Functional magnetic resonance imaging activity during the gradual acquisition and expression of paired-associate memory

Cortical and Subcortical Mechanisms of Orthographic Word-form Learning

We examined the initial stages of orthographic learning in real time as literate adults learned spellings for spoken pseudowords during fMRI scanning. Participants were required to learn and store orthographic word forms because the pseudoword spellings were not uniquely predictable from sound to letter mappings. With eight learning trials per word form, we observed changes in the brain's response as learning was taking place. Accuracy was evaluated during learning, immediately after scanning, and 1 week later. We found evidence of two distinct learning systems-hippocampal and neocortical-operating during orthographic learning, consistent with the predictions of dual systems theories of learning/memory such as the complementary learning systems framework [McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. 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, 102, 419-457, 1995]. The bilateral hippocampus and the visual word form area (VWFA) showed significant BOLD response changes over learning, with the former exhibiting a rising pattern and the latter exhibiting a falling pattern. Moreover, greater BOLD signal increase in the hippocampus was associated with better postscan recall. In addition, we identified two distinct bilateral brain networks that mirrored the rising and falling patterns of the hippocampus and VWFA. Functional connectivity analysis revealed that regions within each network were internally synchronized. These novel findings highlight, for the first time, the relevance of multiple learning systems in orthographic learning and provide a paradigm that can be used to address critical gaps in our understanding of the neural bases of orthographic learning in general and orthographic word-form learning specifically.

Electrocortical correlates of attention differentiate individual capacity in associative learning

Associative learning abilities vary considerably among individuals, with attentional processes suggested to play a role in these variations. However, the relationship between attentional processes and individual differences in associative learning remains unclear, and whether these variations reflect in event-related potentials (ERPs) is unknown. This study aimed to investigate the relationship between attentional processes and associative learning by recording electrocortical activity of 38 young adults (18-32 years) during an associative learning task. Learning performance was assessed using the signal detection index d'. EEG topographic analyses and source localizations were applied to examine the neural correlates of attention and associative learning. Results revealed that better learning scores are associated with (1) topographic differences during early (126-148 ms) processing of the stimulus, coinciding with a P1 ERP component, which corresponded to a participation of the precuneus (BA 7), (2) topographic differences at 573-638 ms, overlapping with an increase of global field power at 530-600 ms, coinciding with a P3b ERP component and localized within the superior frontal gyrus (BA11) and (3) an increase of global field power at 322-507 ms, underlay by a stronger participation of the middle occipital gyrus (BA 19). These insights into the neural mechanisms underlying individual differences in associative learning suggest that better learners engage attentional processes more efficiently than weaker learners, making more resources available and displaying increased functional activity in areas involved in early attentional processes (BA7) and decision-making processes (BA11) during an associative learning task. This highlights the crucial role of attentional mechanisms in individual learning variability.

Neuropsychology of epilepsy surgery and theory-based practice: an opinion review

The present review attempts to discuss how some of the central concepts from the Lurian corpus of theories are relevant to the modern neuropsychology of epilepsy and epilepsy surgery. Through the lenses of the main Lurian concepts (such as the qualitative syndrome analysis), we discuss the barriers to clinical reasoning imposed by quadrant-based views of the brain, or even atheoretical, statistically-based and data-driven approaches. We further advice towards a systemic view inspired by Luria's clinical work and theorizing, given their importance towards our clinical practice, by contrasting it to the modular views when appropriate. Luria provided theory-guided methods of assessment and rehabilitation of higher cortical functions. Although his work did not specifically address epilepsy, his theory and clinical approaches actually apply to the whole neuropathology spectrum and accounting for the whole panorama of neurocognition. This holistic and systemic approach to the brain is consistent with the network approach of the neuroimaging era. As to epilepsy, the logic of cognitive functions organized into complex functional systems, contrary to modular views of the brain, heralds current knowledge of epilepsy as a network disease, as well as the concept of the functional deficit zone.

Is formal scoring better than just looking? A comparison of subjective and objective scoring methods of the Rey Complex Figure Test for lateralizing temporal lobe epilepsy

ObjectiveNeuropsychologists labor over scoring the Rey Complex Figure Test (RCFT), a measure of visuospatial functioning and nonverbal memory. Compelling arguments suggest that pathognomonic signs of the RCFT are observable to the "naked eye." Standard scoring systems are insensitive to lateralizing temporal lobe epilepsy (TLE) and alternative "qualitative" scoring systems are ineffective and time-consuming. Method: We examined accuracy of TLE lateralization using subjective classifications and standard scoring. Participants were 84 TLE patients (53 female; mean age₌36yrs) and 46 controls (27 female; mean age = 27.5). The former were classified as right (n = 41) or left (n = 43) TLE by neurologists using EEG and MRI studies. RCFT were scored using standard scoring with cut-offs of z ≤ -2 classified as impaired and were rated as "characteristic" of RTLE (Ugly) or LTLE (Not Ugly) performance by neuropsychologists. Accuracy of seizure lateralization for both methods was examined. Results: Neuropsychologists' ratings accuracy were at or below chance. Standard scoring criteria showed chance or slightly better lateralization prediction. Standard scoring predicted RTLE laterality more accurately than subjective ratings for copy trials; standard scoring was no better at lateralizing RTLE with delays. Subjective ratings were better at distinguishing TLE patients from controls. Conclusion: Findings highlight concerns regarding the usefulness of the RCFT in TLE lateralization, regardless of scoring approach.

Trial-by-trial predictions of subjective time from human brain activity

Human experience of time exhibits systematic, context-dependent deviations from clock time; for example, time is experienced differently at work than on holiday. Here we test the proposal that differences from clock time in subjective experience of time arise because time estimates are constructed by accumulating the same quantity that guides perception: salient events. Healthy human participants watched naturalistic, silent videos of up to 24 seconds in duration and estimated their duration while fMRI was acquired. We were able to reconstruct trial-by-trial biases in participants’ duration reports, which reflect subjective experience of duration, purely from salient events in their visual cortex BOLD activity. By contrast, salient events in neither of two control regions–auditory and somatosensory cortex–were predictive of duration biases. These results held despite being able to (trivially) predict clock time from all three brain areas. Our results reveal that the information arising during perceptual processing of a dynamic environment provides a sufficient basis for reconstructing human subjective time duration.

Our perception of time isn’t like a clock; it varies depending on other aspects of experience, such as what we see and hear in that moment. Previous studies have shown that differences in simple features, such as an image being larger or smaller, or brighter or dimmer, can change how we perceive time for those experiences. But in everyday life, the properties of these simple features can change frequently, presenting a challenge to understanding real-world time perception based on simple lab experiments. To overcome this problem, we developed a computational model of human time perception based on tracking changes in neural activity across brain regions involved in sensory processing (using non-invasive brain imaging). By measuring changes in brain activity patterns across these regions, our approach accommodates the different and changing feature combinations present in natural scenarios, such as walking on a busy street. Our model reproduces people’s duration reports for natural videos (up to almost half a minute long) and, most importantly, predicts whether a person reports a scene as relatively shorter or longer–the biases in time perception that reflect how natural experience of time deviates from clock time.

Ocular measures during associative learning predict recall accuracy

The ability to form associations between stimuli and commit those associations to memory is a cornerstone of human cognition. Dopamine and noradrenaline are critical neuromodulators implicated in a range of cognitive functions, including learning and memory. Eye blink rate (EBR) and pupil diameter have been shown to index dopaminergic and noradrenergic activity. Here, we examined how these ocular measures relate to accuracy in a paired-associate learning task where participants (N = 73) learned consistent object-location associations over eight trials consisting of pre-trial fixation, encoding, delay, and retrieval epochs. In order to examine how within-subject changes and between-subject changes in ocular metrics related to accuracy, we mean centered individual metric values on each trial based on within-person and across-subject means for each epoch. Within-participant variation in EBR was positively related to accuracy in both encoding and delay epochs: faster EBR within the individual predicted better retrieval. Differences in EBR across participants was negatively related to accuracy in the encoding epoch and in early trials of the pre-trial fixation: faster EBR, relative to other subjects, predicted poorer retrieval. Visual scanning behavior in pre-trial fixation and delay epochs was also positively related to accuracy in early trials: more scanning predicted better retrieval. We found no relationship between pupil diameter and accuracy. These results provide novel evidence supporting the utility of ocular metrics in illuminating cognitive and neurobiological mechanisms of paired-associate learning.

Neural Mechanisms of Observational Learning: A Neural Working Model

Humans and some animal species are able to learn stimulus-response (S-R) associations by observing others' behavior. It saves energy and time and avoids the danger of trying the wrong actions. Observational learning (OL) depends on the capability of mapping the actions of others into our own behaviors, processing outcomes, and combining this knowledge to serve our goals. Observational learning plays a central role in the learning of social skills, cultural knowledge, and tool use. Thus, it is one of the fundamental processes in which infants learn about and from adults (Byrne and Russon, 1998). In this paper, we review current methodological approaches employed in observational learning research. We highlight the important role of the prefrontal cortex and cognitive flexibility to support this learning process, develop a new neural working model of observational learning, illustrate how imitation relates to observational learning, and provide directions for future research.

Computational support, not primacy, distinguishes compensatory memory reorganization in epilepsy

Temporal lobe epilepsy is associated with impairment in episodic memory. A substantial subgroup, however, is able to maintain adequate memory despite temporal lobe pathology. Missing from prior work in cognitive reorganization is a direct comparison of temporal lobe epilepsy patients with intact status with those who are memory impaired. Little is known about the regional activations, functional connectivities and/or network reconfigurations that implement changes in primary computations or support functions that drive adaptive plasticity and compensated memory. We utilized task functional MRI on 54 unilateral temporal lobe epilepsy patients and 24 matched healthy controls during the performance of a paired-associate memory task to address three questions: (i) which regions implement paired-associate memory in temporal lobe epilepsy, and do they vary as a function of good versus poor performance, (ii) is there unique functional connectivity present during memory encoding that accounts for intact status by preservation of primary memory computations or the supportive computations that allow for intact memory responses and (iii) what features during memory encoding are most distinctive: is it the magnitude and location of regional activations, or the presence of enhanced functional connections to key structures such as the hippocampus? The study revealed non-dominant hemisphere regions (right posterior temporal regions) involving both increased regional activity and increased modulatory communication with the hippocampi as most important to intact memory in left temporal lobe epilepsy compared to impaired status. The profile involved areas that are neither contralateral homologues to left hemisphere memory areas, nor regions traditionally considered computationally primary for episodic memory. None of these areas of increased activation or functional connectivity were associated with advantaged memory in healthy controls. Our emphasis on different performance levels yielded insight into two forms of cognitive reorganization: computational primacy, where left temporal lobe epilepsy showed little change relative to healthy controls, and computational support where intact left temporal lobe epilepsy patients showed adaptive abnormalities. The analyses isolated the unique regional activations and mediating functional connectivity that implements truly compensatory reorganization in left temporal lobe epilepsy. The results provided a new perspective on memory deficits by making clear that they arise not just from the knockout of a functional hub, but from the failure to instantiate a complex set of reorganization responses. Such responses provided the computational support to ensure successful memory. We demonstrated that by keeping track of performance levels, we can increase understanding of adaptive brain responses and neuroplasticity in epilepsy.

Distinct Neural Circuits Underlie Prospective and Concurrent Memory-Guided Behavior

The past is the best predictor of the future. This simple postulate belies the complex neurobiological mechanisms that facilitate an individual's use of memory to guide decisions. Previous research has shown integration of memories bias decision-making. Alternatively, memories can prospectively guide our choices. Here, we elucidate the mechanisms and timing of hippocampal (HPC), medial prefrontal cortex (mPFC), and striatal contributions during prospective memory-guided decision-making. We develop an associative learning task in which the correct choice is conditional on the preceding stimulus. Two distinct networks emerge: (1) a prospective circuit consisting of the HPC, putamen, mPFC, and other cortical regions, which exhibit increased activation preceding successful conditional decisions and (2) a concurrent circuit comprising the caudate, dorsolateral prefrontal cortex (dlPFC), and additional cortical structures that engage during the execution of correct conditional choices. Our findings demonstrate distinct neurobiological circuits through which memory prospectively biases decisions and influences choice execution.

A Systematic Review of Human Neuroimaging Evidence of Memory-Related Functional Alterations Associated with Cannabis Use Complemented with Preclinical and Human Evidence of Memory Performance Alterations

Cannabis has been associated with deficits in memory performance. However, the neural correlates that may underpin impairments remain unclear. We carried out a systematic review of functional magnetic resonance imaging (fMRI) studies investigating brain functional alterations in cannabis users (CU) compared to nonusing controls while performing memory tasks, complemented with focused narrative reviews of relevant preclinical and human studies. Twelve studies employing fMRI were identified finding functional brain activation during memory tasks altered in CU. Memory performance studies showed CU performed worse particularly during verbal memory tasks. Longitudinal studies suggest that cannabis use may have a causal role in memory deficits. Preclinical studies have not provided conclusive evidence of memory deficits following cannabinoid exposure, although they have shown evidence of cannabinoid-induced structural and histological alteration. Memory performance deficits may be related to cannabis use, with lower performance possibly underpinned by altered functional activation. Memory impairments may be associated with the level of cannabis exposure and use of cannabis during developmentally sensitive periods, with possible improvement following cessation of cannabis use.

Probing cortical and sub-cortical contributions to instruction-based learning: Regional specialisation and global network dynamics

Diverse cortical networks and striatal brain regions are implicated in instruction-based learning (IBL); however, their distinct contributions remain unclear. We use a modified fMRI paradigm to test two hypotheses regarding the brain mechanisms that underlie IBL. One hypothesis proposes that anterior caudate and frontoparietal regions transiently co-activate when new rules are being bound in working memory. The other proposes that they mediate the application of the rules at different stages of the consolidation process. In accordance with the former hypothesis, we report strong activation peaks within and increased connectivity between anterior caudate and frontoparietal regions when rule-instruction slides are presented. However, similar effects occur throughout a broader set of cortical and sub-cortical regions, indicating a metabolically costly reconfiguration of the global brain state. The distinct functional roles of cingulo-opercular, frontoparietal and default-mode networks are apparent from their activation throughout, early and late in the practice phase respectively. Furthermore, there is tentative evidence of a peak in anterior caudate activity mid-way through the practice stage. These results demonstrate how performance of the same simple task involves a steadily shifting balance of brain systems as learning progresses. They also highlight the importance of distinguishing between regional specialisation and global dynamics when studying the network mechanisms that underlie cognition and learning.

Modulation of associative learning in the hippocampal-striatal circuit based on item-set similarity

Mounting evidence suggests that the medial temporal lobe (MTL) and striatal learning systems support different forms of learning, which can be competitive or cooperative depending on task demands. We have previously shown how activity in these regions can be modulated in a conditional visuomotor associative learning task based on the consistency of response mappings or reward feedback (Mattfeld & Stark, 2015). Here, we examined the shift in learning towards the MTL and away from the striatum by placing strong demands on pattern separation, a process of orthogonalizing similar inputs into distinct representations. Mnemonically, pattern separation processes have been shown to rely heavily on processing in the hippocampus. Therefore, we predicted modulation of hippocampal activity by pattern separation demands, but no such modulation of striatal activity. Using a variant of the conditional visuomotor associative learning task that we have used previously, we presented participants with two blocked conditions: items with high and low perceptual overlap during functional magnetic resonance imaging (fMRI). As predicted, we observed learning-related activity in the hippocampus, which was greater in the high than the low overlap condition, particularly in the dentate gyrus. In contrast, the associative striatum also showed learning related activity, but it was not modulated by overlap condition. Using functional connectivity analyses, we showed that the correlation between the hippocampus and dentate gyrus with the associative striatum was differentially modulated by high vs. low overlap, suggesting that the coordination between these regions was affected when pattern separation demands were high. These findings contribute to a growing literature that suggests that the hippocampus and striatal network both contribute to the learning of arbitrary associations that are computationally distinct and can be altered by task demands.

Dynamics of error-related activity in deterministic learning - an EEG and fMRI study

There is a close relationship between progress in learning and the error-monitoring system. EEG and fMRI studies using probabilistic learning have revealed the distinct dynamics of this system after response and feedback, i.e. an increase of error-related and a decrease of feedback-related activity in the anterior cingulate cortex (ACC). Based on the existing theories, it can be presumed that during deterministic learning feedback-related activity in ACC would also increase. Since these assumptions have not yet been confirmed, it can be only speculated based on the data from the probabilistic paradigms how the information is being integrated within the ACC during deterministic learning. Here we implemented the Paired Associate Deterministic Learning task to the EEG and fMRI experiments. The analysis of EEG data showed a significant increase in the amplitude for both ERN and FN. Similarly, the fMRI results showed an increase in response-related and feedback-related activity of the ACC in erroneous trials. Our findings are in line with the current theories of ACC function: increasing ACC activity can be linked to the detected discrepancy between expected and obtained outcomes. We argue that expectancy violations in the course of deterministic learning are signalled by both, internal and external evaluation system.

Neural oscillations during conditional associative learning

Associative learning requires mapping between complex stimuli and behavioural responses. When multiple stimuli are involved, conditional associative learning is a gradual process with learning based on trial and error. It is established that a distributed network of regions track associative learning, however the role of neural oscillations in human learning remains less clear. Here we used scalp EEG to test how neural oscillations change during learning of arbitrary visuo-motor associations. Participants learned to associative 48 different abstract shapes to one of four button responses through trial and error over repetitions of the shapes. To quantify how well the associations were learned for each trial, we used a state-space computational model of learning that provided a probability of each trial being correct given past performance for that stimulus, that we take as a measure of the strength of the association. We used linear modelling to relate single-trial neural oscillations to single-trial measures of association strength. We found frontal midline theta oscillations during the delay period tracked learning, where theta activity was strongest during the early stages of learning and declined as the associations were formed. Further, posterior alpha and low-beta oscillations in the cue period showed strong desynchronised activity early in learning, while stronger alpha activity during the delay period was seen as associations became well learned. Moreover, the magnitude of these effects during early learning, before the associations were learned, related to improvements in memory seen on the next presentation of the stimulus. The current study provides clear evidence that frontal theta and posterior alpha/beta oscillations play a key role during associative memory formation.

Dynamic functional connectivity shapes individual differences in associative learning

Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc.

Interacting networks of brain regions underlie human spatial navigation: a review and novel synthesis of the literature

Navigation is an inherently dynamic and multimodal process, making isolation of the unique cognitive components underlying it challenging. The assumptions of much of the literature on human spatial navigation are that 1) spatial navigation involves modality independent, discrete metric representations (i.e., egocentric vs. allocentric), 2) such representations can be further distilled to elemental cognitive processes, and 3) these cognitive processes can be ascribed to unique brain regions. We argue that modality-independent spatial representations, instead of providing exact metrics about our surrounding environment, more often involve heuristics for estimating spatial topology useful to the current task at hand. We also argue that egocentric (body centered) and allocentric (world centered) representations are better conceptualized as involving a continuum rather than as discrete. We propose a neural model to accommodate these ideas, arguing that such representations also involve a continuum of network interactions centered on retrosplenial and posterior parietal cortex, respectively. Our model thus helps explain both behavioral and neural findings otherwise difficult to account for with classic models of spatial navigation and memory, providing a testable framework for novel experiments.

Predictions Shape Confidence in Right Inferior Frontal Gyrus

It is clear that prior expectations shape perceptual decision-making, yet their contribution to the construction of subjective decision confidence remains largely unexplored. We recorded fMRI data while participants made perceptual decisions and confidence judgments, manipulating perceptual prior expectations while controlling for potential confounds of attention. Results show that subjective confidence increases as expectations increasingly support the decision, and that this relationship is associated with BOLD activity in right inferior frontal gyrus (rIFG). Specifically, rIFG is sensitive to the discrepancy between expectation and decision (mismatch), and higher mismatch responses are associated with lower decision confidence. Connectivity analyses revealed expectancy information to be represented in bilateral orbitofrontal cortex and sensory signals to be represented in intracalcarine sulcus. Together, our results indicate that predictive information is integrated into subjective confidence in rIFG, and reveal an occipital-frontal network that constructs confidence from top-down and bottom-up signals. This interpretation was further supported by exploratory findings that the white matter density of right orbitofrontal cortex negatively predicted its respective contribution to the construction of confidence. Our findings advance our understanding of the neural basis of subjective perceptual processes by revealing an occipitofrontal functional network that integrates prior beliefs into the construction of confidence.

SIGNIFICANCE STATEMENT

Perceptual decision-making is typically conceived as an integration of bottom-up and top-down influences. However, perceptual decisions are accompanied by a sense of confidence. Confidence is an important facet of perceptual consciousness yet remains poorly understood. Here we implicate right inferior frontal gyrus in constructing confidence from the discrepancy between perceptual judgment and its prior probability. Furthermore, we place right inferior frontal gyrus within an occipitofrontal network, consisting of orbitofrontal cortex and intracalcarine sulcus, which represents and communicates relevant top-down and bottom-up signals. Together, our data reveal a role of frontal regions in the top-down processes enabling perceptual decisions to become available for conscious report.

The influence of low-level stimulus features on the representation of contexts, items, and their mnemonic associations

Since the earliest attempts to characterize the "receptive fields" of neurons, a central aim of many neuroscience experiments is to elucidate the information that is represented in various regions of the brain. Recent studies suggest that, in the service of memory, information is represented in the medial temporal lobe in a conjunctive or associative form with the contextual aspects of the experience being the primary factor or highest level of the conjunctive hierarchy. A critical question is whether the information that has been observed in these studies reflects notions such as a cognitive representation of context or whether the information reflects the low-level sensory differences between stimuli. We performed two functional magnetic resonance imaging experiments to address this question and we found that associative representations observed between context and item (and order) in the human brain can be highly influenced by low-level sensory differences between stimuli. Our results place clear constraints on the experimental design of studies that aim to investigate the representation of contexts and items during performance of associative memory tasks. Moreover, our results raise interesting theoretical questions regarding the disambiguation of memory-related representations from processing-related representations.

Potential implications of Luria's work for the neuropsychology of epilepsy and epilepsy surgery: A perspective for re-examination

The pioneeristic work of Alexander Romanovic Luria into the field of human neuropsychology offered eminent contributions to clinical praxis by providing theory guided methods and instruments for the study of higher cortical functions. However, lots of this knowledge corpus either remains untranslated and thus inaccessible, or in some cases selectively overlooked by academic authorities and consequently not passed to the future generations of experts. Although Luria was not exclusively devoted to the study of epilepsy, his theories and clinical approaches actually penetrate the whole neuropathology spectrum. His holistic and systemic approach to the brain sounds nowadays more than opportune and consistent with the network approach of the modern neuroimaging era. As to epilepsy, the logic underlying the Lurian approach (cognitive functions organized into complex functional systems with intra- and/or inter-hemispheric distribution, as opposed to the modularistic view of the brain) seems consistent with our current knowledge in epileptology with respect to epileptic networks, as well as the modern construct of the functional deficit zone. These contributions seem to be highly promising for the neuropsychology of epilepsy and epilepsy surgery, since they provide clinicians with valuable methods and theories to assist them in the localization -and lateralization- of cognitive deficits. Consequently they are of great applicability in the context of the preoperative neuropsychological monitoring of patients candidates for epilepsy surgery, where neuropsychologist are called upon to provide surgeons with anatomical data.

Scene-selective coding by single neurons in the human parahippocampal cortex

Imaging, electrophysiological, and lesion studies have shown a relationship between the parahippocampal cortex (PHC) and the processing of spatial scenes. Our present knowledge of PHC, however, is restricted to the macroscopic properties and dynamics of bulk tissue; the behavior and selectivity of single parahippocampal neurons remains largely unknown. In this study, we analyzed responses from 630 parahippocampal neurons in 24 neurosurgical patients during visual stimulus presentation. We found a spatially clustered subpopulation of scene-selective units with an associated event-related field potential. These units form a population code that is more distributed for scenes than for other stimulus categories, and less sparse than elsewhere in the medial temporal lobe. Our electrophysiological findings provide insight into how individual units give rise to the population response observed with functional imaging in the parahippocampal place area.

Brain regions that show repetition suppression and enhancement: A meta-analysis of 137 neuroimaging experiments

Repetition suppression and enhancement refer to the reduction and increase in the neural responses for repeated rather than novel stimuli, respectively. This study provides a meta-analysis of the effects of repetition suppression and enhancement, restricting the data used to that involving fMRI/PET, visual stimulus presentation, and healthy participants. The major findings were as follows. First, the global topography of the repetition suppression effects was strikingly similar to that of the "subsequent memory" effects, indicating that the mechanism for repetition suppression is the reduced engagement of an encoding system. The lateral frontal cortex effects involved the frontoparietal control network regions anteriorly and the dorsal attention network regions posteriorly. The left fusiform cortex effects predominantly involved the dorsal attention network regions, whereas the right fusiform cortex effects mainly involved the visual network regions. Second, the category-specific meta-analyses and their comparisons indicated that most parts of the alleged category-specific regions showed repetition suppression for more than one stimulus category. In this regard, these regions may not be "dedicated cortical modules," but are more likely parts of multiple overlapping large-scale maps of simple features. Finally, the global topography of the repetition enhancement effects was similar to that of the "retrieval success" effects, suggesting that the mechanism for repetition enhancement is voluntary or involuntary explicit retrieval during an implicit memory task. Taken together, these results clarify the network affiliations of the regions showing reliable repetition suppression and enhancement effects and contribute to the theoretical interpretations of the local and global topography of these two effects. Hum Brain Mapp 38:1894-1913, 2017. © 2017 Wiley Periodicals, Inc.

Retinal thinning is uniquely associated with medial temporal lobe atrophy in neurologically normal older adults

Given the converging pathologic and epidemiologic data indicating a relationship between retinal integrity and neurodegeneration, including Alzheimer's disease (AD), we aimed to determine if retinal structure correlates with medial temporal lobe (MTL) structure and function in neurologically normal older adults. Spectral-domain optical coherence tomography, verbal and visual memory testing, and 3T-magnetic resonance imaging of the brain were performed in 79 neurologically normal adults enrolled in a healthy aging cohort study. Retinal nerve fiber thinning and reduced total macular and macular ganglion cell volumes were each associated with smaller MTL volumes (ps < 0.04). Notably, these markers of retinal structure were not associated with primary motor cortex or basal ganglia volumes (regions relatively unaffected in AD) (ps > 0.70), or frontal, precuneus, or temporoparietal volumes (regions affected in later AD Braak staging ps > 0.20). Retinal structure was not significantly associated with verbal or visual memory consolidation performances (ps > 0.14). Retinal structure was associated with MTL volumes, but not memory performances, in otherwise neurologically normal older adults. Given that MTL atrophy is a neuropathological hallmark of AD, retinal integrity may be an early marker of ongoing AD-related brain health.

Rapid Encoding of New Memories by Individual Neurons in the Human Brain

The creation of memories about real-life episodes requires rapid neuronal changes that may appear after a single occurrence of an event. How is such demand met by neurons in the medial temporal lobe (MTL), which plays a fundamental role in episodic memory formation? We recorded the activity of MTL neurons in neurosurgical patients while they learned new associations. Pairs of unrelated pictures, one of a person and another of a place, were used to construct a meaningful association modeling the episodic memory of meeting a person in a particular place. We found that a large proportion of responsive MTL neurons expanded their selectivity to encode these specific associations within a few trials: cells initially responsive to one picture started firing to the associated one but not to others. Our results provide a plausible neural substrate for the inception of associations, which are crucial for the formation of episodic memories.

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Contextual associations were used to model the formation of new memories

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Human single neurons changed their firing patterns to encode new associations

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Changes occurred at the exact moment of learning, even after single presentations

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The rapid speed of neural changes is compatible with episodic memory formation

Distributed representation of visual objects by single neurons in the human brain

It remains unclear how single neurons in the human brain represent whole-object visual stimuli. While recordings in both human and nonhuman primates have shown distributed representations of objects (many neurons encoding multiple objects), recordings of single neurons in the human medial temporal lobe, taken as subjects' discriminated objects during multiple presentations, have shown gnostic representations (single neurons encoding one object). Because some studies suggest that repeated viewing may enhance neural selectivity for objects, we had human subjects discriminate objects in a single, more naturalistic viewing session. We found that, across 432 well isolated neurons recorded in the hippocampus and amygdala, the average fraction of objects encoded was 26%. We also found that more neurons encoded several objects versus only one object in the hippocampus (28 vs 18%, p < 0.001) and in the amygdala (30 vs 19%, p < 0.001). Thus, during realistic viewing experiences, typical neurons in the human medial temporal lobe code for a considerable range of objects, across multiple semantic categories.

Glucose, relational memory, and the hippocampus

RATIONALE

Many studies suggest that glucose can temporarily enhance hippocampal-dependent memories. As the hippocampus plays a key role in associative learning, we examined the influence of glucose on verbal paired associate memory.

OBJECTIVE

This study examines how glucose modifies performance on a relational memory task by examining its influence on learning, subsequent forgetting and relearning.

METHODS

A selective reminding procedure was used to show high and low imagability paired associates to 80 participants, who were seen twice. On the first session, they received 25 g glucose pre-learning, 25 g glucose post-learning or placebo. On the second session, 1 week later, they received 25 g glucose or placebo. Cued-recall was evaluated after each learning trial, 1 week later to assess forgetting and after an opportunity to relearn the material forgotten.

RESULTS

Glucose did not influence paired associate acquisition. Those given glucose pre-learning tended to forget less material the following week, and independently, glucose at retrieval facilitated cued-recall. Both forms of facilitation were equally apparent on low and high imagability pairs. The benefit of glucose pre-learning was eliminated once the paired associates had been seen again, but the benefit of glucose at retrieval extended into the second relearning trial.

CONCLUSIONS

The discussion considers the cognitive processes and hippocampal basis for paired associate learning and retention and the implications for glucose's mode of action. It is proposed that glucose during encoding serves to make the delayed memories initially more available, whereas its influence during delayed retrieval makes available memories temporarily more accessible.

Neural activity in the medial temporal lobe reveals the fidelity of mental time travel

Neural circuitry in the medial temporal lobe (MTL) is critically involved in mental time travel, which involves the vivid retrieval of the details of past experience. Neuroscientific theories propose that the MTL supports memory of the past by retrieving previously encoded episodic information, as well as by reactivating a temporal code specifying the position of a particular event within an episode. However, the neural computations supporting these abilities are underspecified. To test hypotheses regarding the computational mechanisms supported by different MTL subregions during mental time travel, we developed a computational model that linked a blood oxygenation level-dependent signal to cognitive operations, allowing us to predict human performance in a memory search task. Activity in the posterior MTL, including parahippocampal cortex, reflected how strongly one reactivates the temporal context of a retrieved memory, allowing the model to predict whether the next memory will correspond to a nearby moment in the study episode. A signal in the anterior MTL, including perirhinal cortex, indicated the successful retrieval of list items, without providing information regarding temporal organization. A hippocampal signal reflected both processes, consistent with theories that this region binds item and context information together to form episodic memories. These findings provide evidence for modern theories that describe complementary roles of the hippocampus and surrounding parahippocampal and perirhinal cortices during the retrieval of episodic memories, shaping how humans revisit the past.

Theta variation and spatiotemporal scaling along the septotemporal axis of the hippocampus

Hippocampal theta has been related to locomotor speed, attention, anxiety, sensorimotor integration and memory among other emergent phenomena. One difficulty in understanding the function of theta is that the hippocampus (HPC) modulates voluntary behavior at the same time that it processes sensory input. Both functions are correlated with characteristic changes in theta indices. The current review highlights a series of studies examining theta local field potential (LFP) signals across the septotemporal or longitudinal axis of the HPC. While the theta signal is coherent throughout the entirety of the HPC, the amplitude, but not the frequency, of theta varies significantly across its three-dimensional expanse. We suggest that the theta signal offers a rich vein of information about how distributed neuronal ensembles support emergent function. Further, we speculate that emergent function across the long axis varies with respect to spatiotemporal scale. Thus, septal HPC processes details of the proximal spatiotemporal environment while more temporal aspects process larger spaces and wider time-scales. The degree to which emergent functions are supported by the synchronization of theta across the septotemporal axis is an open question. Our working model is that theta synchrony serves to bind ensembles representing varying resolutions of spatiotemporal information at interdependent septotemporal areas of the HPC. Such synchrony and cooperative interactions along the septotemporal axis likely support memory formation and subsequent consolidation and retrieval.

Functional contributions and interactions between the human hippocampus and subregions of the striatum during arbitrary associative learning and memory

The hippocampus and striatum are thought to have different functional roles in learning and memory. It is unknown under what experimental conditions their contributions are dissimilar or converge, and the extent to which they interact over the course of learning. In order to evaluate both the functional contributions of as well as the interactions between the human hippocampus and striatum, the present study used high-resolution functional magnetic resonance imaging (fMRI) and variations of a conditional visuomotor associative learning task that either taxed arbitrary associative learning (Experiment 1) or stimulus-response learning (Experiment 2). In the first experiment, we observed changes in activity in the hippocampus and anterior caudate that reflect differences between the two regions consistent with distinct computational principles. In the second experiment, we observed activity in the putamen that reflected content specific representations during the learning of arbitrary conditional visuomotor associations. In both experiments, the hippocampus and ventral striatum demonstrated dynamic functional coupling during the learning of new arbitrary associations, but not during retrieval of well-learned arbitrary associations using control variants of the tasks that did not preferentially tax one system versus the other. These findings suggest that both the hippocampus and subregions of the dorsal striatum contribute uniquely to the learning of arbitrary associations while the hippocampus and ventral striatum interact over the course of learning.

The effects of exposure to dynamic expressions of affect on 5-month-olds' memory

The purpose of this study was to examine the behavioral effects of adults' communicated affect on 5-month-olds' visual recognition memory. Five-month-olds were exposed to a dynamic and bimodal happy, angry, or neutral affective (face-voice) expression while familiarized to a novel geometric image. After familiarization to the geometric image and exposure to the affective expression, 5-month-olds received either a 5-min or 1-day retention interval. Following the 5-min retention interval, infants exposed to the happy affective expressions showed a reliable preference for a novel geometric image compared to the recently familiarized image. Infants exposed to the neutral or angry affective expression failed to show a reliable preference following a 5-min delay. Following the 1-day retention interval, however, infants exposed to the neutral expression showed a reliable preference for the novel geometric image. These results are the first to demonstrate that 5-month-olds' visual recognition memory is affected by the presentation of affective information at the time of encoding.

Multivariate pattern analysis of the human medial temporal lobe revealed representationally categorical cortex and representationally agnostic hippocampus

Contemporary theories of the medial temporal lobe (MTL) suggest that there are functional differences between the MTL cortex and the hippocampus. High-resolution functional magnetic resonance imaging and multivariate pattern analysis were utilized to study whether MTL subregions could classify categories of images, with the hypothesis that the hippocampus would be less representationally categorical than the MTL cortex. Results revealed significant classification accuracy for faces versus objects and faces versus scenes in MTL cortical regions-parahippocampal cortex (PHC) and perirhinal cortex (PRC)-with little evidence for category discrimination in the hippocampus. MTL cortical regions showed significantly greater classification accuracy than the hippocampus. The hippocampus showed significant classification accuracy for images compared to a nonmnemonic baseline task, suggesting that it responded to the images. Classification accuracy in a region of interest encompassing retrosplenial cortex (RSC) and the posterior cingulate cortex (PCC) posterior to RSC, showed a similar pattern of results to PHC, supporting the hypothesis that these regions are functionally related. The results suggest that PHC, PRC, and RSC/PCC are representationally categorical and the hippocampus is more representationally agnostic, which is concordant with the hypothesis of the role of the hippocampus in pattern separation.

Theta dynamics in rat: speed and acceleration across the Septotemporal axis

Theta (6–12 Hz) rhythmicity in the local field potential (LFP) reflects a clocking mechanism that brings physically isolated neurons together in time, allowing for the integration and segregation of distributed cell assemblies. Variation in the theta signal has been linked to locomotor speed, sensorimotor integration as well as cognitive processing. Previously, we have characterized the relationship between locomotor speed and theta power and how that relationship varies across the septotemporal (long) axis of the hippocampus (HPC). The current study investigated the relationship between whole body acceleration, deceleration and theta indices at CA1 and dentate gyrus (DG) sites along the septotemporal axis of the HPC in rats. Results indicate that whole body acceleration and deceleration predicts a significant amount of variability in the theta signal beyond variation in locomotor speed. Furthermore, deceleration was more predictive of variation in theta amplitude as compared to acceleration as rats traversed a linear track. Such findings highlight key variables that systematically predict the variability in the theta signal across the long axis of the HPC. A better understanding of the relative contribution of these quantifiable variables and their variation as a function of experience and environmental conditions should facilitate our understanding of the relationship between theta and sensorimotor/cognitive functions.

Distractibility during retrieval of long-term memory: domain-general interference, neural networks and increased susceptibility in normal aging

The mere presence of irrelevant external stimuli results in interference with the fidelity of details retrieved from long-term memory (LTM). Recent studies suggest that distractibility during LTM retrieval occurs when the focus of resource-limited, top-down mechanisms that guide the selection of relevant mnemonic details is disrupted by representations of external distractors. We review findings from four studies that reveal distractibility during episodic retrieval. The approach cued participants to recall previously studied visual details when their eyes were closed, or were open and irrelevant visual information was present. The results showed a negative impact of the distractors on the fidelity of details retrieved from LTM. An fMRI experiment using the same paradigm replicated the behavioral results and found that diminished episodic memory was associated with the disruption of functional connectivity in whole-brain networks. Specifically, network connectivity supported recollection of details based on visual imagery when eyes were closed, but connectivity declined in the presence of visual distractors. Another experiment using auditory distractors found equivalent effects for auditory and visual distraction during cued recall, suggesting that the negative impact of distractibility is a domain-general phenomenon in LTM. Comparisons between older and younger adults revealed an aging-related increase in the negative impact of distractibility on retrieval of LTM. Finally, a new study that compared categorization abilities between younger and older adults suggests a cause underlying age-related decline of visual details in LTM. The sum of our findings suggests that cognitive control resources, although limited, have the capability to resolve interference from distractors during tasks of moderate effort, but these resources are overwhelmed when additional processes associated with episodic retrieval, or categorization of complex prototypes, are required.

Vicarious neural processing of outcomes during observational learning

Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on the ability to map the actions of others onto our own, process outcomes, and combine these sources of information. Here, we combined newly developed experimental tasks and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms that govern such observational learning. Results show that the neural systems involved in individual trial-and-error learning and in action observation and execution both participate in observational learning. In addition, we identified brain areas that specifically activate for others’ incorrect outcomes during learning in the posterior medial frontal cortex (pMFC), the anterior insula and the posterior superior temporal sulcus (pSTS).

A critical evaluation of the lateralizing significance of material-specific memory deficits in patients with mesial temporal lobe epilepsy with hippocampal sclerosis

To critically assess the value of material-specific memory deficits in lateralizing temporal lobe dysfunction preoperatively, we compared the neuropsychological data of 50 consecutive patients with unilateral mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS; right: 31, left: 19) with those of 50 age- and education-matched healthy control subjects. On case-control comparison, both the subcohorts with left and right MTLE-HS performed poorly on intelligence tests, in addition to individual memory tests. However, comparison of the verbal and visual memory functions between subcohorts with right and left MTLE-HS revealed that learning trials and delayed word list recall were the only tests that hypothesized left temporal lobe dysfunction. We conclude that material-specific memory deficits are largely test driven, but there is a lateralizing role for task-specific deficits in left MTLE-HS. Although neuropsychological data help to define baseline neuropsychological impairment, caution should be exercised in interpreting the lateralizing value of material-specific memory deficits prior to surgery.

Network dysfunction during associative learning in schizophrenia: Increased activation, but decreased connectivity: an fMRI study

Schizophrenia (SCZ) is characterized by disordered activation and disordered connectivity, yet few fMRI studies have convergently investigated both. Here, we compared differences in activation and connectivity between SCZ and controls (HC). Twenty-two subjects (18≤age≤35yrs) participated in a paired-associative learning task, a behavioral domain particularly dependent on fronto-hippocampal connectivity and of relevance to the schizophrenia diathesis. Activation differences were assessed using standard approaches. Seed-based connectivity differences were compared using Psychophysiological Interaction (PPI) with a hippocampus-based seed. SCZ evinced significantly increased activation, but significantly decreased connectivity with the hippocampus across a cortical-striatal learning network. These results assess potentially complementary patterns of network dysfunction in schizophrenia: increased activation suggests inefficient responses relating to functional specialization; decreased connectivity suggests impaired integration of functional signals between regions. Inefficiency and dysconnection appear to collectively characterize functional deficits in schizophrenia.

Oscillatory correlates of memory in non-human primates

The ability to navigate through our environment, explore with our senses, track the passage of time, and integrate these various components to form the experiences which make up our lives is shared among humans and animals. The use of animal models to study memory, coupled with electrophysiological techniques that permit the direct measurement of neural activity as memories are formed and retrieved, has provided a wealth of knowledge about these mechanisms. Here, we discuss current knowledge regarding the specific role of neural oscillations in memory, with particular emphasis on findings derived from non-human primates. Some of these findings provide evidence for the existence in the primate brain of mechanisms previously identified only in rodents and other lower mammals, while other findings suggest parallels between memory-related activity and processes observed in other cognitive modalities, including attention and sensory perception. Taken together, these results provide insight into how network activity may be organized to promote memory formation, and suggest that key aspects of this activity are similar across species, providing important information about the organization of human memory.

Novel space alters theta and gamma synchrony across the longitudinal axis of the hippocampus

Hippocampal theta (6–10 Hz) and gamma (25–50 Hz and 65–100 Hz) local field potentials (LFPs) reflect the dynamic synchronization evoked by inputs impinging upon hippocampal neurons. Novel experience is known to engage hippocampal physiology and promote successful encoding. Does novelty synchronize or desynchronize theta and/or gamma frequency inputs across the septotemporal (long) axis of the hippocampus (HPC)? The present study tested the hypothesis that a novel spatial environment would alter theta power and coherence across the long axis. We compared theta and gamma LFP signals at individual (power) and millimeter distant electrode pairs (coherence) within the dentate gyrus (DG) and CA1 region while rats navigated a runway (1) in a familiar environment, (2) with a modified path in the same environment and (3) in a novel space. Locomotion in novel space was related to increases in theta and gamma power at most CA1 and DG sites. The increase in theta and gamma power was concurrent with an increase in theta and gamma coherence across the long axis of CA1; however, there was a significant decrease in theta coherence across the long axis of the DG. These findings illustrate significant shifts in the synchrony of entorhinal, CA3 and/or neuromodulatory afferents conveying novel spatial information to the dendritic fields of CA1 and DG targets across the long axis of the HPC. This shift suggests that the entire theta/gamma-related input to the CA1 network, and likely output, receives and conveys a more coherent message in response to novel sensory experience. Such may contribute to the successful encoding of novel sensory experience.

Procedural learning of unstructured categories

Unstructured categories are those in which the stimuli are assigned to each contrasting category randomly, and thus there is no rule- or similarity-based strategy for determining category membership. Intuition suggests that unstructured categories are likely to be learned via explicit memorization that is under the control of declarative memory. In contrast to this prediction, neuroimaging studies of unstructured-category learning have reported task-related activation in the striatum, but typically not in the hippocampus--results that seem more consistent with procedural learning than with a declarative-memory strategy. This article reports the first known behavioral test of whether unstructured-category learning is mediated by explicit strategies or by procedural learning. Our results suggest that the feedback-based learning of unstructured categories is mediated by procedural memory.

Dissociating hippocampal and striatal contributions to sequential prediction learning

Behavior may be generated on the basis of many different kinds of learned contingencies. For instance, responses could be guided by the direct association between a stimulus and response, or by sequential stimulus-stimulus relationships (as in model-based reinforcement learning or goal-directed actions). However, the neural architecture underlying sequential predictive learning is not well understood, in part because it is difficult to isolate its effect on choice behavior. To track such learning more directly, we examined reaction times (RTs) in a probabilistic sequential picture identification task in healthy individuals. We used computational learning models to isolate trial-by-trial effects of two distinct learning processes in behavior, and used these as signatures to analyse the separate neural substrates of each process. RTs were best explained via the combination of two delta rule learning processes with different learning rates. To examine neural manifestations of these learning processes, we used functional magnetic resonance imaging to seek correlates of time-series related to expectancy or surprise. We observed such correlates in two regions, hippocampus and striatum. By estimating the learning rates best explaining each signal, we verified that they were uniquely associated with one of the two distinct processes identified behaviorally. These differential correlates suggest that complementary anticipatory functions drive each region's effect on behavior. Our results provide novel insights as to the quantitative computational distinctions between medial temporal and basal ganglia learning networks and enable experiments that exploit trial-by-trial measurement of the unique contributions of both hippocampus and striatum to response behavior.

Advanced Parkinson's disease effect on goal-directed and habitual processes involved in visuomotor associative learning

The present behavioral study re-addresses the question of habit learning in Parkinson's disease (PD). Patients were early onset, non-demented, dopa-responsive, candidates for surgical treatment, similar to those we found earlier as suffering greater dopamine depletion in the putamen than in the caudate nucleus. The task was the same conditional associative learning task as that used previously in monkeys and healthy humans to unveil the striatum involvement in habit learning. Sixteen patients and 20 age- and education-matched healthy control subjects learned sets of 3 visuo-motor associations between complex patterns and joystick displacements during two testing sessions separated by a few hours. We distinguished errors preceding vs. following the first correct response to compare patients' performance during the earliest phase of learning dominated by goal-directed actions with that observed later on, when responses start to become habitual. The disease significantly retarded both learning phases, especially in patients under 60 years of age. However, only the late phase deficit was disease severity-dependent and persisted on the second testing session. These findings provide the first corroboration in Parkinson patients of two ideas well-established in the animal literature. The first is the idea that associating visual stimuli to motor acts is a form of habit learning that engages the striatum. It is confirmed here by the global impairment in visuo-motor learning induced by PD. The second idea is that goal-directed behaviors are predominantly caudate-dependent whereas habitual responses are primarily putamen-dependent. At the advanced PD stages tested here, dopamine depletion is greater in the putamen than in the caudate nucleus. Accordingly, the late phase of learning corresponding to the emergence of habitual responses was more vulnerable to the disease than the early phase dominated by goal-directed actions.

Information content and reward processing in the human striatum during performance of a declarative memory task

Negative feedback can signal poor performance, but it also provides information that can help learners reach the goal of task mastery. The primary aim of this study was to test the hypothesis that the amount of information provided by negative feedback during a paired-associate learning task influences feedback-related processing in the caudate nucleus. To do this, we manipulated the number of response options: With two options, positive and negative feedback provide equal amounts of information, whereas with four options, positive feedback provides more information than does negative feedback. We found that positive and negative feedback activated the caudate similarly when there were two response options. With four options, the caudate’s response to negative feedback was reduced. A secondary goal was to investigate the link between brain-based measures of feedback-related processing and behavioral indices of learning. Analysis of the posttest measures showed that trials with positive feedback were associated with higher posttest confidence ratings. Additionally, when positive feedback was delivered, caudate activity was greater for trials with high than with low posttest confidence. This experiment demonstrated the context sensitivity of feedback processing and provided evidence that feedback processing in the striatum can contribute to the strengthening of the representations available within declarative memory.

Conserved fMRI and LFP signals during new associative learning in the human and macaque monkey medial temporal lobe

We measured local field potential (LFP) and blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in the medial temporal lobes of monkeys and humans, respectively, as they performed the same conditional motor associative learning task. Parallel analyses were used to examine both data sets. Despite significantly faster learning in humans relative to monkeys, we found equivalent neural signals differentiating new versus highly familiar stimuli, first stimulus presentation, trial outcome, and learning strength in the entorhinal cortex and hippocampus of both species. Thus, the use of parallel behavioral tasks and analyses in monkeys and humans revealed conserved patterns of neural activity across the medial temporal lobe during an associative learning task.

Effects of ecstasy/polydrug use on memory for associative information

RATIONALE

Associative learning underpins behaviours that are fundamental to the everyday functioning of the individual. Evidence pointing to learning deficits in recreational drug users merits further examination.

OBJECTIVES

A word pair learning task was administered to examine associative learning processes in ecstasy/polydrug users.

METHODS

After assignment to either single or divided attention conditions, 44 ecstasy/polydrug users and 48 non-users were presented with 80 word pairs at encoding. Following this, four types of stimuli were presented at the recognition phase: the words as originally paired (old pairs), previously presented words in different pairings (conjunction pairs), old words paired with new words, and pairs of new words (not presented previously). The task was to identify which of the stimuli were intact old pairs.

RESULTS

Ecstasy/ploydrug users produced significantly more false-positive responses overall compared to non-users. Increased long-term frequency of ecstasy use was positively associated with the propensity to produce false-positive responses. It was also associated with a more liberal signal detection theory decision criterion value. Measures of long term and recent cannabis use were also associated with these same word pair learning outcome measures. Conjunction word pairs, irrespective of drug use, generated the highest level of false-positive responses and significantly more false-positive responses were made in the divided attention condition compared to the single attention condition.

CONCLUSIONS

Overall, the results suggest that long-term ecstasy exposure may induce a deficit in associative learning and this may be in part a consequence of users adopting a more liberal decision criterion value.

Frontostriatal mechanisms in instruction-based learning as a hallmark of flexible goal-directed behavior

The present review intends to provide a neuroscientific perspective on the flexible (here: almost instantaneous) adoption of novel goal-directed behaviors. The overarching goal is to sketch the emerging framework for examining instruction-based learning and how this can be related to more established research approaches to instrumental learning and goal-directed action. We particularly focus on the contribution of frontal and striatal brain regions drawing on studies in both, animals and humans, but with an emphasize put on human neuroimaging studies. In section one, we review and integrate a selection of previous studies that are suited to generally delineate the neural underpinnings of goal-directed action as opposed to more stimulus-based (i.e., habitual) action. Building on that the second section focuses more directly on the flexibility to rapidly implement novel behavioral rules as a hallmark of goal-directed action with a special emphasis on instructed rules. In essence, the current neuroscientific evidence suggests that the prefrontal cortex and associative striatum are able to selectively and transiently code the currently relevant relationship between stimuli, actions, and the effects of these actions in both, instruction-based learning as well as in trial-and-error learning. The premotor cortex in turn seems to form more durable associations between stimuli and actions or stimuli, actions and effects (but not incentive values) thus representing the available action possibilities. Together, the central message of the present review is that instruction-based learning should be understood as a prime example of goal-directed action, necessitating a closer interlacing with basic mechanisms of goal-directed action on a more general level.