3B) (Dobbins and Wagner, 2005). Hence, PI in this task may arise from the simultaneous activation of mul- tiple contextually relevant details and may be overcome by a selection process in which relevant contextual representations are biased over irrelevant repre- sentations. Recently, Jonides and Nee (2006) have proposed a highly similar selection mechanism for left VLPFC function in this task, also conceptualizing it in terms of a biased competition framework, although in this case, empha- sizing the selection of relevant attentional attributes, such as familiarity, rather than episodic details meant to assign a probe to a temporal context. In general, however, left mid-VLPFC appears critical for the selection of relevant from irrelevant retrieved information. Moreover, the specific focus of activation in mid-VLPFC is highly convergent with that associated with the ‘‘selection component’’ from the study of semantic judgments (see Fig. 16–5C and D). To the extent that retrieval of knowledge-for-action depends on the same system that supports the storage and retrieval of declarative memories more generally, it follows that processes, such as selection, are also required to focus processing on relevant knowledge-for-action. In the next section, I will discuss how PI effects analogous to those investigated here can arise during task-switching, and how a selection process, supported by mid-VLPFC, may be critical in resolving this interference to select the relevant knowledge-for-action. DECLARATIVE KNOWLEDGE AND CONTROL OF TASK SETS As I have argued so far, the ability to strategically guide memory search and to select relevant retrieved representations for further processing are VLPFC and Controlling Memory to Inform Action 377 general-purpose mnemonic control pro cesses that should also play an im- portant role in the retrieval and selection of knowledge-for-action. Our mod- ern world of wireless Internet, cell phones, PDAs, and instant messaging can interrupt whatever task we were trying to complete (e.g., writing a book chap- ter) and force us to retrieve a whole new set of information, both episodic and semantic, about a more immediately pressing task. Hence, calls to memory are a fundamental part of shifting task sets, or task-switching, and so should be informed by research, such as that summarized earlier, on the controlled search, retrieval, and selection of task-relevant knowledge. Our capacity to shift among different tasks may be studied in the laboratory by comparing trials during w hich a simple task is repeated with trials that entail a switch in task. Relative to repeat trials, switch trials are associated with an increase in RT and errors, known as the ‘‘behavioral switch cost’’ (Jersild, 1927; Allport et al., 1994; Rogers and Monsell, 1995; Logan and Bundesen, 2003; Monsell, 2003). Furthermore, preparation in advance of a switch can reduce, although not eliminate, the switch cost (Rogers and Monsell, 1995; Meiran et al., 2000). The difficulty that we experience in switching tasks may be partially at- tributable to the demand to activate a new set of task-relevant representations from memory each time we engage in a new task. For this reason, some form of memory retrieval, or activation of a task set, is at the heart of most models of task-switching (Rogers and Monsell, 1995; Allport and Wylie, 2000; Mayr and Kliegl, 2000; Rubinstein et al., 2001), whether this retrieval is viewed as intentional and controlled or relatively automatic. Interestingly, a number of theorists have increasingly emphasized the resolution of interference from memory during task-switching paradigms as being a prime source of task switch costs (Allport et al., 1994; Allport and Wylie, 2000; Wylie and Allport, 2000; Dreher and Berman, 2002; Mayr, 2002). One such interference theory, termed ‘‘task set priming,’’ proposes that the automatic retrieval of irrelevant, competitive information may produce inter- ference during a task switch (Allport and Wylie, 2000; Wylie and Allport, 2000; Waszak et al., 2003). From this perspective, task performance results in prim- ing of the associations between available cues and any representations that enter processing. An additional encounter with these cues in the context of the same task will result in facilitated access to this information, an effect analogous to repetition priming. However, during a task switch, these primed associations result in facilitated retrieval of irrelevant information (e.g., Waszak et al., 2003), analogous to the instance of short-term PI described earlier. The activation of representations from the previous task competes with performance of the new task. Hence, as with the experiments focusing on short-term item recognition, one might anticipate involvement of mid-VLPFC to resolve this interference. Consistent with this hypothesis, left VLPFC activation has been a common finding across studies of task-switching (Meyer et al., 1997, 1998; Dove et al., 2000; DiGirolamo et al., 2001; Brass and von Cramon, 2002, 2004a, b; Dreher 378 Building Blocks of Rule Representation and Berman, 2002; Konishi et al., 2002; Luks et al., 2002; Shulman et al., 2002; Dreher and Grafman, 2003; Reynolds et al., 2004; Ruge et al., 2005). More- over, patients with lesions broadly located in left lateral PFC show deficits in task-switching (Rogers et al., 1998; Mecklinger et al., 1999; Aron et al., 2003). Recently, Anthony Wagner and I conducted a functional magnetic resonance imaging (fMRI) study meant to draw a direct connection between mid-VLPFC activity during task-switching and the resolution of interference evoked from associative memory during a task switch (Badre and Wagner, 2006). To study task-switching, we employed a standard explicit cueing variant (Meiran et al., 2000), in which participants were instructed as to which task (vowel-consonant letter or odd-even number decision) they would be required to perform before the presentation of an upcoming target (number-letter pair, such as ‘‘a1’’). Categorizations were reported using a manual button press, and category-to-response mappings overlapped between tasks. For example, a left button press might mean ‘‘vowel’’ for the letter task and ‘‘odd’’ for the number task. Hence, this design allows us to manipulate task-switching (going from the letter to the number task, or vice versa), as well as the amount of prepa- ration time (cue-to-stimulus interval). To be theoretically explicit about our conception of memory-induced in- terference during task-switching and our predictions for the associated re- sponse in regions sensitive to interference, such as mid-VLPFC, we developed a simple computational model in which task switch costs arose from proactive interference among competing activated representations (Fig. 16–4A; see color insert). In our model, termed the ‘‘control of associative memory during task-switching,’’ three layers represented the responses (left or right button press), semantic concepts (‘‘odd,’’ ‘‘even,’’ ‘‘vowel,’’ and ‘‘consonant’’), and task goals (letter or number decision) in the explicit cueing task. Units within layers were mutually competitive, such that their simultaneous activation would re- sult in greater conflict. Reciprocal connections between the layers meant that activation of a unit in the task layer (i.e., ‘‘letter task’’) would feed forward to activate relevant units in the concept layer (i.e., ‘‘vowel’’ and ‘‘consonant’’), but also that activation of subordinate representations (e.g., left response) would feed back to activate associated superordinate representations (e.g ., ‘‘vowel’’ and ‘‘odd’’ in the concept layer). Hence, these feedback connections ensured that there would be coactivation at multiple layers and so conflict during every trial, including repeat trials. Greater conflict during switch trials occurred because of associative learn- ing. Specifically, at each response, connections between coactive units were made stronger. During a task switch, then, connections between units of the previously relevant—but now irrelevant—task would be stronger and so would elicit stronger activation of these irrelevant units. The result is greater com- petition and interference in switch trials, and therefore a switch cost. Control in the model took the form of a bias competition mechanism similar to that employed by others (Cohen et al., 1990; Botvinick et al., 2001). VLPFC and Controlling Memory to Inform Action 379 An increase in the top-down bias of the task layer on the conceptual layer was applied during the preparation interval of each trial. At longer intervals of preparation, this increased top-down control permitted relevant representa- tions to come to increasingly dominate the conceptual layer. The model pro- duced switch costs and preparation curves consistent with behavioral data (Fig. 16–4B). To provide quantitative hypotheses about proactive interference among active representations across conditions of the task-switching fMRI experi- ment, we computed an index of conflict from different layers of the model using the Hopfield energy computation (Hopfield, 1982; Botvinick et al., 2001). Conflict in the conceptual layer was found to decrease with more preparation (Fig. 16–4C). By contrast, conflict in the response layer tended to increase with more preparation (Fig. 16–4C). These model indices of conflict fit the fMRI response during task-swi tching. Consistent w ith past reports, the switch versus repeat comparison produced Figure 16–4 A. The model contains three reciprocally connected layers of units re- presenting the task, conceptual, and response components of the explicit cueing task. B. Simulated switch costs and preparation costs track empirically derived behavioral responses very well. However, when control during the preparation period was turned off, there was no decline in switch costs with increased preparation. C. The switch versus repeat contrast revealed activation in left ventrolateral prefrontal cortex (VLPFC) [opercularis and triangularis], supplementary motor area (SMA), and parietal cortex. Responses across preparation intervals in mid-VLPFC matched the model’s predicted conceptual conflict signal. This mid-VLPFC responses dissociated from the response in parietal cortex that appeared to match the predicted response conflict signal from the model. CSI, cue-to-stimulus interval; iPSC, integrated percent signal change. (Adapted from Badre and Wagner, Proceedings of the National Academy of Sciences, 103, 7186– 7191. Copyright PNAS, 2006.) 380 Building Blocks of Rule Representation activation in mid-VLPFC. Cri tically, the model index of conflict from retrieved conceptual representations was characteristic of the decline in switching effects in left mid-VLPFC with increased preparation (Fig. 16–4C). This pattern of data disso ciated this region from inferior parietal cortex, which appeared to track the ramping pattern of conflict from the response layer of the model. A transfer of processing from the conceptual to the response level may be con- sistent with event-related potential data, showing separable temporal compo- nents between early frontal and later parieta l potentials (Lorist et al., 2000; Rushworth et al., 2002; Brass et al., 2005) and similar conflict-based dissoci- ations during task-switching obtained with neuroimaging (Liston et al., 2006). The mid-VLPFC focus identi fied in this experiment is highly convergent with that discussed in previous studies of semantic conflict and proactive interference resolution (Fig. 16–5C through E; see color insert). Hence, in addition to providing important support for interference theories of task- switching, these data also underscore the broader role for mid-VLPFC selec- tion processes in the control of action. CONCLUSIONS The focus of this chapter has been on the relationship between declarative memory and action, and the contribution of left VLPFC in bringing declar- ative knowledge to bear on action. Rules, even when distinguished from non- declarative productions as explicit constructs, are not the only type of declar- ative knowledge relevant to action. Mechanisms for retrieving rules may be the same as those required to retrieve task-relevant declarative knowledge more generally. Hence, understanding the general mechanisms by which PFC con- trols retrieval is fundamental to an understanding of rule-guided behavior, and indeed, more broadly, knowledge-guided behavior. I have distinguished knowledge-for-action as the general case of retrieving declarative knowledge to constrain or guide action, and have summarized a line of research that specifies the mnemonic control processing in left VLPFC that is fundamental to this function. More specifically, left anterior VLPFC appears critical for the biased or controlled retrieval of long-term memory representations maintained in posterior neocortex, such as posterior midd le temporal cortex (Fig. 16–5A and B). By contrast, left mid-VLPFC appears critical for resolving interference among retrieved representations (Fig. 16–5A, C, and D). To the extent that one’s knowledge of people, places, things, or the past is relevant to a task at hand, a call to memory is necessary. Hence, any such in- stance of action will be subject to the same obstacles as any act of mem- ory retrieval. As with any act of retrieval, control will be important in guiding search and overcoming interference to focus processing on the most relevant information in memory. This was illustrated in the study on task-switching. Interference among automatically activated memory representations during VLPFC and Controlling Memory to Inform Action 381 a task switch was argued to be an important contributor to the switch cost. A left mid-VLPFC mechanism, in common with that required to select relevant retrieved representations, may thus be required to overcome this interference (Fig. 16–5C through E). Left VLPFC control processes appear central to knowledge-guided action because they permit the retrieval and selection of task-relevant rules and gen- eral action-relevant knowledge. The characterization of these control pro- cesses is ongoing and controversial, and the progress of this research will likely Figure 16–5 A. Overlap of judgment specificity (red) and associative strength (blue) manipulations on inflated canonical surface. Overlap in mid-ventrolateral prefron- tal cortex (mid-VLPFC) to posterior VLPFC (purple). B. Contrast of weak–associative strength, two-target trials with strong–associative strength, four-target trials reveals activation in anterior VLPFC (Wagner et al., 2001; Badre et al., 2005). C–E. Inflated surface renderings demonstrate the high convergence in mid-VLPFC in response to selection demands across independent data sets, including ‘‘selection component’’ ac- tivation (Badre et al., 2005) [C], negative recent > negative nonrecent contrast (Badre and Wagner, 2005) [D], and switch minus repeat at the shortest cue-to-stimulus in- terval of 250 ms (Badre and Wagner, 2006) [E]. Note that the reference arrow is in the same position in each map. 382 Building Blocks of Rule Representation yield important insights into the manner by which knowledge is retrieved to inform action. Ultimately, however, the discussion of rule-guided behavior must lead to important and difficult questions about the interface between some of the systems mentioned in this chapter. How do retrieved declarative representations feed forward to influence the motor system? What is the re- lationship between the declarative and nondeclarative systems in influencing action? Are there important differences in action or rule representations be- tween a human participant who is explicitly told the stimulus-response con- tingencies in a task a few minutes before beginning the task and a nonhuman primate that acquires the appropriate response contingencies over a long pe- riod of training? Future efforts may begin to address these fundamental ques- tions about the relationship between memory and action. acknowledgments Supported by NIH (F32 NS053337–03). I would like to acknowl- edge A. D. Wagner, my principal collaborator on the empirical work in this chapter. Thanks are also due to B. Buchsbaum and J. Rissman for their insightful comments on early drafts. REFERENCES Allport A, Styles EA, Hsieh S (1994) Shifting intentional set: exploring the dynamic control of tasks. 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