Perspectives on Psychological Science http://pps.sagepub.com/

Brain Imaging, Cognitive Processes, and Brain Networks Brian D. Gonsalves and Neal J. Cohen Perspectives on Psychological Science 2010 5: 744 DOI: 10.1177/1745691610388776 The online version of this article can be found at: http://pps.sagepub.com/content/5/6/744

Published by: http://www.sagepublications.com

On behalf of:

Association For Psychological Science

Additional services and information for Perspectives on Psychological Science can be found at: Email Alerts: http://pps.sagepub.com/cgi/alerts Subscriptions: http://pps.sagepub.com/subscriptions Reprints: http://www.sagepub.com/journalsReprints.nav Permissions: http://www.sagepub.com/journalsPermissions.nav

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

Brain Imaging, Cognitive Processes, and Brain Networks

Perspectives on Psychological Science 5(6) 744–752 ª The Author(s) 2010 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/1745691610388776 http://pps.sagepub.com

Brian D. Gonsalves and Neal J. Cohen Department of Psychology and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign

Abstract The recent, rapid expansion of the application of neuroimaging techniques to a broad variety of questions about the structure and function of mind and brain has led to much necessary and often critical introspection about what these techniques can actually tell us about cognitive processes. In this article, we attempt to place neuroimaging within the broader context of the cognitive neuroscience approach, which emphasizes the benefits of converging methodologies for understanding cognition and how it is supported by the functioning of the brain. Our arguments for what neuroimaging has to offer are supported by two specific examples from research on memory that, we believe, show how neuroimaging data have provided unique insights not only into brain organization, but also into the organization of the mind. Keywords cognitive neuroscience, neuroimaging, memory, parietal cortex, prefrontal cortex

The field of cognitive neuroscience addresses the fundamental question of how the mechanisms of the functioning human brain give rise to cognitive processes, or, in other words, how to understand the linkage between brain and mind. This question has had a very long history, being the subject of enormous attention and debate both in philosophical inquiry and in various scientific disciplines. Over the years, the advent of each new scientific technique promising to offer new insight into brain–cognition relationships has elicited fresh debate not only about the merits of that particular technique but also about the wisdom of the enterprise as a whole. Perhaps never has this been more true than currently, with the recent explosion of research utilizing functional brain imaging, specifically functional magnetic resonance imaging (fMRI), and the tremendous growth of cognitive neuroscience as a discipline. With the rapidly burgeoning use of fMRI within cognitive neuroscience, the increasing infiltration of brain imaging methods and results into the domains of cognitive science, neuroscience, economics, etc., and the enormous success of this work in attracting attention in the popular press and funding from granting agencies, it is perhaps not surprising that some authors have generated challenges to what brain imaging has to offer and have raised concerns about its limitations. Critiques of brain imaging have ranged from pointed questions about the validity of specific kinds of statistical inferences

drawn from fMRI (e.g., Vul, Harris, Winkielman, & Pashler, 2009) to what amount to wholesale dismissals of the utility of fMRI for understanding anything whatsoever about cognition (Uttal, 2001). In this article, we do not attempt to offer a review of these critiques or a defense of fMRI against them, nor do we intend to explore in detail the deep debates about the enterprise of mapping brain to cognition more generally (but see Miller, 2010, this issue; Poldrack, 2010, this issue). Rather, our goal here is to place brain imaging in the larger context of cognitive neuroscience, both in principle and as used in practice, and to address the more specific question of what it can offer toward advancing understanding of cognitive processes on the way to understanding how cognitive processes may be implemented in the brain. Other authors have addressed the potential contributions of brain imaging to the study of cognition (Henson, 2005; Poldrack, 2006). In this article, we point to two current examples from cognitive neuroscience studies of memory in which we believe brain imaging has offered unique insights and has

Corresponding Author: Brian D. Gonsalves, 2055 Beckman Institute, 405 N. Mathews Avenue, Urbana, IL 61801 E-mail: [email protected]

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

Gonsalves and Cohen

745

raised important new research questions about the cognitive processes involved in memory.

Brain Imaging and Cognitive Neuroscience Brain imaging using fMRI has gained increasing prominence as the method of choice for many cognitive neuroscientists. But it is just one of many available techniques for gaining better understanding of the brain and its functions, and, indeed, it is most powerful when considered in the context of a converging-methods approach that takes full advantage of insights obtained from the long history of inquiry into brain– cognition relationships. Moreover, its success, like that of any other approach in cognitive neuroscience, or, for that matter, in any other field, depends critically on the quality of the theoretical or conceptual frameworks that guide construction of experiments and interpretation of results. More to the point, failures or shortcomings in the use of brain imaging research to address major questions in cognitive neuroscience may have less to say about the promise or problems of the technique itself than about the flaws of the conceptual frameworks used by some of its many practitioners and the outsized claims made by some of its proponents. One real challenge here is that any theory capable of successfully guiding the linkage of cognitive processes to brain mechanisms must also correctly capture both the functional architecture of the mind and the structural architecture of the brain—that is, it must identify the right kind or level of functional elements and structural elements for which linkages are being sought. So, how should brain imagers and other cognitive neuroscientists proceed? Do we need to wait for cognitive scientists to work out the critical issues about functional architecture or cognitive organization, and for neuroscientists to work out the details of brain architecture, before we can proceed with experiments that address the mapping between these levels? Or can we go ahead and jump in with full conviction that cognitive neuroscience findings can inform and have already contributed to all these various agendas? We take the latter view, arguing in the remainder of this article that brain imaging, conducted by well-informed cognitive neuroscientists, is making critical contributions to our understanding both of cognitive processes and of the brain networks that support them.

Brain Imaging and Cognitive Processes Perhaps more than other cognitive neuroscience methods, fMRI seems particularly suited to the mapping of cognitive functions to brain structures, and, judging from the wealth of data across brain imaging studies, to cataloging the functions of various brain areas. After all, the results of fMRI studies and meta-analyses of multiple studies are typically presented literally in the form of maps of the brain, revealing those brain areas that ‘‘light up’’ or are ‘‘activated’’ by a given task (actually, in the comparison between tasks or task conditions) and therefore associated with particular cognitive functions or processes. At

least some investigators who rely exclusively on fMRI methods are engaged in what is primarily a brain mapping enterprise as the goal of their research. This should be no surprise; the images showing one or another particular brain region associated with a specific contrast between conditions or showing a particular set (or network) of regions associated with one or another specific task, in experiment after experiment, are very seductive indeed for those interested in mapping function. But, for many investigators, the knowledge gained from fMRI, just as from other cognitive neuroscience methods, can be and often is applied to the analysis of cognitive processes and of the functional architecture of the mind, and not just to a brain mapping enterprise. We see two particularly powerful uses of brain imaging data in understanding cognition: One of these involves dissociation of cognitive processes, and the other involves brain localization data informing cognitive theory. To illustrate, let’s consider one example (of particular interest to the current authors), involving extensive fMRI evidence of robust activation of the hippocampus in task conditions emphasizing relational memory and activation of the medial temporal lobe (MTL) cortical regions (specifically, the perirhinal cortex) associated with item memory (Davachi, Mitchell, & Wagner, 2003; Ranganath et al., 2004). Such data are useful for the dissociation of cognitive processes, as they provide strong evidence that the brain honors the distinction between relational memory and item memory, a distinction proposed on the basis of other lines of evidence (Cohen & Eichenbaum, 1993; Eichenbaum & Cohen, 2001) prior to these fMRI studies. Note that support for the proposal that relational or item memory are the products of functionally distinct cognitive processes or functionally separable memory systems does not depend on the specific localization of activations to the hippocampus or perirhinal cortex. All that matters for the goal of dissociation-of-cognitive-processes is that the two conditions produce distinct functional localizations; any comparison between regions would do. However, the actual identity of the activated regions does matter from the brain localization data informing cognitive theory perspective. This is because we have a wealth of information about these particular regions of the brain, including their anatomical connections, the conditions influencing firing of individual neurons in these regions, conditions that give rise to activation of these regions in other studies, the effects of lesions to these regions, and various theoretical claims about the functional roles of these regions, all of which can be brought to bear and provide a richer context for interpreting the fMRI findings. In our current example, anatomical evidence that the hippocampus is the recipient of converging inputs from all higher order cortical processors (Suzuki & Amaral, 2004), electrophysiological findings that single neurons in hippocampus can code various conjunctions of stimuli, including spatial and contextual relations (Eichenbaum, 2004), and data showing that lesions of hippocampus produce profound deficits in all manner of relational memory tasks (Hannula, Ryan, Tranel,

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

746

Brain Imaging, Cognitive Processes, and Brain Networks

& Cohen, 2007; Hannula, Tranel, & Cohen, 2006; Konkel, Warren, Duff, Tranel, & Cohen, 2008; Ryan, Althoff, Whitlow, & Cohen, 2000) all converge with and support an interpretation of the fMRI evidence identifying hippocampal engagement with relational memory processing. Likewise, the anatomical connections of perirhinal cortex that place it in the (ventral) visual object recognition stream (Suzuki & Amaral, 1994), electrophysiological findings showing changes in the firing of single neurons for repeated visual objects (repetition suppression effects; Xiang & Brown, 1998), and findings that lesions in animals (Buffalo et al., 1999) or in a rare human case (Bowles et al., 2007) impair the processing of item familiarity all converge with and support an interpretation of the fMRI findings identifying perirhinal processing with memory for single items. Much of the early work using functional brain imaging was geared toward providing confirmatory evidence for claims derived from decades of research on brain-damaged individuals or from other cognitive neuroscience methods not unlike the example just considered. This use of imaging has been criticized in some quarters for following previous research rather than blazing new trails. However, even if used in this way, brain imaging is important as it provides a means for assessing cognitive and brain function in healthy individuals and avoids the concerns that some have about drawing broad inferences regarding principles of normal organization from study of limited numbers of brain-damaged individuals. More generally, part of the power of the converging methods approach in cognitive neuroscience comes from the fact that, although each method has certain assumptions that may give some people pause, the different methods have very different assumptions. When findings from these various methods with disparate assumptions all converge on a common conclusion, one can have much more confidence in that conclusion. But brain imaging is not used solely in this limited way. More and more often, it is being used to collect data not available through other means. The different cognitive neuroscience methods have different strengths. Whereas the great power of neuropsychological studies is the ability to identify brain regions critical for particular task performances and, hence, for some putative cognitive process, brain imaging studies can reveal what might turn out to be many areas that are involved in the processing under study. When imaging studies of one or another specific cognitive process reveal the participation of brain regions that were never even suspected based on prior neuropsychological or other methods, then imaging can be said to lead rather than follow in creating new knowledge. We will offer two extended examples of just such findings in the conclusion of this article. But, before turning to the specific examples, some comments are in order regarding a few outstanding issues. When imaging data reveal a set of brain regions linked to the cognitive processes under investigation, how does that go beyond being just another example of brain mapping to actually informing cognitive theory? What is the added value of brain localization data in informing cognitive theory? Information

about the larger set of brain regions (beyond those expected) activated by the psychological function or cognitive process under study raises important clues about what other cognitive processes (beyond those suspected) may be making important contributions. This use of reverse inference (Poldrack & Wagner, 2004) to generate new hypotheses about what cognitive processes may be involved can then be tested rigorously with a variety of cognitive and cognitive neuroscience techniques, whether they be neuroimaging, neuropsychological, behavioral, etc. But the use of reverse inference has also been criticized, on the grounds that it has been used too indiscriminately in drawing conclusions from patterns of brain activation (see Poldrack, 2006, 2008). Attempting to conclude definitively that certain cognitive processes must be engaged based solely on observing which brain areas are activated is not deductively valid, unless there is a selective or one-to-one mapping between the identified brain region and the cognitive process of interest. Such selective mappings are in short supply, as discussed elsewhere in this issue (Poldrack, 2010). Rather than despairing, however, we see the use of reverse inference as less the end point of theorizing and more the starting point; it should be less a mainstay of Discussion sections and more a critical component of Introduction sections.

Cognitive Processes and Brain Networks A different criticism of fMRI has focused on its heavy use for localization of function in the brain. This aspect of fMRI research has garnered enormous attention from the popular press, which often breathlessly recounts how amazing new mind-reading technologies have uncovered the source of greed or romantic love or political ideology in the brain. And it is this aspect of fMRI research that draws unwelcome parallels with the ill-fated discipline of phrenology, which, as is well known, attempted to localize complex psychological constructs to brain tissue underlying particular bumps on the skull. However, it is important to distinguish between the merits of the imaging research itself and the reaction it gets from the popular press, as the latter often will oversimplify or even misrepresent the significance of the former (see Beck, 2010, this issue). And, just as important, it would be unwise to allow the overreaching of some proponents of fMRI to serve as an indictment of the entire scientific endeavor. The use of fMRI as an exercise in localization seems seductively simple. An experimenter sets out to identify the neural correlates of X, where X is some psychological construct. Research participants are placed in the MRI scanner and are required to perform a task or set of tasks—these tasks contrast conditions thought to involve Process X with conditions thought not to involve X and the critical conditions are matched as closely as possible in their involvement of other processes of no interest. In the analysis of brain data, brain activation in the not-X condition(s) is subtracted from activation in the X condition(s), yielding a map of brain activity associated with X; in this way, the neural correlates of X have been identified. Stated this

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

Gonsalves and Cohen

747

way, there do not seem to be any constraints on which psychological constructs (i.e., which Xs) can be profitably examined. But, here, as in any other branch of science, success depends critically on the quality of the theoretical or conceptual frameworks that guide construction of experiments and interpretation of results. To use fMRI successfully, the experimenter must have a sufficiently explicit account of which particular task conditions do and do not involve the critical psychological function X, and, more to the point, which set of conditions differ exclusively with respect to X. Accounts of very complex psychological functions that are explicit enough to articulate the mappings of particular psychological processes or component subprocesses with specific task conditions are very rare indeed. Accordingly, attempts to localize complex constructs such as greed or criminality are likely to fail, no less with the modern technique of fMRI than with the discredited approach of phrenology. This is not because such psychological constructs do not arise from the functioning of the brain, and it does not mean that there is a fundamental problem either with the concept of localization of function or the use of fMRI to study it. Rather, the problem is the dearth of theories that decompose complex psychological constructs into well-defined information processing stages or components (i.e., a well developed cognitive ontology; Poldrack, 2010). There are surely so many subprocesses associated with high-level psychological constructs that the results of fMRI studies will involve activity in many, widely distributed brain regions. Interpretation of such a set of results risks becoming something of a projective test, in which the authors ascribe subprocesses to one or more subsets of the brain areas found to be activated. So, we should probably direct fMRI-based work to the narrower, more well-accepted cognitive constructs, such as language, attention, memory, etc. But can’t the same critique be leveled here too? Even with the progress in distinguishing between working memory and long-term memory (LTM) processes, between declarative and procedural memory or relational and item memory, between recollection-based and familiarity-based recognition processes or encoding and retrieval processes, and between pattern separation and pattern completion mechanisms, shouldn’t we worry that we do not yet have clear agreement on the cognitive ontology of memory? And, isn’t it a problem that so many different brain areas seem to be engaged in various aspects or kinds of memory? Here is where we part company with some of our less optimistic colleagues. Modern cognitive neuroscience has the clear understanding that fundamental cognitive constructs such as memory are composed of multiple interacting subsystems and component subprocesses on the cognitive end, while being supported by large-scale interacting brain networks on the brain end. Results from experiments using various cognitive neuroscience techniques, including brain imaging, have contributed to an appreciation that finer grained analysis of cognitive functions is necessary, along with greater understanding that cognitive functions arise from the activity of extended networks rather than individual circumscribed regions. Thus, although memory may not be localizable in the strict sense

(i.e., restricted to a specific population of neurons in a discrete brain region), more specific processes such as the binding of the various elements of an experience into a relational memory, the recollection of a specific previous episode, the sense of familiarity elicited by a previously seen object, and the holding on-line of a set of goals for performing some task each involves the interactions of different, specific brain circuits and reflects coordinated activity of structures in the medial temporal lobes, prefrontal cortex, and various cortical processing streams separately for the different aspects of memory listed above. The recent trend in cognitive neuroscience toward analysis of networks of brain regions is not, then, a move away from localization of function and toward Lashley’s ideas about mass action; it is a more modern view of localization, which better informs researchers about the right level of grain for mapping functional (cognitive) elements to structural (brain) elements. We turn now to two examples that illustrate current trends in how brain imaging is being used to extend current ideas about the processes involved in particular memory processes and the brain networks that are thought to support them.

Insights From Neuroimaging About Cognitive Processes Involved in Memory In this concluding section, we offer two examples from the cognitive neuroscience of memory that help to illustrate how neuroimaging data have led to novel hypotheses and new research directions regarding the cognitive processes engaged in various aspects of memory and the brain networks that support them. The memory literature has long been dominated by work on the hippocampus and, more recently, its interactions with surrounding MTL cortical structures, and an enormous body of convergent neuropsychological and neuroscientific findings identifies this region of the brain with declarative or relational memory (Cohen & Eichenbaum, 1993; Eichenbaum & Cohen, 2001). From the descriptions of patient H.M.’s profound amnesia following surgical resection of hippocampal and related MTL areas (Milner, Corkin, & Teuber, 1968; Scoville & Milner, 1957) to the discoveries of long-term potentiation (Bliss & Lømo, 1973), place cells and relational cells (Eichenbaum & Cohen, 1988; O’Keefe & Dostrovsky, 1971), multiple memory systems and declarative memory (Cohen & Squire, 1980), and hippocampal reactivation during sleep (Ji & Wilson, 2007), evidence from neuropsychological studies of patients and electrophysiological studies in animals has been unequivocal in pointing to the hippocampus and related MTL structures as critical to any account of memory. It is no surprise, then, that early brain imaging studies of memory focused on this region of the brain, typically borrowing paradigms from the amnesia literature. What was surprising was how ‘‘recalcitrant’’ the hippocampus proved to be across a range of studies in this early period (see Aguirre, Detre, Alsop, & D’Esposito, 1996; Cohen et al., 1999), leading various authors to worry about possible difficulties inherent in imaging the hippocampal region. A burgeoning number of successes in imaging the hippocampus and related MTL structures in more

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

748

Brain Imaging, Cognitive Processes, and Brain Networks

recent years have put any such concerns to rest, leading to tremendous increases in our understanding of the operation of this brain system. But even in the early period, with all its difficulties in imaging hippocampal function, this period was hardly without significant results. Whereas the hippocampus was largely absent in the findings from these early studies, two other brain regions proved to be surprisingly reliable players—study after study of memory revealed the engagement of regions within the prefrontal cortex (PFC) and posterior parietal cortex (PPC). As a result, rather than confirming the role of the hippocampus, the early brain imaging studies instead opened up new avenues of research directed at understanding the cognitive processes being signaled by the observed activities in the PFC and PPC.

Posterior Parietal Cortex (PPC) and Memory Retrieval Our first example of the success of neuroimaging data in generating new hypotheses about cognitive processes comes from research on memory retrieval. Over the years, imaging studies have unexpectedly but consistently shown that parts of the parietal lobe, in particular the medial and lateral portions of the PPC, were active during memory retrieval tasks (Buckner & Wheeler, 2001; Cabeza & Nyberg, 2000; Rugg, Otten, & Henson, 2002). Although unexpected, these findings seemed to converge with the observation of a specific pattern of electrophysiological activity, with a scalp distribution centered over the parietal lobes, associated with memory retrieval in ERP studies of memory (Rugg, 1995). However, these parietal activations represented a divergent set of results from those derived from neuropsychological studies of patients with PPC damage, in which findings have emphasized deficits in attention and motor planning rather than any deficits in memory. One possible interpretation of the unexpected neuroimaging findings emphasizes the correlational nature of this technique. Monitoring of brain activity during the performance of a cognitive task can shed light on what brain areas tend to be engaged during that particular sort of task; they cannot, however, establish the necessity of a brain region for a cognitive task. Given that parietal lobe damage seems not to produce any obvious memory deficits, it is possible that the parietal activations observed during memory retrieval are epiphenomenal. That is, the activation of the PPC in neurologically intact individuals may not play any causal role in memory retrieval; its activation may instead relate to some process that tends to be engaged with processes that are actually critical to memory retrieval (Haramati, Soroker, Dudai, & Levy, 2008). On the other hand, it may be that prior assessments of memory dysfunction in parietal lobe patients were insufficiently challenging to reveal a deficit, and the PPC may have a real role in memory retrieval after all. Many neuropsychological tests of LTM function employ relatively simple recognition tasks, as such tasks are more than adequate to reveal the profound memory impairments seen in amnesia. How is this confusing state of affairs—consistent and robust PPC activations in neuroimaging

studies, in the face of no obvious LTM deficits in patients with damage to the same regions—to be resolved? As presented thus far, this story may seem to be one that is about simply assigning the ‘‘right’’ functions to a specific brain region, that is, a story about cataloging structure-to-function mappings. However, in the process of getting to the bottom of this particular problem, researchers were led to develop a number of novel hypotheses about what cognitive processes are important for various aspects of memory retrieval, and, as a result, the story turns out to be about how brain localization data informs cognitive theory. The new neuroimaging studies of the PPC and memory retrieval have been directed at identifying the aspects of memory retrieval that relate to these parietal activations. Observations about the influence of factors such as retrieval success, the perception of ‘‘oldness,’’ the amount of information being retrieved, and retrieval based on recollection or familiarity on PPC activations were among the important findings in this area (Wagner, Shannon, Kahn, & Buckner, 2005). An important distinction arising from these findings is that the dorsal and ventral portions of the PPC seem to be differentially affected by some of the aforementioned variables, a finding that has led to greater anatomical specificity in subsequent functional hypotheses (Cabeza, Ciaramelli, Olson, & Moscovitch, 2008; Hutchinson, Uncapher, & Wagner, 2009; Naghavi & Nyberg, 2005; Olson & Berryhill, 2009; Vilberg & Rugg, 2008; Wagner, Shannon, Kahn, & Buckner, 2005; Wheeler & Buckner, 2004). As it turns out, this anatomical distinction provides a critical bridge for theorizing about cognitive processes. Rather than seeing the usual association of the PPC with attentional processes as a problem for understanding the PPC activity during memory retrieval tasks, some investigators have attempted to integrate the memory findings with the neuroimaging literature on attentional networks in the brain (Cabeza, 2008; Cabeza et al., 2008; Ciaramelli, Grady, & Moscovitch, 2008). These investigators focused on new ideas about the contributions of specific fronto-parietal brain networks to different aspects of attention, noting in particular claims of two distinct attention subsystems that subserve bottom–up or stimulus-driven attention and top–down or goal-directed attention (Corbetta, Patel, & Shulman, 2008; Corbetta & Shulman, 2002). Critically, these two subsystems map onto dorsal (for goal-directed attention) and ventral (for stimulus-driven attention) regions of the PPC, respectively. Taking seriously an attentional account of PPC contributions to memory, the dissociation between dorsal and ventral PPC attention subsystems can be mapped onto dorsal and ventral PPC activity during memory retrieval: Activity in the dorsal PPC is taken to reflect the engagement of goaldirected attentional processes during memory retrieval, whereas activity in the ventral PPC is taken to reflect reflexive orienting of attention toward the products of memory retrieval. In other words, the roles of the dorsal and ventral PPC in memory retrieval are a function of their roles in attention, a view that requires no additional hypotheses about a special role for the PPC that is specific to memory retrieval (Cabeza et al., 2008). One further interesting aspect of this account is that it

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

Gonsalves and Cohen

749

suggests that the traditional notion of stimulus-driven attention, which typically refers to external stimuli only, should now include the internally derived products of memory retrieval, which are not ‘‘stimuli’’ in the traditional sense. The above is just one thread from the neuroimaging literature on the PPC and memory retrieval; there are other findings and other conceptualizations about the PPC and memory being explored in the field (Hutchinson et al., 2009). But, even this one thread illustrates how brain imaging data can raise important questions and go on to inform cognitive theorizing about not just the linking of particular brain regions with cognitive processes (here, the PPC and memory retrieval), but also component cognitive processes (i.e., the role of different attention subsystems in different aspects of memory retrieval). These ideas have led to a great deal more theorizing about the interactions of memory and attention, tested not only with neuroimaging methods but in neuropsychological studies as well. New more strongly targeted investigations of potential memory deficits in patients with PPC damage have now been undertaken based on the ideas discussed above, and some studies have already revealed more subtle memory problems than previously appreciated (Berryhill, Phuong, Picasso, Cabeza, & Olson, 2007; Davidson et al., 2008; Haramati et al., 2008; Konkel et al., 2008; Simons, Peers, Mazuz, Berryhill, & Olson, 2010), providing tentative support for these new views about attention, memory retrieval, and the PPC.

Prefrontal Cortex (PFC) and Memory Encoding Our second example, concerning the PFC, has strong parallels with the story just discussed. From the very outset of brain imaging studies of memory, including the initial period when findings of hippocampal activation were very rare, researchers have consistently reported activation in the lateral regions of the PFC during the study or encoding phase of memory tasks (Buckner et al., 1995; Kelley et al., 1998; Wagner, Poldrack, et al., 1998). More powerful studies, permitting analysis of subsequent memory (or Dm) effects, demonstrated that not only were lateral PFC areas activated at the time of memory encoding, but the amount of encoding-time activity in the PFC was associated on a trial-by-trial basis with better performance in later memory tests, an effect as robust as that seen in the same studies in MTL areas more usually associated with memory (Brewer, Zhao, Desmond, Glover, & Gabrieli, 1998; Wagner, Schacter, et al., 1998). Thus, whatever processes were being signaled by the PFC activations at the time of encoding were related to how well the study materials would go on to be remembered. What are we to make of the reliable association of PFC activation with encoding of LTM? Do such findings mean that the processes signaled by PFC activity are directly or primarily engaged in LTM processing? Or might they reflect other, nonmnemonic, cognitive processes whose engagement during study might also contribute to memory performance? Consider the possible participation of language-related processes in the left PFC during the study of verbal materials or of materials

that could be given verbal labels in facilitating remembering. The story relies on neuroimaging studies examining regional specificity within the left PFC that show separate phonological (speech-sound-based) processing and semantic (meaningbased) processing activities in the left PFC. The finding of a region in the posterior portion of the left inferior prefrontal cortex (pLIPC)—or, in different terminology, of the ventrolateral prefrontal cortex (pVLPFC)—associated with phonological processes, and a more anterior region (aLIPC or aVLPFC) associated with semantic processes can be related to memory encoding by noting the fundamentally phonological nature of rote rehearsal strategies and the fundamentally semantic nature of elaborative rehearsal, respectively, during encoding (Davachi, Maril, & Wagner, 2001; Fiez, 1997; Poldrack et al., 1999; Wagner, Koutstaal, & Schacter, 1999; Wagner, Pare-Blagoev, Clark, & Poldrack, 2001). Thus, these PFC regions can be active at the time of stimulus processing and have consequences on subsequent memory performance without actually performing processes strictly related to memory encoding, but rather by maintaining their usual phonological or semantic processing roles. A nice piece of evidence for this comes from a study showing that temporary disruption of phonological processing via transcranial magnetic stimulation of the pVLPFC also causes deficient performance on a subsequent memory test (Kahn et al., 2005). Thus, it may be that just as no additional hypotheses about a special role for the PPC specific to memory retrieval are necessary to explain the observed PPC activations during the time of retrieval, so too are no additional hypotheses about a special role for the PFC specific to memory encoding necessarily required to explain the observed PFC activations at the time of encoding. Even as these developments were occurring, other advances in neuroimaging studies of the frontal lobes provide further evidence regarding the importance of brain localization data in contributing to cognitive theory. Discussions of the PFC and memory have long centered on working memory, or the ability to keep memory in an active state while working on it, rather than LTM, which is the ability to create new enduring memories. In contrast with patients like H.M., whose profound impairment of LTM following surgical resection of MTL structures is widely known, patients with PFC damage have much more modest LTM deficits, if any, that are limited largely to tasks involving memory for the temporal order or source of items (Janowsky, Shimamura, & Squire, 1989; Shimamura & Squire, 1987) or memory in high-interference conditions (Thompson-Schill et al., 2002). Multiple lines of evidence have documented a strong association of PFC with working memory, including findings of working memory deficits in monkeys following lesions or temporary inactivation of regions of the PFC (Funahashi, Bruce, & Goldman-Rakic, 1993), persistent activity exhibited by PFC neurons during the delay period of working memory tasks (Goldman-Rakic, 1995), and PFC activation in imaging studies of various working memory tasks in humans (D’Esposito, Postle, & Rympa, 2002; Jonides et al., 1993). The lack of convergence between findings from brain imaging that implicate PFC in LTM encoding and earlier results

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

750

Brain Imaging, Cognitive Processes, and Brain Networks

from other methods implicating PFC in working memory appears very striking. Perhaps working memory and LTM are more interdependent, and less obligatorily dissociated, than had been assumed by classical views. Some of the early imaging papers showing PFC activations during LTM encoding noted the overlap of these activated regions with those usually associated with working memory functioning and speculated that the encoding-time PFC activations reflected working memory processes that contribute to LTM performance tested subsequently (Wagner et al., 1999; Wagner, Schacter, et al., 1998). This idea has received support from several more recent reports showing the beneficial consequences on long-term retention of successful short-term (working memory) maintenance (Blumenfeld & Ranganath, 2006; Ranganath, Cohen, & Brozinsky, 2005). Further calling into question any classically held strict dissociation between an MTL-dependent LTM system and a PFC-dependent working memory system are results from two other lines of work: brain imaging findings of hippocampal activation during the delay period in working memory tasks (Ranganath & D’Esposito, 2001; Stern, Sherman, Kirchhoff, & Hasselmo, 2001) and neuropsychological findings of impairments in hippocampal amnesic patients at short lags and delays (i.e., on the time scale of working memory; Hannula et al., 2006; Olson, Page, Moore, Chatterjee, & Verfaellie, 2006). The new neuropsychological findings are of particular note, helping to bring the different lines of work into convergence by taking their lead from what had seemed to be discrepant neuroimaging findings. Finally, a particularly intriguing possibility raised by a recent neuroimaging finding is that the PFC and hippocampus can each participate in working memory maintenance, trading-off dynamically as a function of memory load, with the PFC interacting with the relevant cortical processors to support working memory for smaller loads and the hippocampus interacting with the same cortical processors to support working memory for larger loads (Rissman, Gazzaley, & D’Esposito, 2008).

Concluding Remarks: Neuroimaging and the Cognitive Processes and Brain Networks Involved in Memory There has been a great deal of interest in recent years in functional brain imaging and the insights it can offer about mind and brain. Along with this interest, there have been many criticisms of the (mis)use of neuroimaging, which tend to be exacerbated by the fact that studies that are perhaps less careful in the conclusions that they draw often get a disproportionate amount of attention from the popular press. However, as noted earlier, the merits of the research should not be confused with the reaction it gets from the popular press (see Beck, 2010). The crux of this issue for us is distinguishing between the kinds of conclusions that can and cannot be drawn from brain imaging data. On the one hand, attempting to definitively conclude that a cognitive process must be engaged in a certain task based on activation of a particular brain region is problematic. On the

other hand, such data can be extremely useful in generating new hypotheses about what cognitive processes may be involved, which can then be tested rigorously with a variety of techniques: neuroimaging, neuropsychological, behavioral, or others. The examples that we have given from the domain of memory research help to illustrate the promise of neuroimaging when used together with other cognitive neuroscience methods and with a commitment to advancing our knowledge about cognition and the brain. Recent developments show us that memory is an even richer construct than many thought, involving the recruitment of multiple cognitive processes implemented in a large network of brain structures. But rather than finding it to be a problem that so many different brain areas are shown in neuroimaging studies to be engaged in memory, those findings instead provide important data for expanding ideas about the set of cognitive processes that memory entails and how memory arises from the activity of brain networks rather than from one or a few circumscribed brain regions. Declaration of Conflicting Interests The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.

References Aguirre, G.K., Detre, J.A., Alsop, D.C., & D’Esposito, M. (1996). The parahippocampus subserves topographical learning in man. Cerebral Cortex, 6, 823–829. Beck, D.M. (2010). The appeal of the brain in the popular press. Perspectives on Psychological Science, 5, 762–766. Berryhill, M., Phuong, L., Picasso, L., Cabeza, R., & Olson, I. (2007). Parietal lobe and episodic memory: Bilateral damage causes impaired free recall of autobiographical memory. Journal of Neuroscience, 27, 14415–14423. Bliss, T. & Lømo, T. (1973). Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. Journal of Physiology, 232, 331–356. Blumenfeld, R.S., & Ranganath, C. (2006). Dorsolateral prefrontal cortex promotes long-term memory formation through its role in working memory organization. Journal of Neuroscience, 26, 916–925. Bowles, B., Crupi, C., Mirsattari, S.M., Pigott, S.E., Parrent, A.G., Pruessner, J.C., et al. (2007). Impaired familiarity with preserved recollection after anterior temporal-lobe resection that spares the hippocampus. Proceedings of the National Academy of Sciences, USA, 104, 16382–16387. Brewer, J.B., Zhao, Z., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (1998). Making memories: Brain activity that predicts how well visual experience will be remembered. Science, 281, 1185–1187. Buckner, R.L., Petersen, S.E., Ojemann, J.G., Miezin, F.M., Squire, L.R., & Raichle, M.E. (1995). Functional anatomical studies of explicit and implicit memory retrieval tasks. Journal of Neuroscience, 15, 12–29.

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

Gonsalves and Cohen

751

Buckner, R.L., & Wheeler, M.E. (2001). The cognitive neuroscience of remembering. Nature Reviews Neuroscience, 2, 624–634. Buffalo, E.A., Ramus, S.J., Clark, R.E., Teng, E., Squire, L.R., & Zola, S.M. (1999). Dissociation between the effects of damage to perirhinal cortex and area TE. Learning & Memory, 6, 572–599. Cabeza, R. (2008). Role of parietal regions in episodic memory retrieval: The dual attentional processes hypothesis. Neuropsychologia, 46, 1813–1827. Cabeza, R., Ciaramelli, E., Olson, I., & Moscovitch, M. (2008). The parietal cortex and episodic memory: an attentional account. Nature Reviews Neuroscience, 9, 613–625. Cabeza, R., & Nyberg, L. (2000). Neural bases of learning and memory: Functional neuroimaging evidence. Current Opinion in Neurology, 13, 415–421. Ciaramelli, E., Grady, C.L., & Moscovitch, M. (2008). Top-down and bottom-up attention to memory: A hypothesis (AtoM) on the role of the posterior parietal cortex in memory retrieval. Neuropsychologia, 46, 1828–1851. Cohen, N.J., & Eichenbaum, H. (1993). Memory, amnesia, and the hippocampal system. Cambridge, MA: MIT Press. Cohen, N.J., Ryan, J., Hunt, C., Romine, L., Wszalek, T., & Nash, C. (1999). Hippocampal system and declarative (relational) memory: Summarizing the data from functional neuroimaging studies. Hippocampus, 9, 83–98. Cohen, N.J., & Squire, L.R. (1980). Preserved learning and retention of pattern-analyzing skill in amnesia: Dissociation of knowing how and knowing that. Science, 210, 207–210. Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the human brain: From environment to theory of mind. Neuron, 58, 306–324. Corbetta, M., & Shulman, G.L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215. Davachi, L., Maril, A., & Wagner, A.D. (2001). When keeping in mind supports later bringing to mind: Neural markers of phonological rehearsal predict subsequent remembering. Journal of Cognitive Neuroscience, 13, 1059–1070. Davachi, L., Mitchell, J. P., & Wagner, A. D. (2003). Multiple routes to memory: Distinct medial temporal lobe processes build item and source memories. Proceedings of the National Academy of Sciences, USA, 100, 2157–2162. Davidson, P.S., Anaki, D., Ciaramelli, E., Cohn, M., Kim, A.S., Murphy, K.J., et al. (2008). Does lateral parietal cortex support episodic memory? Evidence from focal lesion patients. Neuropsychologia, 46, 1743–1755. D’Esposito, M., Postle, B.R., & Rypma, B. (2002). The role of lateral prefrontal cortex in working memory: Evidence from event-related fMRI studies. In K. Hirata, Y. Koga, K. Nagata, & K. Yamazaki (Eds.), Recent advances in human brain mapping (pp. 21–27). New York: Elsevier. Eichenbaum, H. (2004). Hippocampus: Cognitive processes and neural representations that underlie declarative memory. Neuron, 44, 109–120. Eichenbaum, H., & Cohen, N.J. (1988). Representation in the hippocampus: What do the neurons code? Trends in Neuroscience, 11, 244–248.

Eichenbaum, H., & Cohen, N.J. (2001). From conditioning to conscious recollection: Memory systems of the brain. New York: Oxford University Press. Fiez, J.A. (1997). Phonology, semantics, and the role of the left inferior prefrontal cortex. Human Brain Mapping, 5, 79–83. Funahashi, S., Bruce, C.J., & Goldman-Rakic, P.S. (1993). Dorsolateral prefrontal lesions and oculomotor delayed-response performance: Evidence for mnemonic ‘‘scotomas.’’ Journal of Neuroscience, 13, 1479–1497. Goldman-Rakic, P.S. (1995). Cellular basis of working memory. Neuron, 14, 477–485. Hannula, D.E., Ryan, J.D., Tranel, D., & Cohen, N.J. (2007). Rapid onset relational memory effects are evident in eye movement behavior, but not in hippocampal amnesia. Journal of Cognitive Neuroscience, 19, 1690–1705. Hannula, D.E., Tranel, D., & Cohen, N.J. (2006). The long and short of it: Relational memory impairments in amnesia even at short lags. Journal of Neuroscience, 26, 8352–8359. Haramati, S., Soroker, N., Dudai, Y., & Levy, D.A. (2008). The posterior parietal cortex in recognition memory: A neuropsychological study. Neuropsychologia, 46, 1756–1766. Henson, R. (2005). What can functional neuroimaging tell the experimental psychologist? Quarterly Journal of Experimental Psychology: A. Human Experimental Psychology, 58, 193–233. Hutchinson, J.B., Uncapher, M.R., & Wagner, A.D. (2009). Posterior parietal cortex and episodic retrieval: convergent and divergent effects of attention and memory. Learning & Memory, 16, 343–356. Janowsky, J.S., Shimamura, A.P., & Squire, L.R. (1989). Source memory impairment in patients with frontal lobe lesions. Neuropsychologia, 27, 1043–1056. Ji, D., & Wilson, M.A. (2007). Coordinated memory replay in the visual cortex and hippocampus during sleep. Nature Neuroscience, 10, 100–107. Jonides, J., Smith, E.E., Koeppe, R.A., Awh, E., Minoshima, S., & Mintun, M.A. (1993). Spatial working memory in humans as revealed by PET. Nature, 363, 623–625. Kahn, I., Pascual-Leone, A., Theoret, H., Fregni, F., Clark, D., & Wagner, A.D. (2005). Transient disruption of ventrolateral prefrontal cortex during verbal encoding affects subsequent memory performance. Journal of Neurophysiology, 94, 688–698. Kelley, W.M., Miezin, F.M., McDermott, K.B., Buckner, R.L., Raichle, M.E., Cohen, N.J., et al. (1998). Hemispheric specialization in human dorsal frontal cortex and medial temporal lobe for verbal and nonverbal memory encoding. Neuron, 20, 927–936. Konkel, A., Warren, D.E., Duff, M.C., Tranel, D., & Cohen, N.J. (2008). Hippocampal amnesia impairs all manner of relational memory. Frontiers in Human Neuroscience, 2, 1–15. Miller, G.A. (2010). Mistreating psychology in the Decades of the Brain. Perspectives on Psychological Science, 5, 716–743. Milner, B., Corkin, S., & Teuber, H. (1968). Further analysis of the hippocampal amnesic syndrome: 14-year follow-up study of H.M. Neuropsychologia, 6, 215–234. Naghavi, H.R., & Nyberg, L. (2005). Common fronto-parietal activity in attention, memory, and consciousness: shared demands on integration? Consciousness and Cognition, 14, 390–425.

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014

752

Brain Imaging, Cognitive Processes, and Brain Networks

O’Keefe, J., & Dostrovsky, J. (1971). The hippocampus as a spatial map. Preliminary evidence from unit activity in the freelymoving rat. Brain Research, 34, 171–175. Olson, I.R., & Berryhill, M. (2009). Some surprising findings on the involvement of the parietal lobe in human memory. Neurobiology of Learning and Memory, 91, 155–165. Olson, I.R., Page, K., Moore, K.S., Chatterjee, A., & Verfaellie, M. (2006). Working memory for conjunctions relies on the medial temporal lobe. Journal of Neuroscience, 26, 4596–4601. Poldrack, R.A. (2006). Can cognitive processes be inferred from neuroimaging data? Trends in cognitive sciences, 10, 59–63. Poldrack, R.A. (2008). The role of fMRI in cognitive neuroscience: Where do we stand? Current Opinion in Neurobiology, 18, 223–227. Poldrack, R.A. (2010). Mapping mental function to brain structure: How can cognitive neuroimaging succeed? Perspectives on Psychological Science, 5, 753–761. Poldrack, R.A., Wagner, A.D., Prull, M.W., Desmond, J.E., Glover, G.H., & Gabrieli, J.D. (1999). Functional specialization for semantic and phonological processing in the left inferior prefrontal cortex. NeuroImage, 10, 15–35. Ranganath, C., Cohen, M.X., & Brozinsky, C.J. (2005). Working memory maintenance contributes to long-term memory formation: Neural and behavioral evidence. Journal of Cognitive Neuroscience, 17, 994–1010. Ranganath, C., & D’Esposito, M. (2001). Medial temporal lobe activity associated with active maintenance of novel information. Neuron, 31, 865–873. Ranganath, C., Yonelinas, A.P., Cohen, M.X., Dy, C.J., Tom, S.M., & D’Esposito, M. (2004). Dissociable correlates of recollection and familiarity within the medial temporal lobes. Neuropsychologia, 42, 2–13. Rissman, J., Gazzaley, A., & D’Esposito, M. (2008). Dynamic adjustments in prefrontal, hippocampal, and inferior temporal interactions with increasing visual working memory load. Cerebral Cortex, 18(7):1618–1629. Rugg, M.D. (1995). Memory and consciousness: A selective review of issues and data. Neuropsychologia, 33(9):1131–1141. Rugg, M.D., Otten, L.J., & Henson, R.N. (2002). The neural basis of episodic memory: evidence from functional neuroimaging. Philosophical Transactions of the Royal Society of London: Series B. Biological Sciences, 357, 1097–1110. Ryan, J.D., Althoff, R.R., & Whitlow, S. & Cohen, N.J. (2000). Amnesia is a deficit in relational memory. Psychological Science, 11, 454–461. Scoville, W.B., & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. Journal of Neurology, Neurosurgery, and Psychiatry, 20, 11–21.

Shimamura, A.P., & Squire, L.R. (1987). A neuropsychological study of fact memory and source amnesia. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 464–473. Simons, J.S., Peers, P.V., Mazuz, Y.S., Berryhill, M.E., & Olson, I.R. (2010). Dissociation between memory accuracy and memory confidence Following bilateral parietal lesions. Cerebral Cortex, 20, 479–485. Stern, C.E., Sherman, S.J., Kirchhoff, B.A., & Hasselmo, M.E. (2001). Medial temporal and prefrontal contributions to working memory tasks with novel and familiar stimuli. Hippocampus, 11, 337–346. Suzuki, W.A., & Amaral, D.G. (1994). Perirhinal and parahippocampal cortices of the macaque monkey: cortical afferents. Journal of Comparative Neurology, 350, 497–533. Thompson-Schill, S.L., Jonides, J., Marshuetz, C., Smith, E.E., D’Esposito, M., Kan, I.P., et al. (2002). Effects of frontal lobe damage on interference effects in working memory. Cognitive, Affective, & Behavioral Neuroscience, 2, 109–120. Uttal, W. R. (2001). The new phrenology: The limits of localizing cognitive processes in the brain. Cambridge, MA: MIT Press. Vilberg, K.L., & Rugg, M.D. (2008). Memory retrieval and the parietal cortex: a review of evidence from a dual-process perspective. Neuropsychologia, 46, 1787–1799. Vul, E., Harris, C., Winkielman, P., & Pashler, H. (2009). Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspectives on Psychological Science, 4, 274–290. Wagner, A.D., Koutstaal, W., & Schacter, D.L. (1999). When encoding yields remembering: insights from event-related neuroimaging. Philosophical Transactions of the Royal Society of London: Series B. Biological Sciences, 354, 1307–1324. Wagner, A.D., Pare-Blagoev, E.J., Clark, J., & Poldrack, R.A. (2001). Recovering meaning: Left prefrontal cortex guides controlled semantic retrieval. Neuron, 31, 329–338. Wagner, A.D., Poldrack, R.A., Eldridge, L.L., Desmond, J.E., Glover, G.H., & Gabrieli, J.D. (1998). Material-specific lateralization of prefrontal activation during episodic encoding and retrieval. NeuroReport, 9, 3711–3717. Wagner, A.D., Schacter, D.L., Rotte, M., Koutstaal, W., Maril, A., Dale, A.M., et al. (1998). Building memories: Remembering and forgetting of verbal experiences as predicted by brain activity. Science, 281, 1188–1191. Wagner, A.D., Shannon, B.J., Kahn, I., & Buckner, R.L. (2005). Parietal lobe contributions to episodic memory retrieval. Trends in Cognitive Science, 9, 445–453. Wheeler, M.E., & Buckner, R.L. (2004). Functional-anatomic correlates of remembering and knowing. NeuroImage, 21, 1337–1349. Xiang, J.Z., & Brown, M.W. (1998). Differential neuronal encoding of novelty, familiarity and recency in regions of the anterior temporal lobe. Neuropharmacology, 37, 657–676.

Downloaded from pps.sagepub.com at TEXAS SOUTHERN UNIVERSITY on November 28, 2014