Neuroscientific Findings Research Articles

신경과학의 정서연구를 통한 수(受) 고찰

신경과학의 정서연구를 통한 수(受) 고찰

Challenging deep learning models with image distortion based on the abutting grating illusion

Even state-of-the-art deep learning models lack fundamental abilities compared with humans. While many image distortions have been proposed to compare deep learning with humans, they depend on mathematical transformations instead of human cognitive functions. Here, we propose an image distortion based on the abutting grating illusion, which is a phenomenon discovered in humans and animals. The distortion generates illusory contour perception using line gratings abutting each other. We applied the method to MNIST, high-resolution MNIST, and "16-class-ImageNet" silhouettes. Many models, including models trained from scratch and 109 models pretrained with ImageNet or various data augmentation techniques, were tested. Our results show that abutting grating distortion is challenging even for state-of-the-art deep learning models. We discovered that DeepAugment models outperformed other pretrained models. Visualization of early layers indicates that better-performing models exhibit the endstopping property, which is consistent with neuroscience discoveries. Twenty-four human subjects classified distorted samples to validate the distortion.

A wearable platform for closed-loop stimulation and recording of single-neuron and local field potential activity in freely moving humans

Advances in technologies that can record and stimulate deep brain activity in humans have led to impactful discoveries within the field of neuroscience and contributed to the development of novel therapies for neurological and psychiatric disorders. Further progress, however, has been hindered by device limitations in that recording of single-neuron activity during freely moving behaviors in humans has not been possible. Additionally, implantable neurostimulation devices, currently approved for human use, have limited stimulation programmability and restricted full-duplex bidirectional capability. In this study, we developed a wearable bidirectional closed-loop neuromodulation system (Neuro-stack) and used it to record single-neuron and local field potential activity during stationary and ambulatory behavior in humans. Together with a highly flexible and customizable stimulation capability, the Neuro-stack provides an opportunity to investigate the neurophysiological basis of disease, develop improved responsive neuromodulation therapies, explore brain function during naturalistic behaviors in humans and, consequently, bridge decades of neuroscientific findings across species.

Late-life depression and frailty-Epidemiological, clinical and neurobiological associations

Depression is the most common mental disorder in older adults and is influenced by age-related processes. Frailty is awell-established clinical expression of ageing that implies astate of increased vulnerability to stressor events as well as increased risks of disability, hospitalization and death. Neurobiological findings will disentangle the comorbidity of frailty and depression and may inform future management of depression in old age. This narrative review provides an overview of the comorbidity of late-life depression and frailty, with afocus on neuroscientific findings that are organized within the research domain criteria (RDoC) framework. More than one third of old people with depression are affected by frailty, which results in more chronic depression and in poorer efficacy and tolerability of antidepressant medication. Depression and frailty share motivational and psychomotor characteristics, particularly apathy, decreased physical activity and fatigue. In patients with frailty, altered activity of the supplementary motor cortex is associated with motor performance deficits. Patients with late-life depression and apathy are characterized by abnormal structure and altered functional connectivity of the reward network and the salience network, along with altered functional connectivity of these networks with premotor brain areas. Identifying frailty in older adults with depression is relevant for prognostic assessment and treatment. Abetter understanding of the neuronal mechanisms of comorbidity will provide potential targets for future personalized therapeutic interventions.

Neurocognitive Model of Schema-Congruent and -Incongruent Learning in Clinical Disorders: Application to Social Anxiety and Beyond

Negative schemas lie at the core of many common and debilitating mental disorders. Thus, intervention scientists and clinicians have long recognized the importance of designing effective interventions that target schema change. Here, we suggest that the optimal development and administration of such interventions can benefit from a framework outlining how schema change occurs in the brain. Guided by basic neuroscientific findings, we provide a memory-based neurocognitive framework for conceptualizing how schemas emerge and change over time and how they can be modified during psychological treatment of clinical disorders. We highlight the critical roles of the hippocampus, ventromedial prefrontal cortex, amygdala, and posterior neocortex in directing schema-congruent and -incongruent learning (SCIL) in the interactive neural network that comprises the autobiographical memory system. We then use this framework, which we call the SCIL model, to derive new insights about the optimal design features of clinical interventions that aim to strengthen or weaken schema-based knowledge through the core processes of episodic mental simulation and prediction error. Finally, we examine clinical applications of the SCIL model to schema-change interventions in psychotherapy and provide cognitive-behavior therapy for social anxiety disorder as an illustrative example.

Neuroscience-based psychotherapy: A position paper.

In the recent years, discoveries in neuroscience have greatly impacted upon the need to modify therapeutic practice starting from the evidence showing some cerebral mechanisms capable of coping with mental health crisis and traumatic events of the individual's life history by redesigning the narrative plot and the person's sense of the Self. The emerging dialogue between neuroscience and psychotherapy is increasingly intense and modern psychotherapy cannot ignore the heritage deriving from studies about neuropsychological modification of memory traces, neurobiology of attachment theory, cognitive mechanisms involved in psychopathology, neurophysiology of human empathy, neuroimaging evidence about psychotherapeutic treatment, and somatoform disorders connecting the brain and the body. In the present article, we critically examined sectorial literature and claimed that psychotherapy has to referred to a neuroscience-based approach in order to adopt the most tailored interventions for specific groups of patients or therapy settings. We also provided recommendations for care implementation in clinical practice and illustrated challenges of future research.

CULTURAL HISTORY OF PSYCHOANALYSIS IN THE AGE OF NEUROSCIENCE.

In this paper I have chosen the topic of psychoanalysis in the age of neuroscience, with the aim of showing why the cultural history of psychoanalysis still matters. To make myself better understood I shall refrain from evaluating the current findings in neuroscience and limit myself to reporting briefly on them. Although I do not regard myself by any means as an expert in that field, I may be permitted to offer a few ideas about it. In this regard, there is presently a significant predominance of biological ideologies and practices regarding the treatment of mental illness, which implies an increase in the interest in etiology, nosology, definitions, and the effectivity of treatments. Even so, those psychoanalytic historians and/or analysts among us who are committed to psychoanalysis and its therapeutic implications, irrespective of what drugs might be prescribed and what the research findings might conclude, believe that patients still want to be listened to in depth and always will. For that reason, it is justified to ask why the cultural history of psychoanalysis still matters in a contemporary mental health environment that is ever more oriented towards the neurosciences.

Diminished Repetition Suppression Reveals Selective and Systems-Level Face Processing Differences in ASD.

Repeated exposure to a stimulus results in reduced neural response, or repetition suppression, in brain regions responsible for processing that stimulus. This rapid accommodation to repetition is thought to underlie learning, stimulus selectivity, and strengthening of perceptual expectations. Importantly, reduced sensitivity to repetition has been identified in several neurodevelopmental, learning, and psychiatric disorders, including autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by challenges in social communication and repetitive behaviors and restricted interests. Reduced ability to exploit or learn from repetition in ASD is hypothesized to contribute to sensory hypersensitivities, and parallels several theoretical frameworks claiming that ASD individuals show difficulty using regularities in the environment to facilitate behavior. Using fMRI in autistic and neurotypical human adults (females and males), we assessed the status of repetition suppression across two modalities (vision, audition) and with four stimulus categories (faces, objects, printed words, and spoken words). ASD individuals showed domain-specific reductions in repetition suppression for face stimuli only, but not for objects, printed words, or spoken words. Reduced repetition suppression for faces was associated with greater challenges in social communication in ASD. We also found altered functional connectivity between atypically adapting cortical regions and higher-order face recognition regions, and microstructural differences in related white matter tracts in ASD. These results suggest that fundamental neural mechanisms and system-wide circuits are selectively altered for face processing in ASD and enhance our understanding of how disruptions in the formation of stable face representations may relate to higher-order social communication processes.SIGNIFICANCE STATEMENT A common finding in neuroscience is that repetition results in plasticity in stimulus-specific processing regions, reflecting selectivity and adaptation (repetition suppression [RS]). RS is reduced in several neurodevelopmental and psychiatric conditions including autism spectrum disorder (ASD). Theoretical frameworks of ASD posit that reduced adaptation may contribute to associated challenges in social communication and sensory processing. However, the scope of RS differences in ASD is unknown. We examined RS for multiple categories across visual and auditory domains (faces, objects, printed words, spoken words) in autistic and neurotypical individuals. We found reduced RS in ASD for face stimuli only and altered functional connectivity and white matter microstructure between cortical face-recognition areas. RS magnitude correlated with social communication challenges among autistic individuals.

The Neuroscience Of Story: The Role Of Storytelling In Psychotherapy

One of the more interesting discoveries in neuroscience in recent years is the impact that the use of non-directive forms of communication, including stories and metaphors, has on our brain. In this article, we will review the most important literature of recent research in this area, and address both the benefits and risks of the new knowledge gained from these discoveries.

Examining litter specific variability in mice and its impact on neurodevelopmental studies

Our current understanding of litter variability in neurodevelopmental studies using mice may limit translation of neuroscientific findings. Higher variance of measures across litters than within, often termed intra-litter likeness, may be attributable to both pre- and postnatal environment. This study aimed to assess the litter-effect within behavioral assessments (2 timepoints) and anatomy using T1-weighted magnetic resonance images across 72 brain region volumes (4 timepoints) (36 C57bl/6J inbred mice; 7 litters: 19F/17M). Between-litter comparisons of brain and behavioral measures and their associations were evaluated using univariate and multivariate techniques. A power analysis using simulation methods was then performed on modeled neurodevelopment and to evaluate trade-offs between number-of-litters, number-of-mice-per-litter, and sample size. Our results show litter-specific developmental effects, from the adolescent period to adulthood for brain structure volumes and behaviors, and for their associations in adulthood. Our power simulation analysis suggests increasing the number-of-litters in experimental designs to achieve the smallest total sample size necessary for detecting different rates of change in specific brain regions. Our results demonstrate how litter-specific effects may influence development and that increasing the litters to the total sample size ratio should be strongly considered when designing neurodevelopmental studies.

Droplet-based transcriptome profiling of individual synapses.

Synapses are crucial structures that mediate signal transmission between neurons in complex neural circuits and display considerable morphological and electrophysiological heterogeneity. So far we still lack a high-throughput method to profile the molecular heterogeneity among individual synapses. In the present study, we develop a droplet-based single-cell (sc) total-RNA-sequencing platform, called Multiple-Annealing-and-Tailing-based Quantitative scRNA-seq in Droplets, for transcriptome profiling of individual neurites, primarily composed of synaptosomes. In the synaptosome transcriptome, or 'synaptome', profiling of both mouse and human brain samples, we detect subclusters among synaptosomes that are associated with neuronal subtypes and characterize the landscape of transcript splicing that occurs within synapses. We extend synaptome profiling to synaptopathy in an Alzheimer's disease (AD) mouse model and discover AD-associated synaptic gene expression changes that cannot be detected by single-nucleus transcriptome profiling. Overall, our results show that this platform provides a high-throughput, single-synaptosome transcriptome profiling tool that will facilitate future discoveries in neuroscience.

A generative adversarial model of intrusive imagery in the human brain.

The mechanisms underlying the subjective experiences of mental disorders remain poorly understood. This is partly due to long-standing over-emphasis on behavioral and physiological symptoms and a de-emphasis of the patient's subjective experiences when searching for treatments. Here, we provide a new perspective on the subjective experience of mental disorders based on findings in neuroscience and artificial intelligence (AI). Specifically, we propose the subjective experience that occurs in visual imagination depends on mechanisms similar to generative adversarial networks that have recently been developed in AI. The basic idea is that a generator network fabricates a prediction of the world, and a discriminator network determines whether it is likely real or not. Given that similar adversarial interactions occur in the two major visual pathways of perception in people, we explored whether we could leverage this AI-inspired approach to better understand the intrusive imagery experiences of patients suffering from mental illnesses such as post-traumatic stress disorder (PTSD) and acute stress disorder. In our model, a nonconscious visual pathway generates predictions of the environment that influence the parallel but interacting conscious pathway. We propose that in some patients, an imbalance in these adversarial interactions leads to an overrepresentation of disturbing content relative to current reality, and results in debilitating flashbacks. By situating the subjective experience of intrusive visual imagery in the adversarial interaction of these visual pathways, we propose testable hypotheses on novel mechanisms and clinical applications for controlling and possibly preventing symptoms resulting from intrusive imagery.

Neuroeducation and Artistic Expression. An Overview from the Biopsychology Viewpoint

In this research, the relationship between positive emotions and the pathways that govern how artistic concepts are processed in the brain and influence the essential characteristics of learning - focus, memory, and motivation - is investigated. In addition, the brain mechanisms of emotional and cognitive links are investigated in order to give a framework for the present discoveries of neuroscience in order to elucidate the relationship between emotions and cognition. The relationship between emotions and art and artistic activities in general is then established, and its contribution to the educational process is emphasized. In conclusion, the fundamental principles of neuroaesthetics and neuroimaging for this topic are studied, and therapeutic effects of artistic activities are discussed.

Report on the 21st Congress of the International Neuropsychoanalysis Society, San Juan, Puerto Rico, 2022: “Neuropsychoanalysis: Implications for Clinical Technique”

ABSTRACT The 21st Congress of the International Neuropsychoanalysis Society took place in San Juan, Puerto Rico, after two years of waiting because of the lockdown due to the Coronavirus pandemic. The Congress used a hybrid format for the first time to include people who were not able to travel to San Juan. The theme of the Congress was “Neuropsychoanalysis: Implications for Clinical Technique.” The audience had the opportunity of listening to presentations that covered various topics such as memory and learning, transference, the brain explained for the psychodynamically-minded and vice-versa, psychopathology and psychotherapy, modifications to the technique based on neuroscientific findings, clinical praxis and supervision, developmental perspectives, using affective neuroscience in the clinical setting, perspectives on brain injury, emerging psychoanalytic perspectives, research enriching neuropsychoanalytic models, and case presentations.

The Politics of Emotion in Damon Galgut’s The Promise

The “affective turn” of Western literary criticism arose at the beginning of the 21^st century as a result of new discoveries in neuroscience, cognitive science, and other disciplines. As one of the main fields of Affect Studies, discourses of the emotion pry into the emotional dimensions of literary texts to reveal the embodiment, sociality, and politics of emotions. South African writer Damon Galgut constructs a series of affective scenes with both individuality and representativeness in his 2021 Booker Prize-winning novel The Promise and thus turns the fictional world into an affective field. The novelist focuses on the titular event “promise” and takes it as the thread running through four funerals of the white Swart family. Through the lens of Affect Studies, the author attempts to interpret shame, anger and compassion behind the Swarts’ making, breaching, and honouring of the promise and examines how those emotions are dictated by South Africa’s gender, racial and class politics. The author concludes that the compassion-based African Ubuntu philosophy may lead South Africa to the promised land of national reconciliation.

Astrocytic gliotransmission as a pathway for stable stimulation of post-synaptic spiking: Implications for working memory*

The brain consists not only of neurons but also of non-neuronal cells, including astrocytes. Recent discoveries in neuroscience suggest that astrocytes directly regulate neuronal activity by releasing gliotransmitters such as glutamate. In this paper, we consider a biologically plausible mathematical model of a tripartite neuron-astrocyte network. We study the stability of the nonlinear astrocyte dynamics, as well as its role in regulating the firing rate of the postsynaptic neuron. We show that astrocytes enable storing neuronal information temporarily. Motivated by recent findings on the role of astrocytes in explaining mechanisms of working memory, we numerically verify the utility of our analysis in showing the possibility of two competing theories of persistent and sparse neuronal activity of working memory.

Magnetic resonance imaging-based progress in human glymphatic system research

The recently discovered glymphatic system is considered a prominent breakthrough in neuroscience. The glymphatic system serves as a cerebrospinal fluid-interstitial fluid exchange system involving polarization of the water channel protein, aquaporin-4, in astrocyte endfeet. In this review we summarize the MRI findings that have contributed to the research advances of the human glymphatic system and propose prospective future applications.

Jointly Fusing Multi-Scale Spatial-Logical Brain Networks: A Neural Decoding Method.

Functional magnetic resonance imaging (fMRI) is a methodology for measuring human brain activities. It has become more and more popular in neural decoding due to its noninvasive. Neural decoding aims to establishing models to reconstruct external stimuli or features of stimuli from known brain responses, so that we can understand the principles of brain functions such as emotion, cognition and language. Neural decoding based on fMRI is of great significance for further understanding the mechanism of brain operation. Most existing studies take multi-scale topology information of brain networks obtained from fMRI into account in neural decoding. However, they always ignore the simultaneous modeling of network structure and hemodynamic response, thus leading to information loss. In addition, current multi-scale methods usually only utilize spatial or logical reasoning relationship of brain networks, which brings challenge to precise neural decoding. In this work, we present a novel and robust multi-scale spatial and logical reasoning learning framework (MSLR) for fMRI-based neural decoding. Specifically, we first design graph signal wavelet generation module to combine brain network topology and node information to construct multi-scale representation of brain networks in a local to global manner. Then, we develop multi-scale information fusion module that can simultaneously model the spatial and logical reasoning relationship of brain networks, it can also learn discriminative multi-scale features with brain state transition. Finally, we construct a neural decoding module to predict the brain states. We evaluated the framework on the public Human Connectome Project (HCP) dataset that included 986 participants. The experimental results with support vector machine (SVM) outperform current state-of-the-art methods on four evaluation metrics (accuracy: 91.58, kappa coefficient: 0.883, macro F1: 0.865 and hamming distance: 0.105) under 19 different stimuli spanning 7 different cognitive tasks. The interpretation of the learned multi-scale representation replicates neuroscientific findings from previous fMRI studies and renews the multi-scale information flow pattern of brain network in neural decoding.

Enriched learning: behavior, brain, and computation.

The presence of complementary information across multiple sensory or motor modalities during learning, referred to as multimodal enrichment, can markedly benefit learning outcomes. Why is this? Here, we integrate cognitive, neuroscientific, and computational approaches to understanding the effectiveness of enrichment and discuss recent neuroscience findings indicating that crossmodal responses in sensory and motor brain regions causally contribute to the behavioral benefits of enrichment. The findings provide novel evidence for multimodal theories of enriched learning, challenge assumptions of longstanding cognitive theories, and provide counterevidence to unimodal neurobiologically inspired theories. Enriched educational methods are likely effective not only because they may engage greater levels of attention or deeper levels of processing, but also because multimodal interactions in the brain can enhance learning and memory.

Voxel-wise Mapping of Functional Magnetic Resonance Imaging in Impression Formation

Social interactions often involve encountering inconsistent information about social others. We conducted a functional magnetic resonance imaging (fMRI) study to comprehensively investigate voxel-wise temporal dynamics showing how impressions are anchored and/or adjusted in response to inconsistent social information. The participants performed a social impression task inside an fMRI scanner in which they were shown a male face, together with a series of four adjectives that described the depicted person''s personality traits, successively presented beneath the image of the face. Participants were asked to rate their impressions of the person at the end of each trial on a scale of 1 to 8 (where 1 is most negative and 8 is most positive). We established two hypothetical models that represented two temporal patterns of voxel activity: Model 1 featured decreasing patterns of activity towards the end of each trial, anchoring impressions to initially presented information, and Model 2 showed increasing patterns of activity toward the end of each trial, where impressions were being adjusted using new and inconsistent information. Our data-driven model fitting analyses showed that the temporal activity patterns of voxels within the ventral anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex, amygdala, and fusiform gyrus fit Model 1 (i.e., they were more involved in anchoring first impressions) better than they did Model 2 (i.e., showing impression adjustment). Conversely, voxel-wise neural activity within dorsal ACC and lateral OFC fit Model 2 better than it did Model 1, as it was more likely to be involved in processing new, inconsistent information and adjusting impressions in response. Our novel approach to model fitting analysis replicated previous impression-related neuroscientific findings, furthering the understanding of neural and temporal dynamics of impression processing, particularly with reference to functionally segmenting each region of interest based on relative involvement in impression anchoring as opposed to adjustment.