人类大脑记忆机制的神经生物学基础与动态过程研究综述

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参考文献

4Short-Term Memory ImpairmentPubMed

Marco Cascella, Yasir Al Khalili

Short-term memory is also called short-term storage, primary memory, or active memory. The term indicates different systems of memory involved in retaining pieces of information, or memory chunks, for a relatively short time, typically up to 30 seconds. In contrast, long-term memory may hold indefinite information. However, the difference is not just the time variable but also their overall functionality. Nevertheless, the 2 systems are closely related. Practically, short-term memory functions as a temporary scratchpad for recalling a limited amount of data, typically around 7 ± 2 items, in the verbal domain, based on George Miller's concept. This information originates from the sensory register and can be processed through attention and recognition. In contrast, information collected in long-term memory storage consists of memories for performing actions or skills, such as procedural memories (knowing how), and memories of facts, rules, concepts, and events, such as declarative memories (knowing that). Declarative memory includes semantic and episodic memory. The former concerns broad knowledge of facts, rules, concepts, and propositions (general knowledge), whereas the latter concerns personal and experienced events and the contexts in which they occurred (personal recollection). Although short-term memory is closely related to the concept of working memory, both are distinct entities. Short-term memory is a set of storage systems, whereas working memory indicates the cognitive operations and executive functions associated with the organization and manipulation of stored information. Nevertheless, the terms short-term memory and working memory are often used interchangeably. Short-term memory must also be distinguished from sensory memory, such as the acoustical echoic and iconic visual memories, which are shorter in duration, typically fractions of a second, and reflect the stimulus's original sensation or perception. In other words, sensory memory is specific to the stimulus modality of presentation. This raw sensory information undergoes processing and, upon processing to short-term, is expressed in a format different from that perceived initially. The famous Atkinson and Shiffrin (or multi-store) model, proposed in the late 1960s, explains the functional correlations between different types of memory. Many studies demonstrated the anatomical and functional distinctions between memory processes, neural correlates, and the functioning of short-term and long-term memory subsystems. In light of these findings, several memory models have been postulated. Although some authors suggested a single memory system encompassing both short- and long-term storage after 50 years, the Atkinson and Shiffrin model remains a valid approach for explaining the memory dynamics. In light of recent research, however, the model has several problems, mostly concerning the characteristics of short-term memory, the relationship between short-term and working memory, and the transition from short- to long-term memory. Short-term memory is a storage system that includes several subsystems with limited capacity. Rather than a limitation, this restriction is an evolutionary survival advantage, as paying attention to limited but essential information, excluding confounding factors, is important. A classic example in biology is prey, which must focus on the hostile environment to recognize a possible attack by the predator. Given the functional peculiarities of short-term memory, which involves the collection of sensory information, the subsystems are closely related to the modalities of sensory memory. Consequently, several sensory-associated subsystems have been postulated, including the visuospatial, phonological (auditory-verbal), tactile, and olfactory domains. These subsystems involve patterns and functional interconnections with the corresponding cortical and subcortical areas and centers. In 1974, Baddeley and Hitch developed an alternative model called working memory. This model does not exclude the modal model but rather enriches the contents. The short-term store can be used to characterize the functioning of the working memory. Working memory refers to the entire theoretical framework of the structures and processes used for storing and temporarily manipulating information, of which short-term memory is only a component. In other words, short-term memory is a functional storage element, whereas working memory is a set of processes involving storage phases. Working memory is constantly used when we have to understand new information, solve a problem, or make an argument, and it is the cognitive strategy for achieving short-term goals. The importance of this type of operating system of memory is demonstrated by the evidence showing that working memory deficits are associated with several developmental disorders of learning, including attention-deficit hyperactivity disorder, dyslexia, and specific language impairment. A recent study on working and short-term memory in children with attention-deficit hyperactivity disorder suggested that these children had an inadequate hemodynamic response in a region of the brain that underlies phonological working memory. Functional near-infrared spectroscopy is a cost-effective, noninvasive neuroimaging technique that localizes and quantifies neural activation patterns related to executive functions. Another study suggested that working memory impairment and attention lapsing are general features of psychotic disorders. Findings regarding capacity estimates from the Change Localization and Detection tasks related to functional capacity and outcome also implied that these methods may be useful in a clinical context. Short-term and long-term memory can be distinguished based on storage capacity and duration. Short-term memoryhas limitations in the amount and duration of information maintained. In contrast, long-term memory features a seemingly unlimited capacity that can last years. The functional distinctions between memory storage systems and the exact mechanisms for how memories transfer from short-term to long-term memory remain controversial. Do short- and long-term memory represent 1 or more systems with specific subsystems? Although short-term memory probably represents a substructure of long-term memory, a form of long-term–activated storage, rather than looking for a physical division, verifying the mechanisms involved in transitioning from short-term to long-term memory seems appropriate. Although the classic multi-modal model proposed that the storage of short-term memories occurs automatically without manipulation, the matter seems more involved. The phenomenon concerns quantitative (number of memories) and qualitative (quality of memory) features. Regarding quantitative data, although the number of Miller of 7 ± 2 items identifies the number of elements included among individual slots, grouping memory bits into larger chunks (chunking) can allow for greater storage capacity. The qualitative issue, or memory modulation within processing, is fascinating. Short-term memory elements undergo processing, providing a sort of editing involving each element's fragmentation (chunking) and re-elaboration. This phase of memory processing is called encoding and can condition subsequent processing, including storage and retrievalThe encoding process encompasses automatic (without conscious awareness) and effortful processing (through attention, practice, and thought) and allows us to retrieve information to make decisions and answer questions. Three pathways are followed during the encoding step—visual (information represented as a picture), acoustic (information represented as a sound), and semantic encoding (the meaning of the information). These processes interconnect, breaking down information into various components. During recovery, the pathway that has produced the coding facilitates the recovery of the other components through a chain reaction. A particular perfume, for instance, makes us recall a specific episode or image. The encoding process affects the recovery, but the recovery undergoes potential changes that can alter the initial content. In neurofunctional terms, the difference is the occurrence in long-term memory of a series of events that must definitively fix the engram(s). This effect occurs through the establishment of neural networks and is expressed as a neurofunctional phenomenon, including long-term potentiation, which is an increase in the strength of the neural transmission deriving from the strengthening of synaptic connections. This process requires gene expression and the synthesis of new proteins and is related to long-lasting structural alterations in the synapses (synaptic consolidation) of the brain areas involved, such as the hippocampus in declarative memories. Hippocampal neurogenesis regulates the maintenance of long-term potentiation. However, the hippocampal network, including the parahippocampal gyrus, hippocampus, and neocortical areas, is not the storage site for memories but plays a crucial role in forming new memories and their subsequent reactivation. The hippocampus appears to have a limited capacity but acquires information quickly and automatically. Over time, the initially available information is permanent in other brain structures, particularly the cortex), independently from the activity of the hippocampus itself. The crucial mechanism of this transfer involves the reactivation (replay) of neural activity configurations. In other words, the connected hippocampus and the medial temporal structures are crucial for holding an event as a whole as they distribute memory traces in an organized manner. The operating system can store, organize, process, and recover hardware files through different software. This hippocampal-guided reactivation (retrieval) leads to the creation of direct connections between the cortical traces and then to the formation of an integrated representation in the neocortex, including the visual association cortex for visual memory, the temporal cortex for auditory memory, and the left lateral temporal cortex for knowledge of word meanings. Moreover, the hippocampus has other specific tasks, such as spatial memory organization. Recent reviews summarized the progress of hippocampal circuits and functions based on sharp-wave ripples. These ripples are crucial for consolidating spatial, episodic, and social memories in different hippocampal-cortical pathways. Dysregulation of sharp-wave ripples contributes to cognitive impairments in neurodegenerative and neurodevelopmental diseases. Other brain areas are involved in memory processes; for example, learning motor skills has links to the activation of the cerebellar regions and brainstem nuclei. Learning perceptive activities, including improvements in processing perceptive stimuli essential in everyday life activities such as understanding spoken and written language, involves basal ganglia and sensory and associative cortices. In contrast, learning cognitive skills related to problem-solving involves the medial temporal lobes.

6Neurophysiology and neuroanatomy of reflexive and volitional saccades: evidence from studies of humans.PubMed

Jennifer E McDowell, Kara A Dyckman, Benjamin P Austin, et al.

Brain Cogn. 2008 Dec;68(3):255-70. doi: 10.1016/j.bandc.2008.08.016. Epub 2008 Oct 5.

This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually guided saccades (redirections of gaze to a visual stimulus or pro-saccades) and more complex volitional saccades require similar basic neural circuitry with additional neural regions supporting requisite higher level processes. The saccadic system has been studied extensively in non-human (e.g., single-unit recordings) and human (e.g., lesions and neuroimaging) primates. Considerable knowledge of this system's functional neuroanatomy makes it useful for investigating models of cognitive control. The network involved in pro-saccade generation (by definition largely exogenously-driven) includes subcortical (striatum, thalamus, superior colliculus, and cerebellar vermis) and cortical (primary visual, extrastriate, and parietal cortices, and frontal and supplementary eye fields) structures. Activation in these regions is also observed during endogenously-driven voluntary saccades (e.g., anti-saccades, ocular motor delayed response or memory saccades, predictive tracking tasks and anticipatory saccades, and saccade sequencing), all of which require complex cognitive processes like inhibition and working memory. These additional requirements are supported by changes in neural activity in basic saccade circuitry and by recruitment of additional neural regions (such as prefrontal and anterior cingulate cortices). Activity in visual cortex is modulated as a function of task demands and may predict the type of saccade to be generated, perhaps via top-down control mechanisms. Neuroimaging studies suggest two foci of activation within FEF - medial and lateral - which may correspond to volitional and reflexive demands, respectively. Future research on saccade control could usefully (i) delineate important anatomical subdivisions that underlie functional differences, (ii) evaluate functional connectivity of anatomical regions supporting saccade generation using methods such as ICA and structural equation modeling, (iii) investigate how context affects behavior and brain activity, and (iv) use multi-modal neuroimaging to maximize spatial and temporal resolution.

7Temporal Expectation Modulates the Cortical Dynamics of Short-Term Memory.PubMed

Anna Wilsch, Molly J Henry, Björn Herrmann, et al.

J Neurosci. 2018 Aug 22;38(34):7428-7439. doi: 10.1523/JNEUROSCI.2928-17.2018. Epub 2018 Jul 16.

Increased memory load is often signified by enhanced neural oscillatory power in the alpha range (8-13 Hz), which is taken to reflect inhibition of task-irrelevant brain regions. The corresponding neural correlates of memory decay, however, are not yet well understood. In the current study, we investigated auditory short-term memory decay in humans using a delayed matching-to-sample task with pure-tone sequences. First, in a behavioral experiment, we modeled memory performance over six different delay-phase durations. Second, in a MEG experiment, we assessed alpha-power modulations over three different delay-phase durations. In both experiments, the temporal expectation for the to-be-remembered sound was manipulated so that it was either temporally expected or not. In both studies, memory performance declined over time, but this decline was weaker when the onset time of the to-be-remembered sound was expected. Similarly, patterns of alpha power in and alpha-tuned connectivity between sensory cortices changed parametrically with delay duration (i.e., decrease in occipitoparietal regions, increase in temporal regions). Temporal expectation not only counteracted alpha-power decline in heteromodal brain areas (i.e., supramarginal gyrus), but also had a beneficial effect on memory decay, counteracting memory performance decline. Correspondingly, temporal expectation also boosted alpha connectivity within attention networks known to play an active role during memory maintenance. The present data show how patterns of alpha power orchestrate short-term memory decay and encourage a more nuanced perspective on alpha power across brain space and time beyond its inhibitory role. Our sensory memories of the physical world fade quickly. We show here that this decay of short-term memory can be counteracted by so-called temporal expectation; that is, knowledge of when to expect a sensory event that an individual must remember. We also show that neural oscillations in the "alpha" (8-13 Hz) range index both the degree of memory decay (for brief sound patterns) and the respective memory benefit from temporal expectation. Spatially distributed cortical patterns of alpha power show opposing effects in auditory versus visual sensory cortices. Moreover, alpha-tuned connectivity changes within supramodal attention networks reflect the allocation of neural resources as short-term memory representations fade.

31The hippocampus and related neocortical structures in memory transformation.PubMed

Melanie J Sekeres, Gordon Winocur, Morris Moscovitch

Neurosci Lett. 2018 Jul 27;680:39-53. doi: 10.1016/j.neulet.2018.05.006. Epub 2018 May 4.

Episodic memories are multifaceted and malleable, capable of being transformed with time and experience at both the neural level and psychological level. At the neural level, episodic memories are transformed from being dependent on the hippocampus to becoming represented in neocortical structures, such as the medial prefrontal cortex (mPFC), and back again, while at the psychological level, detailed, perceptually rich memories, are transformed to ones retaining only the gist of an experience or a schema related to it. Trace Transformation Theory (TTT) initially proposed that neural and psychological transformations are linked and proceed in tandem. Building on recent studies on the neurobiology of memory transformation in rodents and on the organization of the hippocampus and its functional cortical connectivity in humans, we present an updated version of TTT that is more precise and detailed with respect to the dynamic processes and structures implicated in memory transformation. At the heart of the updated TTT lies the long axis of the hippocampus whose functional differentiation and connectivity to neocortex make it a hub for memory formation and transformation. The posterior hippocampus, connected to perceptual and spatial representational systems in posterior neocortex, supports fine, perceptually rich, local details of memories; the anterior hippocampus, connected to conceptual systems in anterior neocortex, supports coarse, global representations that constitute the gist of a memory. Notable among the anterior neocortical structures is the medial prefrontal cortex (mPFC) which supports representation of schemas that code for common aspects of memories across different episodes. Linking the aHPC with mPFC is the entorhinal cortex (EC) which conveys information needed for the interaction/translation between gist and schemas. Thus, the long axis of the hippocampus, mPFC and EC provide the representational gradient, from fine to coarse and from perceptual to conceptual, that can implement processes implicated in memory transformation. Each of these representations of an episodic memory can co-exist and be in dynamic flux as they interact with one another throughout the memory's lifetime, going from detailed to schematic and possibly back again, all mediated by corresponding changes in neural representation.

34Executive Dysfunction and the Prefrontal Cortex.PubMed

David T Jones, Jonathan Graff-Radford

Continuum (Minneap Minn). 2021 Dec 1;27(6):1586-1601. doi: 10.1212/CON.0000000000001009.

PURPOSE OF REVIEW: This article summarizes the cognitive and behavioral functions of the prefrontal cortex with an emphasis on executive cognitive functions and the clinical consequences associated with executive dysfunction. The clinical manifestations of lesions to the lateral prefrontal, orbitofrontal, medial prefrontal, and frontopolar cortex are reviewed. RECENT FINDINGS: Traditional lesion studies have emphasized the role of a brain region in controlling a cognitive function. With advances in neurology, neuropsychology, and neuroimaging, the participation of the prefrontal cortex in large-scale networks has been established with recognition that cognitive dysfunction can arise not only from a lesion within a network but also from degenerative disease targeting these large-scale, dynamic neural networks. Although executive dysfunction can result from frontal lobe injury, this article highlights the role of distributed processes subserving executive functions. An atypical phenotype of Alzheimer disease has been described that selectively targets parietal-temporal-frontal networks important for core executive functions. SUMMARY: Executive function comprises working memory, cognitive flexibility, and inhibition and depends on top-down (ie, goal-driven) control of distributed processes occurring throughout the brain. The exact behavioral output (ie, function) depends on the content of the processes being controlled. Prefrontal cortex regions serve key cognitive functions related to social, emotional, and motivational aspects of behavior. The dorsal lateral prefrontal cortex plays a role in working memory, goal-driven attention, task switching, planning, problem-solving, and novelty-seeking. The ventral lateral prefrontal cortex plays a role in inhibition, response selection, and monitoring; the medial prefrontal cortex in self-knowledge, motivation, emotional regulation, and updating goal-directed behavior; the orbitofrontal cortex in personality, inhibition, and emotional and social reasoning. Although dysexecutive syndromes have been traditionally associated with dorsolateral prefrontal cortex injury, it is now recognized that they can also result from an impaired parietal-temporal-frontal system, which is targeted in a distinct form of atypical Alzheimer disease. This dysexecutive Alzheimer phenotype is characterized by impaired task performance on a wide battery of neuropsychological tests and simple daily tasks that require executive control. In contrast, dysexecutive syndromes more localized to the frontal lobe involve impaired executive control of social, emotional, and motivational aspects of behavior.

89Multisensory Integration and AgingPubMed

Jennifer L. Mozolic, Christina E. Hugenschmidt, Ann M. Peiffer, et al.

Effective processing of multisensory stimuli relies on both the peripheral sensory organs and central processing in subcortical and cortical structures. As we age, there are significant changes in all sensory systems and a variety of cognitive functions. Visual acuity tends to decrease and hearing thresholds generally increase (Kalina 1997; Liu and Yan 2007), whereas performance levels on tasks of motor speed, executive function, and memory typically decline (Rapp and Heindel 1994; Birren and Fisher 1995; Rhodes 2004). There are also widespread changes in the aging brain, including reductions in gray and white matter volume (Good et al. 2001; Salat et al. 2009), alterations in neurotransmitter systems (Muir 1997; Backman et al. 2006), regional hypoperfusion (Martin et al. 1991; Bertsch et al. 2009), and altered patterns of functional activity during cognitive tasks (Cabeza et al. 2004; Grady 2008). Given the extent of age-related alterations in sensation, perception, and cognition, as well as in the anatomy and physiology of the brain, it is not surprising that multisensory integration also changes with age. Several early studies provided mixed results on the differences between multisensory processing in older and younger adults (Stine et al. 1990; Helfer 1998; Strupp et al. 1999; Cienkowski and Carney 2002; Sommers et al. 2005). For example, Stine and colleagues (1990) reported that although younger adults’ memory for news events was better after audiovisual presentation than after auditory information alone, older adults did not show improvement during the multisensory conditions. In contrast, Cienkowski and Carney (2002) demonstrated that audiovisual integration on the McGurk illusion was similar for older and younger adults, and that in some conditions, older adults were even more likely to report the fusion of visual and auditory information than their young counterparts. Similarly, in a study examining the contribution of somatosensory input to participants’ perception of visuospatial orientation, Strupp et al. (1999) reported an age-related increase in the integration of somatosensory information into the multisensory representation of body orientation. Despite providing a good indication that multisensory processing is somehow altered in aging, the results of these studies are somewhat difficult to interpret due to their use of complex cognitive tasks and illusions, and to the variability in analysis methods. Several newer studies that have attempted to address these factors more clearly demonstrate that multisensory integration is enhanced in older adults (Laurienti et al. 2006; Peiffer et al. 2007; Diederich et al. 2008). On a two-choice audiovisual discrimination task, Laurienti and colleagues (2006) showed that response time (RT) benefits for multisensory versus unisensory targets were larger for older adults than for younger adults (Figure 20.1). That is, older adults’ responses during audiovisual conditions were speeded more than younger adults’, when compared with their respective responses during unisensory conditions. Multisensory gains in older adults remained significantly larger than those observed in younger adults, even after controlling for the presence of two targets in the multisensory condition (redundant target effect; Miller 1982, 1986; Laurienti et al. 2006). Using similar analysis methods, Peiffer et al. (2007) also reported increased multisensory gains in older adults. On a simple RT task, where average unisensory RTs were equivalent in younger and older adults, older adults actually responded than younger adults on multisensory trials because of their enhanced multisensory integration (Peiffer et al. 2007). Diederich and colleagues (2008) have also shown that older adults exhibit greater speeding of responses to multisensory targets than younger adults on a saccadic RT task. The analysis methods used in this experiment indicate a slowing of peripheral sensory processing, as well as a wider time window over which integration of auditory and visual stimuli can occur (Diederich et al. 2008). These experiments highlight several possible explanations that could help answer a critical question about multisensory processing in aging: Why do older adults exhibit greater integration of multisensory stimuli than younger adults? Potential sources of enhanced integration in older adults include age-related cognitive slowing not specific to multisensory processing, inverse effectiveness associated with sensory deficits, alterations in the temporal parameters of integration, and inefficient top–down modulation of sensory processing. In the following sections we will investigate each of these possible explanations in greater detail and offer some alternative hypotheses for the basis of enhanced multisensory integration in older adults.

123Rationale for a Multi-Factorial Approach for the Reversal of Cognitive Decline in Alzheimer's Disease and MCI: A Review.PubMed

Rammohan V Rao, Kaavya G Subramaniam, Julie Gregory, et al.

Int J Mol Sci. 2023 Jan 14;24(2):1659. doi: 10.3390/ijms24021659.

Alzheimer's disease (AD) is a multifactorial, progressive, neurodegenerative disease typically characterized by memory loss, personality changes, and a decline in overall cognitive function. Usually manifesting in individuals over the age of 60, this is the most prevalent type of dementia and remains the fifth leading cause of death among Americans aged 65 and older. While the development of effective treatment and prevention for AD is a major healthcare goal, unfortunately, therapeutic approaches to date have yet to find a treatment plan that produces long-term cognitive improvement. Drugs that may be able to slow down the progression rate of AD are being introduced to the market; however, there has been no previous solution for preventing or reversing the disease-associated cognitive decline. Recent studies have identified several factors that contribute to the progression and severity of the disease: diet, lifestyle, stress, sleep, nutrient deficiencies, mental health, socialization, and toxins. Thus, increasing evidence supports dietary and other lifestyle changes as potentially effective ways to prevent, slow, or reverse AD progression. Studies also have demonstrated that a personalized, multi-therapeutic approach is needed to improve metabolic abnormalities and AD-associated cognitive decline. These studies suggest the effects of abnormalities, such as insulin resistance, chronic inflammation, hypovitaminosis D, hormonal deficiencies, and hyperhomocysteinemia, in the AD process. Therefore a personalized, multi-therapeutic program based on an individual's genetics and biochemistry may be preferable over a single-drug/mono-therapeutic approach. This article reviews these multi-therapeutic strategies that identify and attenuate all the risk factors specific to each affected individual. This article systematically reviews studies that have incorporated multiple strategies that target numerous factors simultaneously to reverse or treat cognitive decline. We included high-quality clinical trials and observational studies that focused on the cognitive effects of programs comprising lifestyle, physical, and mental activity, as well as nutritional aspects. Articles from PubMed Central, Scopus, and Google Scholar databases were collected, and abstracts were reviewed for relevance to the subject matter. Epidemiological, pathological, toxicological, genetic, and biochemical studies have all concluded that AD represents a complex network insufficiency. The research studies explored in this manuscript confirm the need for a multifactorial approach to target the various risk factors of AD. A single-drug approach may delay the progression of memory loss but, to date, has not prevented or reversed it. Diet, physical activity, sleep, stress, and environment all contribute to the progression of the disease, and, therefore, a multi-factorial optimization of network support and function offers a rational therapeutic strategy. Thus, a multi-therapeutic program that simultaneously targets multiple factors underlying the AD network may be more effective than a mono-therapeutic approach.

133Development of novel phosphodiesterase 5 inhibitors for the therapy of Alzheimer's disease.PubMed

Elisa Zuccarello, Erica Acquarone, Elisa Calcagno, et al.

Biochem Pharmacol. 2020 Jun;176:113818. doi: 10.1016/j.bcp.2020.113818. Epub 2020 Jan 21.

Nitric oxide (NO) is a gaseous molecule that plays a multifactorial role in several cellular processes. In the central nervous system, the NO dual nature in neuroprotection and neurotoxicity has been explored to unveil its involvement in Alzheimer's disease (AD). A growing body of research shows that the activation of the NO signaling pathway leading to the phosphorylation of the transcription factor cyclic adenine monophosphate responsive element binding protein (CREB) (so-called NO/cGMP/PKG/CREB signaling pathway) ameliorates altered neuroplasticity and memory deficits in AD animal models. In addition to NO donors, several other pharmacological agents, such as phosphodiesterase 5 (PDE5) inhibitors have been used to activate the pathway and rescue memory disorders. PDE5 inhibitors, including sildenafil, tadalafil and vardenafil, are marketed for the treatment of erectile dysfunction and arterial pulmonary hypertension due to their vasodilatory properties. The ability of PDE5 inhibitors to interfere with the NO/cGMP/PKG/CREB signaling pathway by increasing the levels of cGMP has prompted the hypothesis that PDE5 inhibition might be used as an effective therapeutic strategy for the treatment of AD. To this end, newly designed PDE5 inhibitors belonging to different chemical classes with improved pharmacologic profile (e.g. higher potency, improved selectivity, and blood-brain barrier penetration) have been synthesized and evaluated in several animal models of AD. In addition, recent medicinal chemistry effort has led to the development of agents concurrently acting on the PDE5 enzyme and a second target involved in AD. Both marketed and investigational PDE5 inhibitors have shown to reverse cognitive defects in young and aged wild type mice as well as transgenic mouse models of AD and tauopathy using a variety of behavioral tasks. These studies confirmed the therapeutic potential of PDE5 inhibitors as cognitive enhancers. However, clinical studies assessing cognitive functions using marketed PDE5 inhibitors have not been conclusive. Drug discovery efforts by our group and others are currently directed towards the development of novel PDE5 inhibitors tailored to AD with improved pharmacodynamic and pharmacokinetic properties. In summary, the present perspective reports an overview of the correlation between the NO signaling and AD, as well as an outline of the PDE5 inhibitors used as an alternative approach in altering the NO pathway leading to an improvement of learning and memory. The last two sections describe the preclinical and clinical evaluation of PDE5 inhibitors for the treatment of AD, providing a comprehensive analysis of the current status of the AD drug discovery efforts involving PDE5 as a new therapeutic target.

154Developing a machine learning model for detecting depression, anxiety, and apathy in older adults with mild cognitive impairment using speech and facial expressions: A cross-sectional observational study.PubMed

Ying Zhou, Wei Han, Xiuyu Yao, et al.

Int J Nurs Stud. 2023 Oct;146:104562. doi: 10.1016/j.ijnurstu.2023.104562. Epub 2023 Jul 7.

BACKGROUND: Depression, anxiety, and apathy are highly prevalent in older people with preclinical dementia and mild cognitive impairment. These symptoms have also proven valuable in predicting the progression from mild cognitive impairment to dementia, enabling a timely diagnosis and treatment. However, objective and reliable indicators to detect and distinguish depression, anxiety, and apathy are relatively scarce. OBJECTIVE: This study aimed to develop a machine learning model to detect and distinguish depression, anxiety, and apathy based on speech and facial expressions. DESIGN: An observational, cross-sectional study design. SETTING(S): The memory outpatient department of a tertiary hospital. PARTICIPANTS: 319 older adults diagnosed with mild cognitive impairment. METHODS: Depression, anxiety, and apathy were evaluated by the Public Health Questionnaire, General Anxiety Disorder, and Apathy Evaluation Scale, respectively. Speech and facial expressions of older adults with mild cognitive impairment were digitally captured using audio and video recording software. Open-source data analysis toolkits were utilized to extract speech, facial, and text features. The multiclass classification was used to develop classification models, and shapely additive explanations were used to explain the contribution of each feature within the model. RESULTS: The random forest method was used to develop a multiclass emotion classification model, which performed well in classifying emotions with a weighted-average F1 score of 96.6 %. The model also demonstrated high accuracy, precision, and recall, with 87.4 %, 86.6 %, and 87.6 %, respectively. CONCLUSIONS: The machine learning model developed in this study demonstrated strong classification performance in detecting and differentiating depression, anxiety, and apathy. This innovative approach combines text, audio, and video to provide objective methods for precise classification and remote monitoring of these symptoms in nursing practice. REGISTRATION: This study was registered at the Chinese Clinical Trial Registry (registration number: ChiCTR1900023892; registration date: June 19th, 2019).

155Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.PubMed

Astri J Lundervold, Julie E Billing, Birgitte Berentsen, et al.

BMC Gastroenterol. 2024 Aug 15;24(1):267. doi: 10.1186/s12876-024-03355-z.

PURPOSE: Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms like abdominal pain and changes associated with defecation. The condition is classified as a disorder of the gut-brain interaction (DGBI), and patients with IBS commonly experience psychological distress. The present study focuses on this distress, defined from reports of fatigue, anxiety, depression, sleep disturbances, and performance on cognitive tests. The aim was to investigate the joint contribution of these features of psychological distress in predicting IBS versus healthy controls (HCs) and to disentangle clinically meaningful subgroups of IBS patients. METHODS: IBS patients ( ) and HCs ( ) completed the Chalder Fatigue Scale (CFQ), the Hamilton Anxiety and Depression Scale (HADS), and the Bergen Insomnia Scale (BIS), and performed tests of memory function and attention from the Repeatable Battery Assessing Neuropsychological Symptoms (RBANS). An initial exploratory data analysis was followed by supervised (Random Forest) and unsupervised (K-means) classification procedures. RESULTS: The explorative data analysis showed that the group of IBS patients obtained significantly more severe scores than HCs on all included measures, with the strongest pairwise correlation between fatigue and a quality measure of sleep disturbances. The supervised classification model correctly predicted belongings to the IBS group in 80% of the cases in a test set of unseen data. Two methods for calculating feature importance in the test set gave mental and physical fatigue and anxiety the strongest weights. An unsupervised procedure with showed that one cluster contained 24% of the patients and all but two HCs. In the two other clusters, their IBS members were overall more impaired, with the following differences. One of the two clusters showed more severe cognitive problems and anxiety symptoms than the other, which experienced more severe problems related to the quality of sleep and fatigue. The three clusters were not different on a severity measure of IBS and age. CONCLUSION: The results showed that psychological distress is an integral component of IBS symptomatology. The study should inspire future longitudinal studies to further dissect clinical patterns of IBS to improve the assessment and personalized treatment for this and other patient groups defined as disorders of the gut-brain interaction. The project is registered at https://classic. CLINICALTRIALS: gov/ct2/show/NCT04296552 20/05/2019.

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人类大脑记忆机制的神经生物学基础与动态过程研究综述

1. 记忆的分类体系与核心特征

1.1 基于时间尺度的记忆类型划分

1.2 基于内容属性的记忆功能分类

2. 记忆形成的神经基础与功能网络

2.1 关键脑区的特异性功能定位

2.2 神经可塑性的支撑作用

3. 记忆调控的分子与细胞机制

3.1 关键分子信号通路

3.2 表观遗传修饰的调控功能

4. 记忆动态过程的时间维度解析

4.1 编码阶段：信息的初步整合

4.2 巩固阶段：从脆弱到稳定的转化

4.3 提取阶段：记忆的再激活与重构

5. 记忆异常的病理机制与干预策略

5.1 记忆障碍的典型病理模型

5.2 记忆干预技术的应用进展

6. 记忆研究的前沿技术与未来方向

6.1 多模态神经成像技术的突破

6.2 类脑计算与记忆模拟

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人类大脑记忆机制的神经生物学基础与动态过程研究综述

1. 记忆的分类体系与核心特征

1.1 基于时间尺度的记忆类型划分

1.2 基于内容属性的记忆功能分类

2. 记忆形成的神经基础与功能网络

2.1 关键脑区的特异性功能定位

2.2 神经可塑性的支撑作用

3. 记忆调控的分子与细胞机制

3.1 关键分子信号通路

3.2 表观遗传修饰的调控功能

4. 记忆动态过程的时间维度解析

4.1 编码阶段：信息的初步整合

4.2 巩固阶段：从脆弱到稳定的转化

4.3 提取阶段：记忆的再激活与重构

5. 记忆异常的病理机制与干预策略

5.1 记忆障碍的典型病理模型

5.2 记忆干预技术的应用进展

6. 记忆研究的前沿技术与未来方向

6.1 多模态神经成像技术的突破

6.2 类脑计算与记忆模拟

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