How brain oscillations form memories--a processing based perspective on oscillatory subsequent memory effects

Is transcranial alternating current stimulation effective for improving working memory? A three-level meta-analysis

Working memory, an essential component of cognitive function, can be improved through specific methods. This meta-analysis evaluates the effectiveness of transcranial alternating current stimulation (tACS), an emerging technique for enhancing working memory, and explores its efficacy, influencing factors, and underlying mechanisms. A PRISMA systematic search was conducted. Hedges's g was used to quantify effect sizes. We constructed a three-level meta-analytic model to account for all effect sizes and performed subgroup analyses to assess moderating factors. Recognizing the distinct neural underpinnings of various working memory processes, we separately assessed the effects on n-back tasks and traditional working memory tasks. A total of 39 studies with 405 effect sizes were included (170 from n-back tasks and 235 from other tasks). The overall analysis indicated a net benefit of g = 0.060 of tACS on working memory. Separate analyses showed that tACS had a small positive effect on n-back tasks (g = 0.102), but almost no effect on traditional working memory tasks (g = 0.045). Further analyses revealed mainly: A moderately positive effect of theta tACS (without anti-phase stimulation) on n-back tasks (g = 0.207); and a small effect of offline stimulation on working memory maintenance (g = 0.127). Overall, tACS has minimal impact on working memory improvement, but it shows potential under certain conditions. Specifically, both online and offline theta tACS can improve n-back task performance, while only offline stimulation enhances working memory maintenance. More research is needed to understand the mechanisms behind these effects to make tACS an effective method.

A third kind of episodic memory: Context familiarity is distinct from item familiarity and recollection

Episodic memory is accounted for with two processes: 'familiarity' when generally recognizing an item and 'recollection' when retrieving the full contextual details bound with the item. Paradoxically, people sometimes report contextual information as familiar but without recollecting details, which is not easily accounted for by existing theories. We tested a combination of item recognition confidence and source memory, focusing upon 'item-only hits with source unknown' ('item familiarity'), 'low-confidence hits with correct source memory' ('context familiarity'), and 'high-confidence hits with correct source memory' ('recollection'). Results across multiple within-subjects (trial-wise) and between subjects (individual variability) levels indicated these were behaviorally and physiologically distinct. Behaviorally, a crossover interaction was evident in response times, with context familiarity being slower than each condition during item recognition, but faster during source memory. Electrophysiologically, a Condition x Time x Location triple dissociation was evident in event-related potentials (ERPs), which was then independently replicated. Context familiarity exhibited an independent negative central effect from 800-1200 ms, differentiated from positive ERPs for item-familiarity (400 to 600 ms) and recollection (600 to 900 ms). These three conditions thus reflect mutually exclusive, fundamentally different processes of episodic memory. Context familiarity is a third distinct process of episodic memory.

Summary

Memory for past events is widely believed to operate through two different processes: one called 'recollection' when retrieving confident, specific details of a memory, and another called 'familiarity' when only having an unsure but conscious awareness that an item was experienced before. When people successfully retrieve details such as the source or context of a prior event, it has been assumed to reflect recollection. We demonstrate that familiarity of context is functionally distinct from familiarity of items and recollection and offer a new, tri-component model of memory. The three memory responses were differentiated across multiple behavioral and brain wave measures. What has traditionally been thought to be two kinds of memory processes are actually three, becoming evident when using sensitive enough multi-measures. Results are independently replicated across studies from different labs. These data reveal that context familiarity is a third process of human episodic memory.

Rhythmic Temporal Cues Coordinate Cross-frequency Phase-amplitude Coupling during Memory Encoding

Accumulating evidence suggests that rhythmic temporal cues in the environment influence the encoding of information into long-term memory. Here, we test the hypothesis that these mnemonic effects of rhythm reflect the coupling of high-frequency (gamma) oscillations to entrained lower-frequency oscillations synchronized to the beat of the rhythm. In Study 1, we first test this hypothesis in the context of global effects of rhythm on memory, when memory is superior for visual stimuli presented in rhythmic compared with arrhythmic patterns at encoding [Jones, A., & Ward, E. V. Rhythmic temporal structure at encoding enhances recognition memory, Journal of Cognitive Neuroscience, 31, 1549-1562, 2019]. We found that rhythmic presentation of visual stimuli during encoding was associated with greater phase-amplitude coupling (PAC) between entrained low-frequency (delta) oscillations and higher-frequency (gamma) oscillations. In Study 2, we next investigated cross-frequency PAC in the context of local effects of rhythm on memory encoding, when memory is superior for visual stimuli presented in-synchrony compared with out-of-synchrony with a background auditory beat [Hickey, P., Merseal, H., Patel, A. D., & Race, E. Memory in time: Neural tracking of low-frequency rhythm dynamically modulates memory formation. Neuroimage, 213, 116693, 2020]. We found that the mnemonic effect of rhythm in this context was again associated with increased cross-frequency PAC between entrained low-frequency (delta) oscillations and higher-frequency (gamma) oscillations. Furthermore, the magnitude of gamma power modulations positively scaled with the subsequent memory benefit for in- versus out-of-synchrony stimuli. Together, these results suggest that the influence of rhythm on memory encoding may reflect the temporal coordination of higher-frequency gamma activity by entrained low-frequency oscillations.

Differential online and offline effects of theta-tACS on memory encoding and retrieval

Theta oscillations support memory formation, but their exact contribution to the communication between prefrontal cortex (PFC) and the hippocampus is unknown. We tested the functional relevance of theta oscillations as a communication link between both areas for memory formation using transcranial alternating current stimulation (tACS). Healthy, young participants learned two lists of Dutch-German word pairs and retrieved them immediately and with a 30-min delay. In the encoding group (N = 30), tACS was applied during the encoding of list 1. List 2 was used to test stimulation aftereffects. In the retrieval group (N = 23), we stimulated during the delayed recall. In both groups, we applied tACS bilaterally at prefrontal and tempo-parietal sites, using either individualized theta frequency or 15 Hz (as control), according to a within-subject design. Stimulation with theta-tACS did not alter overall learning performance. An exploratory analysis revealed that immediate recall improved when word-pairs were learned after theta-tACS (list 2). Applying theta-tACS during retrieval had detrimental effects on memory. No changes in the power of the respective frequency bands were observed. Our results do not support the notion that impacting the communication between PFC and the hippocampus during a task by bilateral tACS improves memory. However, we do find evidence that direct stimulation had a trend for negatively interfering effects during immediate and delayed recall. Hints for beneficial effects on memory only occurred with aftereffects of the stimulation. Future studies need to further examine the effects during and after stimulation on memory formation.

Theta and alpha oscillations in human hippocampus and medial parietal cortex support the formation of location-based representations

Our ability to navigate in a new environment depends on learning new locations. Mental representations of locations are quickly accessible during navigation and allow us to know where we are regardless of our current viewpoint. Recent functional magnetic resonance imaging (fMRI) research using pattern classification has shown that these location-based representations emerge in the retrosplenial cortex and parahippocampal gyrus, regions theorized to be critically involved in spatial navigation. However, little is currently known about the oscillatory dynamics that support the formation of location-based representations. We used magnetoencephalogram (MEG) recordings to investigate region-specific oscillatory activity in a task where participants could form location-based representations. Participants viewed videos showing that two perceptually distinct scenes (180° apart) belonged to the same location. This "overlap" video allowed participants to bind the two distinct scenes together into a more coherent location-based representation. Participants also viewed control "non-overlap" videos where two distinct scenes from two different locations were shown, where no location-based representation could be formed. In a post-video behavioral task, participants successfully matched the two viewpoints shown in the overlap videos, but not the non-overlap videos, indicating they successfully learned the locations in the overlap condition. Comparing oscillatory activity between the overlap and non-overlap videos, we found greater theta and alpha/beta power during the overlap relative to non-overlap videos, specifically at time-points when we expected scene integration to occur. These oscillations localized to regions in the medial parietal cortex (precuneus and retrosplenial cortex) and the medial temporal lobe, including the hippocampus. Therefore, we find that theta and alpha/beta oscillations in the hippocampus and medial parietal cortex are likely involved in the formation of location-based representations.

Speaker Competence Affects Prefrontal Theta and Occipital Alpha Power during Selective Word Learning in Preschoolers

In the present study, we investigated the cognitive processes underlying selective word learning in preschoolers. We measured rhythmic neural activity in the theta (4-8 Hz) and alpha frequency range (7-12 Hz) in 67 four-year-olds. EEG was recorded during anticipation and encoding of novel labeling events performed by a speaker who had previously shown either competence (correct) or incompetence (incorrect) in labeling familiar objects. In both groups, children selected the target object equally often upon recall. However, children observing the incompetent speaker revealed weaker representations of novel words indicated by an increased likelihood for selecting familiar but incorrect items upon recall. Modulations in theta and alpha power suggest differential processing of novel label-object pairs depending on the speakers' competence. In the incompetent, but not the competent, speaker condition, increases in prefrontal theta power during anticipation and encoding were related to increased recall success. Findings suggest that theta power in the present study reflects cognitive control. In both conditions, occipital alpha power-indicating attentional processes-reflected familiarity with novel items, but in opposite directions. In familiar item trials, alpha power was increased observing the incompetent and decreased observing the competent speaker. Thus, both cognitive control and attention processes during word learning are differentially affected by speaker characteristics.

EEG decoders track memory dynamics

Encoding- and retrieval-related neural activity jointly determine mnemonic success. We ask whether electroencephalographic activity can reliably predict encoding and retrieval success on individual trials. Each of 98 participants performed a delayed recall task on 576 lists across 24 experimental sessions. Logistic regression classifiers trained on spectral features measured immediately preceding spoken recall of individual words successfully predict whether or not those words belonged to the target list. Classifiers trained on features measured during word encoding also reliably predict whether those words will be subsequently recalled and further predict the temporal and semantic organization of the recalled items. These findings link neural variability predictive of successful memory with item-to-context binding, a key cognitive process thought to underlie episodic memory function.

Data-driven control of oscillator networks with population-level measurement

Controlling complex networks of nonlinear limit-cycle oscillators is an important problem pertinent to various applications in engineering and natural sciences. While in recent years the control of oscillator populations with comprehensive biophysical models or simplified models, e.g., phase models, has seen notable advances, learning appropriate controls directly from data without prior model assumptions or pre-existing data remains a challenging and less developed area of research. In this paper, we address this problem by leveraging the network's current dynamics to iteratively learn an appropriate control online without constructing a global model of the system. We illustrate through a range of numerical simulations that the proposed technique can effectively regulate synchrony in various oscillator networks after a small number of trials using only one input and one noisy population-level output measurement. We provide a theoretical analysis of our approach, illustrate its robustness to system variations, and compare its performance with existing model-based and data-driven approaches.

Harmonic memory signals in the human cerebral cortex induced by semantic relatedness of words

When we memorize multiple words simultaneously, semantic relatedness among those words assists memory. For example, the information about "apple", "banana," and "orange" will be connected via a common concept of "fruits" and become easy to retain and recall. Neural mechanisms underlying this semantic integration in verbal working memory remain unclear. Here I used electroencephalography (EEG) and investigated neural signals when healthy human participants memorized five nouns semantically related (Sem trial) or not (NonSem trial). The regularity of oscillatory signals (8-30 Hz) during the retention period was found to be lower in NonSem than Sem trials, indicating that memorizing words unrelated to each other induced a non-harmonic (irregular) waveform in the temporal cortex. These results suggest that (i) semantic features of a word are retained as a set of neural oscillations at specific frequencies and (ii) memorizing words sharing a common semantic feature produces harmonic brain responses through a resonance or integration (sharing) of the oscillatory signals.

The effect of choice on memory: The role of theta oscillations

People value the opportunity to exercise control over the environment or make their own choices. Recent studies have revealed that simply having the opportunity to make choices can facilitate memory performance, suggesting an interaction between reward (due to choice making) and memory systems. However, little is known about the electrophysiological basis of choice-related memory. In the current study, we used scalp electroencephalography combined with a choice encoding task to examine the role of theta oscillations (which have been widely connected to reward and memory processing) in choice-related memory formation. The encoding task had two conditions. In the choice condition, participants were asked to choose between two occluded memoranda by themselves, whereas in the fixed condition, the decision was made by the computer. Behavioral results showed the choice effect, with better performance in the choice condition than the fixed condition on the recognition test given after a 24-h delay. Increases in theta power during an early latency of encoding period predicted successful memory formation in the choice condition, but not in the fixed condition. Furthermore, decreases in theta power during a late latency predicted successful memory formation in both the fixed and the choice conditions. Finally, we observed increased theta power in the choice condition compared to the fixed condition during an early latency of encoding period and decreased theta power in the choice condition compared to the fixed condition during a late latency. Our results suggest that theta oscillations play a significant role in choice-related memory formation.

An ERP measure of non-conscious memory reveals dissociable implicit processes in human recognition using an open-source automated analytic pipeline

Non-conscious processing of human memory has traditionally been difficult to objectively measure and thus understand. A prior study on a group of hippocampal amnesia (N = 3) patients and healthy controls (N = 6) used a novel procedure for capturing neural correlates of implicit memory using event-related potentials (ERPs): old and new items were equated for varying levels of memory awareness, with ERP differences observed from 400 to 800 ms in bilateral parietal regions that were hippocampal-dependent. The current investigation sought to address the limitations of that study by increasing the sample of healthy subjects (N = 54), applying new controls for construct validity, and developing an improved, open-source tool for automated analysis of the procedure used for equating levels of memory awareness. Results faithfully reproduced prior ERP findings of parietal effects that a series of systematic control analyses validated were not contributed to nor contaminated by explicit memory. Implicit memory effects extended from 600 to 1000 ms, localized to right parietal sites. These ERP effects were found to be behaviorally relevant and specific in predicting implicit memory response times, and were topographically dissociable from other traditional ERP measures of implicit memory (miss vs. correct rejections) that instead occurred in left parietal regions. Results suggest first that equating for reported awareness of memory strength is a valid, powerful new method for revealing neural correlates of non-conscious human memory, and second, behavioral correlations suggest that these implicit effects reflect a pure form of priming, whereas misses represent fluency leading to the subjective experience of familiarity.

Early- and late-phase changes of brain activity and early-phase neuromodulation in the posttraumatic stress disorder rat model

Posttraumatic stress disorder (PTSD) is a complex syndrome that may occur after life-threatening events. Fear memory abnormalities may play vital roles in the pathogenesis of PTSD. Previous work has found that fear memories are not rigid; the retrieval of fear memories may change over time. Furthermore, prior studies suggest that theta wave (4 Hz) activity is highly correlated with fear expression in an animal model. However, the relationship between pathological fear memory and potential brain wave features in PTSD remains largely uncharacterized. Here, we hypothesized that after traumatic stress exposure, the longitudinal dynamics of abnormal fears in PTSD animal models could be reflected by the measurement of local field potentials (LFPs). Using a well-established modified single-prolonged stress and footshock (SPS & FS) PTSD rat model, animals were restrained for 2 h and subsequently subjected to 20 min of forced swimming, then exposed to diethyl ether until they lost consciousness and placed in a conditioning chamber for fear conditioning. To characterize the temporal changes, we characterized freezing behavior brain wave features during the conditioning chamber re-exposure in the early (10 and 30 min; 2, 4, and 6 h) and late (day 1, 3, 7, and 14) phases after traumatic stress exposure. Our results indicate that SPS & FS rats showed co-morbid PTSD phenotypes including significantly higher levels of anxiety-, depression-, and anhedonia-like behaviors, and impaired fear extinction. Delta wave (0.5-4 Hz) suppression in the medial prefrontal cortex, amygdala, and ventral hippocampus occurred 10 and 30 min after traumatic stress, followed by continuous delta wave activity from 2 h to day 14, correlating with fear levels. tDCS reduced delta activity and alleviated PTSD-like phenotypes in the SPS & FS group. In this study, profiling abnormal fears with brain wave correlates may improve our understanding of time-dependent pathological fear memory retrieval in PTSD and facilitate the development of effective intervention strategies.

The association between working memory precision and the nonlinear dynamics of frontal and parieto-occipital EEG activity

Electrophysiological working memory (WM) research shows brain areas communicate via macroscopic oscillations across frequency bands, generating nonlinear amplitude modulation (AM) in the signal. Traditionally, AM is expressed as the coupling strength between the signal and a prespecified modulator at a lower frequency. Therefore, the idea of AM and coupling cannot be studied separately. In this study, 33 participants completed a color recall task while their brain activity was recorded through EEG. The AM of the EEG data was extracted using the Holo-Hilbert spectral analysis (HHSA), an adaptive method based on the Hilbert-Huang transforms. The results showed that WM load modulated parieto-occipital alpha/beta power suppression. Furthermore, individuals with higher frontal theta power and lower parieto-occipital alpha/beta power exhibited superior WM precision. In addition, the AM of parieto-occipital alpha/beta power predicted WM precision after presenting a target-defining probe array. The phase-amplitude coupling (PAC) between the frontal theta phase and parieto-occipital alpha/beta AM increased with WM load while processing incoming stimuli, but the PAC itself did not predict the subsequent recall performance. These results suggest frontal and parieto-occipital regions communicate through theta-alpha/beta PAC. However, the overall recall precision depends on the alpha/beta AM following the onset of the retro cue.

Cortico-ocular Coupling in the Service of Episodic Memory Formation

Encoding of visual information is a necessary requirement for most types of episodic memories. In search for a neural signature of memory formation, amplitude modulation of neural activity has been repeatedly shown to correlate with and suggested to be functionally involved in successful memory encoding. We here report a complementary view on why and how brain activity relates to memory, indicating a functional role of cortico-ocular interactions for episodic memory formation. Recording simultaneous magnetoencephalography and eye tracking in 35 human participants, we demonstrate that gaze variability and amplitude modulations of alpha/beta oscillations (10-20Hz) in visual cortex covary and predict subsequent memory performance between and within participants. Amplitude variation during pre-stimulus baseline was associated with gaze direction variability, echoing the co-variation observed during scene encoding. We conclude that encoding of visual information engages unison coupling between oculomotor and visual areas in the service of memory formation.

Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features

Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the anterior cingulate cortex, which were predominantly hypoconnected. Other significant contributing features were: (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive "uplift" life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life.

Learning of new associations invokes a major change in modulations of cortical beta oscillations in human adults

Large-scale cortical beta (β) oscillations were implicated in the learning processes, but their exact role is debated. We used MEG to explore the dynamics of movement-related β-oscillations while 22 adults learned, through trial and error, novel associations between four auditory pseudowords and movements of four limbs. As learning proceeded, spatial-temporal characteristics of β-oscillations accompanying cue-triggered movements underwent a major transition. Early in learning, widespread suppression of β-power occurred long before movement initiation and sustained throughout the whole behavioral trial. When learning advanced and performance reached asymptote, β-suppression after the initiation of correct motor response was replaced by a rise in β-power mainly in the prefrontal and medial temporal regions of the left hemisphere. This post-decision β-power predicted trial-by-trial response times (RT) at both stages of learning (before and after the rules become familiar), but with different signs of interaction. When a subject just started to acquire associative rules and gradually improved task performance, a decrease in RT correlated with the increase in the post-decision β-band power. When the participants implemented the already acquired rules, faster (more confident) responses were associated with the weaker post-decision β-band synchronization. Our findings suggest that maximal beta activity is pertinent to a distinct stage of learning and may serve to strengthen the newly learned association in a distributed memory network.

Altered alpha/beta desynchronization during item-context binding contributes to the associative deficit in older age

It is proposed that older adults have difficulties to bind item and context and to recruit deep, elaborative processing during encoding. Senescent changes in the oscillatory foundations of these processes are currently unclear. We recorded electroencephalography during item-context memory formation in younger (n = 57) and older (n = 55) adults. At test, we assessed memory for the items and the item-context pairs and examined encoding-related activity based on how much information was recovered at retrieval (miss < item-only < pair). Item memory was comparable between age groups while pair memory was reduced in the older adults. Theta synchronization and alpha/beta desynchronization increased linearly with the amount of information available. Single-trial theta power could not predict subsequent item memory, but predicted pair memory in an age-invariant manner, in line with a mechanism supporting associative memory. In contrast, single-trial alpha/beta power predicted both item and pair memory, in line with a mechanism reflecting the depth of information processing, and predicted pair memory less well in the older than the younger adults. Thus, theta and alpha/beta oscillations contribute differently in shaping the contents of memories and reduced processing capacity contributes to episodic memory decline in older age.

Episodic memory formation in unrestricted viewing

The brain systems of episodic memory and oculomotor control are tightly linked, suggesting a crucial role of eye movements in memory. But little is known about the neural mechanisms of memory formation across eye movements in unrestricted viewing behavior. Here, we leverage simultaneous eye tracking and EEG recording to examine episodic memory formation in free viewing. Participants memorized multi-element events while their EEG and eye movements were concurrently recorded. Each event comprised elements from three categories (face, object, place), with two exemplars from each category, in different locations on the screen. A subsequent associative memory test assessed participants' memory for the between-category associations that specified each event. We used a deconvolution approach to overcome the problem of overlapping EEG responses to sequential saccades in free viewing. Brain activity was time-locked to the fixation onsets, and we examined EEG power in the theta and alpha frequency bands, the putative oscillatory correlates of episodic encoding mechanisms. Three modulations of fixation-related EEG predicted high subsequent memory performance: (1) theta increase at fixations after between-category gaze transitions, (2) theta and alpha increase at fixations after within-element gaze transitions, (3) alpha decrease at fixations after between-exemplar gaze transitions. Thus, event encoding with unrestricted viewing behavior was characterized by three neural mechanisms, manifested in fixation-locked theta and alpha EEG activity that rapidly turned on and off during the unfolding eye movement sequences. These three distinct neural mechanisms may be the essential building blocks that subserve the buildup of coherent episodic memories during unrestricted viewing behavior.

Optimal phase-selective entrainment of heterogeneous oscillator ensembles

We develop a framework to design optimal entrainment signals that entrain an ensemble of heterogeneous nonlinear oscillators, described by phase models, at desired phases. We explicitly take into account heterogeneity in both oscillation frequency and the type of oscillators characterized by different Phase Response Curves. The central idea is to leverage the Fourier series representation of periodic functions to decode a phase-selective entrainment task into a quadratic program. We demonstrate our approach using a variety of phase models, where we entrain the oscillators into distinct phase patterns. Also, we show how the generalizability gained from our formulation enables us to meet a wide range of design objectives and constraints, such as minimum-power, fast entrainment, and charge-balanced controls.

The neural mechanism of non-phase-locked EEG activity in task switching

Flexible switching between different tasks is an important cognitive ability for humans and it is often studied using the task-switching paradigm. Although the neural mechanisms of task switching have been extensively explored in previous studies using event-related potentials techniques, the activity and process mechanisms of non-phase-locked electroencephalography (EEG) have rarely been revealed. For this reason, this paper discusses the processing of non-phase-locked EEG oscillations in task switching based on frequency-band delineation. First, the roles of each frequency band in local brain regions were summarized. In particular, during the proactive control process (the cue-stimulus interval), delta, theta, and alpha oscillations played more roles in the switch condition while beta played more roles in repeat task. In the reactive control process (post-target), delta, alpha, and beta are all related to sensorimotor function. Then, utilizing the functional connectivity (FC) method, delta connections in the frontotemporal regions and theta connections located in the parietal-to-occipital sites are involved in the preparatory period before task switching, while alpha connections located in the sensorimotor areas and beta connections located in the frontal-parietal cortex are involved in response inhibition. Finally, cross-frequency coupling (CFC) play an important role in working memory among different band oscillation. The present study shows that in addition to the processing mechanisms specific to each frequency band, there are some shared and interactive neural mechanism in task switching by using different analysis techniques.

Alpha modulation in younger and older adults during distracted encoding

To successfully encode information into long-term memory, we need top-down control to focus our attention on target stimuli. This attentional focus is achieved by the modulation of sensory neuronal excitability through alpha power. Failure to modulate alpha power and to inhibit distracting information has been reported in older adults during attention and working memory tasks. Given that alpha power during encoding can predict subsequent memory performance, aberrant oscillatory modulations might play a role in age-related memory deficits. However, it is unknown whether there are age-related differences in memory performance or alpha modulation when encoding targets with distraction. Here we show that both older and younger adults are able to encode targets paired with distractors and that the level of alpha power modulation during encoding predicted recognition success. Even though older adults showed signs of higher distractibility, this did not harm their episodic memory for target information. Also, we demonstrate that older adults only modulated alpha power during high distraction, both by enhancing target processing and inhibiting distractor processing. These results indicate that both younger and older adults are able to employ the same inhibitory control mechanisms successfully, but that older adults fail to call upon these when distraction is minimal. The findings of this study give us more insight into the mechanisms involved in memory encoding across the lifespan.

Oscillatory and Aperiodic Neural Activity Jointly Predict Language Learning

Memory formation involves the synchronous firing of neurons in task-relevant networks, with recent models postulating that a decrease in low-frequency oscillatory activity underlies successful memory encoding and retrieval. However, to date, this relationship has been investigated primarily with face and image stimuli; considerably less is known about the oscillatory correlates of complex rule learning, as in language. Furthermore, recent work has shown that nonoscillatory (1/ƒ) activity is functionally relevant to cognition, yet its interaction with oscillatory activity during complex rule learning remains unknown. Using spectral decomposition and power-law exponent estimation of human EEG data (17 females, 18 males), we show for the first time that 1/ƒ and oscillatory activity jointly influence the learning of word order rules of a miniature artificial language system. Flexible word-order rules were associated with a steeper 1/ƒ slope, whereas fixed word-order rules were associated with a shallower slope. We also show that increased theta and alpha power predicts fixed relative to flexible word-order rule learning and behavioral performance. Together, these results suggest that 1/ƒ activity plays an important role in higher-order cognition, including language processing, and that grammar learning is modulated by different word-order permutations, which manifest in distinct oscillatory profiles.

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.

EEG biomarkers of free recall

Brain activity in the moments leading up to spontaneous verbal recall provide a window into the cognitive processes underlying memory retrieval. But these same recordings also subsume neural signals unrelated to mnemonic retrieval, such as response-related motor activity. Here we examined spectral EEG biomarkers of memory retrieval under an extreme manipulation of mnemonic demands: subjects either recalled items after a few seconds or after several days. This manipulation helped to isolate EEG components specifically related to long-term memory retrieval. In the moments immediately preceding recall we observed increased theta (4-8 Hz) power (+T), decreased alpha (8-20 Hz) power (-A), and increased gamma (40-128 Hz) power (+G), with this spectral pattern (+T-A + G) distinguishing the long-delay and immediate recall conditions. As subjects vocalized the same set of studied words in both conditions, we interpret the spectral +T-A + G as a biomarker of episodic memory retrieval.

Encoding contexts are incidentally reinstated during competitive retrieval and track the temporal dynamics of memory interference

The ability to remember an episode from our past is often hindered by competition from similar events. For example, if we want to remember the article a colleague recommended during the last lab meeting, we may need to resolve interference from other article recommendations from the same colleague. This study investigates if the contextual features specifying the encoding episodes are incidentally reinstated during competitive memory retrieval. Competition between memories was created through the AB/AC interference paradigm. Individual word-pairs were presented embedded in a slowly drifting real-word-like context. Multivariate pattern analysis (MVPA) of high temporal-resolution electroencephalographic (EEG) data was used to investigate context reactivation during memory retrieval. Behaviorally, we observed proactive (but not retroactive) interference; that is, performance for AC competitive retrieval was worse compared with a control DE noncompetitive retrieval, whereas AB retrieval did not suffer from competition. Neurally, proactive interference was accompanied by an early reinstatement of the competitor context and interference resolution was associated with the ensuing reinstatement of the target context. Together, these findings provide novel evidence showing that the encoding contexts of competing discrete events are incidentally reinstated during competitive retrieval and that such reinstatement tracks retrieval competition and subsequent interference resolution.

Plasticity impairment exposes CA3 vulnerability in a hippocampal network model of mild traumatic brain injury

Proper function of the hippocampus is critical for executing cognitive tasks such as learning and memory. Traumatic brain injury (TBI) and other neurological disorders are commonly associated with cognitive deficits and hippocampal dysfunction. Although there are many existing models of individual subregions of the hippocampus, few models attempt to integrate the primary areas into one system. In this work, we developed a computational model of the hippocampus, including the dentate gyrus, CA3, and CA1. The subregions are represented as an interconnected neuronal network, incorporating well-characterized ex vivo slice electrophysiology into the functional neuron models and well-documented anatomical connections into the network structure. In addition, since plasticity is foundational to the role of the hippocampus in learning and memory as well as necessary for studying adaptation to injury, we implemented spike-timing-dependent plasticity among the synaptic connections. Our model mimics key features of hippocampal activity, including signal frequencies in the theta and gamma bands and phase-amplitude coupling in area CA1. We also studied the effects of spike-timing-dependent plasticity impairment, a potential consequence of TBI, in our model and found that impairment decreases broadband power in CA3 and CA1 and reduces phase coherence between these two subregions, yet phase-amplitude coupling in CA1 remains intact. Altogether, our work demonstrates characteristic hippocampal activity with a scaled network model of spiking neurons and reveals the sensitive balance of plasticity mechanisms in the circuit through one manifestation of mild traumatic injury.

Evidence from theta-burst stimulation that age-related de-differentiation of the hippocampal network is functional for episodic memory

Episodic memory is supported by hippocampal interactions with a distributed network. Aging is associated with memory decline and network de-differentiation. However, the role of de-differentiation in memory decline has not been directly tested. We reasoned that hippocampal network-targeted stimulation could test these theories, as age-related changes in the network response to stimulation would indicate network reorganization, and corresponding changes in memory would suggest that this reorganization is functional. We compared effects of stimulation on fMRI connectivity and memory in younger versus older adults. Theta-burst network-targeted stimulation of left lateral parietal cortex selectively increased hippocampal network connectivity and modulated memory in younger adults. In contrast, stimulation in older adults increased connectivity throughout the brain, without network selectivity, and did not influence memory. These findings provide evidence that network responses to stimulation are de-differentiated in aging and suggest that age-related de-differentiation is relevant for memory. This manuscript is part of the Special Issue entitled "Cognitive Neuroscience of Healthy and Pathological Aging" edited by Drs. M. N. Rajah, S. Belleville, and R. Cabeza. This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect at https://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

Spectral Pattern Similarity Analysis: Tutorial and Application in Developmental Cognitive Neuroscience

The human brain encodes information in neural activation patterns. While standard approaches to analyzing neural data focus on brain (de-)activation (e.g., regarding the location, timing, or magnitude of neural responses), multivariate neural pattern similarity analyses target the informational content represented by neural activity. In adults, a number of representational properties have been identified that are linked to cognitive performance, in particular the stability, distinctiveness, and specificity of neural patterns. However, although growing cognitive abilities across childhood suggest advancements in representational quality, developmental studies still rarely utilize information-based pattern similarity approaches, especially in electroencephalography (EEG) research. Here, we provide a comprehensive methodological introduction and step-by-step tutorial for pattern similarity analysis of spectral (frequency-resolved) EEG data including a publicly available pipeline and sample dataset with data from children and adults. We discuss computation of single-subject pattern similarities and their statistical comparison at the within-person to the between-group level as well as the illustration and interpretation of the results. This tutorial targets both novice and more experienced EEG researchers and aims to facilitate the usage of spectral pattern similarity analyses, making these methodologies more readily accessible for (developmental) cognitive neuroscientists.

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.

Disentangling neocortical alpha/beta and hippocampal theta/gamma oscillations in human episodic memory formation

To form an episodic memory, we must first process a vast amount of sensory information about the to-be-encoded event and then bind these sensory representations together to form a coherent memory trace. While these two cognitive capabilities are thought to have two distinct neural origins, with neocortical alpha/beta oscillations supporting information representation and hippocampal theta-gamma phase-amplitude coupling supporting mnemonic binding, evidence for a dissociation between these two neural markers is conspicuously absent. To address this, seventeen human participants completed an associative memory task that first involved processing information about three sequentially-presented stimuli, and then binding these stimuli together into a coherent memory trace, all the while undergoing MEG recordings. We found that decreases in neocortical alpha/beta power during sequence perception, but not mnemonic binding, correlated with enhanced memory performance. Hippocampal theta/gamma phase-amplitude coupling, however, showed the opposite pattern; increases during mnemonic binding (but not sequence perception) correlated with enhanced memory performance. These results demonstrate that memory-related decreases in neocortical alpha/beta power and memory-related increases in hippocampal theta/gamma phase-amplitude coupling arise at distinct stages of the memory formation process. We speculate that this temporal dissociation reflects a functional dissociation in which neocortical alpha/beta oscillations could support the processing of incoming information relevant to the memory, while hippocampal theta-gamma phase-amplitude coupling could support the binding of this information into a coherent memory trace.

Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity

Metamemory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical stimulation (tES) during sleep, but evidence for improvements to metamemory sensitivity is limited. Applying tES can enhance sleep-dependent memory consolidation, which along with metamemory requires the coordination of activity across distributed neural systems, suggesting that examining functional connectivity is important for understanding these processes. Nevertheless, little research has examined how functional connectivity modulations relate to overnight changes in metamemory sensitivity. Here, we developed a closed-loop short-duration tES method, time-locked to up-states of ongoing slow-wave oscillations, to cue specific memory replays in humans. We measured electroencephalographic (EEG) coherence changes following stimulation pulses, and characterized network alterations with graph theoretic metrics. Using machine learning techniques, we show that pulsed tES elicited network changes in multiple frequency bands, including increased connectivity in the theta band and increased efficiency in the spindle band. Additionally, stimulation-induced changes in beta-band path length were predictive of overnight changes in metamemory sensitivity. These findings add new insights into the growing literature investigating increases in memory performance through brain stimulation during sleep, and highlight the importance of examining functional connectivity to explain its effects.

Numerous studies have demonstrated a clear link between sleep and memory—namely, memories are consolidated during sleep, leading to more stable and long-lasting representations. We have previously shown that tagging episodes with specific patterns of brain stimulation during encoding and replaying those patterns during sleep can enhance this consolidation process to improve confidence and decision-making of memories (metamemory). Here, we extend this work to examine network-level brain changes that occur following stimulation during sleep that predict metamemory improvements. Using graph theoretic and machine-learning methods, we found that stimulation-induced changes in beta-band path length predicted overnight improvements in metamemory. This novel finding sheds new light on the neural mechanisms of memory consolidation and suggests potential applications for improving metamemory.

Independent dynamics of low, intermediate, and high frequency spectral intracranial EEG activities during human memory formation

A wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various frequency ranges are coordinated across the space of the human cortex and time of memory processing is inconclusive. They can either be coordinated together across the frequency spectrum at the same cortical site and time or induced independently in particular bands. We used a large dataset of human intracranial electroencephalography (iEEG) to parse the spatiotemporal dynamics of spectral activities induced during formation of verbal memories. Encoding of words for subsequent free recall activated low frequency theta, intermediate frequency alpha and beta, and high frequency gamma power in a mosaic pattern of discrete cortical sites. A majority of the cortical sites recorded activity in only one of these frequencies, except for the visual cortex where spectral power was induced across multiple bands. Each frequency band showed characteristic dynamics of the induced power specific to cortical area and hemisphere. The power of the low, intermediate, and high frequency activities propagated in independent sequences across the visual, temporal and prefrontal cortical areas throughout subsequent phases of memory encoding. Our results provide a holistic, simplified model of the spectral activities engaged in the formation of human memory, suggesting an anatomically and temporally distributed mosaic of coordinated brain rhythms.

Semantic Congruence Drives Long-Term Memory and Similarly Affects Neural Retrieval Dynamics in Young and Older Adults

Learning novel information can be promoted if it is congruent with already stored knowledge. This so-called semantic congruence effect has been broadly studied in healthy young adults with a focus on neural encoding mechanisms. However, the impacts on retrieval, and possible impairments during healthy aging, which is typically associated with changes in declarative long-term memory, remain unclear. To investigate these issues, we used a previously established paradigm in healthy young and older humans with a focus on the neural activity at a final retrieval stage as measured with electroencephalography (EEG). In both age groups, semantic congruence at encoding enhanced subsequent long-term recognition memory of words. Compatible with this observation, semantic congruence led to differences in event-related potentials (ERPs) at retrieval, and this effect was not modulated by age. Specifically, congruence modulated old/new ERPs at a fronto-central (Fz) and left parietal (P3) electrode in a late (400–600 ms) time window, which has previously been associated with recognition memory processes. Importantly, ERPs to old items also correlated with the positive effect of semantic congruence on long-term memory independent of age. Together, our findings suggest that semantic congruence drives subsequent recognition memory across the lifespan through changes in neural retrieval processes.

Stress enhances emotional memory-related theta oscillations in the medial temporal lobe

Stressful events impact memory formation, in particular for emotionally arousing stimuli. Although these stress effects on emotional memory formation have potentially far-reaching implications, the underlying neural mechanisms are not fully understood. Specifically, the temporal processing dimension of the mechanisms involved in emotional memory formation under stress remains elusive. Here, we used magnetoencephalography (MEG) to examine the neural processes underlying stress effects on emotional memory formation with high temporal and spatial resolution and a particular focus on theta oscillations previously implicated in mnemonic binding. Healthy participants (n = 53) underwent a stress or control procedure before encoding emotionally neutral and negative pictures, while MEG was recorded. Memory for the pictures was probed in a recognition test 24 h after encoding. In this recognition test, stress did not modulate the emotional memory enhancement but led to significantly higher confidence in memory for negative compared to neutral stimuli. Our neural data revealed that stress increased memory-related theta oscillations specifically in medial temporal and occipito-parietal regions. Further, this stress-related increase in theta power emerged during memory formation for emotionally negative but not for neutral stimuli. These findings indicate that acute stress can enhance, in the medial temporal lobe, oscillations at a frequency that is ideally suited to bind the elements of an ongoing emotional episode, which may represent a mechanism to facilitate the storage of emotionally salient events that occurred in the context of a stressful encounter.

Riding the slow wave: Exploring the role of entrained low-frequency oscillations in memory formation

Neural oscillations are proposed to support a variety of behaviors, including long-term memory, yet their functional significance remains an active area of research. Here, we explore a potential functional role of low-frequency cortical oscillations in episodic memory formation. Recent theories suggest that low-frequency oscillations orchestrate rhythmic attentional sampling of the environment by dynamically modulating neural excitability across time. When these oscillations entrain to low-frequency rhythms present in the environment, such as speech or music, the brain can build temporal predictions about the onset of relevant events so that these events can be more efficiently processed. Building upon this literature, we propose that entrained low-frequency oscillations may similarly influence the temporal dynamics of episodic memory by rhythmically modulating encoding across time (mnemonic sampling). Central to this proposal is the phenomenon of cross-frequency phase-amplitude coupling, whereby the amplitudes of faster (higher frequency) rhythms, such as gamma oscillations, couple to the phase of slower (lower-frequency) rhythms entrained to environmental stimuli. By imposing temporal structure on higher-frequency oscillatory activity previously linked to memory formation, entrained low-frequency oscillations could dynamically orchestrate memory formation and optimize encoding at specific moments in time. We discuss prior experimental and theoretical work relevant to this proposal.

Watching Movies Unfold, a Frame-by-Frame Analysis of the Associated Neural Dynamics

Our lives unfold as sequences of events. We experience these events as seamless, although they are composed of individual images captured in between the interruptions imposed by eye blinks and saccades. Events typically involve visual imagery from the real world (scenes), and the hippocampus is frequently engaged in this context. It is unclear, however, whether the hippocampus would be similarly responsive to unfolding events that involve abstract imagery. Addressing this issue could provide insights into the nature of its contribution to event processing, with relevance for theories of hippocampal function. Consequently, during magnetoencephalography (MEG), we had female and male humans watch highly matched unfolding movie events composed of either scene image frames that reflected the real world, or frames depicting abstract patterns. We examined the evoked neuronal responses to each image frame along the time course of the movie events. Only one difference between the two conditions was evident, and that was during the viewing of the first image frame of events, detectable across frontotemporal sensors. Further probing of this difference using source reconstruction revealed greater engagement of a set of brain regions across parietal, frontal, premotor, and cerebellar cortices, with the largest change in broadband (1–30 Hz) power in the hippocampus during scene-based movie events. Hippocampal engagement during the first image frame of scene-based events could reflect its role in registering a recognizable context perhaps based on templates or schemas. The hippocampus, therefore, may help to set the scene for events very early on.

Normal and Abnormal Sharp Wave Ripples in the Hippocampal-Entorhinal Cortex System: Implications for Memory Consolidation, Alzheimer's Disease, and Temporal Lobe Epilepsy

The appearance of hippocampal sharp wave ripples (SWRs) is an electrophysiological biomarker for episodic memory encoding and behavioral planning. Disturbed SWRs are considered a sign of neural network dysfunction that may provide insights into the structural connectivity changes associated with cognitive impairment in early-stage Alzheimer's disease (AD) and temporal lobe epilepsy (TLE). SWRs originating from hippocampus have been extensively studied during spatial navigation in rodents, and more recent studies have investigated SWRs in the hippocampal-entorhinal cortex (HPC-EC) system during a variety of other memory-guided behaviors. Understanding how SWR disruption impairs memory function, especially episodic memory, could aid in the development of more efficacious therapeutics for AD and TLE. In this review, we first provide an overview of the reciprocal association between AD and TLE, and then focus on the functions of HPC-EC system SWRs in episodic memory consolidation. It is posited that these waveforms reflect rapid network interactions among excitatory projection neurons and local interneurons and that these waves may contribute to synaptic plasticity underlying memory consolidation. Further, SWRs appear altered or ectopic in AD and TLE. These waveforms may thus provide clues to understanding disease pathogenesis and may even serve as biomarkers for early-stage disease progression and treatment response.

The Sync-Fire/deSync model: Modelling the reactivation of dynamic memories from cortical alpha oscillations

We propose a neural network model to explore how humans can learn and accurately retrieve temporal sequences, such as melodies, movies, or other dynamic content. We identify target memories by their neural oscillatory signatures, as shown in recent human episodic memory paradigms. Our model comprises three plausible components for the binding of temporal content, where each component imposes unique limitations on the encoding and representation of that content. A cortical component actively represents sequences through the disruption of an intrinsically generated alpha rhythm, where a desynchronisation marks information-rich operations as the literature predicts. A binding component converts each event into a discrete index, enabling repetitions through a sparse encoding of events. A timing component - consisting of an oscillatory "ticking clock" made up of hierarchical synfire chains - discretely indexes a moment in time. By encoding the absolute timing between discretised events, we show how one can use cortical desynchronisations to dynamically detect unique temporal signatures as they are reactivated in the brain. We validate this model by simulating a series of events where sequences are uniquely identifiable by analysing phasic information, as several recent EEG/MEG studies have shown. As such, we show how one can encode and retrieve complete episodic memories where the quality of such memories is modulated by the following: alpha gate keepers to content representation; binding limitations that induce a blink in temporal perception; and nested oscillations that provide preferential learning phases in order to temporally sequence events.

Disrupted Modulation of Alpha and Low Beta Oscillations Mediates Temporal Sequence Memory Deficits in People With Schizophrenia

BACKGROUND

People with schizophrenia (SZ) exhibit impaired episodic memory when relating objects to each other in time and space. Empirical studies and computational models suggest that low-frequency neural oscillations may be a mechanism by which the brain keeps track of temporal relationships during encoding and retrieval, with modulation of oscillatory power as sequences are learned. It is unclear whether sequence memory deficits in SZ are associated with altered neural oscillations.

METHODS

Using electroencephalography, this study examined neural oscillations in 51 healthy control subjects and 37 people with SZ during a temporal sequence learning task. Multiple 5-object picture sequences were presented across 4 study-test blocks in either fixed or random order. Participants answered semantic questions for each object (e.g., living/nonliving), and sequence memory was operationalized as faster responses for fixed versus random sequences. Differences in oscillatory power between fixed versus random sequences provided a neural index of temporal sequence memory.

RESULTS

Although both groups showed reaction time differences in late blocks (blocks 3 and 4), this evidence of sequence memory was reduced in people with SZ relative to healthy control subjects. Decreases in globally distributed prestimulus alpha (8-12 Hz) and beta 1 (13-20 Hz) power for fixed versus random sequences in late blocks were also attenuated in people with SZ relative to healthy control subjects. Moreover, changes in oscillatory power predicted individual reaction time differences and fully mediated the relationship between group and sequence memory.

CONCLUSIONS

Disrupted modulation of alpha and beta 1 electroencephalography oscillations is a candidate mechanism of temporal sequence memory deficits in people with SZ.

Enhancing vs. inhibiting semantic performance with transcranial magnetic stimulation over the anterior temporal lobe: Frequency- and task-specific effects

Accumulating, converging evidence indicates that the anterior temporal lobe (ATL) appears to be the transmodal hub for semantic representation. A series of repetitive transcranial magnetic stimulation (rTMS) investigations utilizing the ‘virtual lesion’ approach have established the brain-behavioural relationship between the ATL and semantic processing by demonstrating that inhibitory rTMS over the ATL induced impairments in semantic performance in healthy individuals. However, a growing body of rTMS studies suggest that rTMS might also be a tool for cognitive enhancement and rehabilitation, though there has been no previous exploration in semantic cognition. Here, we explored a potential role of rTMS in enhancing and inhibiting semantic performance with contrastive rTMS protocols (1 Hz vs. 20 Hz) by controlling practice effects. Twenty-one healthy participants were recruited and performed an object category judgement task and a pattern matching task serving as a control task before and after the stimulation over the ATL (1 Hz, 20 Hz, and sham). A task familiarization procedure was performed prior to the experiment in order to establish a ‘stable baseline’ prior to stimulation and thus minimize practice effect. Our results demonstrated that it is possible to modulate semantic performance positively or negatively depending on the ATL stimulation frequency: 20 Hz rTMS was optimal for facilitating cortical processing (faster RT in a semantic task) contrasting with diminished semantic performance after 1 Hz rTMS. In addition to cementing the importance of the ATL to semantic representation, our findings suggest that 20 Hz rTMS leads to semantic enhancement in healthy individuals and potentially could be used for patients with semantic impairments as a therapeutic tool.

The role of the anterior nuclei of the thalamus in human memory processing

Extensive neuroanatomical connectivity between the anterior thalamic nuclei (ATN) and hippocampus and neocortex renders them well-placed for a role in memory processing, and animal, lesion, and neuroimaging studies support such a notion. The deep location and small size of the ATN have precluded their real-time electrophysiological investigation during human memory processing. However, ATN electrophysiological recordings from patients receiving electrodes implanted for deep brain stimulation for pharmacoresistant focal epilepsy have enabled high temporal resolution study of ATN activity. Theta frequency synchronization of ATN and neocortical oscillations during successful memory encoding, enhanced phase alignment, and coupling between ATN local gamma frequency activity and frontal neocortical and ATN theta oscillations provide evidence of an active role for the ATN in memory encoding, potentially integrating information from widespread neocortical sources. Greater coupling of a broader gamma frequency range with theta oscillations at rest than during memory encoding provides additional support for the hypothesis that the ATN play a role in selecting local, task-relevant high frequency activity associated with particular features of a memory trace.

Effects of age differences in memory formation on neural mechanisms of consolidation and retrieval

Episodic memory decline is a hallmark of cognitive aging and a multifaceted phenomenon. We review studies that target age differences across different memory processing stages, i.e., from encoding to retrieval. The available evidence suggests that age differences during memory formation may affect the quality of memory representations in an age-graded manner with downstream consequences for later processing stages. We argue that low memory quality in combination with age-related neural decline of key regions of the episodic memory network puts older adults in a double jeopardy situation that finally results in broader memory impairments in older compared to younger adults.

Frontoparietal Beta Amplitude Modulation and its Interareal Cross-frequency Coupling in Visual Working Memory

Visual working memory (VWM) relies on sustained neural activities that code information via various oscillatory frequencies. Previous studies, however, have emphasized time-frequency power changes, while overlooking the possibility that rhythmic amplitude variations can also code frequency-specific VWM information in a completely different dimension. Here, we employed the recently-developed Holo-Hilbert spectral analysis to characterize such nonlinear amplitude modulation(s) (AM) underlying VWM in the frontoparietal systems. We found that the strength of AM in mid-frontal beta and gamma oscillations during late VWM maintenance and VWM retrieval correlated with people's VWM performance. When behavioral performance was altered with transcranial electric stimulation, AM power changes during late VWM maintenance in beta, but not gamma, tracked participants' VWM variations. This beta AM likely codes information by varying its amplitude in theta period for long-range propagation, as our connectivity analysis revealed that interareal theta-beta couplings-bidirectional between mid-frontal and right-parietal during VWM maintenance and unidirectional from right-parietal to left-middle-occipital during late VWM maintenance and retrieval-underpins VWM performance and individual differences.

The phase of Theta oscillations modulates successful memory formation at encoding

Several studies have shown that attention and perception can depend upon the phase of ongoing neural oscillations at stimulus onset. Here, we extend this idea to the memory domain. We tested the hypothesis that ongoing fluctuations in neural activity impact memory encoding in two experiments using a picture paired-associates task in order to gauge episodic memory performance. Experiment 1 was behavioural only and capitalized on the principle of phase resetting. We tested if subsequent memory performance fluctuates rhythmically, time-locked to a resetting cue presented before the to-be-remembered pairs at different time intervals. We found an indication that behavioural performance was periodically and selectively modulated at Theta frequency (~4 Hz). In Experiment 2, we focused on pre-stimulus ongoing activity using scalp EEG while participants performed a paired-associates task. The pre-registered analysis, using large electrode clusters and generic Theta and Alpha spectral ranges, returned null results of the pre-stimulus phase-behaviour correlation. However, as expected from prior literature, we found that variations in stimulus-related Theta-power predicted subsequent memory performance. Therefore, we used this post-stimulus effect in Theta power to guide a post-hoc pre-stimulus phase analysis in terms of scalp and frequency of interest. This analysis returned a correlation between the pre-stimulus Theta phase and subsequent memory. Altogether, these results suggest that pre-stimulus Theta activity at encoding may impact later memory performance.

Event-related potential and EEG oscillatory predictors of verbal memory in mild cognitive impairment

Reliable biomarkers of memory decline are critical for the early detection of Alzheimer's disease. Previous work has found three EEG measures, namely the event-related brain potential P600, suppression of oscillatory activity in the alpha frequency range (∼10 Hz) and cross-frequency coupling between low theta/high delta and alpha/beta activity, each of which correlates strongly with verbal learning and memory abilities in healthy elderly and patients with mild cognitive impairment or prodromal Alzheimer's disease. In the present study, we address the question of whether event-related or oscillatory measures, or a combination thereof, best predict the decline of verbal memory in mild cognitive impairment and Alzheimer's disease. Single-trial correlation analyses show that despite a similarity in their time courses and sensitivities to word repetition, the P600 and the alpha suppression components are minimally correlated with each other on a trial-by-trial basis (generally |r _s| < 0.10). This suggests that they are unlikely to stem from the same neural mechanism. Furthermore, event-related brain potentials constructed from bandpass filtered (delta, theta, alpha, beta or gamma bands) single-trial data indicate that only delta band activity (1-4 Hz) is strongly correlated (r = 0.94, P < 0.001) with the canonical P600 repetition effect; event-related potentials in higher frequency bands are not. Importantly, stepwise multiple regression analyses reveal that the three event-related brain potential/oscillatory measures are complementary in predicting California Verbal Learning Test scores (overall R ^{2 '} s in 0.45-0.63 range). The present study highlights the importance of combining EEG event-related potential and oscillatory measures to better characterize the multiple mechanisms of memory failure in individuals with mild cognitive impairment or prodromal Alzheimer's disease.

Single-Trial EEG Connectivity of Default Mode Network Before and During Encoding Predicts Subsequent Memory Outcome

The successful memory process produces specific activity in the brain network. As the brain activity of the prestimulus and encoding phases has a crucial effect on subsequent memory outcomes (e.g., remembered or forgotten), previous studies have tried to predict the memory performance in this period. Conventional studies have used the spectral power or event-related potential of specific regions as the classification feature. However, as multiple brain regions work collaboratively to process memory, it could be a better option to use functional connectivity within the memory-related brain network to predict subsequent memory performance. In this study, we acquired the EEG signals while performing an associative memory task that remembers scene-word pairs. For the connectivity analysis, we estimated the cross-mutual information within the default mode network with the time-frequency spectra at the prestimulus and encoding phases. Then, we predicted the success or failure of subsequent memory outcome with the connectivity features. We found that the classifier with support vector machine achieved the highest classification accuracy of 80.83% ± 12.65% (mean ± standard deviation) using the beta (13-30 Hz) connectivity at encoding phase among the multiple frequency bands and task phases. Using the prestimulus beta connectivity, the classification accuracy of 72.45% ± 12.52% is also achieved. Among the features, the connectivity related to the dorsomedial prefrontal cortex was found to contribute to successful memory encoding. The connectivity related to the posterior cingulate cortex was found to contribute to the failure of memory encoding. The present study showed for the first time the successful prediction with high accuracy of subsequent memory outcome using single-trial functional connectivity.

Learning something new versus changing your ways: Distinct effects on midfrontal oscillations and cardiac activity for learning and flexible adjustments

We need to be able to learn new behaviour, but also be capable of changing existing routines, when they start conflicting with our long-term goals. Little is known about to what extent blank-slate learning of new and adjustment of existing behavioural routines rely on different neural and bodily mechanisms. In the current study, participants first acquired novel stimulus-response contingencies, which were subsequently randomly changed to create the need for flexible adjustments. We measured midfrontal theta oscillations via EEG as an indicator of neural conflict processing, as well as heart rate as a proxy of autonomic activity. Participants' trial-wise learning progress was estimated via computation modelling. Theta power and heart rate significantly differed between correct and incorrect trials. Differences between correct and incorrect trials in both neural and cardiac feedback processing were more pronounced for adjustments compared to blank-slate learning. This indicates that both midfrontal and cardiac processing are sensitive to changes in stimulus-response contingencies. Increases in individual learning rates predicted lower impact of performance feedback on midfrontal theta power, but higher impact on heart rate. This suggests that cardiac and midfrontal reactivity are partially reflective of different mechanisms related to feedback learning. Our results shed new light on the role of neural and autonomic mechanisms for learning and behavioural adjustments.

Neural measures of subsequent memory reflect endogenous variability in cognitive function

Human cognition exhibits a striking degree of variability: Sometimes we rapidly forge new associations whereas at other times new information simply does not stick. Correlations between neural activity during encoding and subsequent retrieval performance have implicated such "subsequent memory effects" (SMEs) as important for understanding the neural basis of memory formation. Uncontrolled variability in external factors that also predict memory performance, however, confounds the interpretation of these effects. By controlling for a comprehensive set of external variables, we investigated the extent to which neural correlates of successful memory encoding reflect variability in endogenous brain states. We show that external variables that reliably predict memory performance have relatively small effects on electroencephalographic (EEG) correlates of successful memory encoding. Instead, the brain activity that is diagnostic of successful encoding primarily reflects fluctuations in endogenous neural activity. These findings link neural activity during learning to endogenous states that drive variability in human cognition. (PsycInfo Database Record (c) 2021 APA, all rights reserved).