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Models of visual cognition generally assume that brain networks predict the contents of a stimulus to facilitate its subsequent categorization. However, understanding prediction and categorization at a network level has remained challenging, partly because we need to reverse engineer their information processing mechanisms from the dynamic neural signals. Here, we used connectivity measures that can isolate the communications of a specific content to reconstruct these network mechanisms in each individual participant (N = 11, both sexes). Each was cued to the spatial location (left vs right) and contents [low spatial frequency (LSF) vs high spatial frequency (HSF)] of a predicted Gabor stimulus that they then categorized. Using each participant's concurrently measured MEG, we reconstructed networks that predict and categorize LSF versus HSF contents for behavior. We found that predicted contents flexibly propagate top down from temporal to lateralized occipital cortex, depending on task demands, under supervisory control of prefrontal cortex. When they reach lateralized occipital cortex, predictions enhance the bottom-up LSF versus HSF representations of the stimulus, all the way from occipital-ventral-parietal to premotor cortex, in turn producing faster categorization behavior. Importantly, content communications are subsets (i.e., 55-75%) of the signal-to-signal communications typically measured between brain regions. Hence, our study isolates functional networks that process the information of cognitive functions.SIGNIFICANCE STATEMENT An enduring cognitive hypothesis states that our perception is partly influenced by the bottom-up sensory input but also by top-down expectations. However, cognitive explanations of the dynamic brain networks mechanisms that flexibly predict and categorize the visual input according to task-demands remain elusive. We addressed them in a predictive experimental design by isolating the network communications of cognitive contents from all other communications. Our methods revealed a Prediction Network that flexibly communicates contents from temporal to lateralized occipital cortex, with explicit frontal control, and an occipital-ventral-parietal-frontal Categorization Network that represents more sharply the predicted contents from the shown stimulus, leading to faster behavior. Our framework and results therefore shed a new light of cognitive information processing on dynamic brain activity.
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Mapeamento Encefálico , Imageamento por Ressonância Magnética , Masculino , Feminino , Humanos , Lobo Occipital , Encéfalo , Cognição , Estimulação Luminosa , Percepção VisualRESUMO
The electronic states of metal catalysts can be redistributed by the rectifying contact between metal and semiconductor e.g., N-doped carbon (NC), while the interfacial regulation degree is very limited. Herein, a deep electronic state regulation is achieved by constructing a novel double-heterojunctional Co/Co3O4@NC catalyst containing Co/Co3O4 and Co3O4/NC heterojunctions. When used for dilute electrochemical NO3 - reduction reaction (NO3RR), the as-prepared Co/Co3O4@NC exhibits an outstanding Faradaic efficiency for NH3 formation (FENH3) of 97.9%, -0.4 V versus RHE and significant NH3 yield of 303.5 mmol h-1 gcat -1 at -0.6 V at extremely low nitrate concentrations (100 ppm NO3 --N). Experimental and theoretical results reveal that the dual junctions of Co/Co3O4 and Co3O4/NC drive a unidirectional electron transfer from Co to NC (CoâCo3O4âNC), resulting in electron-deficient Co atoms. The electron-deficient Co promotes NO3 - adsorption, the rate-determining step (RDS) for NO3RR, facilitating the dilute NO3RR to NH3. The design strategy provides a novel reference for unidirectional multistage regulation of metal electronic states boosting electrochemical dilute NO3RR, which opens up an avenue for deep electronic state regulation of electrocatalyst breaking the limitation of the electronic regulation degree by rectifying contact.
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Electrochemically converting NO3 - into NH3 offers a promising route for water treatment. Nevertheless, electroreduction of dilute NO3 - is still suffering from low activity and/or selectivity. Herein, B as a modifier was introduced to tune electronic states of Cu and further regulate the performance of electrochemical NO3 - reduction reaction (NO3 RR) with dilute NO3 - concentration (≤100â ppm NO3 - -N). Notably, a linear relationship was established by plotting NH3 yield vs. the oxidation state of Cu, indicating that the increase of Cu+ content leads to an enhanced NO3 - -to-NH3 conversion activity. Under a low NO3 - -N concentration of 100â ppm, the optimal Cu(B) catalyst displays a 100 % NO3 - -to-NH3 conversion at -0.55 to -0.6â V vs. RHE, and a record-high NH3 yield of 309â mmol h-1 gcat -1 , which is more than 25â times compared with the pristine Cu nanoparticles (12â mmol h-1 gcat -1 ). This research provides an effective method for conversion of dilute NO3 - to NH3 , which has certain guiding significance for the efficient and green conversion of wastewater in the future.
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We developed a tandem electrocatalyst for CO2 -to-CO conversion comprising the single Cu site co-coordinated with N and S anchored carbon matrix (Cu-S1 N3 ) and atomically dispersed Cu clusters (Cux ), denoted as Cu-S1 N3 /Cux . The as-prepared Cu-S1 N3 /Cux composite presents a 100 % Faradaic efficiency towards CO generation (FECO ) at -0.65â V vs. RHE and high FECO over 90 % from -0.55 to -0.75â V, outperforming the analogues with Cu-N4 (FECO only 54 % at -0.7â V) and Cu-S1 N3 (FECO 70 % at -0.7â V) configurations. The unsymmetrical Cu-S1 N3 atomic interface in the carbon basal plane possesses an optimized binding energy for the key intermediate *COOH compared with Cu-N4 site. At the same time, the adjacent Cux effectively promotes the protonation of *CO2 - by accelerating water dissociation and offering *H to the Cu-S1 N3 active sites. This work provides a tandem strategy for facilitating proton-coupled electron transfer over the atomic-level catalytic sites.
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Communication involves successfully deriving a speaker's meaning beyond the literal expression. Using fMRI, it was investigated how the listener's brain realizes distinctions between enrichment-based meanings and literal semantic meanings. The neural patterns of the Mandarin scalar quantifier you-de (similar to some in English) which implies the meanings not all and not most via scalar enrichment, with the specific quantifier shao-shu-de (similar to less than half in English) which lexico-semantically encodes the meanings not all and not most, were compared. Listeners heard sentences using either quantifier, paired with pictures in which either less than half, more than half, or all of the people depicted in the picture were doing the described activity; thus, the conditions included both implicature-based and semantics-based picture-sentence mismatches. Imaging results showed bilateral ventral IFG was activated for both kinds of mismatch, whereas basal ganglia and left dorsal IFG were activated uniquely for implicature-based mismatch. These findings suggest that resolving conflicts involving inferential aspects of meaning employs different neural mechanisms than the processing based on literal semantic meaning, and that the dorsal prefrontal/basal ganglia pathway makes a contribution to implicature-based interpretation. Furthermore, within the implicature-based conditions, different neural generators were implicated in the processing of strong implicature mismatch (you-de in the context of a picture in which "all" would have been true) and weak implicature mismatch (you-de in the context of a picture in which "most" would have been true), which may have important implications for theories of pragmatic comprehension. Hum Brain Mapp 38:3848-3864, 2017. © 2017 Wiley Periodicals, Inc.
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Encéfalo/fisiologia , Compreensão/fisiologia , Reconhecimento Visual de Modelos/fisiologia , Percepção da Fala/fisiologia , Adolescente , Adulto , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Feminino , Humanos , Modelos Lineares , Imageamento por Ressonância Magnética , Masculino , Testes Neuropsicológicos , Semântica , Adulto JovemRESUMO
Iron phthalocyanine (FePc) is an attractive nonprecious metal candidate for electrocatalytic oxygen reduction reaction (ORR). However, its low catalytic performance under acidic and neutral conditions limits its practical application. Herein, the FePc-based covalent organic polymers (COPFePc) polymerized in situ on the functionalized multiwalled carbon nanotubes (R-MWCNT) containing different electron-withdrawing or electron-donating groups (COPFePc/R-MWCNT, R = COOH, OH or NH2) were synthesized for ORR. Among them, COPFePc/COOH-MWCNT exhibited the best ORR performance under pH-universal conditions (acidic, neutral, and alkaline). Density-functional theory (DFT) calculations demonstrate that the electron-withdrawing or electron-donating effect of the functional groups in COPFePc/R-MWCNT causes charge redistribution of the active center Fe. The COOH functional group with an electron-withdrawing ability shifts the d-band center of Fe away from the Fermi energy level and reduces the binding strength of oxygen-containing intermediates, accelerating the ORR kinetics and optimizing the catalytic activity.
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The compressive performance of organic fiber has always been a key problem, limiting its development. In this paper, silicon oxide, alumina, and titanium oxide particles were separately deposited on the surface of high-strength and high-modulus polyimide (PI) fibers to form a structural supporting shell by using a magnetron sputtering method. The theoretical thickness was calculated by thermogravimetric analysis in good agreement with the actual thickness determined from scanning electron microscopy. The mechanics, surface, and interface properties of the measured fibers were analyzed mainly from the aspects of surface energy, interfacial shear strength (IFSS), and compression strength. The results showed that after magnetron sputtering, the inorganic shells were uniformly deposited on the surface of PI fiber, resulting in an increase in the content of inorganic elements as well as the roughness. As a result, the surface energy and IFSS of silica-coated fiber was increased by 174 and 85.6%, respectively, and compression strength was increased by 45.7%. This study provides a new approach for improving the interface property and compression strength of high-strength and high-modulus PI-fiber-reinforced composites.
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To interpret our surroundings, the brain uses a visual categorization process. Current theories and models suggest that this process comprises a hierarchy of different computations that transforms complex, high-dimensional inputs into lower-dimensional representations (i.e., manifolds) in support of multiple categorization behaviors. Here, we tested this hypothesis by analyzing these transformations reflected in dynamic MEG source activity while individual participants actively categorized the same stimuli according to different tasks: face expression, face gender, pedestrian gender, and vehicle type. Results reveal three transformation stages guided by the pre-frontal cortex. At stage 1 (high-dimensional, 50-120 ms), occipital sources represent both task-relevant and task-irrelevant stimulus features; task-relevant features advance into higher ventral/dorsal regions, whereas task-irrelevant features halt at the occipital-temporal junction. At stage 2 (121-150 ms), stimulus feature representations reduce to lower-dimensional manifolds, which then transform into the task-relevant features underlying categorization behavior over stage 3 (161-350 ms). Our findings shed light on how the brain's network mechanisms transform high-dimensional inputs into specific feature manifolds that support multiple categorization behaviors.
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Lobo Occipital , Humanos , Masculino , Feminino , Adulto , Lobo Occipital/fisiologia , Adulto Jovem , Córtex Pré-Frontal/fisiologia , MagnetoencefalografiaRESUMO
Social class is a powerful hierarchy that determines many privileges and disadvantages. People form impressions of others' social class (like other important social attributes) from facial appearance, and these impressions correlate with stereotype judgments. However, what drives these related subjective judgments remains unknown. That is, what makes someone look like they are of higher or lower social class standing (e.g., rich or poor), and how does this relate to harmful or advantageous stereotypes? We addressed these questions using a perception-based data-driven method to model the specific three-dimensional facial features that drive social class judgments and compared them to those of stereotype-related judgments (competence, warmth, dominance, and trustworthiness), based on White Western culture participants and face stimuli. Using a complementary data-reduction analysis and machine learning approach, we show that social class judgments are driven by a unique constellation of facial features that reflect multiple embedded stereotypes: poor-looking (vs. rich-looking) faces are wider, shorter, and flatter with downturned mouths and darker, cooler complexions, mirroring features of incompetent, cold, and untrustworthy-looking (vs. competent, warm, and trustworthy-looking) faces. Our results reveal the specific facial features that underlie the connection between impressions of social class and stereotype-related social traits, with implications for central social perception theories, including understanding the causal links between stereotype knowledge and social class judgments. We anticipate that our results will inform future interventions designed to interrupt biased perception and social inequalities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Reconhecimento Facial , Estereotipagem , Humanos , Percepção Social , Atitude , Julgamento , Classe Social , Expressão Facial , ConfiançaRESUMO
Precise electronic state regulation through coordination environment optimization by metal-support interaction is a promising strategy to facilitate catalysis reaction, while the limited density of functional groups in the bulk substrate restricts the regulation degree. Herein, different sizes of Ti3C2Tx MXene with hydroxyl (-OH) terminal including the MXene layer (ML-OH, 3 µm), the MXene nanosheet (MNS-OH, 600 nm), and the MXene quantum dot (MQD-OH, 8 nm) were prepared to anchor CoPc, and the effect of -OH density on the performance of electrochemical CO2 reduction was systematically investigated. Notably, a linear relationship was established by plotting reactivity vs hydroxyl density. With the highest -OH density, CoPc/MQD-OH exhibits a superior Faradaic efficiency for CO formation (FECO) of â¼100% at -0.9 to -1.0 V vs RHE and a high FECO of >90% over a wide potential window from -0.8 to -1.4 V. The mechanism exploration shows that the axial coordination interaction of the -OH terminal with Co increases the electron density of the Co site, thus promoting the adsorption and activation of CO2. This work provides a new insight into designing of molecular catalysts with high efficiency and tunable structure for other electrochemical conversions.
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Unidirectional cascade electron transfer induced by multi-junctions is essential for deep electronic state regulation of the catalytic active sites, while this advanced concept has rarely been investigated in the field of electrocatalysis. In the present work, a dual junction heterostructure (FePc/L-R/CN) is designed by anchoring iron phthalocyanine (FePc)/MXene (L-Ti3 C2 -R, RâOH or F) heterojunction on g-C3 N4 nanosheet substrates for electrocatalysis. The unidirectional cascade electron transfer (g-C3 N4 â L-Ti3 C2 -R â FePc) induced by the dual junction of FePc/L-Ti3 C2 -R and L-Ti3 C2 -R/g-C3 N4 makes the Fe center electron-rich and therefore facilitates the adsorption of O2 in the oxygen reduction reaction (ORR). Moreover, the electron transfer between FePc and MXene is facilitated by the axial FeâO coordination interaction of Fe with the OH in alkalized MXene nanosheets (L-Ti3 C2 -OH). As a result, FePc/L-OH/CN exhibits an impressive ORR activity with a half-wave potential (E1/2 ) of 0.92 V, which is superior over the catalysts with a single junction and the state-of-the-art Pt/C (E1/2 = 0.85 V). This work provides a broad idea for deep regulation of electronic state by the unidirectional cascade multi-step charge transfer and can be extended to other proton-coupled electron transfer processes.
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Prediction-for-perception theories suggest that the brain predicts incoming stimuli to facilitate their categorization.1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17 However, it remains unknown what the information contents of these predictions are, which hinders mechanistic explanations. This is because typical approaches cast predictions as an underconstrained contrast between two categories18,19,20,21,22,23,24-e.g., faces versus cars, which could lead to predictions of features specific to faces or cars, or features from both categories. Here, to pinpoint the information contents of predictions and thus their mechanistic processing in the brain, we identified the features that enable two different categorical perceptions of the same stimuli. We then trained multivariate classifiers to discern, from dynamic MEG brain responses, the features tied to each perception. With an auditory cueing design, we reveal where, when, and how the brain reactivates visual category features (versus the typical category contrast) before the stimulus is shown. We demonstrate that the predictions of category features have a more direct influence (bias) on subsequent decision behavior in participants than the typical category contrast. Specifically, these predictions are more precisely localized in the brain (lateralized), are more specifically driven by the auditory cues, and their reactivation strength before a stimulus presentation exerts a greater bias on how the individual participant later categorizes this stimulus. By characterizing the specific information contents that the brain predicts and then processes, our findings provide new insights into the brain's mechanisms of prediction for perception.
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Encéfalo , Sinais (Psicologia) , Humanos , Encéfalo/fisiologia , Mapeamento Encefálico , Estimulação LuminosaRESUMO
Herein, we report a facile strategy for constructing hybrid coordination configurations by combining functionalized graphene quantum dots (GQDs) with CoPc (CoPc/R-GQDs, with R being -NH2 or -OH) for electrochemical CO2 reduction. Benefiting from the high density of functional groups that can be provided by GQDs and the strong electron-donating property of -NH2, the examined CoPc/NH2-GQDs achieved a 100% faradaic efficiency for CO formation (FECO) at -0.8 to -0.9 V vs. RHE, and high FECO (over 90%) over a wide potential range of 500 mV. This work has presented a novel approach for catalyst design, specifically involving molecular engineering of quantum dots, which can also be applied to other essential electrochemical reactions.
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Background: Microvascular damage is a key pathological factor in acute lower limb ischemia/reperfusion (I/R) injury. Current evidence suggests that sulforaphane (SFN) protects tissue from I/R injury. However, the role of SFN in acute lower limb I/R injury remains elusive. This study aimed to investigate the role and potential mechanism of SFN in I/R-related microvascular damage in the limb. Methods: Limb viability was evaluated by laser Doppler imaging, tissue edema analysis and histological analysis. Western blotting and immunofluorescence were applied to analyze the levels of apoptosis, oxidative stress, autophagy, transcription factor EB (TFEB) activity and mucolipin 1 (MCOLN1)-calcineurin signaling pathway. Results: SFN administration significantly ameliorated I/R-induced hypoperfusion, tissue edema, skeletal muscle fiber injury and endothelial cell (EC) damage in the limb. Pharmacological inhibition of NFE2L2 (nuclear factor, erythroid 2 like 2) reversed the anti-oxidation and anti-apoptosis effects of SFN on ECs. Additionally, silencing of TFEB by interfering RNA abolished the SFN-induced autophagy restoration, anti-oxidant response and anti-apoptosis effects on ECs. Furthermore, silencing of MCOLN1 by interfering RNA and pharmacological inhibition of calcineurin inhibited the activity of TFEB induced by SFN, demonstrating that SFN regulates the activity of TFEB through the MCOLN1-calcineurin signaling pathway. Conclusion: SFN protects microvascular ECs against I/R injury by TFEB-mediated autophagy restoration and anti-oxidant response.
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Antioxidantes , Traumatismo por Reperfusão , Camundongos , Animais , Antioxidantes/metabolismo , Células Endoteliais/metabolismo , Calcineurina , Isotiocianatos/farmacologia , RNA , Fator 2 Relacionado a NF-E2/genética , Fator 2 Relacionado a NF-E2/metabolismo , Traumatismo por Reperfusão/tratamento farmacológico , Isquemia/tratamento farmacológico , Extremidade InferiorRESUMO
An essential pathogenic element of acute limb ischemia/reperfusion (I/R) injury is microvascular dysfunction. The majority of studies indicates that fibroblast growth factor 2 (FGF2) exhibits protective properties in cases of acute I/R injury. Albeit its specific role in the context of acute limb I/R injury is yet unknown. An impressive post-reperfusion increase in FGF2 expression was seen in a mouse model of hind limb I/R, followed by a decline to baseline levels, suggesting a key role for FGF2 in limb survivability. FGF2 appeared to reduce I/R-induced hypoperfusion, tissue edema, skeletal muscle fiber injury, as well as microvascular endothelial cells (ECs) damage within the limb, according to assessments of limb vitality, Western blotting, and immunofluorescence results. The bioinformatics analysis of RNA-sequencing revealed that ferroptosis played a key role in FGF2-facilitated limb preservation. Pharmacological inhibition of NFE2L2 prevented ECs from being affected by FGF2's anti-oxidative and anti-ferroptosis activities. Additionally, silencing of kruppel-like factor 2 (KLF2) by interfering RNA eliminated the antioxidant and anti-ferroptosis effects of FGF2 on ECs. Further research revealed that the AMPK-HDAC5 signal pathway is the mechanism via which FGF2 regulates KLF2 activity. Data from luciferase assays demonstrated that overexpression of HDAC5 prevented KLF2 from becoming activated by FGF2. Collectively, FGF2 protects microvascular ECs from I/R injury by KLF2-mediated ferroptosis inhibition and antioxidant responses.
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Fator 2 de Crescimento de Fibroblastos , Traumatismo por Reperfusão , Animais , Camundongos , Antioxidantes , Western Blotting , Células Endoteliais , Fator 2 de Crescimento de Fibroblastos/genética , Traumatismo por Reperfusão/genéticaRESUMO
Deep neural networks (DNNs) can resolve real-world categorization tasks with apparent human-level performance. However, true equivalence of behavioral performance between humans and their DNN models requires that their internal mechanisms process equivalent features of the stimulus. To develop such feature equivalence, our methodology leveraged an interpretable and experimentally controlled generative model of the stimuli (realistic three-dimensional textured faces). Humans rated the similarity of randomly generated faces to four familiar identities. We predicted these similarity ratings from the activations of five DNNs trained with different optimization objectives. Using information theoretic redundancy, reverse correlation, and the testing of generalization gradients, we show that DNN predictions of human behavior improve because their shape and texture features overlap with those that subsume human behavior. Thus, we must equate the functional features that subsume the behavioral performances of the brain and its models before comparing where, when, and how these features are processed.
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Carbon-based single-atom catalysts (SACs) with well-defined and homogeneously dispersed metal-N4 moieties provide a great opportunity for CO2 reduction. However, controlling the binding strength of various reactive intermediates on catalyst surface is necessary to enhance the selectivity to a desired product, and it is still a challenge. In this work, the authors prepared Sn SACs consisting of atomically dispersed SnN3 O1 active sites supported on N-rich carbon matrix (Sn-NOC) for efficient electrochemical CO2 reduction. Contrary to the classic Sn-N4 configuration which gives HCOOH and H2 as the predominant products, Sn-NOC with asymmetric atomic interface of SnN3 O1 gives CO as the exclusive product. Experimental results and density functional theory calculations show that the atomic arrangement of SnN3 O1 reduces the activation energy for *COO and *COOH formation, while increasing energy barrier for HCOO* formation significantly, thereby facilitating CO2 -to-CO conversion and suppressing HCOOH production. This work provides a new way for enhancing the selectivity to a specific product by controlling individually the binding strength of each reactive intermediate on catalyst surface.
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Facial attractiveness confers considerable advantages in social interactions,1,2 with preferences likely reflecting psychobiological mechanisms shaped by natural selection. Theories of universal beauty propose that attractive faces comprise features that are closer to the population average3 while optimizing sexual dimorphism.4 However, emerging evidence questions this model as an accurate representation of facial attractiveness,5-7 including representing the diversity of beauty preferences within and across cultures.8-12 Here, we demonstrate that Western Europeans (WEs) and East Asians (EAs) evaluate facial beauty using culture-specific features, contradicting theories of universality. With a data-driven method, we modeled, at both the individual and group levels, the attractive face features of young females (25 years old) in two matched groups each of 40 young male WE and EA participants. Specifically, we generated a broad range of same- and other-ethnicity female faces with naturally varying shapes and complexions. Participants rated each on attractiveness. We then reverse correlated the face features that drive perception of attractiveness in each participant. From these individual face models, we reconstructed a facial attractiveness representation space that explains preference variations. We show that facial attractiveness is distinct both from averageness and from sexual dimorphism in both cultures. Finally, we disentangled attractive face features into those shared across cultures, culture specific, and specific to individual participants, thereby revealing their diversity. Our results have direct theoretical and methodological impact for representing diversity in social perception and for the design of culturally and ethnically sensitive socially interactive digital agents.
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Beleza , Cultura , Face , Adulto , Povo Asiático , Feminino , Humanos , Masculino , Caracteres Sexuais , População BrancaRESUMO
Hybrid layers consisting of copper nanoparticles and polyimide have been successfully fabricated using copper nitrate as the copper precursor and pyromellitic dianhydride/oxydianiline-(PMDA/ODA-) based polyimide films as the substrate. The fabrication method relies on the potassium hydroxide-induced chemical modification of the polyimide surface to introduce carboxylic acid groups, the incorporation of copper ions through subsequent ion exchange reaction, and followed by the polyol in situ reduction of copper ions contained polyimide layers in ethylene glycol solution at 197 degrees C. The amount of copper ions in the modified layer strongly depended on the ion exchange time. The copper nanoparticles size changed from 3 nm to 27 nm when the reduction time increased from 5 min to 30 min. These experiments provided an efficient route for copper metallization of polyimide substrate. The detailed reaction progress and resulted films were characterized by Attenuated total reflection-Fourier transform infrared, X-ray photoelectron spectroscopy, inductively coupled plasma atomic emission spectrometer, X-ray diffraction, transmission and scanning electron microscope.
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The information contents of memory are the cornerstone of the most influential models in cognition. To illustrate, consider that in predictive coding, a prediction implies that specific information is propagated down from memory through the visual hierarchy. Likewise, recognizing the input implies that sequentially accrued sensory evidence is successfully matched with memorized information (categorical knowledge). Although the existing models of prediction, memory, sensory representation and categorical decision are all implicitly cast within an information processing framework, it remains a challenge to precisely specify what this information is, and therefore where, when and how the architecture of the brain dynamically processes it to produce behaviour. Here, we review a framework that addresses these challenges for the studies of perception and categorization-stimulus information representation (SIR). We illustrate how SIR can reverse engineer the information contents of memory from behavioural and brain measures in the context of specific cognitive tasks that involve memory. We discuss two specific lessons from this approach that generally apply to memory studies: the importance of task, to constrain what the brain does, and of stimulus variations, to identify the specific information contents that are memorized, predicted, recalled and replayed. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.