Memory Encoding Research Articles

Behavioral, neurological, and psychiatric frailty of autobiographical memory.

Autobiographical-episodic memory is considered to be the most complex of the five long-term memory systems. It is autonoetic, which means, self-reflective, relies on emotional colorization, and needs the features of place and time; it allows mental time traveling. Compared to the other four long-term memory systems-procedural memory, priming, perceptual, and semantic memory-it develops the latest in phylogeny and ontogeny, and is the most vulnerable of the five systems, being easily impaired by brain damage and psychiatric disorders. Furthermore, it is characterized by its fragility and proneness to distortion due to environmental influences and subsequent information. On the brain level, a distinction has to be made between memory encoding and consolidating, memory storage, and memory retrieval. For encoding, structures of the limbic system, with the hippocampus in its center, are crucial, for storage of widespread cortical networks, and for retrieval again a distributed recollection network, in which the prefrontal cortex plays a crucial role, is engaged. Brain damage and psychiatric diseases can lead to what is called "focal retrograde amnesia." In this context, the clinical picture of dissociative or functional or psychogenic amnesia is central, as it may result in autobiographical-emotional amnesia of the total past with the consequence of an impairment of the self as well. The social environment therefore can have a major impact on the brain and on autobiographical-episodic memory processing. This article is categorized under: Psychology > Memory.

Comparative research on structure function recognition based on deep learning

PurposeThe research on structure function recognition mainly concentrates on identifying a specific part of academic literature and its applicability in the multidiscipline perspective. A specific part of academic literature, such as sentences, paragraphs and chapter contents are also called a level of academic literature in this paper. There are a few comparative research works on the relationship between models, disciplines and levels in the process of structure function recognition. In view of this, comparative research on structure function recognition based on deep learning has been conducted in this paper.Design/methodology/approachAn experimental corpus, including the academic literature of traditional Chinese medicine, library and information science, computer science, environmental science and phytology, was constructed. Meanwhile, deep learning models such as convolutional neural networks (CNN), long and short-term memory (LSTM) and bidirectional encoder representation from transformers (BERT) were used. The comparative experiments of structure function recognition were conducted with the help of the deep learning models from the multilevel perspective.FindingsThe experimental results showed that (1) the BERT model performed best, with F1 values of 78.02, 89.41 and 94.88%, respectively at the level of sentence, paragraph and chapter content. (2) The deep learning models performed better on the academic literature of traditional Chinese medicine than on other disciplines in most cases, e.g. F1 values of CNN, LSTM and BERT, respectively arrived at 71.14, 69.96 and 78.02% at the level of sentence. (3) The deep learning models performed better at the level of chapter content than other levels, the maximum F1 values of CNN, LSTM and BERT at 91.92, 74.90 and 94.88%, respectively. Furthermore, the confusion matrix of recognition results on the academic literature was introduced to find out the reason for misrecognition.Originality/valueThis paper may inspire other research on structure function recognition, and provide a valuable reference for the analysis of influencing factors.

Sensory suppression and increased neuromodulation during actions disrupt memory encoding of unpredictable self-initiated stimuli.

Actions modulate sensory processing by attenuating responses to self- compared to externally generated inputs, which is traditionally attributed to stimulus-specific motor predictions. Yet, suppression has been also found for stimuli merely coinciding with actions, pointing to unspecific processes that may be driven by neuromodulatory systems. Meanwhile, the differential processing for self-generated stimuli raises the possibility of producing effects also on memory for these stimuli; however, evidence remains mixed as to the direction of the effects. Here, we assessed the effects of actions on sensory processing and memory encoding of concomitant, but unpredictable sounds, using a combination of self-generation and memory recognition task concurrently with EEG and pupil recordings. At encoding, subjects performed button presses that half of the time generated a sound (motor-auditory; MA) and listened to passively presented sounds (auditory-only; A). At retrieval, two sounds were presented and participants had to respond which one was present before. We measured memory bias and memory performance by having sequences where either both or only one of the test sounds were presented at encoding, respectively. Results showed worse memory performance - but no differences in memory bias -, attenuated responses, and larger pupil diameter for MA compared to A sounds. Critically, the larger the sensory attenuation and pupil diameter, the worse the memory performance for MA sounds. Nevertheless, sensory attenuation did not correlate with pupil dilation. Collectively, our findings suggest that sensory attenuation and neuromodulatory processes coexist during actions, and both relate to disrupted memory for concurrent, albeit unpredictable sounds.

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 women, 18 men), 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.

Arousal-modulated memory encoding and retrieval in adults with autism spectrum disorder.

Recently, we have shown that pupil dilation during a recognition memory task can serve as an index of memory retrieval difficulties in autism. At the time of publication, we were unaware of specific data-analysis methods that can be used to shed further light on the origins of such memory related pupil dilation. Specifically, by distinguishing "tonic" from "phasic" changes in pupil dilation and considering their temporal progression, it is possible to draw inferences about the functional integrity of a locus coeruleus-norepinephrine system (LC-NE) that is known to play a key role in regulating memory encoding and retrieval processes. We therefore apply these analyses to our previously published eye-tracking data of adults with ASD (N=24) and neurotypical development (TD, N=30) during the recognition memory task. In this re-analysis, we related pupil dilation during encoding and retrieval to recognition accuracy in a per-trial analysis of linear mixed models. In ASD, we replicated attenuated recognition accuracy, which was accompanied by attenuated pupil dilation during encoding and retrieval. Group differences in pupil dilation during retrieval occurred late during the trial (after 1.75 s) and indicated an altered top-down processing like attenuated attribution of semantic salience in response to previously encoded stimuli. In addition, only in the ASD group were higher pupil dilation during encoding and lower pupil dilation during retrieval associated with decreased recognition accuracy. This supports altered modulation of memory encoding and retrieval in ASD, with LC-NE phasic activity as promising underlying mechanism. LAY SUMMARY: We investigated the changes of pupil size during memory testing in autism spectrum disorder. Adults with ASD remembered fewer items correctly than neurotypical individuals (TD). This reduced memory was related to increased pupillary responses at study and decreased pupil dilation at test only for adults with ASD indicating a different modulation of memory by the locus coeruleus.

ჰიპოკამპის გამა სიხშირის ოსცილაციების უჯრედული მექანიზმები

Gamma oscillations are known as cognitive rhythms due to their occurrence during the cognitive functions such as working memory, episodic memory, memory encoding and retrieval, sensory binding and attention. Gamma oscillations can be easily transferred into epileptic activity. Altered gamma rhythms are seen during the brain disorders such as schizophrenia, dementia and autism. Hence, studying the mechanisms of gamma rhythms is of great importance. Recent discoveries revealed new details of gamma oscillations. The classical view about the parvalbumin containing perisomatic basket cells that drives the gamma oscillation is valid for CA3 region of hippocampus but it may not be so for CA1 region. However, medial ganglionic eminence (MGE) derived axo-axonic cells action potential discharge follows the gamma rhythm in CA1 together with caudal ganglionic eminence (CGE) derived trilaminar and back-projecting interneurons. Oriense-Lacunosum-Moleculare (OLM) cells appear to have dual origine and can be modulated by gamma frequency. Using the modern technologies and relying on the current knowledge and new insights about neuronal elements in gamma frequency oscillation will help the scientists to study the mechanisms of cognitive rhythms in more details.

Functional connectivity with medial temporal regions differs across cultures during post-encoding rest.

Connectivity of the brain at rest can reflect individual differences and impact behavioral outcomes, including memory. The present study investigated how culture influences functional connectivity with regions of the medial temporal lobe. In this study, 46 Americans and 59 East Asians completed a resting state scan after encoding pictures of objects. To investigate cross-cultural differences in resting state functional connectivity, left parahippocampal gyrus (anterior and posterior regions) and left hippocampus were selected as seed regions. These regions were selected, because they were previously implicated in a study of cultural differences during the successful encoding of detailed memories. Results revealed that left posterior parahippocampal gyrus had stronger connectivity with temporo-occipital regions for East Asians compared with Americans and stronger connectivity with parieto-occipital regions for Americans compared with East Asians. Left anterior parahippocampal gyrus had stronger connectivity with temporal regions for East Asians than Americans and stronger connectivity with frontal regions for Americans than East Asians. Although connectivity did not relate to memory performance, patterns did relate to cultural values. The degree of independent self-construal and subjective value of tradition were associated with functional connectivity involving left anterior parahippocampal gyrus. Findings are discussed in terms of potential cultural differences in memory consolidation or more general trait or state-based processes, such as holistic versus analytic processing.

A missense mutation in Kcnc3 causes hippocampal learning deficits in mice

Although a wide variety of genetic tools has been developed to study learning and memory, the molecular basis of memory encoding remains incompletely understood. Here, we undertook an unbiased approach to identify novel genes critical for memory encoding. From a large-scale, invivo mutagenesis screen using contextual fear conditioning, we isolated in mice a mutant, named Clueless, with spatial learning deficits. A causative missense mutation (G434V) was found in the voltage-gated potassium channel, subfamily C member 3 (Kcnc3) gene in a region that encodes a transmembrane voltage sensor. Generation of a Kcnc3G434V CRISPR mutant mouse confirmed this mutation as the cause of the learning defects. While G434V had no effect on transcription, translation, or trafficking of the channel, electrophysiological analysis of the G434V mutant channel revealed a complete loss of voltage-gated conductance, a broadening of the action potential, and decreased neuronal firing. Together, our findings have revealed a role for Kcnc3 in learning and memory.

Post-Authorship Attribution Using Regularized Deep Neural Network

Post-authorship attribution is a scientific process of using stylometric features to identify the genuine writer of an online text snippet such as an email, blog, forum post, or chat log. It has useful applications in manifold domains, for instance, in a verification process to proactively detect misogynistic, misandrist, xenophobic, and abusive posts on the internet or social networks. The process assumes that texts can be characterized by sequences of words that agglutinate the functional and content lyrics of a writer. However, defining an appropriate characterization of text to capture the unique writing style of an author is a complex endeavor in the discipline of computational linguistics. Moreover, posts are typically short texts with obfuscating vocabularies that might impact the accuracy of authorship attribution. The vocabularies include idioms, onomatopoeias, homophones, phonemes, synonyms, acronyms, anaphora, and polysemy. The method of the regularized deep neural network (RDNN) is introduced in this paper to circumvent the intrinsic challenges of post-authorship attribution. It is based on a convolutional neural network, bidirectional long short-term memory encoder, and distributed highway network. The neural network was used to extract lexical stylometric features that are fed into the bidirectional encoder to extract a syntactic feature-vector representation. The feature vector was then supplied as input to the distributed high networks for regularization to minimize the network-generalization error. The regularized feature vector was ultimately passed to the bidirectional decoder to learn the writing style of an author. The feature-classification layer consists of a fully connected network and a SoftMax function to make the prediction. The RDNN method was tested against thirteen state-of-the-art methods using four benchmark experimental datasets to validate its performance. Experimental results have demonstrated the effectiveness of the method when compared to the existing state-of-the-art methods on three datasets while producing comparable results on one dataset.

HIGH DIMENSIONAL WEATHER DATA USED IN A DEEP GENERATIVE MODEL TO PREDICT TRAJECTORIES OF AIRCRAFT

The effectiveness of the aviation community depends on accurate forecasting of a 4D aircraft's trajectory, whether in real time or for counter-reality analysis. creating an effective tree-matching technique for the first time in this research to create feature maps that resemble images for historical flight trajectories using high- fidelity meteorological information, including wind, temperature, and convective conditions. Approach the orbit's tracking points as a conditional Gaussian mixture with parameters so they can benefit from our suggested integrated iterative neural network depth generation model. A network of mixed density LSTM decoders and a long memory (LSTM) encoder network make up the terminal. The decoder network learns additional spatial correlations-time from past flight routes and outputs the parameters of the Gaussian composite after the encoder network combines the most recent recorded flight plan information into fixed- length state variables. To learn feature representations from three-dimensional weather feature maps, transformation layers are added into the pipeline.

Agency enhances temporal order memory in an interactive exploration game.

Agency has been shown to facilitate episodic memory. However, most paradigms use simple list-learning tasks, which preclude the ability to characterize more associative forms of memory, such as binding of items into spatial and temporal context. Across two studies, we characterize the role of agency on associative memory formation. We delineate agentive from passive memory encoding by allowing agency participants to play an online text-based game meant to simulate free exploration of objects in different rooms and yoking each passive participant's trajectory to an agentive participant, thus equating their exposure to the stimuli. To assess memory differences, we gathered three measures: item descriptions, spatial location, and temporal order. While memory for spatial location and item features did not differ between groups, there was a marked enhancement of temporal order memory in the agentive group across two independent samples. These findings support a model of self-directed learning, in which agency facilitates the binding of items into a temporal context, which allows for the sequential binding of information into continuous narratives.

A synaptic signal for novelty processing in the hippocampus

Episodic memory formation and recall are complementary processes that rely on opposing neuronal computations in the hippocampus. How this conflict is resolved in hippocampal circuits is unclear. To address this question, we obtained in vivo whole-cell patch-clamp recordings from dentate gyrus granule cells in head-fixed mice trained to explore and distinguish between familiar and novel virtual environments. We find that granule cells consistently show a small transient depolarisation upon transition to a novel environment. This synaptic novelty signal is sensitive to local application of atropine, indicating that it depends on metabotropic acetylcholine receptors. A computational model suggests that the synaptic response to novelty may bias granule cell population activity, which can drive downstream attractor networks to a new state, favouring the switch from recall to new memory formation when faced with novelty. Such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Functional near-infrared spectroscopy of prefrontal cortex during memory encoding and recall in elderly with type 2 diabetes mellitus.

Low-frequency Fahræus-Lindqvist-driven oscillations in the small vessels are crucial because oscillations in small vessels support nutrient supply. Understanding of this is critical in type 2 diabetes mellitus (T2DM) to develop therapeutic measures in order to prevent Alzheimer's Disease Related Dementias. Indeed, vascular factors are known to contribute to cerebrovascular disease as well as mild cognitive impairment and dementia, which are predicted to affect 152 million people by 2050 (Alzheimer's Disease International London, UK, 2019). In this clinical study, we performed functional near-infrared spectroscopy (fNIRS) of the forehead to investigate the effect of the Mini-Cog with three-item recall test on the prefrontal cortex (PFC) activation and the relative oscillatory power in the 0.01-0.02-Hz (FahræΣus-Lindqvist effect) and 0.021-0.052 Hz (smooth muscle autonomic innervation) frequency bands in elderly (60 years and older) T2DM and age-matched controls. We found a significant (p<0.01) difference in the PFC activation between elderly subjects with T2DM and age-matched elderly controls. Moreover, power spectral density (PSD) analysis revealed a significantly lower relative power in 0.021-0.052 Hz (smooth muscle autonomic innervation) frequency band in elderly subjects with T2DM during the Mini-Cog three-item recall test. Furthermore, a drop in the oscillatory power in the 0.01-0.02 Hz frequency band during Mini-Cog three-item recall test was found more pronounced in the elderly subjects with T2DM. Therefore, our study highlighted portable brain imaging to capture cerebrovascular reactivity to cognitive load that may provide a biomarker of cerebrovascular dysfunction in T2DM. Clinical Relevance-Our study establishes forehead portable brain imaging under cognitive load for monitoring cerebrovascular function in T2DM.

Hippocampal and motor regions contribute to memory benefits after enacted encoding: cross-sectional and longitudinal evidence.

The neurobiological underpinnings of action-related episodic memory and how enactment contributes to efficient memory encoding are not well understood. We examine whether individual differences in level (n = 338) and 5-year change (n = 248) in the ability to benefit from motor involvement during memory encoding are related to gray matter (GM) volume, white matter (WM) integrity, and dopamine-regulating genes in a population-based cohort (age range = 25-80years). A latent profile analysis identified 2 groups with similar performance on verbal encoding but with marked differences in the ability to benefit from motor involvement during memory encoding. Impaired ability to benefit from enactment was paired with smaller HC, parahippocampal, and putamen volume along with lower WM microstructure in the fornix. Individuals with reduced ability to benefit from encoding enactment over 5years were characterized by reduced HC and motor cortex GM volume along with reduced WM microstructure in several WM tracts. Moreover, the proportion of catechol-O-methyltransferase-Val-carriers differed significantly between classes identified from the latent-profile analysis. These results provide converging evidence that individuals with low or declining ability to benefit from motor involvement during memory encoding are characterized by low and reduced GM volume in regions critical for memory and motor functions along with altered WM microstructure.

We Know You Are Living in Bali: Location Prediction of Twitter Users Using BERT Language Model

Twitter user location data provide essential information that can be used for various purposes. However, user location is not easy to identify because many profiles omit this information, or users enter data that do not correspond to their actual locations. Several related works attempted to predict location on English-language tweets. In this study, we attempted to predict the location of Indonesian tweets. We utilized machine learning approaches, i.e., long-short term memory (LSTM) and bidirectional encoder representations from transformers (BERT) to infer Twitter users’ home locations using display name in profile, user description, and user tweets. By concatenating display name, description, and aggregated tweet, the model achieved the best accuracy of 0.77. The performance of the IndoBERT model outperformed several baseline models.

Widespread ripples synchronize human cortical activity during sleep, waking, and memory recall

Declarative memory encoding, consolidation, and retrieval require the integration of elements encoded in widespread cortical locations. The mechanism whereby such "binding" of different components of mental events into unified representations occurs is unknown. The "binding-by-synchrony" theory proposes that distributed encoding areas are bound by synchronous oscillations enabling enhanced communication. However, evidence for such oscillations is sparse. Brief high-frequency oscillations ("ripples") occur in the hippocampus and cortex and help organize memory recall and consolidation. Here, using intracranial recordings in humans, we report that these ∼70-ms-duration, 90-Hz ripples often couple (within ±500 ms), co-occur (≥ 25-ms overlap), and, crucially, phase-lock (have consistent phase lags) between widely distributed focal cortical locations during both sleep and waking, even between hemispheres. Cortical ripple co-occurrence is facilitated through activation across multiple sites, and phase locking increases with more cortical sites corippling. Ripples in all cortical areas co-occur with hippocampal ripples but do not phase-lock with them, further suggesting that cortico-cortical synchrony is mediated by cortico-cortical connections. Ripple phase lags vary across sleep nights, consistent with participation in different networks. During waking, we show that hippocampo-cortical and cortico-cortical coripples increase preceding successful delayed memory recall, when binding between the cue and response is essential. Ripples increase and phase-modulate unit firing, and coripples increase high-frequency correlations between areas, suggesting synchronized unit spiking facilitating information exchange. co-occurrence, phase synchrony, and high-frequency correlation are maintained with little decrement over very long distances (25 cm). Hippocampo-cortico-cortical coripples appear to possess the essential properties necessary to support binding by synchrony during memory retrieval and perhaps generally in cognition.

Hotspot of human verbal memory encoding in the left anterior prefrontal cortex.

SummaryBackgroundTreating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation.MethodsThe areas that are critical for successful encoding of verbal memory as well as the underlying neural activities were determined directly in the human brain with intracranial electrophysiological recordings in epilepsy patients. We recorded a broad range of spectral activities across the cortex of 135 patients as they memorised word lists for subsequent free recall.FindingsThe greatest differences in the spectral power between encoding subsequently recalled and forgotten words were found in low theta frequency (3–5 Hz) activities of the left anterior prefrontal cortex. This subsequent memory effect was proportionally greater in the lower frequency bands and in the more anterior cortical regions. We found the peak of this memory signal in a distinct part of the prefrontal cortex at the junction between the Broca's area and the frontal pole. The memory effect in this confined area was significantly higher (Tukey–Kramer test, p<0.05) than in other anatomically distinct areas.InterpretationOur results suggest a focal hotspot of human verbal memory encoding located in the higher-order processing region of the prefrontal cortex, which presents a prospective target for modulating cognitive functions in the human patients. The memory effect provides an electrophysiological biomarker of low frequency neural activities, at distinct times of memory encoding, and in one hotspot location in the human brain.FundingOpen-access datasets were originally collected as part of a BRAIN Initiative project called Restoring Active Memory (RAM) funded by the Defence Advanced Research Project Agency (DARPA). CT, ML, MTK and this research were supported from the First Team grant of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund.

Neural Oscillations in Aversively Motivated Behavior.

Fear and anxiety-based disorders are highly debilitating and among the most prevalent psychiatric disorders. These disorders are associated with abnormal network oscillations in the brain, yet a comprehensive understanding of the role of network oscillations in the regulation of aversively motivated behavior is lacking. In this review, we examine the oscillatory correlates of fear and anxiety with a particular focus on rhythms in the theta and gamma-range. First, we describe neural oscillations and their link to neural function by detailing the role of well-studied theta and gamma rhythms to spatial and memory functions of the hippocampus. We then describe how theta and gamma oscillations act to synchronize brain structures to guide adaptive fear and anxiety-like behavior. In short, that hippocampal network oscillations act to integrate spatial information with motivationally salient information from the amygdala during states of anxiety before routing this information via theta oscillations to appropriate target regions, such as the prefrontal cortex. Moreover, theta and gamma oscillations develop in the amygdala and neocortical areas during the encoding of fear memories, and interregional synchronization reflects the retrieval of both recent and remotely encoded fear memories. Finally, we argue that the thalamic nucleus reuniens represents a key node synchronizing prefrontal-hippocampal theta dynamics for the retrieval of episodic extinction memories in the hippocampus.

2022 Practice Census Shows Impact of COVID-19 Pandemic on Hair Restoration

Our ability to focus attention on task-relevant information and ignore distractions is reflected by differential enhancement and suppression of neural activity in sensory cortex (i.e., top-down modulation). Such selective, goal-directed modulation of activity may be intimately related to memory, such that the focus of attention biases the likelihood of successfully maintaining relevant information by limiting interference from irrelevant stimuli. Despite recent studies elucidating the mechanistic overlap between attention and memory, the relationship between top-down modulation of visual processing during working memory (WM) encoding, and subsequent recognition performance has not yet been established. Here, we provide neurophysiological evidence in healthy, young adults that top-down modulation of early visual processing (&lt; 200 ms from stimulus onset) is intimately related to subsequent WM performance, such that the likelihood of successfully remembering relevant information is associated with limiting interference from irrelevant stimuli. The consequences of a failure to ignore distractors on recognition performance was replicated for two types of feature-based memory, motion direction and color. Moreover, attention to irrelevant stimuli was reflected neurally during the WM maintenance period as an increased memory load. These results suggest that neural enhancement of relevant information is not the primary determinant of high-level performance, but rather optimal WM performance is dependent on effectively filtering irrelevant information through neural suppression to prevent overloading a limited memory capacity.

More elaborate processing of own-race faces and less elaborate processing of other-race faces contribute to the other-race effect in face memory.

Research suggests that own-race faces are naturally memorized in a more elaborate (e.g., many features of a face or the whole face) way, whereas other-race faces are memorized in a less elaborate (e.g., only selected features of the face) manner. Here, we tested if instructions for judgements about the whole face and a single facial feature modulated the other-race effect in face memory. White participants performed whole-face and single-feature tasks while memorizing White and Black faces for later recognition. Encoding instructions had a stronger impact on own-race than other-race faces. Whole-face instructions increased the other-race effect, whereas single-feature instructions decreased it. Own-race faces in the whole-face task demonstrated event-related potential (ERP) patterns of memory encoding comparable to previously observed natural memory encoding, suggesting naturally more elaborate encoding of own-race faces. ERPs of memory encoding for other-race faces were similar between task conditions and comparable to previously observed natural encoding patterns, suggesting naturally less elaborate encoding. No impact of the encoding tasks was found on ERPs related to memory retrieval, which may be an artefact of a perceptual task that does not enhance semantic details in memory. The current results indicate that some contributions to the other-race effect are more elaborate (more detailed) memory encoding for own-race faces and less elaborate (less detailed) memory encoding for other-race faces. This study also provides evidence for more malleability of own-race than other-race faces through task instructions, consistent with assumptions of perceptual learning theories of the other-race effect.