Alpha-band oscillations track the retrieval of precise spatial representations from long-term memory

Reward-based option competition in human dorsal stream and transition from stochastic exploration to exploitation in continuous space

Primates exploring and exploiting a continuous sensorimotor space rely on dynamic maps in the dorsal stream. Two complementary perspectives exist on how these maps encode rewards. Reinforcement learning models integrate rewards incrementally over time, efficiently resolving the exploration/exploitation dilemma. Working memory buffer models explain rapid plasticity of parietal maps but lack a plausible exploration/exploitation policy. The reinforcement learning model presented here unifies both accounts, enabling rapid, information-compressing map updates and efficient transition from exploration to exploitation. As predicted by our model, activity in human frontoparietal dorsal stream regions, but not in MT+, tracks the number of competing options, as preferred options are selectively maintained on the map, while spatiotemporally distant alternatives are compressed out. When valuable new options are uncovered, posterior β1/α oscillations desynchronize within 0.4 to 0.7 s, consistent with option encoding by competing β1-stabilized subpopulations. Together, outcomes matching locally cached reward representations rapidly update parietal maps, biasing choices toward often-sampled, rewarded options.

Encoded and updated spatial working memories share a common representational format in alpha activity

Working memory (WM) flexibly updates information to adapt to the dynamic environment. Here, we used alpha-band activity in the EEG to reconstruct the content of dynamic WM updates and compared this representational format to static WM content. An inverted encoding model using alpha activity precisely tracked both the initially encoded position and the updated position following an auditory cue signaling mental updating. The timing of the update, as tracked in the EEG, correlated with reaction times and saccade latency. Finally, cross-training analyses revealed a robust generalization of alpha-band reconstruction of WM contents before and after updating. These findings demonstrate that alpha activity tracks the dynamic updates to spatial WM and that the format of this activity is preserved across the encoded and updated representations. Thus, our results highlight a new approach for measuring updates to WM and show common representational formats during dynamic mental updating and static storage.

To remember or not to remember: Neural oscillations and ERPs as predictors of intentional associative fear learning

It is widely accepted that impaired safety learning to a safe stimulus is a pathological feature of anxiety disorders. Safety learning refers to learning that a stimulus is associated with the absence of threat. Cognitive mechanisms that underlie successful threat and safety learning are, however, poorly understood. This study aimed to identify various physiological markers, including neural oscillations and event-related potentials (ERPs) that predict successful threat and safety learning. Therefore, to detect potential differences in these markers, we measured EEG in a fear learning framework combined with a subsequent memory paradigm. Thirty-seven participants were asked to memorize a series of associations between faces and an aversive unconditioned stimulus (US) or its omission. We found a decrease of power in the alpha band in occipital brain regions during learning for both threatening (conditioned stimuli, CS+) and safe faces (control stimuli, CS-) that were subsequently remembered to be associated with a US or not. No effects in theta band were found. In regard to ERPs, a late positive potential (LPP) and a P300 component were larger for remembered than for forgotten CS-US associations. The P300 was also enhanced to remembered US and US omissions, thus replicating previous findings. These results point to the importance of cognitive resource allocation as an underlying mechanism of fear learning and electrophysiological measurements as potential biomarkers for successful threat and safety learning.

Spatiotemporal dynamics of self-generated imagery reveal a reverse cortical hierarchy from cue-induced imagery

Visual imagery allows for the construction of rich internal experience in our mental world. However, it has remained poorly understood how imagery experience derives volitionally as opposed to being cue driven. Here, using electroencephalography and functional magnetic resonance imaging, we systematically investigate the spatiotemporal dynamics of self-generated imagery by having participants volitionally imagining one of the orientations from a learned pool. We contrast self-generated imagery with cue-induced imagery, where participants imagined line orientations based on associative cues acquired previously. Our results reveal overlapping neural signatures of cue-induced and self-generated imagery. Yet, these neural signatures display substantially differential sensitivities to the two types of imagery: self-generated imagery is supported by an enhanced involvement of the anterior cortex in representing imagery contents. By contrast, cue-induced imagery is supported by enhanced imagery representations in the posterior visual cortex. These results jointly support a reverse cortical hierarchy in generating and maintaining imagery contents in self-generated versus externally cued imagery.

Working Memory Is Complex and Dynamic, Like Your Thoughts

Working memory is where thoughts are held and manipulated. For many years, the dominant model was that working memory relied on steady-state neural dynamics. A neural representation was activated and then held in that state. However, as often happens, the more we examine working memory (especially with new technology), the more complex it looks. Recent discoveries show that working memory involves multiple mechanisms, including discontinuous bouts of spiking. Memories are also dynamic, evolving in a task-dependent manner. Cortical rhythms may control those dynamics, thereby endowing top-down "executive" control over our thoughts.

Perception and memory have distinct spatial tuning properties in human visual cortex

Reactivation of earlier perceptual activity is thought to underlie long-term memory recall. Despite evidence for this view, it is unclear whether mnemonic activity exhibits the same tuning properties as feedforward perceptual activity. Here, we leverage population receptive field models to parameterize fMRI activity in human visual cortex during spatial memory retrieval. Though retinotopic organization is present during both perception and memory, large systematic differences in tuning are also evident. Whereas there is a three-fold decline in spatial precision from early to late visual areas during perception, this pattern is not observed during memory retrieval. This difference cannot be explained by reduced signal-to-noise or poor performance on memory trials. Instead, by simulating top-down activity in a network model of cortex, we demonstrate that this property is well explained by the hierarchical structure of the visual system. Together, modeling and empirical results suggest that computational constraints imposed by visual system architecture limit the fidelity of memory reactivation in sensory cortex.

Neural activity from perception is thought to be reactivated during memory recall. Here, the authors show that memory reactivation in visual cortex exhibits different tuning properties from those observed during perception.

Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches

Vision plays a peculiar role in intelligence. Visual information, forming a large part of the sensory information, is fed into the human brain to formulate various types of cognition and behaviours that make humans become intelligent agents. Recent advances have led to the development of brain-inspired algorithms and models for machine vision. One of the key components of these methods is the utilization of the computational principles underlying biological neurons. Additionally, advanced experimental neuroscience techniques have generated different types of neural signals that carry essential visual information. Thus, there is a high demand for mapping out functional models for reading out visual information from neural signals. Here, we briefly review recent progress on this issue with a focus on how machine learning techniques can help in the development of models for contending various types of neural signals, from fine-scale neural spikes and single-cell calcium imaging to coarse-scale electroencephalography (EEG) and functional magnetic resonance imaging recordings of brain signals.

Readiness to remember: predicting variability in episodic memory

Learning and remembering are fundamental to our lives, so what causes us to forget? Answers often highlight preparatory processes that precede learning, as well as mnemonic processes during the act of encoding or retrieval. Importantly, evidence now indicates that preparatory processes that precede retrieval attempts also have powerful influences on memory success or failure. Here, we review recent work from neuroimaging, electroencephalography, pupillometry, and behavioral science to propose an integrative framework of retrieval-period dynamics that explains variance in remembering in the moment and across individuals as a function of interactions among preparatory attention, goal coding, and mnemonic processes. Extending this approach, we consider how a 'readiness to remember' (R2R) framework explains variance in high-level functions of memory and mnemonic disruptions in aging.

Pattern reinstatement and attentional control overlap during episodic long-term memory retrieval

Episodic long-term memory (eLTM) retrieval involves the reinstatement of neural patterns from the encoding phase. However, recent evidence suggests that comparable cortical activity patterns can also be linked to attentional control processes on the level of memory representations. The current investigation assesses these two processes independently based on alpha-beta-band activity in the electroencephalogram (EEG). During encoding, subjects were presented with an object on a certain position on the screen and had to imagine it on a new position. In each trial, either the task-irrelevant presentation position or the task-relevant imagination position was lateralized. In the retrieval phase, subjects first made an old/new judgement based on centrally presented objects and then reported the imagination position. Pattern reinstatement should be reflected in similar lateralized alpha-beta activity during encoding and retrieval. Conversely, the influence of attentional control processes during retrieval would be associated with the suppression of alpha-beta power contralateral to the to-be-reported imagination position and with the increase of activity contralateral to the irrelevant presentation position. Our results support this latter pattern. This shows that an experimental differentiation between selective attention and pattern reinstatement processes is necessary when studying the neural basis of eLTM retrieval.

Alpha rhythm modulations in the intraparietal sulcus reflect decision signals during item recognition

Theoretical work and empirical observations suggest a contribution of regions along the intraparietal sulcus to the process of evidence accumulation during episodic memory retrieval. In the present study, we recorded magnetoencephalographic signals in a group of healthy human participants to test whether the pattern of oscillatory modulations in the lateral parietal lobe is consistent with the mnemonic accumulator hypothesis. To this aim, the dynamic properties and the spatial distribution of MEG oscillatory power modulations were investigated during an item recognition task in which the amount of evidence for old vs. new memory decisions was manipulated across three levels. A data-driven approach was employed to identify brain nodes where oscillatory activity was sensitive to both retrieval success and the amount of evidence for old decisions. The analysis identified three nodes in the left lateral parietal lobe where the event-related desynchronization (ERD) in the alpha frequency band showed both effects. Further analyses revealed that the alpha ERD in the intraparietal sulcus, but not in other parietal nodes: i. showed modulation of duration in response to the amount of evidence for both old and new decisions, ii. was behaviorally significant, and iii. more accurately tracked the subjective memory judgment rather than the objective memory status. The present findings provide support for a recent anatomical-functional model of the parietal involvement in episodic memory retrieval and suggest that the alpha ERD in the intraparietal sulcus might represent a neural signature of the evidence accumulation process during simple memory-based decisions.

Neural Reinstatement of Overlapping Memories in Young and Older Adults

When we update our episodic memories with new information, mnemonic competition between old and new memories may result because of the presence of shared features. Behavioral studies suggest that this competition can lead to proactive interference, resulting in unsuccessful memory updating, particularly for older adults. It is difficult with behavioral data alone to measure the reactivation of old, overlapping memories during retrieval and its impact on memory for new memories. Here, we applied encoding-retrieval representational similarity (ERS) analysis to EEG data to estimate event-specific encoding-related neural reinstatement of old associations during the retrieval of new ones and its impact on memory for new associations in young and older adults. Our results showed that older adults' new associative memory performance was more negatively impacted by proactive interference from old memories than that of young adults. In both age groups, ERS for old associative memories was greater for trials for which new associative memories were forgotten than remembered. In contrast, ERS for new associative memories was greater when they were remembered than forgotten. In addition, older adults showed relatively attenuated target (i.e., new associates) and lure (i.e., old associates) ERS effects compared to younger adults. Collectively, these results suggest that the neural reinstatement of interfering memories during retrieval contributes to proactive interference across age, whereas overall attenuated ERS effect in older adults might reflect their reduced memory fidelity.

N,N-dimethyltryptamine and Amazonian ayahuasca plant medicine

OBJECTIVE

Reports have indicated possible uses of ayahuasca for the treatment of conditions including depression, addictions, post-traumatic stress disorder, anxiety and specific psychoneuroendocrine immune system pathologies. The article assesses potential ayahuasca and N,N-dimethyltryptamine (DMT) integration with contemporary healthcare. The review also seeks to provide a summary of selected literature regarding the mechanisms of action of DMT and ayahuasca; and assess to what extent the state of research can explain reports of unusual phenomenology.

DESIGN

A narrative review.

RESULTS

Compounds in ayahuasca have been found to bind to serotonergic receptors, glutaminergic receptors, sigma-1 receptors, trace amine-associated receptors, and modulate BDNF expression and the dopaminergic system. Subjective effects are associated with increased delta and theta oscillations in amygdala and hippocampal regions, decreased alpha wave activity in the default mode network, and stimulations of vision-related brain regions particularly in the visual association cortex. Both biological processes and field of consciousness models have been proposed to explain subjective effects of DMT and ayahuasca, however, the evidence supporting the proposed models is not sufficient to make confident conclusions. Ayahuasca plant medicine and DMT represent potentially novel treatment modalities.

CONCLUSIONS

Further research is required to clarify the mechanisms of action and develop treatments which can be made available to the general public. Integration between healthcare research institutions and reputable practitioners in the Amazon is recommended.

Alpha suppression indexes a spotlight of visual-spatial attention that can shine on both perceptual and memory representations

Although researchers have been recording the human electroencephalogram (EEG) for almost a century, we still do not completely understand what cognitive processes are measured by the activity of different frequency bands. The 8- to 12-Hz activity in the alpha band has long been a focus of this research, but our understanding of its links to cognitive mechanisms has been rapidly evolving recently. Here, we review and discuss the existing evidence for two competing perspectives about alpha activity. One view proposes that the suppression of alpha-band power following the onset of a stimulus array measures attentional selection. The competing view is that this same activity measures the buffering of the task-relevant representations in working memory. We conclude that alpha-band activity following the presentation of stimuli appears to be due to the operation of an attentional selection mechanism, with characteristics that mirror the classic views of attention as selecting both perceptual inputs and representations already stored in memory.

Shared Representational Formats for Information Maintained in Working Memory and Information Retrieved from Long-Term Memory

Current theories propose that the short-term retention of information in working memory (WM) and the recall of information from long-term memory (LTM) are supported by overlapping neural mechanisms in occipital and parietal cortex. However, the extent of the shared representations between WM and LTM is unclear. We designed a spatial memory task that allowed us to directly compare the representations of remembered spatial information in WM and LTM with carefully matched behavioral response precision between tasks. Using multivariate pattern analyses on functional magnetic resonance imaging data, we show that visual memories were represented in a sensory-like code in both memory tasks across retinotopic regions in occipital and parietal cortex. Regions in lateral parietal cortex also encoded remembered locations in both tasks, but in a format that differed from sensory-evoked activity. These results suggest a striking correspondence in the format of representations maintained in WM and retrieved from LTM across occipital and parietal cortex. On the other hand, we also show that activity patterns in nearly all parietal regions, but not occipital regions, contained information that could discriminate between WM and LTM trials. Our data provide new evidence for theories of memory systems and the representation of mnemonic content.

Multi-scale neural decoding and analysis

Objective.

Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code. Multi-modal techniques can overcome tradeoffs in the spatial and temporal resolution of a single modality to reveal deeper and more comprehensive understanding of system-level neural mechanisms. Uncovering multi-scale dynamics is essential for a mechanistic understanding of brain function and for harnessing neuroscientific insights to develop more effective clinical treatment.

Approach.

We discuss conventional methodologies used for characterizing neural activity at different scales and review contemporary examples of how these approaches have been combined. Then we present our case for integrating activity across multiple scales to benefit from the combined strengths of each approach and elucidate a more holistic understanding of neural processes.

Main results.

We examine various combinations of neural activity at different scales and analytical techniques that can be used to integrate or illuminate information across scales, as well the technologies that enable such exciting studies. We conclude with challenges facing future multi-scale studies, and a discussion of the power and potential of these approaches.

Significance.

This roadmap will lead the readers toward a broad range of multi-scale neural decoding techniques and their benefits over single-modality analyses. This Review article highlights the importance of multi-scale analyses for systematically interrogating complex spatiotemporal mechanisms underlying cognition and behavior.

Decreased Alpha Peak Frequency Is Linked to Episodic Memory Impairment in Pathological Aging

The Free and Cued Selective Reminding Test (FCSRT) is a largely validated neuropsychological test for the identification of amnestic syndrome from the early stage of Alzheimer's disease (AD). Previous electrophysiological data suggested a slowing down of the alpha rhythm in the AD-continuum as well as a key role of this rhythmic brain activity for episodic memory processes. This study therefore investigates the link between alpha brain activity and alterations in episodic memory as assessed by the FCSRT. For that purpose, 37 patients with altered FCSRT performance underwent a comprehensive neuropsychological assessment, supplemented by 18F-fluorodeoxyglucose positron emission tomography/structural magnetic resonance imaging (18FDG-PET/MR), and 10 min of resting-state magnetoencephalography (MEG). The individual alpha peak frequency (APF) in MEG resting-state data was positively correlated with patients' encoding efficiency as well as with the efficacy of semantic cues in facilitating patients' retrieval of previous stored word. The APF also correlated positively with patients' hippocampal volume and their regional glucose consumption in the posterior cingulate cortex. Overall, this study demonstrates that alterations in the ability to learn and store new information for a relatively short-term period are related to a slowing down of alpha rhythmic activity, possibly due to altered interactions in the extended mnemonic system. As such, a decreased APF may be considered as an electrophysiological correlate of short-term episodic memory dysfunction accompanying pathological aging.

The diminishing precision of memory for time

Knowing when an event took place can provide several benefits to episodic memory, such as distinguishing among multiple traces, learning sequences of events, and guiding a search strategy. As a tool for understanding memory, time is particularly appealing given its ever-changing quality, the constant possibility to associate it with encoded events, and the ease with which it can be targeted at retrieval. Whereas studies of episodic retrieval typically employ categorical and probabilistic measures of retrieval success, characterizing a continuous feature such as time warrants measures particularly sensitive to the fidelity, or precision, of retrieved information. Here, we adapt a paradigm for assessing the fine-grained precision of retrieval to understand the nature of judging the time at which a memory was encoded. Subjects studied a series of pictures and then undertook a test in which they placed each picture, as precisely as possible, along a continuous time line representing the study list. Based on mixture-modeling analyses of the test response errors, the primary results were that temporal judgments were less accurate with passing time, and this change was due to diminished precision as opposed to an increased rate of guessing. Moreover, although we observed a negligible influence of guessing, subjects exhibited a clear effect of bias that favored recent responses. Together, in contrast to numerous studies of memory for other continuous features (e.g., color and location), our findings demonstrate a novel pattern of decision factors, suggesting that the retrieval of time might highlight distinct attributes of episodic memory.

Decoding chromaticity and luminance from patterns of EEG activity

A long-standing question in the field of vision research is whether scalp-recorded EEG activity contains sufficient information to identify stimulus chromaticity. Recent multivariate work suggests that it is possible to decode which chromaticity an observer is viewing from the multielectrode pattern of EEG activity. There is debate, however, about whether the claimed effects of stimulus chromaticity on visual evoked potentials (VEPs) are instead caused by unequal stimulus luminances, which are achromatic differences. Here, we tested whether stimulus chromaticity could be decoded when potential confounds with luminance were minimized by (1) equating chromatic stimuli in luminance using heterochromatic flicker photometry for each observer and (2) independently varying the chromaticity and luminance of target stimuli, enabling us to test whether the pattern for a given chromaticity generalized across wide variations in luminance. We also tested whether luminance variations can be decoded from the topography of voltage across the scalp. In Experiment 1, we presented two chromaticities (appearing red and green) at three luminance levels during separate trials. In Experiment 2, we presented four chromaticities (appearing red, orange, yellow, and green) at two luminance levels. Using a pattern classifier and the multielectrode pattern of EEG activity, we were able to accurately decode the chromaticity and luminance level of each stimulus. Furthermore, we were able to decode stimulus chromaticity when we trained the classifier on chromaticities presented at one luminance level and tested at a different luminance level. Thus, EEG topography contains robust information regarding stimulus chromaticity, despite large variations in stimulus luminance.

α-Band activity tracks a two-dimensional spotlight of attention during spatial working memory maintenance

Covert spatial attention is thought to facilitate the maintenance of locations in working memory, and EEG α-band activity (8-12 Hz) is proposed to track the focus of covert attention. Recent work has shown that multivariate patterns of α-band activity track the polar angle of remembered locations relative to fixation. However, a defining feature of covert spatial attention is that it facilitates processing in a specific region of the visual field, and prior work has not determined whether patterns of α-band activity track the two-dimensional (2-D) coordinates of remembered stimuli within a visual hemifield or are instead maximally sensitive to the polar angle of remembered locations around fixation. Here, we used a lateralized spatial estimation task, in which observers remembered the location of one or two target dots presented to one side of fixation, to test this question. By applying a linear discriminant classifier to the topography of α-band activity, we found that we were able to decode the location of remembered stimuli. Critically, model comparison revealed that the pattern of classifier choices observed across remembered positions was best explained by a model assuming that α-band activity tracks the 2-D coordinates of remembered locations rather than a model assuming that α-band activity tracks the polar angle of remembered locations relative to fixation. These results support the hypothesis that this α-band activity is involved in the spotlight of attention, and arises from mid- to lower-level visual areas involved in maintaining spatial locations in working memory.NEW & NOTEWORTHY A substantial body of work has shown that patterns of EEG α-band activity track the angular coordinates of attended and remembered stimuli around fixation, but whether these patterns track the two-dimensional coordinates of stimuli presented within a visual hemifield remains an open question. Here, we demonstrate that α-band activity tracks the two-dimensional coordinates of remembered stimuli within a hemifield, showing that α-band activity reflects a spotlight of attention focused on locations maintained in working memory.

The Importance of Considering Model Choices When Interpreting Results in Computational Neuroimaging

Model-based analyses open exciting opportunities for understanding neural information processing. In a commentary published in eNeuro, Gardner and Liu (2019) discuss the role of model specification in interpreting results derived from complex models of neural data. As a case study, they suggest that one such analysis, the inverted encoding model (IEM), should not be used to assay properties of "stimulus representations" because the ability to apply linear transformations at various stages of the analysis procedure renders results "arbitrary." Here, we argue that the specification of all models is arbitrary to the extent that an experimenter makes choices based on current knowledge of the model system. However, the results derived from any given model, such as the reconstructed channel response profiles obtained from an IEM analysis, are uniquely defined and are arbitrary only in the sense that changes in the model can predictably change results. IEM-based channel response profiles should therefore not be considered arbitrary when the model is clearly specified and guided by our best understanding of neural population representations in the brain regions being analyzed. Intuitions derived from this case study are important to consider when interpreting results from all model-based analyses, which are similarly contingent upon the specification of the models used.

Retrospective Cues Mitigate Information Loss in Human Cortex during Working Memory Storage

Working memory (WM) enables the flexible representation of information over short intervals. It is well established that WM performance can be enhanced by a retrospective cue presented during storage, yet the neural mechanisms responsible for this benefit are unclear. Here, we tested several explanations for retrospective cue benefits by quantifying changes in spatial WM representations reconstructed from alpha-band (8-12 Hz) EEG activity recorded from human participants (both sexes) before and after the presentation of a retrospective cue. This allowed us to track cue-related changes in WM representations with high temporal resolution (tens of milliseconds). Participants encoded the locations of two colored discs for subsequent report. During neutral trials, an uninformative cue instructed participants to remember the locations of both discs across a blank delay, and we observed a monotonic decrease in the fidelity of reconstructed spatial WM representations with time. During valid trials, a 100% reliable cue indicated that the color of the disc participants would be probed to report. Critically, valid cues were presented immediately after the termination of the encoding display ["valid early" (VE) trials] or midway through the delay period ["valid late" (VL) trials]. During VE trials, the gradual loss of location-specific information observed during neutral trials was eliminated, while during VL trials it was partially reversed. Our findings suggest that retrospective cues engage several different mechanisms that together serve to mitigate information loss during WM storage.SIGNIFICANCE STATEMENT Working memory (WM) performance can be improved by a cue presented during storage. This effect, termed a retrospective cue benefit, has been used to explore the limitations of attentional prioritization in WM. However, the mechanisms responsible for retrospective cue benefits are unclear. Here we tested several explanations for retrospective cue benefits by examining how they influence WM representations reconstructed from human EEG activity. This approach allowed us to visualize, quantify, and track the effects of retrospective cues with high temporal resolution (on the order of tens of milliseconds). We show that under different circumstances retrospective cues can both eliminate and even partially reverse information loss during WM storage, suggesting that retrospective cue benefits have manifold origins.