Memory Structure Research Articles

The neural networks of touch observation

Abstract Studies have consistently demonstrated that the mere observation of touch engages our own somatosensory cortices. However, a systematic evaluation of the involved networks is missing. Here, we present results of a meta-analytic connectivity modeling (MACM) approach based on clusters revealed by activation likelihood estimation (ALE) combined with resting-state analysis to detect networks subserving our ability to empathize with tactile experiences of other people. ALE analysis revealed 8 clusters in frontal, temporal, and parietal brain areas, which behavioral domain profiles predominantly refer to cognition and perception. The MACM analysis further identified distinct networks that are subserved by subcortical structures, revealed that all clusters involved in touch observation are connected to dorso-medial frontal and anterior cingulate cortex control regions, and showed that medial temporal lobe memory structures do not inform network activation during touch observation (confirmed by post hoc resting-state connectivity analyses). Our data highlight the importance of higher-level control areas and suggest only a minor role for past bodily experiences in the ad hoc perception of other people’s experiences.

Recurrent Neural Networks and Three-Point Bending Test on the Identification of Material Hardening Parameters

The continuous evolution of metallic alloys in the automotive industry has led to the development of more advanced and flexible constitutive models that attempt to accurately describe the various fundamental properties and behavior of these materials. These models have become increasingly complex, incorporating a larger number of parameters that require an accurate calibration procedure to fit the constitutive parameters with experimental data. In this context, machine learning (ML) methodologies have the potential to advance material constitutive modeling, enhancing the efficiency of the material parameter calibration procedure. Recurrent neural networks (RNNs) stand out among various learning algorithms due to their ability to process sequential data and overcome limitations imposed by nonlinearities and multiple parameters involved in phenomenological models. This study explores the modeling capabilities of long short-term memory (LSTM) structures, a type of RNN, in predicting the hardening behavior of a sheet metal material using the results of a standardized experimental three-point bending test, with the aim of extending this methodology to other experimental tests and constitutive models. Additionally, a variable analysis is performed to select the most important variables for this experimental test and assess the influence of friction, material thickness, and elastic and plastic properties on the accuracy of predictions made by neural networks. The required data for designing and training the network solutions are collected from numerical simulations using finite element methodology (FEM), which are subsequently validated by experiments. The results demonstrate that the proposed LSTM-based approach outperforms traditional identification techniques in predicting the material hardening parameters. This suggests that the developed procedure can be effectively applied to efficiently characterize different materials, especially those extensively used in industrial applications, ranging from mild steels to advanced high-strength steels.

Seizure-induced LIN28A disrupts pattern separation via aberrant hippocampal neurogenesis.

Prolonged seizures can disrupt stem cell behavior in the adult hippocampus, an important brain structure for spatial memory. Here, using a mouse model of pilocarpine-induced status epilepticus (SE), we characterized spatiotemporal expression of Lin28a mRNA and proteins after SE. Unlike Lin28a transcripts, induction of LIN28A protein after SE was detected mainly in the subgranular zone, where immunoreactivity was found in progenitors, neuroblasts, and immature and mature granule neurons. To investigate roles of LIN28A in epilepsy, we generated Nestin-Cre:Lin28aloxP/loxP (conditional KO [cKO]) and Nestin-Cre:Lin28a+/+ (WT) mice to block LIN28A upregulation in all neuronal lineages after acute seizure. Adult-generated neuron- and hippocampus-associated cognitive impairments were absent in epileptic LIN28A-cKO mice, as evaluated by pattern separation and contextual fear conditioning tests, respectively, while sham-manipulated WT and cKO animals showed comparable memory function. Moreover, numbers of hilar PROX1-expressing ectopic granule cells (EGCs), together with PROX1+/NEUN+ mature EGCs, were significantly reduced in epileptic cKO mice. Transcriptomics analysis and IHC validation at 3 days after pilocarpine administration provided potential LIN28A downstream targets such as serotonin receptor 4. Collectively, our findings indicate that LIN28A is a potentially novel target for regulation of newborn neuron-associated memory dysfunction in epilepsy by modulating seizure-induced aberrant neurogenesis.

Elemental structures of memory: Marston Mats in Vietnam and beyond

Elemental structures of memory: Marston Mats in Vietnam and beyond

Метафора дыма: реконструкция культурных смыслов (на материале якутской лингвокультуры)

The paper examines the linguistic and cultural semantics of the Yakut word buruo (smoke) by exploring its metaphorical manifestations in vocabulary, phraseology, and folklore. The folklore text is analyzed using a structural-semiotic approach to examine language as a cultural verbal code. For the first time, the smoke metaphor is recognized as a source of riddles, proverbs, good wishes, incantations, euphemisms, and others. Otherwise, the metaphor is found to have meaning- and text-forming functions. In the Yakut linguoculture, the smoke metaphor creates a micro paradigm of linguistic units with the general semantics of “descendants, a continuation of the family.” The metaphor under study is suggested to be a cultural element of the Sakha people’s folklore, specifically related to the patriarchal family structure and the roles of sons and daughters in procreation. The smoke metaphor, a tool for creating new concepts and pictorial means in language and culture, proves to be an element of the informational structures of oral collective memory. It preserves the principle of patrilineage, gender stereotypes, and traditional ideas of the Sakha people about the succession of generations and procreation, understood as “development, advancement through stages of development.” A significant finding is that a polysemous word, phraseology, paremy, epithet, folklore formula, symbol, and others can preserve considerable information in a coiled form and serve as an optimal way of its oral transmission in time and space. To conclude, folklore text metaphors are not only emotionally rich but also involve “condensed” meaning, with a symbol representing the information compression.

An optimized LSTM-based equalizer for 100 Gigabit/s-class short-range fiber-optic communications

<p>Intensity modulation/direct detection (IM/DD) remains to be the preferred optical transmission scheme for short-range applications for its simplicity of application, inexpensiveness, and small footprint. However, the impairments of low-cost device and fiber chromatic dispersion lead to the limitation of system performance when the data rate rises to 100 Gbps or higher. In this paper, we demonstrated that an equalizer using neural networks can effectively improve the transmission performance of high-speed IM/DD systems. An optimization of a long short-term memory (LSTM) structure in terms of network depth and distribution of neurons in hidden layers leads to an enhancement of the overall performance of the 50 Gbaud PAM4 communications. Furthermore, the results for a system using a LSTM-based equalizer give the better outcome than the traditional feed-forward equalizer (FFE) or artificial neural network (ANN)-based equalizer.</p>

The fate of the leaders of the Black -Hundred movement in Soviet Russia: modern Russian historiography

The article discusses the issues of the formation of the historical policy of the Republic of Turkmenistan under the presidency of S.A. Niyazov (1991-2006). The basic concepts of the origin of the Turkmen nation are analyzed. The idea is substantiated that the Rukhnama is the fundamental epic in the formation of historical policy in the republic. Attention is drawn to the figure of S.A. Niyazov as key figures in the historical politics of the republic. In addition, the article examines the figures of the father and mother of the first President of Turkmenistan. Their important component in creating a commemorative narrative together with the figure of Turkmenbashi is emphasized. The key attention in the article is paid to the formation of the commemorative calendar of the republic, as one of the factors in the action of historical policy in the country. The key memorable dates that testify to the history and origins of the emergence of Turkmen statehood are analyzed. The main legal acts and news portals are considered, indicating the formation of commemorative practices in the Republic of Turkmenistan from 1991 to 2006. The important role of memory institutions is highlighted. Much attention is paid to international, scientific, educational and cultural (museum) organizations that have a significant influence on the formation of the country's institutional and commemorative policy. The main tasks and directions of activity of specialized memory structures are analyzed.

Simulation of the resistance switching performance and synaptic behavior of TiO2-based RRAM devices with CoFe2O4 insertion layers.

The electrothermal coupling model of Pt/CoFe2O4/TiO2/TiN devices was established to study their resistive switching characteristics and basic biological synaptic properties in our research. The processes of set and reset are simulated, and the distribution of the temperature, the electric field and the concentration of oxygen vacancies in the dielectric layer are obtained. The switching performance of the TiO2-based device is significantly improved after the CoFe2O4 layer is inserted, with the switching voltage, working current and power consumption being reduced, while the switching ratio is increased. By changing the thermal conductivity of the top electrode, the rupture position of the conductive filament can be controlled. The I-V characteristics of the Pt/CoFe2O4/TiO2/TiN device during the reset and set processes are fitted linearly in logarithmic coordinates, and the ohmic conduction mechanism or the space-limited charge conduction mechanism is mainly satisfied in the high and low resistance states. Finally, the application of dual-layer devices on biological synapses is studied, and the basic biological characteristics of enhancement, inhibition and paired pulse promotion are simulated successfully. In addition, the redox reaction induced by oxygen vacancy migration also promotes the formation and rupture of the conductive filament. Results of the study show this ferrite material as an insertion layer in a resistive random-access memory structure that offers potential for future information storage and bioneuromorphic computation devices.

Multiple sclerosis is associated with differences in semantic memory structure.

Although language is often considered to be largely intact in multiple sclerosis (MS), word-finding difficulties are a common complaint. Recent work suggests that declines in language are not solely the result of motoric and cognitive slowing that is most strongly associated with MS. Network science approaches have been effectively used to examine network structure as it relates to clinical conditions, aging, and language. The present study utilizes a network science approach to investigate whether individuals with MS exhibit less interconnected and resilient semantic networks compared to age-matched neurotypical peers. We used semantic fluency data from 89 participants with MS and 88 neurotypical participants to estimate and analyze the semantic network structure for each participant group. Additionally, we conducted a percolation analysis to examine the resilience of each network. Network measures showed that individuals with MS had lower local and global clustering coefficients, longer average shortest path lengths, and higher modularity values compared to neurotypical peers. Small-worldness, network portrait divergence measures, and community detection analyses were consistent with these results and indicated that macroscopic properties of the two networks differed and that the semantic network for individuals with MS was more fractured than the neurotypical peer network. Moreover, a spreading activation simulation and percolation analysis suggested that the semantic networks of individuals with MS are less flexible and activation degrades faster than those of age-matched neurotypical participants. These differing semantic network structures suggest that language retrieval difficulties in MS partially result from decline in language-specific factors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Seq2Seq 모델을 활용한 교육용 챗봇 구현에 관한 연구

With the development of mobile devices and the activation of messenger use, it is necessary to use chatbot as a communication tool with students. If individuals can ask various questions and receive customized answers owing to differences in levels among students, it will help improve academic achievement. For students to naturally communicate with chatbot, they must be able to provide familiar and accurate answers similar to those of Georgia Tech's Jill Watson. In this study, a chatbot capable of natural language processing and improving the Seq2Seq algorithm of the long short-term memory structure was implemented. The implemented chatbot learned from the open daily life conversation data, and consequently, it exhibited high accuracy and low loss rate within a short time, and the answer was excellent.

Experimental substantiation of the risks of developing health disorders when exposed to smoke from wildfires

Introduction. An increase in the number of wildfires, along with the lack of a chemical control system for the quality of the atmosphere during smoke, leads to a risk of developing health disorders for rescuers and firefighters exposed to high concentrations of toxic smoke components.
 The study aims to identify causal relationships based on experimental modeling between exposure to natural fire smoke and the functional state of the nervous and reproductive systems.
 Materials and methods. The authors conducted studies on white rats of both sexes. The animals were placed in inhalation chambers and exposed to forest fire smoke of varying concentrations and duration of exposure. The scientists examined the functional state of the nervous system (open field method, Morris test, electroencephalography, histology of nervous tissue), the reproductive system (number of Leydig cells, average number of spermatogonia, spermatogenesis index), the presence of genotoxicity (DNA comet method), DNA methylation and the effect on offspring (postnatal development, species-specific behavior). We calculated the total exposure limit in each group of animals in accordance with the indicators of CO and PM2.5 content in the chambers.
 Results. The researchers found that with a total exposure load of 0.03–0.22 mg, there were initial changes in the morphofunctional state of the central nervous system. With an increase in the load to 4 mg, violations of the indicators of behavior and electrical activity of the brain were accompanied by significant changes in the structure of the nervous tissue of the rat brain. The reproductive function of rats under the influence of smoke changed, starting with a total exposure dose of 10.8 mg. We observed a decrease in spermatogenesis and a change in the cyclic function of the ovaries. A violation of the postnatal development of offspring has already been detected with a total dose of 0.22 to 4 mg. Prolonged exposure to tobacco smoke for one month was accompanied by a pronounced violation of the spermatogenetic function of the testicles and an increase in neonatal mortality in offspring, as well as a violation of the structure of behavior and spatial memory in adulthood. The genotoxic effect of smoke was not detected, and a change in DNA methylation in blood cells was detected at the maximum total dose of smoke components.
 Limitation. The study is limited to studying the effect of wildfire smoke on the nervous and reproductive systems of mongrel white male rats.
 Conclusion. The results obtained are a fundamental foundation for solving such tasks as the development of risk-oriented preventive health-saving measures for workers in extreme situations in conditions of smoke during wildfires and making effective management decisions.
 Ethics. The study was approved by the local Ethics Committee of the East-Siberian Institute of Medical and Ecological Research (Protocol LK of East-Siberian Institute of Medical and Ecological Research No. 32/19 dated 09/10/2019), conducted in accordance with the European Convention for the Protection of Vertebrates Used for Experiments or Other Scientific Purposes (ETS No. 123), Directive of the European Parliament and the Council of the European Union 2010/63/EC dated 09/22/2010 on the protection of animals used for scientific purposes.

BEHAVIORAL METHODS EMPLOYED TO INVESTIGATE THE STRUCTURE OF AUTOBIOGRAPHICAL MEMORIES

Memory research conducted in laboratories require controlled experiments in order to eliminate the confounding factors that can affect memory retrieval. However autobiographical memories require the retrieval of distant memories which are most of the time not verifiable. Due to the differences related to Autobiographical memory these controlled experiments cannot be used and different methods are required. Cue word technique, diary studies, recording event by using devices, Autobiographical Memory Interview and Autobiographical Interview are some of the behavioral methods employed for Autobiographical memory research. These methods have both some advantages and some disadvantages, which should be considered before they are used. The findings from the studies employing these methods indicated that Autobiographical memory has a hierarchical organization, it consists of a sementic component and an episodic component, and some of the cues are ineffective for the retrieval of autobiographical memories. Most of these methods can also be employed in research investigating the impaired components of autobiographical memory for patients with memory disorders like Alzheimer’s disease. In this review the bahavioral methods empleyed to investigate the structure of Autobiographical memories will be explored. First the differences of autobiographical memory from memory investigated in laboratory and the need for different methods in autobiographical memory research will be mentioned. Then behavioral methods to investigate the structure of Autobiographical memory, how they are used and the findings obtained from these studies seperately and in common will be discussed.

Long-term consequences of acute toxic prenatal hypoxia induced by sodium nitrite in rat experiments

Introduction. Gestational hypoxia plays an important role in fetal development, as it causes the development of oxidative stress and delayed psychomotor development. The aim of the study was to evaluate the prenatal effect of sodium nitrite on indices characterizing orienting and exploratory activity, mental activity and the degree of hypoxia in rat offspring. Materials and methods. Acute hypoxia was modeled by administration of sodium nitrite at a dose of 30 mg/kg intramuscularly to five pregnant rats during 16–19 days of gestation. Five females constituted a control group. In 50 born rats, orientation and exploration activity, cognitive functions, intensity of lipid peroxidation and glycolysis were studied. Results. The offspring of females that underwent acute hypoxia significantly lagged behind in the positive dynamics of body weight gain compared to control individuals. Thirty-day-old rats showed a pronounced disorder of the structure of behavioral pattern, learning process and long-term memory, increased content of diene conjugates, malonic dialdehyde and the level of lactate dehydrogenase activity in blood. Discussion. It was found that offspring whose mothers suffered acute hypoxia of toxic genesis developed pronounced behavioral disorders of psychomotor agitation and cognitive dysfunction characterized by decreased learning ability and impaired long-term memory. The content of primary and secondary products of lipid peroxidation and lactate dehydrogenase was increased in rats. The development of cellular oxidative stress under conditions of intrauterine hypoxia leads to oxygen deficiency in the fetus and a switch from tissue respiration to glycolysis, which underlies CNS damage. Conclusion. It was shown that sodium nitrite administration during the period from the 16th to the 19th day of gestation caused hyperactivity, depressed emotional status, and decreased orienting and exploratory activity and the ability to learn and retain a memory trace in rat offspring. Increased levels of diene conjugates and malonic dialdehyde, lactate dehydrogenase activity were observed in rats.

The modulation and elimination of temporal organization in free recall.

Experiences occur in a continual succession, and the temporal structure of those experiences is often preserved in memory. The temporal contiguity effect of free recall reveals the temporal structure of memory: when a particular item is remembered, the next response is likely to come from a nearby list position. This effect is remarkably robust, appearing across a wide variety of methodological variations of the task. The temporal contiguity effect is also central to retrieved-context models, which propose temporal organization arises from the interaction of a temporal context representation with the contents of memory. Across six experiments, we demonstrate methodological manipulations that dramatically modulate and even eliminate temporal organization in free recall. We find that temporal organization is strongly modulated and in some cases potentially eliminated by strong semantic structure, the presence of retrieval practice, and a long list length. Other factors such as orienting task, paired-associate item structure, and retention interval duration have more subtle effects on temporal organization. In an accompanying set of simulations, we show that the modulation and elimination of the temporal organization follows lawful patterns predicted by the context maintenance and retrieval (CMR) retrieved-context model. We also find cases where CMR does not specifically predict the modulation of temporal organization, and in these cases our analysis suggests how the theory might be developed to account for these effects. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The giant leap to humankind

Penny (2009) urges that biologists stress more strongly the biological continuity between great apes and humans. Besides stressing genetic similarities, he suggests that great apes also share psychological capacities, including language and tool use. I argue that he underestimates the psychological differences. There is no evidence that great apes have anything approaching human language, or human technological capacity. A main ingredient of human cognition is recursion, which lifted communication to true combinatorial language and simple tool use to advanced combinatorial technology. Recursion may also explain the combinatorial structure of human memory, imagination, and theory of mind. Part of the key, as Penny recognises, may lie in the trajectory of human brain growth, but there is still much to understand in how micro-tweaking of the genome achieved such dramatic differences between ape and human.

CD4 memory has a hierarchical structure created by requirements for infection-derived signals at an effector checkpoint.

Our recent studies reveal that the persistence, location, and amount of both antigen and signals that induce pathogen recognition responses determine the number of CD4 memory cells, the subsets that develop, their location, and hence their protective efficacy. Non-replicating vaccines provide antigen that is short-lived and generate low levels of only some memory subsets that are mostly restricted to secondary lymphoid tissue. In contrast, exposure to long-lived replicating viruses and bacteria provides high levels of diverse antigens in sites of infection and induces strong pathogen recognition signals for extended periods of time, resulting in much higher levels of memory cells of diverse subsets in both lymphoid and nonlymphoid sites. These include memory subsets with highly potent functions such as T follicular helpers and cytotoxic CD4 effectors at sites of infection, where they can most effectively combat the pathogen early after re-infection. These effectors also do not develop without antigen and pathogen recognition signals at the effector stage, and both subsets must receive these signals in the tissue sites where they will become resident. We postulate that this leads to a hierarchical structure of memory, with the strongest memory induced only by replicating pathogens. This paradigm suggests a likely roadmap for markedly improving vaccine design.

Social media platform-oriented topic mining and information security analysis by big data and deep convolutional neural network

The aim of this work is to conduct topic mining and data analysis of social network security using social network-based big data. The deep convolution neural network (DCNN) is used to analyze social network security issues. Traditional neural network models cannot handle long sequence data when extracting information on Weibo security topics. Thus, the long short-term memory (LSTM) structure in the memory intelligence algorithm extracts Weibo topic information. Specifically, the social network security topics are mined through Big Data, and CNN searches Weibo security topics. CNN can learn the grammar and semantic information of Weibo topics to obtain in-depth data features. Afterward, the performance of the improved DCNN model is compared with the AlexNet, Convolutional Neural Network (CNN), and Deep Neural Network (DNN) by considering the model's accuracy, recall, and F1 value, respectively. The experimental results show that after 120 iterations, the recognition accuracy of the improved DCNN model peaks at 96.17 %, at least 5.4 % superior to the other three models. Additionally, the intrusion detection model's accuracy, recall, and F1 value are 88.57 %, 75.22 %, and 72.05 %, respectively. In the worst case, the constructed model's accuracy, recall, and F1 value are 3.1 % higher than those of the other methods. The training and testing time consumption of the improved DCNN security detection model stabilized at 65.86 s and 27.90 s, much shorter than similar literature approaches. The experimental conclusion is that the improved DCNN under deep learning has the characteristic of lower delay, and the model shows good network data security transmission.

Indoor Air Quality Analysis Using Recurrent Neural Networks: A Case Study of Environmental Variables

In the pursuit of energy efficiency and reduced environmental impact, adequate ventilation in enclosed spaces is essential. This study presents a hybrid neural network model designed for monitoring and prediction of environmental variables. The system comprises two phases: An IoT hardware–software platform for data acquisition and decision-making and a hybrid model combining short-term memory and convolutional recurrent structures. The results are promising and hold potential for integration into parallel processing AI architectures.

Verbal memory deficits in schizophrenia

Schizophrenia is a severe mental disorder characterized by multifactorial etiology, encompassing genetic and environmental risk factors, as well as structural brain abnormalities. The disorder manifests through a spectrum of symptoms, broadly categorized as positive, negative, and cognitive impairments. Among these cognitive deficits, verbal memory impairment stands out as a substantial and pivotal symptom of schizophrenia, significantly predicting future functional outcomes. This deficit primarily arises from a substantial decline in encoding ability coupled with a mild increase in forgetting rate. To assess the extent of this impairment, word list learning tasks are commonly employed. Research has established a clear association between verbal memory deficits and alterations in hippocampal volume, aberrant brain responses, and anomalies in spontaneous brain activity. Although targeted pharmacological interventions for verbal memory deficits are currently lacking, medications aimed at enhancing cognitive function, such as aripiprazole, present a viable interim option. Future research endeavors should focus on exploring the fundamental aspects of memory and brain structure and function, while incorporating advanced techniques like repetitive transcranial magnetic stimulation (rTMS) into investigations of verbal memory deficits. Additionally, the development of animal models capable of simulating verbal memory deficits holds promise for advancing our understanding of this critical aspect of schizophrenia.

ХУДОЖЕСТВЕННАЯ ВИЗУАЛИЗАЦИЯ ЦИФРОВОЙ ПАМЯТИ В СОВРЕМЕННОМ МЕДИААРТЕ

The engagement of researchers and artists with the issue of memory in the digital culture is linked to the recognition of a qualitatively new role of technology in shaping the structures of contemporary human consciousness. The total digitalization of socio-cultural space not only alters the configuration of memory structures but also creates a situation where the cultural space itself becomes entirely dependent on them. In addition to academic research on digital memory (Digital Memory Studies, DMS), media artists are exploring its interpretation by creating artistic models of digital memory. The aim of the article is to present artistic experiences of visual modeling of digital memory in modern media art as a response to multi-level transformations in memory structures, using the work of well-known representatives of contemporary technological artistic practices such as Woody Vasulka, Rafael Lozano-Hemmer, and Refik Anadol as examples.