Remembering to attend: The anterior cingulate cortex and remote memory

Behavioural Brain Research 245 (2013) 63–75

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Behavioural Brain Research journal homepage: www.elsevier.com/locate/bbr

Review

Remembering to attend: The anterior cingulate cortex and remote memory Aldis P. Weible ∗ Institute of Neuroscience, 212 Lewis Integrative Science Building, University of Oregon, Eugene 97405, OR, United States

h i g h l i g h t s  The rodent anterior cingulate cortex is involved in remote memory recall.  How the anterior cingulate cortex facilitates remote recall is unknown.  Studies suggest a role for cingulate attention and motor processes in remote recall.

a r t i c l e

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Article history: Received 25 September 2012 Received in revised form 8 February 2013 Accepted 10 February 2013 Available online 20 February 2013 Keywords: Long-term memory Mnemonic Anterior cingulate cortex

a b s t r a c t Damage to the hippocampus, as first demonstrated with patient HM, results in a profound anterograde and temporally-graded retrograde amnesia. The observation that older memories could still be consciously recollected led to the proposal that, over time, information initially processed in the hippocampus is stored in a distributed cortical network. The anterior cingulate cortex (ACC) has recently been implicated in this process. Studies in rodents have demonstrated that the ACC is necessary for recalling behaviors learned a month or more in the past, but not for the same behaviors learned the previous day. Precisely how the ACC contributes to the recall of remote memories is unknown. Is this role distinct from myriad others proposed for the ACC, or has the approach taken in these studies of assessing function at different points after learning provided a new window through which to view established processes? The present review seeks to address this question. First, the data will be presented implicating the ACC in recall of remote memory. This will be followed by a discussion of studies describing two other primary roles of the ACC, mediating attention and premotor planning, with an emphasis on data collected in rodents, as these will be most directly comparable to the memory studies presented. The available evidence supports a connection among these roles, and suggests a possible synthesis for otherwise seemingly disparate functions reported for the ACC. © 2013 Elsevier B.V. All rights reserved.

Contents 1. 2.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Memory encoding and storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. The prospective approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Consolidation theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. The synaptic tagging hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The ACC and remote recall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Accumulating evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Counter-examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Anatomical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Functional diversity of the ACC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. The ACC and attention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Evidence of top-down control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

∗ Corresponding author. Tel.: +1 541 346 6302; fax: +1 541 346 4548. E-mail address: [email protected] 0166-4328/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.bbr.2013.02.010

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4.3. The ACC and gaze control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Memory as a distributed phenomenon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3. Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction In 1882, the French psychologist Ribot [1] proposed perhaps the earliest formal description of temporally-graded retrograde amnesia. He saw the study of “diseases of memory” as a strategy by which healthy mnemonic processes might better be understood. Limited by the understanding of the day, his classifications were by symptom rather than underlying neurological bases. During the first half of the twentieth century, attempts were made at identifying where in the brain memories were stored [2]. However, it was not until the initial study of patient H.M. in 1957 [3] that some localization of function was achieved. The bilateral surgical resection of H.M.’s medial temporal lobe (MTL), performed in an attempt to ameliorate symptoms of intractable epilepsy, resulted in a profound anterograde and temporally-graded retrograde amnesia, but spared other cognitive abilities. At the time, it was unclear which structures were responsible for mediating the abilities that had been lost (the surgery involved the hippocampus, parahippocampal gyrus, uncus and amygdala), much less how. Nevertheless, H.M.’s surgery provided the first clear evidence of a particular region of the brain disproportionately associated with memory. That some of his older memories could still be recalled also suggested a neurological basis for Ribot’s observations and provided the first clues that long-term storage of information occurred elsewhere in the brain, a process that has come to be known as consolidation [4–8]. In the time since H.M.’s initial characterization, much has been learned about the neural underpinnings of memory. Clinical data and ever-improving neuroimaging techniques have yielded valuable insights into how different regions of the brain support the development and stabilization of long-term representations [9,10]. Animal models have also proven useful, and are free of many of the limitations associated with human subjects, such as the functional and neuroanatomical heterogeneity of pathology in the clinical population, or the challenge in neuroimaging studies of differentiating between structures that are essential to task performance rather than merely active. These models have revealed in extensive detail the contributions of the hippocampus and parahippocampal structures to learning and memory. Furthermore, these studies have identified a multitude of cortical structures that are involved during the recall of remote memory, consistent with evidence from the human literature of long-term storage of information in a domain-specific manner throughout a distributed cortical network [10–12]. One cortical structure recently implicated in rodent studies of remote recall is the anterior cingulate cortex (ACC). The data from these studies are compelling, but shed little light on how the ACC contributes to this process. Early imaging data in humans revealed ACC involvement during recall of familiar associations [13], an effect subsequently proposed to reflect attention [14,15]. However, the ACC has been associated with a wide variety of attentional as well as other functions, such as action/outcome valuations [16,17], novelty detection [18,19], determination of salience [20,21], associative learning [22–27], premotor planning and movement execution [28–30], processing of pain [31,32], error detection [33–35], monitoring or resolving conflict [36–38], mediating

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adaptation to changes in cognitive load [39], processing of reward [40] and decision making [41]. The present review examines how the proposed role in memory may be interpreted in the context of this functional diversity. Section 2 includes a brief description of studies that illustrate the transition of information from the hippocampus to the long-term cortical store, and how these data relate to the process of consolidation. In Section 3, studies implicating the ACC in remote memory recall are described. In Section 4, evidence of two of the most well established roles of the ACC, attention as well as premotor planning and movement execution, are examined. Finally, in Section 5, the evidence for ACC involvement in remote memory recall are discussed in the context of these two major functional roles. The goal of the present review is not to develop a grand unifying theory of ACC function. Rather, it is to examine how the ACC may support remote memory recall, drawing upon the existing literature. The focus here will be predominantly on data from mouse, rat and rabbit, as these should relate most directly, and avoid more fundamental questions of cross-species neuroanatomical and functional homology [e.g., 42, 43, 44]. Nevertheless, many of the correlates discussed here have clear parallels to the primate and human literature. 2. Memory encoding and storage The memory impairments exhibited by patient H.M. were attributable to the bilateral excision of his hippocampus and associated parahippocampal structures. However, the specific involvement of these structures was only revealed decades later through the use of animal models of amnesia [10]. Particularly helpful to the study of retrograde amnesia were investigations that assessed function at different points after learning. This “prospective approach” has enabled defining a rough time course for the transition to hippocampus-independent recall of remotely learned information. 2.1. The prospective approach One of the first studies to clearly demonstrate this transition examined the role of the hippocampus in conditioning and recall of contextual fear [45]. Rats were trained to associate the conditioning chamber with a shock. The hippocampus was then lesioned 1, 7, 14 or 28 days later. Contextual fear memory, evidenced by freezing behavior in the training chamber, was completely abolished in rats lesioned 1 day after training. When lesions were performed 7 or 14 days after training, some freezing was observed, indicating partial sparing of the fear memory. Rats from the 28-day group behaved comparably to controls. By assessing the impact of hippocampal lesions at different time points after training, this study revealed how recall of contextual fear memory gradually came to involve structures outside the hippocampus proper. 2.2. Consolidation theory The evidence indicates that long-term storage of information occurs in a distributed cortical network [4,11,12]. This storage is

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considered to be “domain-specific” [10] such that, for example, different sensory cortices will contain modality-specific elements, or “feature fragments”, that are associated with previous experiences [12]. This was demonstrated recently in a study of cued fear conditioning [46]. Rats were trained to associate a tone conditioned stimulus (CS) with a footshock unconditioned stimulus (US). Lesions of secondary (Te2) auditory cortex 1 month after training disrupted subsequent freezing behavior to the tone. In rats assayed for immediate early gene (IEG) expression, c-Fos and Zif268 levels were increased in the superficial layers (LII-LIV) of Te2 immediately following recall of remote fear memory. Considered to be indirect measures of neuronal activation [47–49], IEGs constitute an early genomic response critical to the initiation, maintenance and stabilization of neuronal plasticity and the formation of long-term memories [50]. These effects were seen for other sensory modalities as well, and were modality specific. These results demonstrate that conditioning stimuli are among the feature fragments stabilized and ultimately stored in the cortical network. As mentioned briefly in Section 1, the gradual stabilization of memory is referred to as consolidation. The concept of memory consolidation was first proposed more than a century ago in studies of rehearsal and the effects of interference [51,52]. Consolidation is viewed as occurring at both synaptic and systems levels [4,6–8]. Synaptic consolidation occurs rapidly, and refers to the increased gene expression and synaptic modification that happens within the first minutes to hours after learning. Systems consolidation, by contrast, occurs over much broader time scales, and includes hard-wired changes within and between nodes of the distributed cortical network. This two-speed process is believed to contribute to the stability of the hippocampal-cortical system [4,6]. The hippocampus has been viewed as a temporary repository for new learning, maintaining representations through rapidly developed but short-lived modifications [4]. These representations are repeatedly reactivated by the hippocampal system, strengthening the connections among the cortical storage sites that will ultimately be capable of supporting memory recall independently. Reactivation of the memory trace occurs either in the waking state or involuntarily during sleep. During reactivation, evidence suggests that the memory again becomes labile and, for a time at least, is sensitive to disruption by protein synthesis inhibitors [53]. Whether memories are ever fully consolidated, or are instead perpetually returned to the labile state during reactivation in a process referred to as reconsolidation, is a source of some debate. It is similarly unclear whether consolidation and reconsolidation refer to distinct processes, and whether reconsolidation occurs under all conditions. Numerous well-written reviews are available addressing these various issues [54–58]. In the present review, the term “reactivation” refers specifically to the evidence of increased IEG expression elicited by re-exposure to the training environment. The debate regarding the functional implications of this phenomenon is not discussed in detail. 2.3. The synaptic tagging hypothesis Despite their strikingly different time courses, recent evidence [59] suggests that synaptic and systems consolidation processes work in parallel, consistent with the model proposed by Alvarez and Squire [11] that information related to an event is initially stored as short-lived modifications between parahippocampal structures and the distributed cortical network that are repeatedly reactivated. Social transmission of food preference (STFP) is a paradigm in which rats learn about the relative safety of potential food sources through sampling the odor of those sources on the breath of littermates. Rats were tested 1 day or 30 days after exposure. Recent recall of the behavior was dependent on the hippocampus. Remote recall was dependent upon the orbitofrontal cortex (OFC), a region

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of the brain that also exhibits increased c-Fos expression following remote recall of STFP behavior [60]. Morphological changes observed at synaptic terminals within the OFC indicate that it may store information relating to the behavior. Building upon an updated view of the Hebbian model [61] examining synaptic tagging as a mechanism temporally associated with rapid, synaptic consolidation [62], the investigators examined whether the hippocampus and OFC exhibited signs of simultaneous tagging at the time of encoding. Temporary inactivation of the OFC immediately before STFP did not disrupt recall when tested 7 days later, a time point at which the hippocampal representation would still have been capable of supporting the behavior. However, the same inactivation disrupted remote recall when tested 30 days later and eliminated the morphological changes in the OFC associated with memory consolidation. This effect was specific to individual iterations of STFP. These data indicate that hippocampal-cortical interactions at the time of encoding of specific events are crucial to the subsequent cortical storage of information relating to those events. 2.4. Summary Memories are stabilized in a process known as consolidation. During encoding, reciprocal connections between nodes in a distributed cortical network and the parahippocampal gyrus become activated, likely reflecting mechanisms associated with rapid, synaptic consolidation. Iterative reactivation of the memory trace, coordinated by the hippocampus, strengthens the connections within the network over time, reflecting the slower process of systems consolidation. As this process progresses, the critical role of the hippocampus diminishes, eventually leading to a state where remote memory recall may be achieved independently, and is mediated instead by concurrently activated cortical nodes. 3. The ACC and remote recall The hippocampus is clearly important for the recall of certain types of recently learned information, and is essential to guiding the reactivation and stabilization of memory in the cortex. What is less clear is where in the cortex these processes occur and how the structures involved contribute to remote recall. Recently, the prospective approach that has proven so valuable in examining hippocampal involvement in consolidation has identified some of the nodes within the cortical network. One of these is the ACC. 3.1. Accumulating evidence Recognizing how little was known about how the brain changes over time to support recall of remotely learned information, Bontempi et al. [63] cast a wide net and assessed metabolic activity multiple regions at different time points following training in a spatial discrimination task. Mice learned to discriminate three baited from five un-baited arms of a distally-cued eight arm radial maze, and were then injected with the metabolic marker (14 C)2deoxyglucose (2-DG) 1 min before the final acquisition session, or before retention tests performed either 5 days or 25 days later. Activity in the hippocampus and entorhinal cortex that had been elevated following the final acquisition session and the 5 day retention test was significantly decreased when assessed 25 days after training. The opposite pattern was observed in the ACC, where significantly increased 2-DG uptake was observed only at the remote retention interval. These data fit the model of cortical consolidation, and indicated that the ACC was potentially involved in the process of remote memory recall. The authors conceded that interpretation of this result was somewhat hampered by a decrease in performance accuracy at the 25-day interval, and that

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increased activation in the ACC could have reflected the greater effort associated with recall of a memory trace weakened over time, a hypothesis also discussed by Rudy et al. [64]. Nevertheless, these results were compelling, and focused attention on ACC involvement in the recall of remote memories. Subsequent studies expanded on this initial result. In one of these [65], mice were shocked in a conditioning chamber, and then returned to the chamber either 1 day or 36 days later to assess contextual fear memory. Robust freezing was observed at both retention intervals, reflecting a strong association between the conditioning chamber and the aversive footshock US. Levels of the IEGs Zif268 and c-Fos were elevated in area CA1 of the hippocampus at the recent, but not the remote, retention interval. The opposite pattern was observed in the ACC where IEGs were elevated specifically at the remote retention interval. Remote memory deficient ␣-CaMKII+/− mutant mice [66] exhibited reduced freezing at the 36 day retention interval and no elevation in IEG expression in the ACC. Expression of growth-associated protein 43 (GAP-43), a marker for synaptogenesis, was also suppressed in the ACC of ␣CaMKII+/− mutant mice at the remote retention interval. In another study, Maviel et al. [67] reported similar results using a spatial reference memory task, and demonstrated that silencing of the ACC with lidocaine also selectively disrupted remote memory retrieval. The basic strategy in these two papers was the same as that employed previously: examine the functional involvement of the hippocampus, the ACC and other cortical structures at different retention intervals. The addition of behavioral manipulations and molecular techniques, however, demonstrated the critical role of the ACC in remote recall. Systems consolidation involves the progressive development of cortico-cortical connections that are ultimately responsible for the storage of remote memory [4,7,9,68,69]. Evidence of these changes first hinted at in the previous studies [63,65,67] was then demonstrated directly by Restivo et al. [70] who examined changes in spine density at recent (1 day) and remote (36 day) retention intervals following contextual fear conditioning. Increased spine density in the hippocampus was only observed at the recent retention interval, whereas similar changes in ACC layers II/III were found specifically at the remote retention interval. Excitotoxic lesions of the hippocampus revealed that the hippocampal–cortical interactions driving these changes in the ACC likely occurred within three weeks of training. The time course of these changes was refined by Vetere et al. [71], who demonstrated that the increases in layers II/III were most pronounced during the first week after training. Furthermore, suppression of spinogenesis during the first post-training week disrupted subsequent expression of freezing behavior when assessed 7 days or 48 days after training. While the effect on recent memory recall is somewhat at odds with the findings of Lesburguères et al. [59], these data are nonetheless consistent with the importance of ongoing hippocampal–cortical interactions from the time of initial encoding for the subsequent consolidation of information in the cortical network. What do these structural changes represent? What types of information does the ACC convey during remote recall? Careful behavioral analysis provides some clues. Teixeira et al. [72] trained mice to swim to a platform in a pool surrounded by distal visual cues. Recent (1 day) and remote (30 day) recall tests consisted of a single probe trial for which the platform had been removed. Expression levels of the IEG c-Fos were elevated in the ACC selectively following remote recall, and silencing the ACC at this time point with a local infusion of lidocaine significantly reduced time spent in the target zone where the platform had been. However, silencing of the ACC did not disrupt memory for procedural aspects of the task, as this did not elicit a return of thigmotactic behavior typically exhibited by naive mice [73]. Rather, these mice explored all parts of the pool equally, indicating that, whereas the procedural memory

for the task remained, mice were no longer able to recognize where the platform had been. A recent in vivo electrophysiological study of object/place associations in the mouse ACC sheds some additional light on these questions [74]. In this study, two groups of mice were allowed to explore a pair of objects in a cylindrical arena. Six hours later, the mice were returned to the arena with only one of the two objects remaining. Single Exposure (S-Exp) mice had only the one previous exploration session with both objects. In contrast, Repeated Exposure (R-Exp) mice had already been extensively habituated to both objects in the arena for an average of two weeks. Following removal of the one object, both groups of mice continued to explore where that object had been, demonstrating memory for it. Mice also continued to explore the remaining object. The proportion of ACC neurons responding around the remaining object was similar between groups. However, only extensively habituated R-Exp mice had neurons responding to the absent object. Of those neurons, some continued to respond following the object’s removal, while others started responding specifically to the object’s absence. Furthermore, firing throughout the environment was more stable in the habituated R-Exp mice across the 6-h delay. In a separate group of habituated mice, responses to object removal were assessed following a delay of 30 days. Here, too, the absent object location was indicated by both the behavior and spiking activity, consistent with a consolidated representation of the environment. While ACC neurons are not inherently spatial [74–76], these data indicate that stable spatial representations can develop over time that include salient locations (e.g., that of a previously explored object, or a submerged platform in the water maze). Furthermore, whereas neurons that continue to fire where the object had been represent a neural memory for that object, responses that arise specifically from the object’s absence are reminiscent of top-down executive processes such as error detection [33] or conflict monitoring [36,37] that are also associated with the ACC. This will be discussed further in Section 4. It is worth noting that the evidence of ACC involvement in remote memory recall is not restricted to hippocampus-dependent tasks. Ding et al. [77] examined the effects of silencing the ACC on recent and remote recall of conditioned taste aversion (CTA), a behavioral paradigm in which a novel appetitive substance (e.g., saccharin-flavored water) is paired with the malaise-inducing agent lithium chloride. The hallmark of learning is avoidance of the “novel” substance upon re-exposure to the conditioning chamber. This association does not require the hippocampus [78,79]. However, silencing the ACC 30 days after training blocked subsequent expression of CTA, demonstrating that the ACC is also involved in the consolidation of non-hippocampal mediated learning. 3.2. Counter-examples The studies described in the preceding section provide multiple lines of evidence for ACC involvement in remote recall. Nonetheless, examples running counter to this proposed role do exist. Oswald et al. [27] eyeblink conditioned rabbits to associate a tone CS with a mildly aversive airpuff US temporally separated by a stimulus-free “memory trace” interval. Lesions of the ACC performed immediately after training impaired subsequent recall of the conditioned response, whereas lesions performed 1 week after training produced no discernible effects. Though the timing of the lesions does not match, this alone cannot account for such a strikingly different outcome from that of the studies described in the previous section. Two other recent studies have also failed to detect a role for the ACC in remote recall. DeCoteau et al. [80] used a successive go/nogo visual scene discrimination task to assess object-based longterm memory. Standard scenes of four objects in an enclosure were

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rewarded, whereas scenes in which one of the familiar objects had been replaced with a novel object went unrewarded. Learning was scored in terms of differential latencies to enter rewarded versus unrewarded enclosures. The ACC was lesioned only after animals reached criterion which required an average of 39 days of training, well beyond when consolidation-associated structural changes in the ACC are first observed [71]. However, these lesions failed to produce a persistent deficit in performance. In another study by Ross and Eichenbaum [60], rats were tested for non-spatial social transmission of food preference at one of four time points after training (immediately, 1 day, 2 days or 21 days). Expression of the IEG c-Fos was indistinguishable in the ACC among the different time points as well as compared with controls, interpreted as a lack of involvement of the structure during recall. These results suggest the possibility that the ACC is involved in consolidation of only certain types of information. Bontempi et al. [63], Maviel et al. [67] and Teixeira et al. [72] examined ACC function in spatial tasks. Furthermore, contextual fear conditioning, while not an explicitly spatial task, requires spatial exploration of the conditioning chamber [81], further distinguishing these counterexamples from Frankland et al. [65], Restivo et al. [70] and Vetere et al. [71]. However, the evidence that remote recall of conditioned taste aversion is also disrupted by ACC inactivation [77] suggests that a spatial hypothesis is incorrect. A closer examination of the histology and methodology reported in two of these counter-examples [60,80] indicates that the focus was on a subregion of the ACC distinct from that targeted in the studies described in Section 3.1, a difference that may explain the absence of an effect. The rationale behind this hypothesis is discussed in greater detail in the following section. 3.3. Anatomical considerations The term “anterior cingulate cortex” implies a unitary structure. It is, in fact, a highly heterogeneous region consisting of at least six distinct subregions in primates and humans [41,82,83] and at least three in rodents and rabbits [84–86], and includes functionally and neuroanatomically segregated rostral and caudal components (Fig. 1). In humans, the rostral ACC is associated with “affective” processes, whereas the caudal component plays a more “cognitive” role [82,83,87–89]. Studies in rodents and rabbits also reflect this functional distinction. Nociceptive neuronal responses are observed largely in the rostral ACC [90,91] and appear to regulate processing the affective component of pain [92,93]. Simple associative learning tasks with an aversive and unavoidable unconditioned stimulus (US) also selectively recruit the rostral component [92,94,95]. In contrast, developing attentionally demanding associations specifically involves the caudal component [23,25]. Neuroanatomically, the rostral ACC (anterior to the genu of the corpus callosum) is more closely associated with prelimbic and infralimbic regions of the medial prefrontal cortex, and is less densely interconnected with other midline cortical regions [84,96]. What few projections there are directly between the hippocampus and the ACC are limited almost exclusively to the rostral component [97–99], and there are also clear differences in connectivity between the two components and the rest of the parahippocampal region [100]. These data clearly indicate the importance of differentiating between rostral and caudal ACC when ascribing function. In examining the histology reported for the lesions [80] and IEG sampling [60], it is apparent that DeCoteau et al. as well as Ross and Eichenbaum are targeting the rostral ACC. In contrast, the studies described in Section 3.1 all report results associated specifically with the caudal ACC (the only exception being the study by Frankland et al. [65], for which this degree of detail was unavailable). This neuroanatomical explanation could easily account for the absence

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of ACC involvement in remote recall reported in these two studies. Notably, however, this would not explain the effects observed by Oswald et al. [27] who did target the caudal subdivision, suggesting that the question of task or content specificity remains open. 3.4. Summary Numerous lines of evidence indicate that the ACC is part of a distributed cortical network involved in consolidation and the recall of remote memory (Table 1). First, disrupting ACC function at different time points after training selectively impairs remote recall. Second, reactivation of the remote memory is associated with increased expression of IEGs Zif268 and c-Fos, proxy measures of neuronal activity, as well as GAP-43, a marker for spinogenesis. Third, the ability to recall remote memories is associated with an increase in the size and density of spines on the processes of layer II/III pyramidal neurons. These structural changes are evident as early as one week after training. Fourth, and finally, the neural representation of the environment stabilizes over time, and includes correlates specific to highly familiar, salient locations. Importantly, the data suggest that it is specifically the caudal component of the ACC that is involved in remote memory recall, a region that is functionally and neuroanatomically distinct from the more rostral component. 4. Functional diversity of the ACC The studies described in the previous section implicate the rodent ACC in recall of remote memory, and indicate that the ACC is part of the distributed cortical network involved in consolidation. But in what way does the ACC contribute to remote recall? What information does it convey? Changes in IEG expression and morphology cannot answer these questions, and ACC single neuron data coupled with the prospective approach have only begun to emerge. As discussed in Section 2, theories relating to this process describe domain-specific storage of information, and a hierarchical structure of increasing complexity in which local ensembles in distinct sensory and motor cortical regions are activated in concert by higher-order structures. Prospective studies in rodents provide clear evidence of modality-specific storage of information in different secondary sensory cortical regions, consistent with the distributed nature of memory storage. Based on its neuroanatomical connectivity and the diversity of cognitive processes and behaviors with which it is associated, the ACC is more likely to function in a higher-order, integrative capacity. One approach to addressing how the ACC contributes to remote recall is to examine some of the other roles ascribed to the structure. In the human and primate literature, among the most thoroughly documented functions of the ACC are those relating to attention as well as premotor planning and movement execution. In this section, several studies will be discussed that demonstrate these functions in rodents and rabbits. Two additional studies will also be discussed highlighting ACC involvement in top-down control. In one, data were presented indicating that the ACC may facilitate acquisition of behaviors that are typically considered hippocampus-dependent. In the other, deactivation of the hippocampus during remote recall directly affected IEG expression patterns in the ACC. As with the studies described in Section 3.1, these studies all reported results collected from the caudal subdivision of the ACC. Together, these results will help define how the ACC is likely to support the recall of remotely learned information. 4.1. The ACC and attention The human and primate literature regarding the role of the ACC in attention is extensive [for some reviews, see 15, 82, 101–105].

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Fig. 1. The anterior cingulate cortex (ACC) includes multiple, distinct subregions. The ACC, illustrated in midline sagittal views, exhibits a functional and neuroanatomical heterogeneity that is preserved across the phylogenetic spectrum, from rodents (A) and rabbits (B) through non-human (C) and human (D) primates. The rostral ACC (areas 24a,b, as well as area 24c in primates) is functionally associated with “affective” processes, and is neuroanatomically more closely associated with other medial prefrontal structures including the prelimbic (area 32) and infralimbic (area 25) cortices. The caudal ACC (areas 24a -c ) plays a more “cognitive” role, and exhibits distinct connections with other midline as well as parahippocampal cortices. The dorsal aspect of the ACC is more closely associated with motor processes, and exhibits more prominent direct projections to the primary motor cortex. cc: corpus callosum; gcc: genu, corpus callosum. Individual panels adapted from (A) Paxinos and Franklin [85], (B) Vogt et al. [86], (C) Walton and Mars [41] and (D) Bush et al. [82].

This is in part due to the broad range of attentionally demanding conditions in which activation of the ACC is observed, such as error detection [33,34], monitoring or resolving conflict [36,37], processing of reward [40] and decision making [41], as well as simpler conditions of associative learning [22,24], novel object recognition [106] and pattern monitoring [107]. This diversity of function reflects the multiple levels of attention with which the ACC is involved [15,108], from alerting, associated with brainstem structures such as the locus ceruleus that are structurally and functionally coupled with the ACC [29,109], to executive control in which the ACC facilitates top-down direction and cognitive flexibility. In mice, rats and rabbits, the ACC is involved in a similarly broad range of attentionally demanding tasks and conditions, as illustrated below. The ACC is involved in hippocampus-dependent trace conditioning paradigms that require the association of a CS and US separated in time by a stimulus-free trace interval [21–25,110–112]. Learning is demonstrated by expression of the conditioned response (CR) during the trace interval, prior to US onset. Lesions of the ACC disrupt trace fear conditioning, as reflected by a lower incidence of freezing behavior (the CR) in response to a tone (the CS) associated with a footshock (the US) [23]. Training also elicited an increase in c-Fos expression in the ACC, reflecting increased neuronal activation in the region. This effect was specific to the presence of the trace interval, as no similar increase was observed with delay conditioning, a less demanding version of the task with no discontinuity between the CS and US. Use of a visual distracter selectively impaired acquisition, consistent with the effect of distracters during trace conditioning in humans [113]. The lesion and distracter

data together were interpreted as evidence for the role of attention, in part supported by the ACC, in establishing the CS–US contingency. Single neuron data collected during trace eyeblink conditioning support this conclusion. As with trace fear conditioning, pretraining lesions of the ACC disrupted acquisition of the eyeblink CR [25,110]. Neurons in the ACC were found to be highly responsive to both the tone-CS and the airpuff-US from the start of training [21], with stimuli eliciting either increases or decreases in activity. With the paired presentations of trace conditioning, CS-elicited changes in firing rate were maintained across training sessions. Rate increasing responses were greatest early in training, before acquisition of the CR. In contrast, rate decreasing responses to the CS grew more pronounced as behavioral performance improved, such that by the end of training firing remained suppressed throughout the entire trace interval. Similar changes observed at the start of pseudo conditioning (involving unpaired CS–US presentations) were not maintained. These data reflect the preference of ACC neurons for novel and/or salient stimuli while also revealing how these responses change with learning, and illustrate the highly specific and complex impact of behaviorally relevant associations on activity in this region of the brain. Under certain circumstances, the rodent ACC may also act to direct attention away from irrelevant stimuli. Ng et al. [114] examined the effect of ACC lesions on performance of an attention set-shifting task [115]. In this task, animals learn to dig in the one baited cup of a pair differentiated by cues of one of two perceptual dimensions (e.g., odor cues or digging media). Over the course of many days, animals learn to attend specifically to one perceptual

Table 1 Multiple lines of evidence implicate the anterior cingulate cortex in remote memory recall. Study Bontempi et al. [63] Frankland et al. [65]

Behavior Spatial discrimination Contextual fear conditioning

Maviel et al. [67]

Spatial reference memory

Teixeira et al. [72]

Water maze

Ding et al. [77] Restivo et al. [70] Vetere et al. [71]

Conditioned taste aversion Contextual fear conditioning Contextual fear conditioning

Weible et al. [74]

Absent object recognition

Evidence - Remote increases in glucose utilization. - Remote increases in immediate early gene expression. - Reduced GAP-43 in CamKII+/− at remote intervals. - Lidocaine silences remote recall - Remote increases in immediate early gene expression - Remote increases in GAP-43 - Lidocaine silences remote recall - Remote increases in immediate early gene expression - Lidocaine silences remote recall. - Post-training hippocampus lesions block remote recall and increases in spine density. - Myocyte enhancer factor 2 up-regulation disrupts remote recall - Training increases LII/III spine density - Familiarity stabilizes neural representations.

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dimension while ignoring the other. Then, discriminations with new pairs of cues in both dimensions are presented, following first the original, relevant perceptual dimension (an intradimensional shift, or IDS) and then switching to the previously irrelevant dimension (an extradimensional shift, or EDS). Control animals were able to rapidly learn the new discriminations in the same dimension (the IDS), but were slow to shift to the new perceptual dimension (the EDS), reflecting the progressive strengthening of attention to the initial relevant dimension. Pre-training lesions of the ACC significantly impaired performance during the IDS, but completely spared learning new discriminations during the EDS. Therefore, ACC lesions did not impair the ability to learn discriminations, per se, but instead appear to have impaired the ability to ignore the irrelevant dimension when new pairs were presented. This study provides evidence for the role of the ACC in distinguishing between relevant and irrelevant cues when required to make decisions. Neuronal correlates associated with attention are also seen in animals performing at asymptote. Totah et al. [116] demonstrated this with rats trained to perform a three-choice serial reaction time task. Rats were presented with a choice of three cue holes on one wall of an operant chamber, each with an internal light-emitting diode. Following a brief pre-cue period, one of the three cue holes was randomly illuminated. Selection of the illuminated hole resulted in the delivery of two sucrose pellets from the opposite wall. Incorrect trials and omissions (no cue hole selection within a 5 s trial window) resulted in a time-out. Single neuron spiking data were collected once rats reached behavioral criterion (which required an average of 41 days of training). Analyses revealed that ACC involvement during the pre-cue period was greatest preceding correct trials compared with incorrect trials and omissions, both in the proportion of neurons responding as well as their response magnitudes. The predictive value of these responses was observed both in neurons exhibiting increases in firing rate as well as neurons exhibiting decreases. Increases in firing rate tended to peak in amplitude 2–3 s prior to cue onset. Decreases persisted up to the presentation of the cue itself, and roughly mirrored increases observed in the more rostrally-located prelimbic cortex. Both patterns of activity were also more pronounced on trials immediately following an error, though the same information was available from one trial to the next, regardless of behavioral outcome. These data demonstrate the involvement of the ACC in both preparatory attention and error detection, and illustrate the predictability of past and future performance based on the spiking activity of individual ACC neurons alone. These studies illustrate the central role of the ACC in both the acquisition and ongoing performance of numerous classical and operant conditioning tasks. The maintenance of the CS-associated response specifically during trace conditioning [21] likely reflects the attentional mechanism that is disrupted by distracters in both mice [23] and humans [113]. Over time, the influence of distracters can be ameliorated, as the ACC facilitates selective attention to relevant stimuli by suppressing attention to irrelevant stimuli [114]. Specific patterns of activity preceding correct trials and following incorrect trials in the serial reaction time task [116] reflect a role for the rodent ACC in both preparatory attention and error detection, respectively, consistent with data from humans and primates [15,33,117]. Together, the data from these studies demonstrate how attentional processes in the ACC that are crucial at the start of training continue to support behavior long after tasks have been learned. 4.2. Evidence of top-down control The process of systems consolidation, as discussed in Section 2.2, is generally viewed as occurring over the course of weeks or more, and involves the reactivation of functionally coupled

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connections between distributed cortical and parahippocampal structures. However, when occurring against the backdrop of previous experience, cortical structures can rapidly encode and stabilize newly learned information independently of the hippocampus. This phenomenon, known as schema-dependent learning, was recently demonstrated by Tse et al. [118,119]. Rats were trained to associate each of six different flavored food pellets given in a start box with a specific reward location in a contextually rich arena. Rats typically reached asymptotic performance with six of these paired-associates (or PAs) within six weeks. For the critical training session, they were then separated into three groups: original paired-associates (OPA), new paired-associates (NPA) and new map (NM). The OPA group was given six trials with the original PAs. The NPA group was presented first with 4 original, then 2 new PAs. The NM group was presented with all new PAs. A 3-h delay separated the presentation of the first 4 PAs and PAs 5 and 6. The development of new PAs is generally dependent upon the hippocampus, though when presented in the context of previously learned associations (the schema), new PAs can be acquired without hippocampal involvement [118]. The data suggest that the ACC is involved in this process. Elevated IEG levels were observed in the ACC following recall of the OPAs, consistent with the reactivation of a consolidated representation that would have developed over the six weeks of training. However, rapid acquisition of new PAs by the NPA group was associated with an even greater elevation in IEG expression in the ACC, as well as other midline cortical structures [119]. These data argue that top-down mechanisms [120,121] mediated in part by the ACC enable the rapid, systems consolidation of information into an existing, stable mental schema, in effect by-passing the hippocampus and facilitating the expression of behaviors that would take a naive animal weeks to learn. The results described in this study may also be evidence that reconsolidation and reactivation may not be synonymous, and that certain components of the neural circuitry mediating remote recall undergo reconsolidation specifically when memories require updating [122,123]. Interestingly, the ability of the cortical network to recall remotely learned information independently of the hippocampus depends critically on when the hippocampus is removed from the circuit [124]. This discovery, enabled by the rapid kinetics of optogenetic silencing, revealed continued involvement of the hippocampus in remote recall in the intact brain, and provided further insights on remote recall and top-down processing in the ACC. Conventional physical, genetic or pharmacological lesion techniques typically take minutes to days to take effect [45,81,125–127], potentially enabling the recruitment of compensatory mechanisms. With optogenetic techniques, silencing of neuronal activity can be achieved on the order of milliseconds [128,129]. Using such techniques, Goshen et al. [124] demonstrated that silencing of CA1 pyramidal neurons disrupted both acquisition and recent recall of contextual fear memory, replicating previous results. Remarkably, silencing of CA1 neurons during remote memory retrieval, referred to as “precise” silencing, also disrupted expression of contextual fear. In contrast, “prolonged” silencing that began 30 min prior to the test of remote memory, a time course analogous to more conventional inactivation techniques, spared contextual fear memory. The authors attributed this to an inability to recognize the environment, and suggested that, in the intact brain, the hippocampus remains functionally coupled with the distributed cortical network and acts as a “default activator” during remote recall. Particularly relevant to the present discussion was the impact of these two forms of silencing on ACC function. Precise CA1 silencing disrupted increases in c-Fos expression in the ACC that normally accompany remote recall of contextual fear memory [see also 65], indicating that exposure to the familiar environment alone does not reactivate the representation in the ACC. In contrast, prolonged CA1 silencing was associated with an increase in

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c-Fos expression greater than that observed in controls in which the hippocampus was active. These results reveal that activation of the ACC is proportional to the demands placed upon it and that, in compensation for the absence of the hippocampus, top-down control mechanisms mediated in part by the ACC take a greater role in recognizing and attending to the salient features of the environment in support of recalling remotely learned behaviors.

long after structural changes associated with consolidation are likely to have occurred. The most thoroughly examined motor function of the rodent ACC, oculomotor control, is potentially critical to these attentional processes by directing gaze and minimizing involuntary deviations of gaze elicited by peripheral distracters. These functions of the ACC are engaged in both novel situations and during performance of well-established behaviors, and facilitate the cognitive flexibility necessary to adapt to changing conditions.

4.3. The ACC and gaze control Equally well studied as its role in attention is the involvement of the ACC in premotor planning and movement execution. This requires that any discussion of ACC function must consider potential involvement of motor processes. In humans and primates, the cingulate motor areas (CMAs) are found within the cingulate sulcus, dorsal to the cingulate gyrus which is more generally associated with attentional and cognitive processes [82,83]. Defined in part by their direct projections to primary motor cortex [28,30], the CMAs are functionally associated with simple movements [for reviews, see 28,29,130] as well as the integration of sensory information and the execution of task-related behaviors [e.g., 131,132]. The clear structural segregation of the CMAs from the rest of the ACC in humans and primates is absent in rodents and rabbits, though patterns of neuroanatomical connectivity similar to those of the primate ACC have been described [133–135]. The functional organization of primary motor and neighboring cortices, including the ACC, has been examined by assessing microstimulation-evoked motor responses in anesthetized animals [136–139]. Using this approach, the most recent of these studies identified correlates that are potentially relevant to the present discussion. Brecht et al. [136] mapped out the motor responses of the dorsal and ventral subdivisions of the ACC. Microstimulation of the ACC was consistently associated with eye/periocular movements, interpreted as evidence that the ACC is likely involved in oculomotor control. The presence of corticospinal projection neurons in the rodent ACC suggests that it may be involved in other motor processes, as well [140]. However, the functional relevance of these connections has not been examined in detail. Based on theirs and previous work, Brecht et al. [136] suggested that the stimulation-evoked eye movements may be related to lower-level autonomic functions. However, the human literature describes ACC involvement in directing and maintaining gaze during specific behaviors [141,142]. For example, the ACC is involved in producing memory guided saccades, anti-saccades and visually guided sequences of saccades [143], and is necessary for inhibiting involuntary saccades [142]. Furthermore, neuronal response latencies to visual stimuli suggest that the ACC is involved in signaling the context of those stimuli relative to the production of saccades and other gaze associated movements [144]. These results are indicative of a complex role for the ACC in oculomotor control, and together with evidence of reciprocal connections between the ACC and visual cortices [134] suggest that the correlates observed in the rodent may be equally important in directing gaze during learned behaviors. 4.4. Summary The growing body of evidence implicating the ACC in recall of remote memory represents only the most recent in a long list of functions ascribed to the structure. Two of the most thoroughly documented functions, especially in humans and non-human primates, relate to attention and to premotor processing and movement control. These functions of the ACC are evident in mice, rats and rabbits as well. Attentional mechanisms in the ACC, including top-down control, support both acquisition and performance of a range of behaviors and learning paradigms, and are still evident

5. Discussion 5.1. Memory as a distributed phenomenon The ACC is associated with an enormous range of functions, as the partial list in Section 1 indicates. Recently added to this list is a role for the ACC in recall of remote memory. The evidence for this role is compelling. Lesions of the ACC a month or more after training disrupt subsequent expression of learned behaviors [65,67,72,77]. Measures of glucose utilization [63] and IEG expression [65,67,72] both indicate an increase in activation at this remote interval. Over time, neural representations of space and object/place associations stabilize [74]. Perhaps most significantly, successful recall at the remote interval is associated with changes in synaptic connectivity and morphology [70,71], consistent with models of systems consolidation. But how does the ACC facilitate recall of remotely learned information? Consolidation is considered to occur across a distributed cortical network. Remote recall involves the reactivation of this network, with different nodes providing different elements of the whole memory [10,12]. As discussed in Section 2.2, for example, the consolidation of sensory information is modality specific, with “feature fragments” of the memory stored in associated secondary sensory cortical regions [12,46]. Absent an unlikely degree of redundancy, the increased activation observed with remote recall in structures such as orbitofrontal [60], temporal [63,65] parietal and posterior cingulate [67] cortices, in addition to the ACC, suggests this distributed organization extends to higher-order structures as well. However, the lesion effects and changes in IEG expression patterns that have been reported reveal little of how each structure supports the recall process. What is required is an understanding of how neurons function individually and at the network level during remote recall. We have only begun to scratch the surface in this respect with the ACC [74], and considerably more work is required. However, understanding the contributions of other structures will also prove informative, as this will help place changes in ACC activity into context. One structure for which such data have recently come to light is the medial prefrontal cortex (mPFC). Lesion [145] and inactivation [67], IEG expression [63,65,67,119], synapse morphology and spine density [146] data all point toward the involvement of the mPFC in systems consolidation and remote recall, at least for certain types of information [65]. During trace conditioning, for example, some mPFC neurons develop a sustained increase in firing through the trace interval [147]. Over time, this response profile becomes both more robust and more wide-spread [148–150], and is accompanied by greater synchronization of oscillatory activity between the mPFC and other cortical structures [151] reflecting changes in the cortical network associated with consolidation. These data, seen in the context of the primate literature on working memory [152–154], have been interpreted as evidence that the mPFC is involved in linking conditioning stimuli and providing timing information critical to executing appropriately timed conditioned responses [148,155,156]. If this is indeed the case, it suggests that the ACC contributes upstream of the mPFC to the process of remote recall.

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5.2. Synthesis The evidence suggests that ACC-mediated attentional mechanisms similar to those involved in acquisition and performance of numerous different conditioning paradigms [21–25,116,157] also support remote memory recall and that motor processes in the ACC such as those regulating gaze control would contribute to this process. Specifically, the ACC is likely involved in learning and recalling which elements in the environment to attend to and which to ignore, and optimizing conditions for the rapid integration of new information. Lesions disrupt the ability to prioritize attentional resources effectively, leading to the deficits observed during both task acquisition as well as tests of remote retrieval. This conclusion is based in part on the synaptic tagging hypothesis discussed in Section 2.3: a set of neurons that is activated at the time of encoding is also involved through reactivation in the gradual stabilization and eventual consolidation of the memory trace [59,62]. This suggests that similarities in neuronal activation would be observed during both encoding and the recall of remote memory. At the time of encoding, neuronal correlates in the ACC often reflect attentional processes, such as novelty detection, determination of salience, and the formation of associations [32,74,76,150]. These processes, which are so critical to new learning, continue to be relevant to the performance of well-established behaviors, and the data suggest that these correlates persist well beyond the time when consolidation-associated structural changes are first observed [71]. For example, objects in the environment evoke neuronal responses (either increases or decreases in firing rate) when they are novel, and continue doing so long after that novelty has passed, presumably because they remain salient to the animal as evidenced by their continued exploration. Over time, these correlates stabilize as object/place associations, becoming integrated into a stable neural representation of the environment [74,76]. This evidence for a neural representation stabilized with experience has clear implications for the successful performance of many of the tasks described in Section 3.1. Persistent encoding-associated neural correlates are observed during trace eyeblink conditioning as well. CS-elicited increases in firing rate seen at the start of training remain well after the CR has been learned, though the amplitude of such responses is much reduced [21,149]. CS-elicited decreases in activity do not attenuate over time, and in fact provide the better indicator for acquisition of the task [21]. This decrease is initially locked to the CS presentation itself, but then expands to include the trace interval as the animal begins exhibiting conditioned responses. Together with the object exploration data, these results demonstrate that attention-related neuronal correlates observed during encoding are maintained weeks later. As the predominant correlate in the ACC of trace conditioned animals, the CS-elicited decrease in firing warrants further consideration. There are at least three ways in which this correlate could reflect or support attention during remote recall. First, the reduction in spiking activity may serve to increase the signal-to-noise of task-related excitatory responses elsewhere in the brain, such as those in the mPFC that may be providing timing information for execution of the behavioral response [116,148,150,155,156]. Second, it may serve as an inhibitory mechanism blocking the impact of distracters that compete for attention, consistent with the findings of Ng et al. [114] during intradimensional set-shifting. One might reason that this second interpretation would conflict with the proposed role in novelty detection. However, during trace eyeblink conditioning and intradimensional set-shifting, this suppression is learned, and specific to the demands of the task. In the case of the former, the animal learns that the CS signals the imminent occurrence of an aversive, avoidable event, and that a specific response must be performed at a specific time to be

Fig. 2. Diverse and reciprocal connectivity supports the role of the anterior cingulate cortex (ACC) in processes such as mediating attention, task acquisition, top-down control and remote recall. The wiring diagram illustrates the major connections of the caudal ACC (cACC) discussed in the present review. Sensory information reaches the ACC through numerous, often reciprocal, subcortical and cortical pathways. The ACC is similarly connected with centers of motor processing and output. The basal forebrain cholinergic system (BFCS) and locus ceruleus (LC) are crucial for arousal and the maintenance of sustained attention, while top-down modulation of behavior is accomplished via interactions with other higher-order structures such as the medial prefrontal and posterior cingulate cortices (mPFC and PCC, respectively). Communication with the hippocampal formation occurs via parahippocampal structures such as the perirhinal and entorhinal cortices. Arrows indicate the direction of connectivity. IL: infralimbic cortex; LEC: lateral entorhinal cortex; MEC: medial entorhinal cortex; PL: prelimbic cortex; PRh: perirhinal cortex; rACC: rostral anterior cingulate cortex.

effective. In the latter, the novelty with each new pair in the non-rewarded stimulus dimension can be ignored because the animal learns that the entire dimension is irrelevant. In fact, this leads to the third, and perhaps most intriguing possibility. The CS-elicited decrease would effectively raise the signal-to-noise of neural responses within the ACC itself to novelty or change when it may be most relevant. In the well-trained animal, the CS initiates a period of increased arousal and preparation for a learned behavior. Detecting and rapidly integrating changes from the expected sequence of events at this point would be crucial to adaptively modifying that behavior. Such a mechanism would fit with observed activation in the ACC during schema-based learning [119], as well as the rapid development of structural changes associated with extinction [146]. Therefore, this correlate would in fact represent the active management of one of the prime attentional processes of the ACC, the tendency to attend to novel stimuli. Frankland et al. [65] noted that it had yet to be determined whether the ACC was a site of memory storage or if it was instead involved in integrating stored representations from the distributed cortical network. Subsequent work [70,71] demonstrated that the ACC exhibits a central hallmark of a consolidated representation: a remodeling of cortical connections that is essential for recall of remote memory. But this does not preclude an integrative role. Compared with numerous other cortical regions, pyramidal neurons in the ACC have a more branched and spinous dendritic arbor and larger soma, suggesting that these neurons are well suited to integrating the activity of a high density of divergent connections [158]. Those connections perhaps most relevant to the present discussion are illustrated in Fig. 2. The ACC interacts with sensory and motor regions via numerous direct and indirect pathways [134,159–164] as well as higher-order structures involved in top-down control [84,161,163]. The ACC is also reciprocally connected with lower-order structures associated with arousal [109,165] and receives basal forebrain cholinergic input that is critical for attentional processing [163,166–169]. Importantly, it also has the reciprocal connections with parahippocampal structures such as perirhinal and medial and lateral entorhinal cortices that would be expected to show reactivation during the consolidation process [100,161,170,171]. Together, these data indicate that the

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ACC is ideally positioned to function in an integrative capacity, regulating attentional resources to incoming stimuli in the context of past experience.

5.3. Summary and conclusions A wealth of data implicates the ACC in attention. Recently, numerous studies have also demonstrated a role for the ACC in recall of remote memory. However, the specific contribution of the ACC during this process is still unknown. The role of the ACC in attention is evident in both novel situations as well as during performance of well-learned tasks. Many of the spiking correlates evoked during encoding are still evident at asymptotic performance, and pre-training lesions of the ACC disrupt acquisition of numerous tasks as effectively as lesions performed immediately prior to remote recall. When considered together, these studies suggest that the ACC supports attention to, and recognition of, those cues that are most relevant to successful recall of remotely learned behaviors. This likely involves a balance of excitatory and inhibitory mechanisms gating the strength of converging inputs during task performance, occurring against a backdrop of a stable, consolidated neural representation of the environment. During reexposure to the environment, reactivation returns the consolidated representation to a state where these same attentional processes and top-down control mechanisms can facilitate the rapid updating of the representation, enabling the cognitive flexibility that is essential for adapting to a constantly changing, dynamic world.

References [1] Ribot T. Les Maladies de la Memoire [Diseases of memory]. New York: Appleton-Century-Crofts; 1881 [English translation]. [2] Lashley KS. Brain mechanisms and intelligence: a quantitative study of injuries of the brain. Chicago: Chicago Univ. Press; 1929. [3] Scoville WB, Milner B. Loss of recent memory after bilateral hippocampal lesions. Journal of Neurology, Neurosurgery and Psychiatry 1957;20(1):11–21. [4] Squire LR, Alvarez P. Retrograde amnesia and memory consolidation: a neurobiological perspective. Current Opinion in Neurobiology 1995;5(2):169–77. [5] Marr D. A theory for cerebral neocortex. Proceedings of the Royal Society of London Series B: Biological Sciences 1970;176(43):161–234. [6] McClelland JL, McNaughton BL, O‘Reilly RC. Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychological Review 1995;102(3):419–57. [7] Dudai Y. The neurobiology of consolidations, or, how stable is the engram? Annual Review of Psychology 2004;55:51–86. [8] Dudai YM, Morris RGM. To consolidat or not to consolidate: what are the questions? In: Bulhuis J, editor. Brain, perception, memory. Advances in cognitive sciences. Oxford: Oxford Univ. Press; 2000. p. 149–62. [9] Squire LR, Bayley PJ. The neuroscience of remote memory. Current Opinion in Neurobiology 2007;17(2):185–96. [10] Squire LR, Wixted JT. The cognitive neuroscience of human memory since H.M. Annual Review of Neuroscience 2011;34:259–88. [11] Alvarez P, Squire LR. Memory consolidation and the medial temporal lobe: a simple network model. Proceedings of the National Academy of Sciences of the United States of America 1994;91(15):7041–5. [12] Damasio AR. Time-locked multiregional retroactivation: a systems-level proposal for the neural substrates of recall and recognition. Cognition 1989;33(1-2):25–62. [13] Petersen SE, Fox PT, Posner MI, Mintun M, Mand ME, Raichle ME. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature 1988;331(6157):585–9. [14] Pardo JV, Pardo PJ, Janer KW, Raichle ME. The anterior cingulate cortex mediates processing selection in the Stroop attentional conflict paradigm. Proceedings of the National Academy of Sciences of the United States of America 1990;87(1):256–9. [15] Petersen SE, Posner MI. The attention system of the human brain: 20 years after. Annual Review of Neuroscience 2012;35:73–89. [16] Rudebeck PH, Walton ME, Smyth AN, Bannerman DM, Rushworth MF. Separate neural pathways process different decision costs. Nature Neuroscience 2006;9(9):1161–8. [17] Rushworth MF, Walton ME, Kennerley SW, Bannerman DM. Action sets and decisions in the medial frontal cortex. Trends in Cognitive Sciences 2004;8(9):410–7.

[18] Downar J, Crawley AP, Mikulis DJ, Davis KD. A multimodal cortical network for the detection of changes in the sensory environment. Nature Neuroscience 2000;3(3):277–83. [19] Downar J, Crawley AP, Mikulis DJ, Davis KD. A cortical network sensitive to stimulus salience in a neutral behavioral context across multiple sensory modalities. Journal of Neurophysiology 2002;87(1):615–20. [20] Downar J, Mikulis DJ, Davis KD. Neural correlates of the prolonged salience of painful stimulation. Neuroimage 2003;20(3):1540–51. [21] Weible AP, Weiss C, Disterhoft JF. Activity profiles of single neurons in caudal anterior cingulate cortex during trace eyeblink conditioning in the rabbit. Journal of Neurophysiology 2003;90(2):599–612. [22] Buchel C, Dolan RJ, Armony JL, Friston KJ. Amygdala-hippocampal involvement in human aversive trace conditioning revealed through eventrelated functional magnetic resonance imaging. Journal of Neuroscience 1999;19(24):10869–76. [23] Han CJ, O’Tuathaigh CM, van Trigt L, Quinn JJ, Fanselow MS, Mongeau R, et al. Trace but not delay fear conditioning requires attention and the anterior cingulate cortex. Proceedings of the National Academy of Sciences of the United States of America 2003;100(22):13087–92. [24] Knight DC, Cheng DT, Smith CN, Stein EA, Helmstetter FJ. Neural substrates mediating human delay and trace fear conditioning. Journal of Neuroscience 2004;24(1):218–28. [25] Weible AP, McEchron MD, Disterhoft JF. Cortical involvement in acquisition and extinction of trace eyeblink conditioning. Behavioral Neuroscience 2000;114(6):1058–67. [26] Darling RD, Takatsuki K, Griffin AL, Berry SD. Eyeblink conditioning contingent on hippocampal theta enhances hippocampal and medial prefrontal responses. Journal of Neurophysiology 2011;105(5):2213–24. [27] Oswald BB, Maddox SA, Tisdale N, Powell DA. Encoding and retrieval are differentially processed by the anterior cingulate and prelimbic cortices: a study based on trace eyeblink conditioning in the rabbit. Neurobiology of Learning and Memory 2010;93(1):37–45. [28] Dum RP, Strick PL. Motor areas in the frontal lobe of the primate. Physiology and Behavior 2002;77(4-5):677–82. [29] Paus T. Primate anterior cingulate cortex: where motor control, drive and cognition interface. Nature Reviews Neuroscience 2001;2(6):417–24. [30] Picard N, Strick PL. Motor areas of the medial wall: a review of their location and functional activation. Cerebral Cortex 1996;6(3):342–53. [31] Vogt BA, Vogt L, Farber NB, Bush G. Architecture and neurocytology of monkey cingulate gyrus. Journal of Comparative Neurology 2005;485(3):218–39. [32] Wang JY, Luo F, Chang JY, Woodward DJ, Han JS. Parallel pain processing in freely moving rats revealed by distributed neuron recording. Brain Research 2003;992(2):263–71. [33] Niki H, Watanabe M. Prefrontal and cingulate unit activity during timing behavior in the monkey. Brain Research 1979;171(2):213–24. [34] Posner MI, Dehaene S. Attentional networks. Trends in Neurosciences 1994;17(2):75–9. [35] Schall JD, Boucher L. Executive control of gaze by the frontal lobes. Cognitive, Affective, & Behavioral Neuroscience 2007;7(4):396–412. [36] Botvinick MM, Braver TS, Barch DM, Carter CS, Cohen JD. Conflict monitoring and cognitive control. Psychological Review 2001;108(3):624–52. [37] Carter CS, van Veen V. Anterior cingulate cortex and conflict detection: an update of theory and data. Cognitive, Affective, & Behavioral Neuroscience 2007;7(4):367–79. [38] Kuhl BA, Bainbridge WA, Chun MM. Neural reactivation reveals mechanisms for updating memory. Journal of Neuroscience 2012;32(10):3453–61. [39] Sheth SA, Mian MK, Patel SR, Asaad WF, Williams ZM, Dougherty DD, et al. Human dorsal anterior cingulate cortex neurons mediate ongoing behavioural adaptation. Nature 2012;488(7410):218–21. [40] Hampton AN, O‘Doherty PJ. Decoding the neural substrates of reward-related decision making with functional MRI. Proceedings of the National Academy of Sciences of the United States of America 2007;104(4):1377–82. [41] Walton ME, Mars RB. Probing human and monkey anterior cingulate cortex in variable environments. Cognitive, Affective, & Behavioral Neuroscience 2007;7(4):413–22. [42] DeVito LM, Eichenbaum H. Distinct contributions of the hippocampus and medial prefrontal cortex to the “what-where-when” components of episodiclike memory in mice. Behavioural Brain Research 2010;215(2):318–25. [43] Seamans JK, Lapish CC, Durstewitz D. Comparing the prefrontal cortex of rats and primates: insights from electrophysiology. Neurotoxicity Research 2008;14(2-3):249–62. [44] Uylings HB, Groenewegen HJ, Kolb B. Do rats have a prefrontal cortex? Behavioural Brain Research 2003;146(1–2):3–17. [45] Kim JJ, Fanselow MS. Modality-specific retrograde amnesia of fear. Science 1992;256(5057):675–7. [46] Sacco T, Sacchetti B. Role of secondary sensory cortices in emotional memory storage and retrieval in rats. Science 2010;329(5992):649–56. [47] Jones MW, Errington ML, French PJ, Fine A, Bliss TV, Garel S, et al. A requirement for the immediate early gene Zif268 in the expression of late LTP and long-term memories. Nature Neuroscience 2001;4(3):289–96. [48] Hall J, Thomas KL, Everitt BJ. Cellular imaging of zif268 expression in the hippocampus and amygdala during contextual and cued fear memory retrieval: selective activation of hippocampal CA1 neurons during the recall of contextual memories. Journal of Neuroscience 2001;21(6):2186–93. [49] Fleischmann A, Hvalby W, Jensen V, Strekalova T, Zacher C, Layer LE, et al. Impaired long-term memory and NR2A-type NMDA receptor-dependent

A.P. Weible / Behavioural Brain Research 245 (2013) 63–75

[50]

[51] [52] [53] [54]

[55] [56] [57] [58] [59]

[60]

[61] [62] [63]

[64]

[65]

[66]

[67] [68] [69] [70]

[71]

[72]

[73]

[74]

[75]

[76]

[77]

[78]

[79] [80]

[81]

synaptic plasticity in mice lacking c-Fos in the CNS. Journal of Neuroscience 2003;23(27):9116–22. Davis S, Bozon B, Laroche S. How necessary is the activation of the immediate early gene zif268 in synaptic plasticity and learning? Behavioural Brain Research 2003;142(1–2):17–30. Lechner HA, Squire LR, Byrne JH. 100 years of consolidation—remembering Muller and Pilzecker. Learning and Memory 1999;6(2):77–87. Müller GE, Pilzecker A. Experimentelle Beitrage zur Lehre vom Gedachtnis. Z. Psychol. Erganzungsband 1900;1:1–300. Nader K, Schafe GE, Le Doux JE. Fear memories require protein synthesis in the amygdala for reconsolidation after retrieval. Nature 2000;406(6797):722–6. Alberini CM. Mechanisms of memory stabilization: are consolidation and reconsolidation similar or distinct processes? Trends in Neurosciences 2005;28(1):51–6. Alberini CM, Chen DY. Memory enhancement: consolidation, reconsolidation and insulin-like growth factor 2. Trends in Neurosciences 2012;35(5):274–83. Nader K, Einarsson EO. Memory reconsolidation: an update. Annals of the New York Academy of Sciences 2010;1191:27–41. Nader K, Wang SH. Fading in. Learning and Memory 2006;13(5):530–5. Dudai Y, Eisenberg M. Rites of passage of the engram: reconsolidation and the lingering consolidation hypothesis. Neuron 2004;44(1):93–100. Lesburgueres E, Gobbo OL, Alaux-Cantin S, Hambucken A, Trifilieff P, Bontempi B. Early tagging of cortical networks is required for the formation of enduring associative memory. Science 2011;331(6019):924–8. Ross RS, Eichenbaum H. Dynamics of hippocampal and cortical activation during consolidation of a nonspatial memory. Journal of Neuroscience 2006;26(18):4852–9. Hebb DO. The organization of behaviour. New York: Wiley; 1949. Frey U, Morris RG. Synaptic tagging and long-term potentiation. Nature 1997;385(6616):533–6. Bontempi B, Laurent-Demir C, Destrade C, Jaffard R. Time-dependent reorganization of brain circuitry underlying long-term memory storage. Nature 1999;400(6745):671–5. Rudy JW, Biedenkapp JC, O‘Reilly RC. Prefrontal cortex and the organization of recent and remote memories: an alternative view. Learning and Memory 2005;12(5):445–6. Frankland PW, Bontempi B, Talton LE, Kaczmarek L, Silva AJ. The involvement of the anterior cingulate cortex in remote contextual fear memory. Science 2004;304(5672):881–3. Frankland PW, O’Brien C, Ohno M, Kirkwood A, Silva AJ. Alpha-CaMKIIdependent plasticity in the cortex is required for permanent memory. Nature 2001;411(6835):309–13. Maviel T, Durkin TP, Menzaghi F, Bontempi B. Sites of neocortical reorganization critical for remote spatial memory. Science 2004;305(5680):96–9. Frankland PW, Bontempi B. The organization of recent and remote memories. Nature Reviews Neuroscience 2005;6(2):119–30. Squire LR, Stark CE, Clark RE. The medial temporal lobe. Annual Review of Neuroscience 2004;27:279–306. Restivo L, Vetere G, Bontempi B, Ammassari-Teule M. The formation of recent and remote memory is associated with time-dependent formation of dendritic spines in the hippocampus and anterior cingulate cortex. Journal of Neuroscience 2009;29(25):8206–14. Vetere G, Restivo L, Cole CJ, Ross PJ, Ammassari-Teule M, Josselyn SA, et al. Spine growth in the anterior cingulate cortex is necessary for the consolidation of contextual fear memory. Proceedings of the National Academy of Sciences of the United States of America 2011;108(20):8456–60. Teixeira CM, Pomedli SR, Maei HR, Kee N, Frankland PW. Involvement of the anterior cingulate cortex in the expression of remote spatial memory. Journal of Neuroscience 2006;26(29):7555–64. Wolfer DP, Stagljar-Bozicevic M, Errington ML, Lipp HP. Spatial memory and learning in transgenic mice: fact or artifact? News in Physiological Sciences 1998;13:118–23. Weible AP, Rowland DC, Monaghan CK, Wolfgang NT, Kentros CG. Neural correlates of long-term object memory in the mouse anterior cingulate cortex. Journal of Neuroscience 2012;32(16):5598–608. Hok V, Save E, Lenck-Santini PP, Poucet B. Coding for spatial goals in the prelimbic/infralimbic area of the rat frontal cortex. Proceedings of the National Academy of Sciences of the United States of America 2005;102(12): 4602–7. Weible AP, Rowland DC, Pang R, Kentros C. Neural correlates of novel object and novel location recognition behavior in the mouse anterior cingulate cortex. Journal of Neurophysiology 2009;102(4):2055–68. Ding HK, Teixeira CM, Frankland PW. Inactivation of the anterior cingulate cortex blocks expression of remote: but not recent, conditioned taste aversion memory. Learning and Memory 2008;15(5):290–3. Josselyn SA, Kida S, Silva AJ. Inducible repression of CREB function disrupts amygdala-dependent memory. Neurobiology of Learning and Memory 2004;82(2):159–63. Yamamoto T, Fujimoto Y. Brain mechanisms of taste aversion learning in the rat. Brain Research Bulletin 1991;27(3-4):403–6. DeCoteau WE, McElvaine D, Smolentzov L, Kesner RP. Effects of rodent prefrontal lesions on object-based: visual scene memory. Neurobiology of Learning and Memory 2009;92(4):552–8. McHugh TJ, Jones MW, Quinn JJ, Balthasar N, Coppari R, Elmquist JK, et al. Dentate gyrus NMDA receptors mediate rapid pattern separation in the hippocampal network. Science 2007;317(5834):94–9.

73

[82] Bush G, Luu P, Posner MI. Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Sciences 2000;4(6):215–22. [83] Devinsky O, Morrell MJ, Vogt BA. Contributions of anterior cingulate cortex to behaviour. Brain 1995;118(Pt 1):279–306. [84] Jones BF, Groenewegen HJ, Witter MP. Intrinsic connections of the cingulate cortex in the rat suggest the existence of multiple functionally segregated networks. Neuroscience 2005;133(1):193–207. [85] Paxinos G, Franklin KBJ. The mouse brain in stereotaxic coordinates. 2nd ed. San Diego: Academic Press; 2001 [xxv, 1 v. (various pagings)]. [86] Vogt BA, Sikes RW, Swadlow HA, Weyand TG. Rabbit cingulate cortex: cytoarchitecture, physiological border with visual cortex, and afferent cortical connections of visual, motor, postsubicular, and intracingulate origin. Journal of Comparative Neurology 1986;248(1):74–94. [87] Bush G, Whalen PJ, Rosen BR, Jenike MA, McInerney SC, Rauch SL. The counting Stroop: an interference task specialized for functional neuroimaging—validation study with functional MRI. Human Brain Mapping 1998;6(4):270–82. [88] Rolls ET. The affective and cognitive processing of touch: oral texture, and temperature in the brain. Neuroscience and Biobehavioral Reviews 2010;34(2):237–45. [89] Whalen PJ, Bush G, McNally RJ, Wilhelm S, McInerney SC, Jenike MA, et al. The emotional counting Stroop paradigm: a functional magnetic resonance imaging probe of the anterior cingulate affective division. Biological Psychiatry 1998;44(12):1219–28. [90] Hsu MM, Shyu BC. Electrophysiological study of the connection between medial thalamus and anterior cingulate cortex in the rat. Neuroreport 1997;8(12):2701–7. [91] Vogt BA. Pain and emotion interactions in subregions of the cingulate gyrus. Nature Reviews Neuroscience 2005;6(7):533–44. [92] Johansen JP, Fields HL, Manning BH. The affective component of pain in rodents: direct evidence for a contribution of the anterior cingulate cortex. Proceedings of the National Academy of Sciences of the United States of America 2001;98(14):8077–82. [93] Kuo CC, Yen CT. Comparison of anterior cingulate and primary somatosensory neuronal responses to noxious laser-heat stimuli in conscious: behaving rats. Journal of Neurophysiology 2005;94(3):1825–36. [94] Bissiere S, Plachta N, Hoyer D, McAllister KH, Olpe HR, Grace AA, et al. The rostral anterior cingulate cortex modulates the efficiency of amygdaladependent fear learning. Biological Psychiatry 2008;63(9):821–31. [95] Malin EL, Ibrahim DY, Tu JW, McGaugh JL. Involvement of the rostral anterior cingulate cortex in consolidation of inhibitory avoidance memory: interaction with the basolateral amygdala. Neurobiology of Learning and Memory 2007;87(2):295–302. [96] Shibata H, Naito J. Organization of anterior cingulate and frontal cortical projections to the retrosplenial cortex in the rat. Journal of Comparative Neurology 2008;506(1):30–45. [97] Cenquizca LA, Swanson LW. Spatial organization of direct hippocampal field CA1 axonal projections to the rest of the cerebral cortex. Brain Research Reviews 2007;56(1):1–26. [98] Conde F, Maire-Lepoivre E, Audinat E, Crepel F. Afferent connections of the medial frontal cortex of the rat. II. Cortical and subcortical afferents. Journal of Comparative Neurology 1995;352(4):567–93. [99] Hoover WB, Vertes RP. Anatomical analysis of afferent projections to the medial prefrontal cortex in the rat. Brain Structure and Function 2007;212(2):149–79. [100] Jones BF, Witter MP. Cingulate cortex projections to the parahippocampal region and hippocampal formation in the rat. Hippocampus 2007;17(10):957–76. [101] Coull JT. Neural correlates of attention and arousal: insights from electrophysiology, functional neuroimaging and psychopharmacology. Progress in Neurobiology 1998;55(4):343–61. [102] Fossella J, Fan J, Liu X, Guise K, Brocki K, Hof PF, et al. Provisional hypotheses for the molecular genetics of cognitive development: imaging genetic pathways in the anterior cingulate cortex. Biological Psychology 2008;79(1): 23–9. [103] Mesulam MM. Spatial attention and neglect: parietal, frontal and cingulate contributions to the mental representation and attentional targeting of salient extrapersonal events. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 1999;354(1387):1325–46. [104] Sarter M, Gehring WJ, Kozak R. More attention must be paid: the neurobiology of attentional effort. Brain Research Reviews 2006;51(2):145–60. [105] Segalowitz SJ, Dywan J. Individual differences and developmental change in the ERN response: implications for models of ACC function. Psychological Research 2009;73(6):857–70. [106] Pihlajamaki M, Tanila H, Konenen M, Hanninen T, Aronen HJ, Soininen H. Distinct and overlapping fMRI activation networks for processing of novel identities and locations of objects. European Journal of Neuroscience 2005;22(8):2095–105. [107] Huettel SA, Mack PB, McCarthy G. Perceiving patterns in random series: dynamic processing of sequence in prefrontal cortex. Nature Neuroscience 2002;5(5):485–90. [108] Posner MI, Petersen SE. The attention system of the human brain. Annual Review of Neuroscience 1990;13:25–42. [109] Gompf HS, Mathai C, Fuller PM, Wood DA, Pedersen NP, Saper CB, et al. Locus ceruleus and anterior cingulate cortex sustain wakefulness in a novel environment. Journal of Neuroscience 2010;30(43):14543–51.

74

A.P. Weible / Behavioural Brain Research 245 (2013) 63–75

[110] Kronforst-Collins MA, Disterhoft JF. Lesions of the caudal area of rabbit medial prefrontal cortex impair trace eyeblink conditioning. Neurobiology of Learning and Memory 1998;69(2):147–62. [111] Moyer Jr JR, Deyo RA, Disterhoft JF. Hippocampectomy disrupts trace eyeblink conditioning in rabbits. Behavioral Neuroscience 1990;104(2):243–52. [112] Solomon PR, Vander Schaaf ER, Thompson RF, Weisz DJ. Hippocampus and trace conditioning of the rabbit’s classically conditioned nictitating membrane response. Behavioral Neuroscience 1986;100(5):729–44. [113] Clark RE, Manns JR, Squire LR. Classical conditioning: awareness, and brain systems. Trends in Cognitive Sciences 2002;6(12):524–31. [114] Ng CW, Noblejas MI, Rodefer JS, Smith CB, Poremba A. Double dissociation of attentional resources: prefrontal versus cingulate cortices. Journal of Neuroscience 2007;27(45):12123–31. [115] Birrell JM, Brown VJ. Medial frontal cortex mediates perceptual attentional set shifting in the rat. Journal of Neuroscience 2000;20(11):4320–4. [116] Totah NK, Kim YB, Homayoun H, Moghaddam B. Anterior cingulate neurons represent errors and preparatory attention within the same behavioral sequence. Journal of Neuroscience 2009;29(20):6418–26. [117] Johnston K, Levin HM, Koval MJ, Everling S. Top-down control-signal dynamics in anterior cingulate and prefrontal cortex neurons following task switching. Neuron 2007;53(3):453–62. [118] Tse D, Langston RF, Kakeyama M, Bethus I, Spooner PA, Wood ER, et al. Schemas and memory consolidation. Science 2007;316(5821):76–82. [119] Tse D, Takeuchi T, Kakeyama M, Kajii Y, Okuno H, Tohyama C, et al. Schemadependent gene activation and memory encoding in neocortex. Science 2011;333(6044):891–5. [120] Kuhl BA, Shah AT, DuBrow S, Wagner AD. Resistance to forgetting associated with hippocampus-mediated reactivation during new learning. Nature Neuroscience 2010;13(4):501–6. [121] Osada T, Adachi Y, Kimura HM, Miyashita Y. Towards understanding of the cortical network underlying associative memory. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 2008;363(1500):2187–99. [122] Frankland PW, Ding HK, Takahashi E, Suzuki A, Kida S, Silva AJ. Stability of recent and remote contextual fear memory. Learning and Memory 2006;13(4):451–7. [123] Lee JL. Reconsolidation: maintaining memory relevance. Trends in Neurosciences 2009;32(8):413–20. [124] Goshen I, Brodsky M, Prakash R, Wallace J, Gradinaru V, Vamakrishnan C, et al. Dynamics of retrieval strategies for remote memories. Cell 2011;147(3):678–89. [125] Kitamura T, Saitoh Y, Takashima N, Murayama A, Niibori Y, Ageta H, et al. Adult neurogenesis modulates the hippocampus-dependent period of associative fear memory. Cell 2009;139(4):814–27. [126] Nakashiba T, Young JZ, McHugh TJ, Buhl DL, Tonegawa S. Transgenic inhibition of synaptic transmission reveals role of CA3 output in hippocampal learning. Science 2008;319(5867):1260–4. [127] Wiltgen BJ, Zhou M, Cai Y, Balaji J, Karlsson MG, Parivash SN, et al. The hippocampus plays a selective role in the retrieval of detailed contextual memories. Current Biology 2010;20(15):1336–44. [128] Boyden ES, Zhang F, Bamberg E, Nagel G, Deisseroth K. Millisecond-timescale: genetically targeted optical control of neural activity. Nature Neuroscience 2005;8(9):1263–8. [129] Deisseroth K, Feng G, Majewska AK, Miesenbock G, Ting A, Schnitzer MJ. Nextgeneration optical technologies for illuminating genetically targeted brain circuits. Journal of Neuroscience 2006;26(41):10380–6. [130] Kollias SS, Alkadhi H, Jaermann T, Crelier G, Hepp-Reymond MC. Identification of multiple nonprimary motor cortical areas with simple movements. Brain Research Brain Research Reviews 2001;36(2-3):185–95. [131] Beudel M, de Jong BM. Overlap and segregation in predorsal premotor cortex activations related to free selection of self-referenced and target-based finger movements. Cerebral Cortex 2009;19(10):2361–71. [132] Isomura Y, Ito Y, Akazawa T, Nambu A, Takada M. Neural coding of “attention for action” and “response selection” in primate anterior cingulate cortex. Journal of Neuroscience 2003;23(22):8002–12. [133] Rouiller EM, Moret V, Liang F. Comparison of the connectional properties of the two forelimb areas of the rat sensorimotor cortex: support for the presence of a premotor or supplementary motor cortical area. Somatosensory and Motor Research 1993;10(3):269–89. [134] Vogt BA, Miller MW. Cortical connections between rat cingulate cortex and visual: motor, and postsubicular cortices. Journal of Comparative Neurology 1983;216(2):192–210. [135] Wang JY, Zhang HT, Chang JY, Woodward DJ, Baccala LA, Lou F. Anticipation of pain enhances the nociceptive transmission and functional connectivity within pain network in rats. Mol Pain 2008;4:34. [136] Brecht M, Krauss A, Muhammad S, Sinai-Esfahani L, Bellanca S, Margrie TW. Organization of rat vibrissa motor cortex and adjacent areas according to cytoarchitectonics: microstimulation, and intracellular stimulation of identified cells. Journal of Comparative Neurology 2004;479(4):360–73. [137] Gioanni Y, Lamarche M. A reappraisal of rat motor cortex organization by intracortical microstimulation. Brain Research 1985;344(1):49–61. [138] Hall RD, Lindholm EP. Organization of motor and somatosensory neocortex in the albino rat. Brain Research 1974;66:23–38. [139] Neafsey EJ, Bold EL, Haas G, Hurley-Gius KM, Quirk G, Sievert CF, et al. The organization of the rat motor cortex: a microstimulation mapping study. Brain Research 1986;396(1):77–96.

[140] Miller MW. The origin of corticospinal projection neurons in rat. Experimental Brain Research 1987;67(2):339–51. [141] Haller S, Fasler D, Ohlendorf S, Radue EW, Greenlee MW. Neural activation associated with corrective saccades during tasks with fixation: pursuit and saccades. Experimental Brain Research 2008;184(1):83–94. [142] Paus T, Kalina M, Patockova L, Angerova Y, Cerny R, Mecir P, et al. Medial vs lateral frontal lobe lesions and differential impairment of central-gaze fixation maintenance in man. Brain 1991;114(Pt 5):2051–67. [143] Gaymard B, Rivaud S, Cassarini JF, Dubard T, Rancurel G, Agid Y, et al. Effects of anterior cingulate cortex lesions on ocular saccades in humans. Experimental Brain Research 1998;120(2):173–83. [144] Pouget P, Emeric EE, Stuphorn V, Reis K, Schall JD. Chronometry of visual responses in frontal eye field: supplementary eye field, and anterior cingulate cortex. Journal of Neurophysiology 2005;94(3):2086–92. [145] Takehara K, Kawahara S, Kirino Y. Time-dependent reorganization of the brain components underlying memory retention in trace eyeblink conditioning. Journal of Neuroscience 2003;23(30):9897–905. [146] Vetere G, Restivo L, Novembre G, Aceti M, Lumaca M, Ammassari-Teule M. Extinction partially reverts structural changes associated with remote fear memory. Learning and Memory 2011;18(9):554–7. [147] Gilmartin MR, McEchron MD. Single neurons in the medial prefrontal cortex of the rat exhibit tonic and phasic coding during trace fear conditioning. Behavioral Neuroscience 2005;119(6):1496–510. [148] Takehara-Nishiuchi K, McNaughton BL. Spontaneous changes of neocortical code for associative memory during consolidation. Science 2008;322(5903):960–3. [149] Yoon T, Disterhoft JF, Weiss C. Activity of single neurons in the rabbit prefrontal cortex during trace eyeblink conditioning. Society for Neuroscience Abstacts, 2010(807.13/KKK48). [150] Yoon T, Hattori S, Disterhoft JF, and Weiss C. Differential pattern of neural activity from the prefrontal cortex after the consolidation of trace eyeblink conditioning in rabbits. Society for Neuroscience Abstacts, 2011(730.14/ZZ30). [151] Takehara-Nishiuchi K, Maal-Bared G, Morrissey MD. Increased entorhinal-prefrontal theta synchronization parallels decreased entorhinalhippocampal theta synchronization during learning and consolidation of associative memory. Frontiers in Behavioral Neuroscience 2011; 5:90. [152] Fuster JM. Unit activity in prefrontal cortex during delayed-response performance: neuronal correlates of transient memory. Journal of Neurophysiology 1973;36(1):61–78. [153] Fuster JM. The prefrontal cortex—an update: time is of the essence. Neuron 2001;30(2):319–33. [154] Goldman-Rakic PS. Regional and cellular fractionation of working memory. Proceedings of the National Academy of Sciences of the United States of America 1996;93(24):13473–80. [155] Weiss C, Disterhoft JF. Eyeblink conditioning: motor control, and the analysis of limbic-cerebellar interactions. Behavioral and Brain Sciences 1996;19(3):479–81. [156] Weiss C, Disterhoft JF. Exploring prefrontal cortical memory mechanisms with eyeblink conditioning. Behavioral Neuroscience 2011;125(3):318–26. [157] Totah NK, Jackson ME, Moghaddam B. Preparatory attention relies on dynamic interactions between prelimbic cortex and anterior cingulate cortex. Cerebral Cortex 2012. [158] Elston GN, Benavides-Piccione R, Defelipe J. A study of pyramidal cell structure in the cingulate cortex of the macaque monkey with comparative notes on inferotemporal and primary visual cortex. Cerebral Cortex 2005;15(1): 64–73. [159] Fitzpatrick DC, Olsen JF, Suga N. Connections among functional areas in the mustached bat auditory cortex. Journal of Comparative Neurology 1998;391(3):366–96. [160] Kolb B, Walkey J. Behavioural and anatomical studies of the posterior parietal cortex in the rat. Behavioural Brain Research 1987;23(2):127–45. [161] Musil SY, Olson CR. Organization of cortical and subcortical projections to anterior cingulate cortex in the cat. Journal of Comparative Neurology 1988;272(2):203–18. [162] Thompson SM, Robertson RT. Organization of subcortical pathways for sensory projections to the limbic cortex. I. Subcortical projections to the medial limbic cortex in the rat. Journal of Comparative Neurology 1987;265(2):175–88. [163] Weible AP, Weiss C, Disterhoft JF. Connections of the caudal anterior cingulate cortex in rabbit: neural circuitry participating in the acquisition of trace eyeblink conditioning. Neuroscience 2007;145(1):288–302. [164] Gonzalez-Burgos G, Barrionuevo G, Lewis DA. Horizontal synaptic connections in monkey prefrontal cortex: an in vitro electrophysiological study. Cerebral Cortex 2000;10(1):82–92. [165] Aston-Jones G, Cohen JD. An integrative theory of locus coeruleusnorepinephrine function: adaptive gain and optimal performance. Annual Review of Neuroscience 2005;28:403–50. [166] Voytko ML. Cognitive functions of the basal forebrain cholinergic system in monkeys: memory or attention? Behavioural Brain Research 1996;75(1–2):13–25. [167] Everitt BJ, Robbins TW. Central cholinergic systems and cognition. Annual Review of Psychology 1997;48:649–84. [168] Sarter M, Hasselmo ME, Bruno JP, Givens B. Unraveling the attentional functions of cortical cholinergic inputs: interactions between signal-driven and

A.P. Weible / Behavioural Brain Research 245 (2013) 63–75 cognitive modulation of signal detection. Brain Research Brain Research Reviews 2005;48(1):98–111. [169] Lamour Y, Dutar P, Jobert A. Cortical projections of the nucleus of the diagonal band of Broca and of the substantia innominata in the rat: an anatomical study using the anterograde transport of a conjugate of wheat germ agglutinin and horseradish peroxidase. Neuroscience 1984;12(2):395–408.

75

[170] Room P, Groenewegen HJ. Connections of the parahippocampal cortex. I. Cortical afferents. Journal of Comparative Neurology 1986;251(4): 415–50. [171] Witter MP, Groenewegen HJ. Connections of the parahippocampal cortex in the cat. III. Cortical and thalamic efferents. Journal of Comparative Neurology 1986;252(1):1–31.