This study examined the effect of unitization and contribution of familiarity in the recognition of word pairs. Compound words were presented as word pairs and were contrasted with noncompound word pairs in an associative recognition task. In Experiments 1 and 2, yes-no recognition hit and false-alarm rates were significantly higher for compound than for noncompound word pairs, with no difference in discrimination in both within- and between-subject comparisons. Experiment 2 also showed that item recognition was reduced for words from compound compared to noncompound word pairs, providing evidence of the unitization of the compound pairs. A two-alternative forced-choice test used in Experiments 3A and 3B provided evidence that the concordant effect for compound word pairs was largely due to familiarity. A discrimination advantage for compound word pairs was also seen in these experiments. Experiment 4A showed that a different pattern of results is seen when repeated noncompound word pairs are compared to compound word pairs. Experiment 4B showed that memory for the individual items of compound word pairs was impaired relative to items in repeated and nonrepeated noncompound word pairs, and Experiment 5 demonstrated that this effect is eliminated when the elements of compound word pairs are not unitized. The concordant pattern seen in yes-no recognition and the discrimination advantage in forced-choice recognition for compound relative to noncompound word pairs is due to greater reliance on familiarity at test when pairs are unitized.

In normal aging, memory for associations declines more than memory for individual items. Unitization is an encoding process defined by creation of a new single entity to represent a new arbitrary association. The current study tested the hypothesis that age-related differences in associative memory can be reduced by encoding instructions that promote unitization. In two experiments, groups of 20 young and 20 older participants learned new associations between a word and a background color under two conditions. In the item detail condition, they had to imagine that the item is the same color as the background-an instruction promoting unitization of the associations. In the context detail condition, which did not promote unitization, they had to imagine that the item interacted with another colored object. At test, they had to retrieve the color that was associated with each word (source memory). In both experiments, the results showed an age-related decrement in source memory performance in the context detail but not in the item detail condition. Moreover, Experiment 2 examined receiver operating characteristics in older participants and indicated that familiarity contributed more to source memory performance in the item detail than in the context detail condition. These findings suggest that unitization of new associations can overcome the associative memory deficit observed in aging, at least for item-color associations.

Traditional memory research has focused on identifying separate memory systems and exploring different stages of memory processing. This approach has been valuable for establishing a taxonomy of memory systems and characterizing their function but has been less informative about the nature of stored memory representations. Recent research on visual memory has shifted toward a representation-based emphasis, focusing on the contents of memory and attempting to determine the format and structure of remembered information. The main thesis of this review will be that one cannot fully understand memory systems or memory processes without also determining the nature of memory representations. Nowhere is this connection more obvious than in research that attempts to measure the capacity of visual memory. We will review research on the capacity of visual working memory and visual long-term memory, highlighting recent work that emphasizes the contents of memory. This focus impacts not only how we estimate the capacity of the system--going beyond quantifying how many items can be remembered and moving toward structured representations--but how we model memory systems and memory processes.

Visual long-term memory can store thousands of objects with surprising visual detail, but just how detailed are these representations, and how can one quantify this fidelity? Using the property of color as a case study, we estimated the precision of visual information in long-term memory, and compared this with the precision of the same information in working memory. Observers were shown real-world objects in random colors and were asked to recall the colors after a delay. We quantified two parameters of performance: the variability of internal representations of color (fidelity) and the probability of forgetting an object's color altogether. Surprisingly, the fidelity of color information in long-term memory was comparable to the asymptotic precision of working memory. These results suggest that long-term memory and working memory may be constrained by a common limit, such as a bound on the fidelity required to retrieve a memory representation.

A model of memory retrieval is described. The model embodies 4 main claims: (a) temporal memory--traces of items are represented in memory partly in terms of their temporal distance from the present; (b) scale-similarity--similar mechanisms govern retrieval from memory over many different timescales; (c) local distinctiveness--performance on a range of memory tasks is determined by interference from near psychological neighbors; and (d) interference-based forgetting--all memory loss is due to interference and not trace decay. The model is applied to data on free recall and serial recall. The account emphasizes qualitative similarity in the retrieval principles involved in memory performance at all timescales, contrary to models that emphasize distinctions between short-term and long-term memory.

Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. However, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide variety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity limits will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recording of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity-limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed.

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

Experiences unfold over time, but little is known about the mechanisms that support the formation of coherent episodic memories for temporally extended events. Recent work in animals has provided evidence for signals in hippocampus that could link events across temporal gaps; however, it is unknown whether and how such signals might be related to later memory for temporal information in humans. We measured patterns of fMRI BOLD activity as people encoded items that were separated in time and manipulated the presence of shared or distinct context across items. We found that hippocampal pattern similarity in the BOLD response across trials predicted later temporal memory decisions when context changed. By contrast, pattern similarity in lateral occipital cortex was related to memory only when context remained stable. These data provide evidence in humans that representational stability in hippocampus across time may be a mechanism for temporal memory organization.

Contralateral delay activity (CDA) has long been argued to track the number of items stored in visual working memory (WM). Recently, however, Berggren and Eimer [Berggren, N., & Eimer, M. Does contralateral delay activity reflect working memory storage or the current focus of spatial attention within visual working memory? Journal of Cognitive Neuroscience, 28, 2003-2020, 2016] proposed the alternative hypothesis that the CDA tracks the current focus of spatial attention instead of WM storage. This hypothesis was based on the finding that, when two successive arrays of memoranda were placed in opposite hemifields, CDA amplitude was primarily determined by the position and number of items in the second display, not the total memory load across both displays. Here, we considered the alternative interpretation that participants dropped the first array from WM when they encoded the second array because the format of the probe display was spatially incompatible with the initial sample display. In this case, even if the CDA indexes active storage rather than spatial attention, CDA activity would be determined by the second array. We tested this idea by directly manipulating the spatial compatibility of sample and probe displays. With spatially incompatible displays, we replicated Berggren and Eimer's findings. However, with spatially compatible displays, we found clear evidence that CDA activity tracked the full storage load across both arrays, in line with a WM storage account of CDA activity. We propose that expectations of display compatibility influenced whether participants viewed the arrays as parts of a single extended event or two independent episodes. Thus, these findings raise interesting new questions about how event boundaries may shape the interplay between passive and active representations of task-relevant information.

Human memory is thought to consist of long-term storage and short-term storage mechanisms, the latter known as working memory. Although it has long been assumed that information retrieved from long-term memory is represented in working memory, we lack neural evidence for this and need neural measures that allow us to watch this retrieval into working memory unfold with high temporal resolution. Here, we show that human electrophysiology can be used to track information as it is brought back into working memory during retrieval from long-term memory. Specifically, we found that the retrieval of information from long-term memory was limited to just a few simple objects' worth of information at once, and elicited a pattern of neurophysiological activity similar to that observed when people encode new information into working memory. Our findings suggest that working memory is where information is buffered when being retrieved from long-term memory and reconcile current theories of memory retrieval with classic notions about the memory mechanisms involved.

Using two exclusion tasks, the present study examined how the ERP correlates of face recognition are affected by the nature of the information to be retrieved. Intrinsic (facial expression) and extrinsic (background scene) visual information were paired with face identity and constituted the exclusion criterion at test time. Although perceptual information had to be taken into account in both situations, the FN400 old-new effect was observed only for old target faces on the expression-exclusion task, whereas it was found for both old target and old non-target faces in the background-exclusion situation. These results reveal that the FN400, which is generally interpreted as a correlate of familiarity, was modulated by the retrieval of intra-item and intrinsic face information, but not by the retrieval of extrinsic information. The observed effects on the FN400 depended on the nature of the information to be retrieved and its relationship (unitization) to the recognition target. On the other hand, the parietal old-new effect (generally described as an ERP correlate of recollection) reflected the retrieval of both types of contextual features equivalently. The current findings are discussed in relation to recent controversies about the nature of the recognition processes reflected by the ERP correlates of face recognition.

Models of working memory (WM) commonly focus on how information is encoded into and retrieved from storage at specific moments. However, in the majority of real-life processes, past information is used continuously to process incoming information across multiple timescales. Considering single-unit, electrocorticography, and functional imaging data, we argue that (i) virtually all cortical circuits can accumulate information over time, and (ii) the timescales of accumulation vary hierarchically, from early sensory areas with short processing timescales (10s to 100s of milliseconds) to higher-order areas with long processing timescales (many seconds to minutes). In this hierarchical systems perspective, memory is not restricted to a few localized stores, but is intrinsic to information processing that unfolds throughout the brain on multiple timescales.

Early studies of memory-impaired patients with medial temporal lobe (MTL) damage led to the view that the hippocampus and related MTL structures are involved in the formation of long-term memory and that immediate memory and working memory are independent of these structures. This traditional idea has recently been revisited. Impaired performance in patients with MTL lesions on tasks with short retention intervals, or no retention interval, and neuroimaging findings with similar tasks have been interpreted to mean that the MTL is sometimes needed for working memory and possibly even for visual perception itself. We present a reappraisal of this interpretation. Our main conclusion is that, if the material to be learned exceeds working memory capacity, if the material is difficult to rehearse, or if attention is diverted, performance depends on long-term memory even when the retention interval is brief. This fundamental notion is better captured by the terms subspan memory and supraspan memory than by the terms short-term memory and long-term memory. We propose methods for determining when performance on short-delay tasks must depend on long-term (supraspan) memory and suggest that MTL lesions impair performance only when immediate memory and working memory are insufficient to support performance. In neuroimaging studies, MTL activity during encoding is influenced by the memory load and correlates positively with long-term retention of the material that was presented. The most parsimonious and consistent interpretation of all the data is that subspan memoranda are supported by immediate memory and working memory and are independent of the MTL.

Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic (EEG) interpretation and analysis when rejecting contaminated EEG segments results in an unacceptable data loss. Many methods have been proposed to remove artifacts from EEG recordings, especially those arising from eye movements and blinks. Often regression in the time or frequency domain is performed on parallel EEG and electrooculographic (EOG) recordings to derive parameters characterizing the appearance and spread of EOG artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing out eye artifacts inevitably involves subtracting relevant EEG signals from each record as well. Regression methods become even more problematic when a good regressing channel is not available for each artifact source, as in the case of muscle artifacts. Use of principal component analysis (PCA) has been proposed to remove eye artifacts from multichannel EEG. However, PCA cannot completely separate eye artifacts from brain signals, especially when they have comparable amplitudes. Here, we propose a new and generally applicable method for removing a wide variety of artifacts from EEG records based on blind source separation by independent component analysis (ICA). Our results on EEG data collected from normal and autistic subjects show that ICA can effectively detect, separate, and remove contamination from a wide variety of artifactual sources in EEG records with results comparing favorably with those obtained using regression and PCA methods. ICA can also be used to analyze blink-related brain activity.

Neural measures of working memory storage, such as the contralateral delay activity (CDA), are powerful tools in working memory research. CDA amplitude is sensitive to working memory load, reaches an asymptote at known behavioral limits, and predicts individual differences in capacity. An open question, however, is whether neural measures of load also track trial-by-trial fluctuations in performance. Here, we used a whole-report working memory task to test the relationship between CDA amplitude and working memory performance. If working memory failures are due to decision-based errors and retrieval failures, CDA amplitude would not differentiate good and poor performance trials when load is held constant. If failures arise during storage, then CDA amplitude should track both working memory load and trial-by-trial performance. As expected, CDA amplitude tracked load (Experiment 1), reaching an asymptote at three items. In Experiment 2, we tracked fluctuations in trial-by-trial performance. CDA amplitude was larger (more negative) for high-performance trials compared with low-performance trials, suggesting that fluctuations in performance were related to the successful storage of items. During working memory failures, participants oriented their attention to the correct side of the screen (lateralized P1) and maintained covert attention to the correct side during the delay period (lateralized alpha power suppression). Despite the preservation of attentional orienting, we found impairments consistent with an executive attention theory of individual differences in working memory capacity; fluctuations in executive control (indexed by pretrial frontal theta power) may be to blame for storage failures.

Forming new associations is a fundamental process of building our knowledge system. At the brain level, how prior-knowledge influences acquisition of novel associations has not been thoroughly investigated. Based on recent cognitive neuroscience literature on multiple-component memory processing, we hypothesize that prior-knowledge triggers additional evaluative, semantic, or episodic-binding processes, mainly supported by the ventromedial prefrontal cortex (vmPFC), anterior temporal pole (aTPL), and hippocampus (HPC), to facilitate new memory encoding. To test this hypothesis, we scanned 20 human participants with functional magnetic resonance imaging (fMRI) while they associated novel houses with famous or nonfamous faces. Behaviorally, we found beneficial effects of prior-knowledge on associative memory. At the brain level, we found that the vmPFC and HPC, as well as the parahippocampal place area (PPA) and fusiform face area, showed stronger activation when famous faces were involved. The vmPFC, aTPL, HPC, and PPA also exhibited stronger activation when famous faces elicited stronger emotions and memories, and when associations were later recollected. Connectivity analyses also suggested that HPC connectivity with the vmPFC plays a more important role in the famous than nonfamous condition. Taken together, our results suggest that prior-knowledge facilitates new associative encoding by recruiting additional perceptual, evaluative, or associative binding processes.

Short-term memory storage can be divided into separate subsystems for verbal information and visual information, and recent studies have begun to delineate the neural substrates of these working-memory systems. Although the verbal storage system has been well characterized, the storage capacity of visual working memory has not yet been established for simple, suprathreshold features or for conjunctions of features. Here we demonstrate that it is possible to retain information about only four colours or orientations in visual working memory at one time. However, it is also possible to retain both the colour and the orientation of four objects, indicating that visual working memory stores integrated objects rather than individual features. Indeed, objects defined by a conjunction of four features can be retained in working memory just as well as single-feature objects, allowing sixteen individual features to be retained when distributed across four objects. Thus, the capacity of visual working memory must be understood in terms of integrated objects rather than individual features, which places significant constraints on cognitive and neurobiological models of the temporary storage of visual information.

Participants memorized briefly presented sets of digits, a subset of which had to be accessed as input for arithmetic tasks (the active set), whereas another subset had to be remembered independently of the concurrent task (the passive set). Latencies for arithmetic operations were a function of the setsize of active but not passive sets. Object-switch costs were observed when successive operations were applied to different digits within an active set. Participants took 2 s to encode a passive set so that it did not affect processing latencies (Experiment 2). The results support a model distinguishing 3 states of representations in working memory: the activated part of long-term memory, a capacity limited region of direct access, and a focus of attention.

We report 4 experiments examining whether associations in visual working memory are subject to proactive interference from long-term memory (LTM). Following a long-term learning phase in which participants learned the colors of 120 unique objects, a working memory (WM) test was administered in which participants recalled the precise colors of 3 concrete objects in an array. Each array in the WM test consisted of 1 old (previously learned) object with a new color (old-mismatch), 1 old object with its old color (old-match), and 1 new object. Experiments 1 to 3 showed that WM performance was better in the old-match condition than in the new condition, reflecting a beneficial contribution from LTM. In the old-mismatch condition, participants sometimes reported colors associated with the relevant shape in LTM, but the probability of successful recall was equivalent to that in the new condition. Thus, information from LTM only intruded in the absence of reportable information in WM. Experiment 4 tested for, and failed to find, proactive interference from the preceding trial in the WM test: Performance in the old-mismatch condition, presenting an object from the preceding trial with a new color, was equal to performance with new objects. Experiment 5 showed that long-term memory for object-color associations is subject to proactive interference. We conclude that the exchange of information between LTM and WM appears to be controlled by a gating mechanism that protects the contents of WM from proactive interference but admits LTM information when it is useful. (PsycINFO Database Record

The article introduces an interference model of working memory for information in a continuous similarity space, such as the features of visual objects. The model incorporates the following assumptions: (a) Probability of retrieval is determined by the relative activation of each retrieval candidate at the time of retrieval; (b) activation comes from 3 sources in memory: cue-based retrieval using context cues, context-independent memory for relevant contents, and noise; (c) 1 memory object and its context can be held in the focus of attention, where it is represented with higher precision, and partly shielded against interference. The model was fit to data from 4 continuous-reproduction experiments testing working memory for colors or orientations. The experiments involved variations of set size, kind of context cues, precueing, and retro-cueing of the to-be-tested item. The interference model fit the data better than 2 competing models, the Slot-Averaging model and the Variable-Precision resource model. The interference model also fared well in comparison to several new models incorporating alternative theoretical assumptions. The experiments confirm 3 novel predictions of the interference model: (a) Nontargets intrude in recall to the extent that they are close to the target in context space; (b) similarity between target and nontarget features improves recall, and (c) precueing-but not retro-cueing-the target substantially reduces the set-size effect. The success of the interference model shows that working memory for continuous visual information works according to the same principles as working memory for more discrete (e.g., verbal) contents. Data and model codes are available at https://osf.io/wgqd5/. (PsycINFO Database Record

In this meta-analysis, the authors evaluated recent suggestions that older adults' episodic memory impairments are partially due to a reduced ability to encode and retrieve associated/bound units of information. Results of 90 studies of episodic memory for both item and associative information in 3,197 young and 3,192 older adults provided support for the age-related associative/binding deficit suggestion, indicating a larger effect of age on memory for associative information than for item information. Moderators assessed included the type of associations, encoding instructions, materials, and test format. Results indicated an age-related associative deficit in memory for source, context, temporal order, spatial location, and item pairings, in both verbal and nonverbal material. An age-related associative deficit was quite pronounced under intentional learning instructions but was not clearly evident under incidental learning instructions. Finally, test format was also found to moderate the associative deficit, with older adults showing an associative/binding deficit when item memory was evaluated via recognition tests but not when item memory was evaluated via recall tests, in which case the age-related deficits were similar for item and associative information.

A critical question in visual working or short-term memory (VSTM) research is whether the ability to remember briefly presented visual stimuli can be increased. Here we test whether VSTM for locations and shapes is improved by training that allows one to utilize another memory system, visual longterm memory (VLTM). Training was done by repeatedly presenting a subset of memory displays, creating long-term memory traces for these displays. Surprisingly, VSTM performance for repeated displays was not higher than for nonrepeated ones, even though participants recognized repeated displays on a forced-choice test given at the end of the experiment. We suggest that the fidelity of information held by VLTM is inferior to that of information held by VSTM and thus provides no additional benefit over what is extracted on the fly by VSTM.

A current controversy in memory research concerns whether recognition is supported by distinct processes of familiarity and recollection, or instead by a single process wherein familiarity and recollection reflect weak and strong memories, respectively. Recent studies using receiver operating characteristic (ROC) analyses in an animal model have shown that manipulations of the memory demands can eliminate the contribution of familiarity while sparing recollection. Here it is shown that a different manipulation, specifically the addition of a response deadline in recognition testing, results in the opposite performance pattern, eliminating the contribution of recollection while sparing that of familiarity. This dissociation, combined with the earlier findings, demonstrates that familiarity and recollection are differentially sensitive to specific memory demands, strongly supporting the dual process view.

There has been much interest in how the hippocampus codes time in support of episodic memory. Notably, while rodent hippocampal neurons, including populations in subfield CA1, have been shown to represent the passage of time in the order of seconds between events, there is limited support for a similar mechanism in humans. Specifically, there is no clear evidence that human hippocampal activity during long-term memory processing is sensitive to temporal duration information that spans seconds. To address this gap, we asked participants to first learn short event sequences that varied in image content and interval durations. During fMRI, participants then completed a recognition memory task, as well as a recall phase in which they were required to mentally replay each sequence in as much detail as possible. We found that individual sequences could be classified using activity patterns in the anterior hippocampus during recognition memory. Critically, successful classification was dependent on the conjunction of event content and temporal structure information (with unsuccessful classification of image content or interval duration alone), and further analyses suggested that the most informative voxels resided in the anterior CA1. Additionally, a classifier trained on anterior CA1 recognition data could successfully identify individual sequences from the mental replay data, suggesting that similar activity patterns supported participants' recognition and recall memory. Our findings complement recent rodent hippocampal research, and provide evidence that long-term sequence memory representations in the human hippocampus can reflect duration information in the order of seconds.

The influential notion that the hippocampus supports associative memory by interacting with functionally distinct and distributed brain regions has not been directly tested in humans. We therefore used targeted noninvasive electromagnetic stimulation to modulate human cortical-hippocampal networks and tested effects of this manipulation on memory. Multiple-session stimulation increased functional connectivity among distributed cortical-hippocampal network regions and concomitantly improved associative memory performance. These alterations involved localized long-term plasticity because increases were highly selective to the targeted brain regions, and enhancements of connectivity and associative memory persisted for ~24 hours after stimulation. Targeted cortical-hippocampal networks can thus be enhanced noninvasively, demonstrating their role in associative memory.

To test how preexisting long-term memory influences visual STM, this study takes advantage of individual differences in participants' prior familiarity with Pokémon characters and uses an ERP component, the contralateral delay activity (CDA), to assess whether observers' prior stimulus familiarity affects STM consolidation and storage capacity. In two change detection experiments, consolidation speed, as indexed by CDA fractional area latency and/or early-window (500-800 msec) amplitude, was significantly associated with individual differences in Pokémon familiarity. In contrast, the number of remembered Pokémon stimuli, as indexed by Cowan's K and late-window (1500-2000 msec) CDA amplitude, was significantly associated with individual differences in Pokémon familiarity when STM consolidation was incomplete because of a short presentation of Pokémon stimuli (500 msec, Experiment 2), but not when STM consolidation was allowed to complete given sufficient encoding time (1000 msec, Experiment 1). Similar findings were obtained in between-group analyses when participants were separated into high-familiarity and low-familiarity groups based on their Pokémon familiarity ratings. Together, these results suggest that stimulus familiarity, as a proxy for the strength of preexisting long-term memory, primarily speeds up STM consolidation, which may subsequently lead to an increase in the number of remembered stimuli if consolidation is incomplete. These findings thus highlight the importance of research assessing how effects on representations (e.g., STM capacity) are in general related to (or even caused by) effects on processes (e.g., STM consolidation) in cognition.

It is well accepted that recognition memory reflects the contribution of two separable memory retrieval processes, namely recollection and familiarity. However, fundamental questions remain regarding the functional nature and neural substrates of these processes. In this article, we describe a simple quantitative model of recognition memory (i.e., the dual-process signal detection model) that has been useful in integrating findings from a broad range of cognitive studies, and that is now being applied in a growing number of neuroscientific investigations of memory. The model makes several strong assumptions about the behavioral nature and neural substrates of recollection and familiarity. A review of the literature indicates that these assumptions are generally well supported, but that there are clear boundary conditions in which these assumptions break down. We argue that these findings provide important insights into the operation of the processes underlying recognition. Finally, we consider how the dual-process approach relates to recent neuroanatomical and computational models and how it might be integrated with recent findings concerning the role of medial temporal lobe regions in other cognitive functions such as novelty detection, perception, implicit memory and short-term memory.

Transitive inference (TI) is the ability to infer the relationship between items (e.g., A>C) after having learned a set of premise pairs (e.g., A>B and B>C). Previous studies in humans have identified a distributed neural network, including cortex, hippocampus, and thalamus, during TI judgments. We studied two aspects of TI using functional magnetic resonance imaging of subjects who had acquired the six-item sequence (A>B>C>D>E>F) of visual stimuli. First, the identification of novel pairs not containing end items (i.e., B>D, C>E, B>E) was associated with greater left hippocampal activation compared with the identification of novel pairs containing end items A and F. This demonstrates that the identification of stimulus pairs requiring the flexible representation of a sequence is associated with hippocampal activation. Second, for the three novel pairs devoid of end items we found greater right hippocampal activation for pairs B>D and C>E compared with pair B>E. This indicates that TI decisions on pairs derived from more adjacent items in the sequence are associated with greater hippocampal activation. Hippocampal activation thus scales with the degree of relational processing necessary for TI judgments. Both findings confirm a role of the hippocampus in transitive inference in humans.

Memory enables flexible use of past experience to inform new behaviors. Although leading theories hypothesize that this fundamental flexibility results from the formation of integrated memory networks relating multiple experiences, the neural mechanisms that support memory integration are not well understood. Here, we demonstrate that retrieval-mediated learning, whereby prior event details are reinstated during encoding of related experiences, supports participants' ability to infer relationships between distinct events that share content. Furthermore, we show that activation changes in a functionally coupled hippocampal and ventral medial prefrontal cortical circuit track the formation of integrated memories and successful inferential memory performance. These findings characterize the respective roles of these regions in retrieval-mediated learning processes that support relational memory network formation and inferential memory in the human brain. More broadly, these data reveal fundamental mechanisms through which memory representations are constructed into prospectively useful formats.