Morgan Barense is an Associate Professor in the Department of Psychology at the University of Toronto. Rogers is an associate professor in the Department of Psychology at the University of Wisconsin-Madison.
Introduction
Theoretical Concepts That are Difficult to Measure Behaviorally, e.g., Retrieval States
Another example is the study by Ranganath and Paller (1999), who examined event-related potentials (ERPs) locked to the onset of correctly rejected, new (unstudied) items in a recognition memory test. For example, Donaldson and colleagues (2001) showed condition-related activity associated with blocks of a recognition memory task (relative to blocks of a fixation task) in bilateral frontal opercular areas.
Supplementing Behavioral Dissociations with Neuroimaging Dissociations, e.g., Dual‐Process Theories
This method is called "state trace analysis" and was developed in the psychological literature by Bamber (1979). While this finding overturns previous claims that a single dimension of memory strength can explain neuroimaging data in the medial temporal lobe during recognition.
Inferring Memory Processes Directly from Local Brain Activity (Reverse Inference)
The nature of the mapping between brain measurement and cognitive process is, of course, at the heart of cognitive neuroscience. Generally speaking, the implication of this Bayesian formulation is that although activity in a particular brain area is highly likely to occur with a specific function—for example, a cognitive process reliably activates that area—this is not very informative if the same area is also activated in many other situations where that function is not involved.
Anatomical and Functional Scale, High‐Resolution fMRI, and Contact with Animal Models
This debate then returns to the persistent issue of cognitive theory, that is, the ontology of basic cognitive processes and their involvement in specific tasks. Pattern separation refers to the ability to orthogonalize similar input patterns (e.g., to separate two episodes that occurred in similar contexts), whereas pattern completion refers to the ability to group different input patterns together (e.g., to separate the details of a given episodic memory to complete only a partial indication).
Multivariate Pattern Analysis: Processes Versus Representations?
They presented participants with a series of images, with some images being the same as previous images in the series, or similar but not identical. This approach provides an interesting potential way to test the computational models of the MTL described in the previous section (e.g., in terms of pattern separation and completion).
Functional and Effective Connectivity in Memory, e.g., within MTL
Instead, DCM analysis showed that subsequent R ratings were associated with increased effective connectivity to the hippocampus from the superior temporal gyrus – an area that showed the usual reduction in activity for primed words compared to unprimed words. Given that much communication between brain regions during memory encoding and retrieval is likely to occur on the scale of tenths of a second, methods for testing effective connectivity will theoretically be more illuminating when applied to MEG/EEG data than to fMRI data. in connectivity over such fast time scales will be invisible to fMRI.
Closing the Loop: Inferring Causality from Neuroimaging Data
Regardless of whether this explanation is correct, the more important question for present purposes is that some reasons for successful memory encoding may be found in the functional coupling between areas, rather than in local activity within those areas. For example, intracranial EEG data acquired directly from the medial temporal lobes of patients undergoing surgery have shown transient increases in coupling between the hippocampus and perirhinal cortex in the gamma frequency band (around 40 Hz) associated with successful memory encoding (Fell et al., 2001).
Conclusion
What is normally meant by the claim that neuroimaging data are only correlative is that they cannot tell us about the causal role of a brain region in a cognitive process in the same way that lesion data can. In The Cognitive Neuroscience of Memory: Episodic Encoding and Retrieval (ed. E. L. Wilding, A. E. Parker, and T. J. Bussey).
Activation and Information in the Interpretation of Physiological Signals
An obvious next step would be a direct test of the assumption that increased delay period activity carries trial-specific stimulus information. However, after the onset of the first retrocue, classifier evidence for the two memory items differed.
Implications of MVPA for ROI‐Based Analyses
The most important finding of the Lewis-Peacock et al. 2013) studies is that UMIs are not maintained in an active state. It also reinforces the idea that sustained activity need not be the neural basis for the STR of information (LaRocque et al., 2013; Lewis‐Peacock and Postle, 2012; Stokes and Duncan, 2014).
Limitations and Outstanding Questions
More recently, it has been suggested that there are load-dependent changes in “contralateral latency”. This means that this information does not appear to be transferred into the sustained activity of individual neurons.
Acknowledgments
Implicit memory manifests through restricted behaviors during indirect testing. As described above, indirect memory tests have been almost exclusively used
Moreover, the influence of implicit memory on these tests is often quite trivial: a small increase or decrease in response time, the slight feeling of preference for a previously seen stimulus, or a small bias to complete a word fragment with one possible ending above another. . Limitation: Almost all tests used to measure implicit memory use limited scores such as those mentioned above as dependent measures.
Implicit memory concerns only familiar stimuli having pre‐existing memory representations. Implicit memory is almost always studied using words and
Limitation: This has led most accounts of implicit memory to ignore other types of stimuli, and therefore it is commonly thought that implicit memory can only concern a limited range of stimulus categories. Limitation: Implicit memory has not been routinely tested at delays comparable to those used in many long-term memory studies, and therefore implicit memory is often considered a very short-lived phenomenon.
Implicit memory involves processing by only those brain regions that are not involved in explicit memory. The many dissociations between neural correlates of
Implicit memory concerns a wide range of Behaviors measured in a variety of tasks
Indeed, in a subsequent event-related potential (ERP) study (Voss and Paller, 2009), the neural correlates of highly accurate G responses based on implicit memory were distinct from the neural correlates of explicit memory signaled by responses R and K. This indicates that implicit memory is operative and capable of driving behavior even during tests of direct memory such as recognition that are generally accepted as pure tests of explicit memory.
Implicit memory can occur during recollection Involving Long‐term semantic memory
Voss, Baym, and Paller (2008) reasoned that if implicit memory supported accurate responses during a recognition memory test, these would be especially measurable when subjects did not report R or K (i.e., when explicit memory was not driving the recognition memory test). the answer). Although RWI itself has traditionally been attributed to familiarity-based recognition that occurs in the absence of memory, the findings of Ryals and colleagues present an intriguing possibility that RWI may be a form of unconscious recognition that can manifest outside (or simultaneously with) conscious familiarity, demonstrating again that implicit memory can occur during direct recognition tests.
Implicit memory can co‐occur with Familiarity and recollection in explicit tasks
These abilities appear to selectively associate with conceptual implicit memory during tests designed to tap, as well as tests designed to measure explicit memory. In many circumstances, especially when it comes to common words and nameable images, familiarity and conceptual implicit memory are correlated.
Implicit memory concerns many stimulus categories, Including Novel objects and words
In a subsequent study, Voss, Schendan, and Paller (2010) found further evidence that the FN400 is associated with conceptual implicit memory for significant geometric shapes (“swirls”). Taken together, this research suggests that conceptual implicit memory processing is widespread across tests designed to measure familiarity and recollection; is so widespread that its neural correlates have been misattributed to those we know.
Implicit memory is not Necessarily short‐Lived
Although the neural effects of conceptual semantic priming have received some attention using standard priming paradigms (e.g., Heath et al., 2012; Rissman, Eliassen, & Blumstein, 2003), it will be important to examine the role of to investigate implicit processes in explicit memory tests that use a multitude of stimulus types to understand the extent to which similar neural processes are involved in priming, regardless of stimulus format.
Implicit memory is supported by a variety of Brain regions, even those that are strongly Linked to explicit memory
Indeed, some recent evidence indicates that memory-based cognitive control may depend on interactions between the hippocampus and PFC, but may occur without conscious awareness. Overall, these findings indicate that implicit memory is not well dissociated from explicit memory in terms of the neuroanatomy responsible and may be supported by all structures relevant to memory (see also Chapter 18).
Another brain region thought to be primarily associated with explicit recollection is the prefrontal cortex (PFC), which through its interaction with the hippocampus is thought to build explicit recollection memory (e.g., Kirwan, Wixted, & Squire, 2008; see also Chapter 7). Neural correlates of conceptual implicit memory and their contamination of putative neural correlates of explicit memory.
Contemporary support for the Golden Age hypothesis
After reading such a sentence, participants viewed the property name (e.g., “wings”) and had to decide whether the property was true of the item named in the sentence (e.g., duck). Judgment speed and accuracy varied according to the spatial configuration and relationships implied by the sentence.
The broader Architecture of the Cortical semantic network
Visually guided reaching and grasping deficits appear to be associated with damage to more dorsal regions, while loss of object-associated action knowledge is best predicted by pathology in the left inferior parietal lobe. The stimulus is encoded in a visual representation of shape, which in turn causes an activation pattern in the hub.
A Critical Appraisal and Comparison of the Three views
Indeed, this pattern provides part of the evidence supporting the view that a left-lateralized verbal semantic system exists (Mesulam et al., 2003). Given these null results and the many potential confounding factors in the extant literature, the importance of category specificity for theories of the gross architecture of the semantic network remains unclear.
Conclusions and open questions
Ventral and inferolateral aspects of the anterior temporal lobe are critical for semantic memory: Evidence from a new direct comparison of distortion-corrected fMRI, rTMS, and semantic dementia. What brain lesion locus tells us about the nature of cognitive impairment underlying the category of specific disorders: a review.
Theoretical framework
Retrieval occurs when this representation is reactivated, which in turn leads to the restoration of the pattern of cortical activity encoded in the representation. 3 The framework outlined in Figure 5.1 implies that retrieval consists of little more than "re-enacting" the processing involved in the original experience.
Empirical findings Encoding
Crucially, modality-selective subsequent memory effects were evident in a subset of the same regions (Figure 5.3). Top panel: subsequent memory effects (relative to correctly recognized study words for which no contextual feature could be accurately recalled) associated with accurate memory for the location (left) and color (right) of the study word.
Concluding Comments
A comparison of the neural correlates of recall performance in tests of recall and recognition memory. Dissociation of neural correlates of recognition memory according to familiarity, memory, and amount of information retrieved.
What is High Resolution When it Comes to Human MTL Imaging?
By increasing the spatial resolution in the coronal plane, these methods maximize the ability to identify anatomical landmarks (Amaral and Insausti, 1990; Duvernoy, 1998; Insausti et al., 1998; Pruessner et al., that distinguish boundaries between MTL subregions. brain of In recent years, several advances have been made in inter-participant registration techniques (Avants et al., 2011; Ekstrom et al., 2009; Yassa and Stark, 2009) that allow reliable voxel-wise group-level analyses.
Anatomically Derived Theories of MTL Subregional Function
For example, information about recovered memories due to completion of the CA3 pattern would reach the subiculum via CA1; via back projections to PRC and PHC (Figure 6.2, black arrows), the subiculum could then facilitate the recovery of the content-specific neocortical patterns active during initial learning. In each of the following sections, we review how hr-fMRI has informed these influential theories of MTL subregional function, beginning with empirical work on content representation in the human MTL.
Empirical Evidence for Content‐Based Dissociations between Human MTL Subregions
New insights into content representation in the MTL have emerged from the application of multivariate pattern information analyzes to hr-fMRI data. Recent hr-fMRI studies indexing connectivity within the MTL circuit provide converging evidence for functional differences along the anterior-posterior hippocampal axis, particularly in CA1 and the subiculum (Libby et al., 2012).
Differentiation of Function between Hippocampal Subfields
In contrast, responses in CA1 and subiculum were associated with success effects at the time of retrieval (Eldridge et al., 2005; In another study, participants studied three-dimensional room layouts prior to hr-fMRI scanning (Duncan et al., 2012).
Limitations and Future Directions for High‐Resolution fMRI of Human MTL
Concluding Remarks
Selective and shared contributions of the hippocampus and perirhinal cortex to episodic element and associative encoding. A quantitative evaluation of cross-participant registration techniques for MR studies of the medial temporal lobe.
Venterolateral PFC and the two‐Process model
Thus, similar to the anterior vlPFC, the mid‐vlPFC often shows increased activation under conditions that require controlled retrieval ( Badre et al., 2005 ; Wagner et al., 2001 ). In accordance with this prediction, Badre et al. 2005 ) directly contrasted the number of available retrieval cues against associative strength and produced activation in anterior vlPFC but not mid-vlPFC.
Separable Functional Frontal networks
The ventral controlled retrieval network includes the anterior vlPFC (aVLPFC), the anterior temporal cortex (aTC), the anterior parahippocampal gyrus (aPHG) and the hippocampus (HPC), while the dorsal frontoparietal postretrieval control network includes the dorsolateral PFC (DLPFC) and the inferior parietal lobes (IPS). . In addition to connecting with the ventral feedback pathway, the anterior vlPFC also correlated with the middle vlPFC and the dorsal frontoparietal postretrieval control network (Figure 7.4).
Semantic processing in the left inferior prefrontal cortex: a combined functional magnetic resonance imaging and transcranial magnetic stimulation study. Comparative cytoarchitectonic analysis of human and macaque ventrolateral prefrontal cortex and corticocortical connectivity patterns in the monkey.
False memory paradigms
False memories occur when participants believe that a presented word was accompanied by a visual representation, when in fact the participant had been asked to imagine the item. False memories occur when the misinformation is retrieved instead (eg remembering a yield sign instead of a stop sign).
Neuroimaging of False memories
Fabiani and colleagues (2000) also saw differential activity across posterior electrode sites for true compared with false memories. Another region that has been shown to distinguish between true and false memories is the medial temporal lobe (MTL).
Conclusions and Future directions
True and false memories in healthy older adults and Alzheimer's-type dementia. Imaging the reconstruction of true and false memories using sensory reactivation and misinformation paradigms.
Recognition memory and the medial temporal lobes
Differences in lesion extent and documentation, patient selection, and general memory impairment have been suggested to account for the findings in patients in whom these impairments were not selective (for discussion, see Bowles et al., 2010; Holdstock et al., 2008 ). In fact, neuropsychological research has only recently revealed that judgment of familiarity can be selectively impaired following systemic (Cohn, Moscovitch, & Davidson, 2010; . Davidson et al., 2006) or focal brain lesions in the temporal or frontal cortex. (Aly et al., 2011; Bowles et al., 2007; Martin et al., 2011).
Déjà vu: some basic considerations
In the present chapter, we will review promising new research that speaks to our understanding of the cognitive and neural mechanisms that support familiarity-based recognition, focusing specifically on the phenomenon of déjà vu. Despite these limitations, promising new research has begun to shed light on both déjà vu and related feelings of familiarity.
Crucially, the authors found that old scenes that had been incorrectly labeled as 'new' were more likely to induce feelings of déjà vu than new scenes that were similar in form to those presented during the study and were correctly regarded as unfamiliar. Furthermore, accurately rated novel scenes that were configurationally similar to studied scenes were more likely to induce feelings of déjà vu than accurately rated novel, configurationally different scenes.
Déjà vu in temporal lobe epilepsy
In contrast, only 2.2% of the stimulations of the amygdala and 2.1% of the anterior HC produced déjà vu. We will return to this point after reviewing research on behavioral correlates of the presence of déjà vu in TLE.
The selective deficits observed in these patients contrasted with the broader pattern of recognition memory impairments in the TLE patient group. Specifically, these individuals exhibited deficits that affected both memory and cognition in the R/K paradigm; it also affected the ability to challenge familiarity in the cued-by-recall task.
