Following the crowd: brain substrates of long-term memory conformity.
Ontology highlight
ABSTRACT:
SUBMITTER: Edelson M
PROVIDER: S-EPMC3284232 | biostudies-literature | 2011 Jul
REPOSITORIES: biostudies-literature
Publications
Following the crowd: brain substrates of long-term memory conformity.
Edelson Micah M Sharot Tali T Dolan Raymond J RJ Dudai Yadin Y
Science (New York, N.Y.) 20110701 6038
Human memory is strikingly susceptible to social influences, yet we know little about the underlying mechanisms. We examined how socially induced memory errors are generated in the brain by studying the memory of individuals exposed to recollections of others. Participants exhibited a strong tendency to conform to erroneous recollections of the group, producing both long-lasting and temporary errors, even when their initial memory was strong and accurate. Functional brain imaging revealed that s ...[more]
Similar Datasets
Project description:Murine cytomegalovirus (MCMV) brain infection stimulates microglial cell-driven proinflammatory chemokine production which precedes the presence of brain-infiltrating systemic immune cells. Here, we show that in response to MCMV brain infection, antigen-specific CD8(+) T cells migrated into the brain and persisted as long-lived memory cells. The role of these persistent T cells in the brain is unclear because most of our understanding of antimicrobial T cell responses comes from analyses of lymphoid tissue. Strikingly, memory T cells isolated from the brain exhibited an effector phenotype and produced IFN-γ upon restimulation with viral peptide. Furthermore, we observed time-dependent and long-term activation of resident microglia, indicated by chronic MHC class II up-regulation and TNF-α production. The immune response in this immunologically restricted site persisted in the absence of active viral replication. Lymphocyte infiltrates were detected until 30 days post-infection (p.i.), with CD8(+) and CD4(+) T cells present at a 3:1 ratio, respectively. We then investigated the role of IFN-γ in chronic microglial activation by using IFN-γ-knockout (GKO) mice. At 30 days p.i., GKO mice demonstrated a similar phenotypic brain infiltrate when compared to wild-type mice (Wt), however, MHC class II expression on microglia isolated from these GKO mice was significantly lower compared to Wt animals. When IFN-γ producing CD8(+) T cells were reconstituted in GKO mice, MHC class II up-regulation on microglial cells was restored. Taken together, these results suggest that MCMV brain infection results in long-term persistence of antigen-specific CD8(+) T cells which produce IFN-γ and drive chronic microglial cell activation. This response was found to be dependent on IFN-γ production by viral Ag-specific T cells during the chronic phase of disease.
| S-EPMC3204167 | biostudies-literature
Project description:Evidence has shown that the insulin and insulin receptor (IR) play a role in cognitive function. However, the detailed mechanisms underlying insulin's action on learning and memory are not yet understood. Here we investigated changes in long-term memory-associated expression of the IR and downstream molecules in the rat hippocampus. After long-term memory consolidation following a water maze learning experience, gene expression of IR showed an up-regulation in the CA1, but a down-regulation in the CA3 region. These were correlated with a significant reduction in hippocampal IR protein levels. Learning-specific increases in levels of downstream molecules such as IRS-1 and Akt were detected in the synaptic membrane accompanied by decreases in Akt phosphorylation. Translocation of Shc protein to the synaptic membrane and activation of Erk1/2 were also observed after long-term memory formation. Despite the clear memory-correlated alterations in IR signaling pathways, insulin deficits in experimental diabetes mellitus (DM) rats induced by intraperitoneal injections of streptozotocin resulted in only minor memory impairments. This may be due to higher glucose levels in the DM brain, and to compensatory mechanisms from other signaling pathways such as the insulin-like growth factor-1 receptor (IGF-1R) system. Our results suggest that insulin/IR signaling plays a modulatory role in learning and memory processing, which may be compensated for by alternative pathways in the brain when an insulin deficit occurs.
| S-EPMC1356184 | biostudies-literature
Project description:This dataset contains 48 raw files corresponding to repeat runs of 12 peptide digests of whole Lymnaea stagnalis CNS from LTM (denoted as "L"), no LTM (denoted as "NL"), and yoke control (denoted as "Y") animals collected 24 hours following aversive operant conditioning (n=4 animals per group). Database files contain the predicted Lymnaea stagnalis proteome used for searches as well as the reference mouse proteome used for annotation of Lymnaea stagnalis sequences.
2024-04-08 | MSV000094487 | MassIVE
Project description:The human brain has a remarkable capacity to store a lifetime of information through visual or auditory routes. It excels and exceeds any artificial memory system in mixing and integrating multiple pieces of information encoded. In this study, a group of verbal memory experts was evaluated by multiple structural brain analysis methods to record the changes in the brain structure. The participants were professional Hindu pandits (priests/scholars) trained in reciting Vedas and other forms of Hindu scriptures. These professional Vedic priests are experts in memorization and recitation of oral texts with precise diction. Vedas are a collection of hymns. It is estimated that there are more than 20,000 mantras and shlokas in the four Vedas. The analysis included the measurement of the grey and white matter density, gyrification, and cortical thickness in a group of Vedic pandits and comparing these measures with a matched control group. The results revealed an increased grey matter (GM) and white matter (WM) in the midbrain, pons, thalamus, parahippocampus, and orbitofrontal regions in pandits. The whole-brain corelation analysis using length of post-training teaching duration showed significant correlation with the left angular gyrus. We also found increased gyrification in the insula, supplementary motor area, medial frontal areas, and increased cortical thickness (CT) in the right temporal pole and caudate regions of the brain. These findings, collectively, provide unique information regarding the association between crucial memory regions in the brain and long-term practice of oral recitation of scriptures from memory with the proper diction that also involved controlled breathing.
| S-EPMC8102627 | biostudies-literature
Project description:Brain-computer interface (BCI) systems having the ability to classify brain waves with greater accuracy are highly desirable. To this end, a number of techniques have been proposed aiming to be able to classify brain waves with high accuracy. However, the ability to classify brain waves and its implementation in real-time is still limited. In this study, we introduce a novel scheme for classifying motor imagery (MI) tasks using electroencephalography (EEG) signal that can be implemented in real-time having high classification accuracy between different MI tasks. We propose a new predictor, OPTICAL, that uses a combination of common spatial pattern (CSP) and long short-term memory (LSTM) network for obtaining improved MI EEG signal classification. A sliding window approach is proposed to obtain the time-series input from the spatially filtered data, which becomes input to the LSTM network. Moreover, instead of using LSTM directly for classification, we use regression based output of the LSTM network as one of the features for classification. On the other hand, linear discriminant analysis (LDA) is used to reduce the dimensionality of the CSP variance based features. The features in the reduced dimensional plane after performing LDA are used as input to the support vector machine (SVM) classifier together with the regression based feature obtained from the LSTM network. The regression based feature further boosts the performance of the proposed OPTICAL predictor. OPTICAL showed significant improvement in the ability to accurately classify left and right-hand MI tasks on two publically available datasets. The improvements in the average misclassification rates are 3.09% and 2.07% for BCI Competition IV Dataset I and GigaDB dataset, respectively. The Matlab code is available at https://github.com/ShiuKumar/OPTICAL .
| S-EPMC6591300 | biostudies-literature
Project description:Accurate seizure prediction will transform epilepsy management by offering warnings to patients or triggering interventions. However, state-of-the-art algorithm design relies on accessing adequate long-term data. Crowd-sourcing ecosystems leverage quality data to enable cost-effective, rapid development of predictive algorithms. A crowd-sourcing ecosystem for seizure prediction is presented involving an international competition, a follow-up held-out data evaluation, and an online platform, Epilepsyecosystem.org, for yielding further improvements in prediction performance. Crowd-sourced algorithms were obtained via the 'Melbourne-University AES-MathWorks-NIH Seizure Prediction Challenge' conducted at kaggle.com. Long-term continuous intracranial electroencephalography (iEEG) data (442 days of recordings and 211 lead seizures per patient) from prediction-resistant patients who had the lowest seizure prediction performances from the NeuroVista Seizure Advisory System clinical trial were analysed. Contestants (646 individuals in 478 teams) from around the world developed algorithms to distinguish between 10-min inter-seizure versus pre-seizure data clips. Over 10 000 algorithms were submitted. The top algorithms as determined by using the contest data were evaluated on a much larger held-out dataset. The data and top algorithms are available online for further investigation and development. The top performing contest entry scored 0.81 area under the classification curve. The performance reduced by only 6.7% on held-out data. Many other teams also showed high prediction reproducibility. Pseudo-prospective evaluation demonstrated that many algorithms, when used alone or weighted by circadian information, performed better than the benchmarks, including an average increase in sensitivity of 1.9 times the original clinical trial sensitivity for matched time in warning. These results indicate that clinically-relevant seizure prediction is possible in a wider range of patients than previously thought possible. Moreover, different algorithms performed best for different patients, supporting the use of patient-specific algorithms and long-term monitoring. The crowd-sourcing ecosystem for seizure prediction will enable further worldwide community study of the data to yield greater improvements in prediction performance by way of competition, collaboration and synergism.10.1093/brain/awy210_video1awy210media15817489051001.
| S-EPMC6136083 | biostudies-other
Project description:BACKGROUND:Systemic inflammation is associated with increased cognitive decline and risk for Alzheimer's disease. Microglia (MG) activated during systemic inflammation can cause exaggerated neuroinflammatory responses and trigger progressive neurodegeneration. Dimethyl fumarate (DMF) is a FDA-approved therapy for multiple sclerosis. The immunomodulatory and anti-oxidant properties of DMF prompted us to investigate whether DMF has translational potential for the treatment of cognitive impairment associated with systemic inflammation. METHODS:Primary murine MG cultures were stimulated with lipopolysaccharide (LPS) in the absence or presence of DMF. MG cultured from nuclear factor (erythroid-derived 2)-like 2-deficient (Nrf2 -/- ) mice were used to examine mechanisms of DMF actions. Conditioned media generated from LPS-primed MG were used to treat hippocampal neuron cultures. Adult C57BL/6 and Nrf2 -/- mice were subjected to peripheral LPS challenge. Acute neuroinflammation, long-term memory function, and reactive astrogliosis were examined to assess therapeutic effects of DMF. RESULTS:DMF suppressed inflammatory activation of MG induced by LPS. DMF suppressed NF-?B activity through Nrf2-depedent and Nrf2-independent mechanisms in MG. DMF treatment reduced MG-mediated toxicity towards neurons. DMF suppressed brain-derived inflammatory cytokines in mice following peripheral LPS challenge. The suppressive effect of DMF on neuroinflammation was blunted in Nrf2 -/- mice. Importantly, DMF treatment alleviated long-term memory deficits and sustained reactive astrogliosis induced by peripheral LPS challenge. DMF might mitigate neurotoxic astrocytes associated with neuroinflammation. CONCLUSIONS:DMF treatment might protect neurons against toxic microenvironments produced by reactive MG and astrocytes associated with systemic inflammation.
| S-EPMC5877396 | biostudies-literature
Project description:We characterized the transcriptional response accompanying maintenance of long-term sensitization (LTS) memory in the pleural ganglia of Aplysia californica using microarray (N = 8) and qPCR (N = 11 additional samples). We found that 24 h after memory induction there is strong regulation of 1198 transcripts (748 up and 450 down) in a pattern that is almost completely distinct from what is observed during memory encoding (1 h after training). There is widespread up-regulation of transcripts related to all levels of protein production, from transcription (e.g., subunits of transcription initiation factors) to translation (e.g., subunits of eIF1, eIF2, eIF3, eIF4, eIF5, and eIF2B) to activation of components of the unfolded protein response (e.g., CREB3/Luman, BiP, AATF). In addition, there are widespread changes in transcripts related to cytoskeleton function, synaptic targeting, synaptic function, neurotransmitter regulation, and neuronal signaling. Many of the transcripts identified have previously been linked to memory and plasticity (e.g., Egr, menin, TOB1, IGF2 mRNA binding protein 1/ZBP-1), though the majority are novel and/or uncharacterized. Interestingly, there is regulation that could contribute to metaplasticity potentially opposing or even eroding LTS memory (down-regulation of adenylate cyclase and a putative serotonin receptor, up-regulation of FMRFa and a FMRFa receptor). This study reveals that maintenance of a "simple" nonassociative memory is accompanied by an astonishingly complex transcriptional response.
| S-EPMC5602346 | biostudies-literature
Project description:This study describes a functional magnetic resonance imaging study of humans engaged in long-term memory (LTM) and working memory tasks. A pattern classifier learned to identify patterns of brain activity associated with viewing and making judgments about three categories of pictures (famous people, famous locations, and common objects). The evaluation of these stimuli relied on perception and long-term semantic and/or episodic memories. We investigated whether this classifier could successfully decode brain activity from a subsequent delayed paired-associate recognition working memory task that required the short-term retention of the same stimuli. We reasoned that the LTM-trained classifier would be able to decode delay-period activity only if that activity reflected, to some extent, the temporary activation of LTM. Our results demonstrated successful decoding: delay-period activity from a distributed network of brain regions matched learned patterns of activity for task-relevant stimuli to a greater extent than for task-irrelevant stimuli. In varying degrees throughout the delay, activity reflected the target (a retrospective code) and its associate (a prospective code) with considerable variability among subjects. Although prefrontal cortex (PFC) demonstrated category-specific patterns of activity during the LTM task, these patterns were not reinstated in PFC during the working memory task. We conclude that the short-term retention of information can be supported by the temporary reactivation of LTM representations.
| S-EPMC2699183 | biostudies-other
Project description:Fundamental theories of human cognition have long posited that the short-term maintenance of actions is supported by one of the "core knowledge" systems of human visual cognition, yet its neural substrates are still not well understood. In particular, it is unclear whether the visual short-term memory (VSTM) of actions has distinct neural substrates or, as proposed by the spatio-object architecture of VSTM, shares them with VSTM of objects and spatial locations. In two experiments, we tested these two competing hypotheses by directly contrasting the neural substrates for VSTM of actions with those for objects and locations. Our results showed that the bilateral middle temporal cortex (MT) was specifically involved in VSTM of actions because its activation and its functional connectivity with the frontal-parietal network (FPN) were only modulated by the memory load of actions, but not by that of objects/agents or locations. Moreover, the brain regions involved in the maintenance of spatial location information (i.e., superior parietal lobule, SPL) was also recruited during the maintenance of actions, consistent with the temporal-spatial nature of actions. Meanwhile, the frontoparietal network (FPN) was commonly involved in all types of VSTM and showed flexible functional connectivity with the domain-specific regions, depending on the current working memory tasks. Together, our results provide clear evidence for a distinct neural system for maintaining actions in VSTM, which supports the core knowledge system theory and the domain-specific and domain-general architectures of VSTM.
| S-EPMC6866292 | biostudies-literature