Advances In Neuroscience Research Articles

Mind and Machine: A Philosophical Examination of Matt Carter’s “Minds & Computers: An Introduction to the Philosophy of Artificial Intelligence”

In his book “Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence”, Matt Carter presents a comprehensive exploration of the philosophical questions surrounding artificial intelligence (AI). Carter argues that the development of AI is not merely a technological challenge but fundamentally a philosophical one. He delves into key issues like the nature of mental states, the limits of introspection, the implications of memory decay, and the functionalist framework that allows for the possibility of AI. Carter contrasts functionalism with reductive materialism, highlighting how the former accommodates the concept of artificial minds. He also emphasizes the significance of computationalism, which combines functionalism with computational theory to provide a robust explanation for mental processes. The book further discusses formal systems, the role of register machines in computation, and the inherent challenges in AI research, particularly in developing natural languag processing systems. Carter’s work underscores the limitations of current computational models of cognition while remaining hopeful that advances in neuroscience may lead to stronger AI systems in the future. This book provides critical insights for researchers in AI and cognitive science, motivating further inquiry into the philosophical foundations of artificial intelligence and its practical implications.

Analysis of the brain’s responses to the approach-avoidance behavior in architectural experience

Creating an optimal environment that addresses the users? psychological and behavioral needs requires a deep understanding of mental processes. Advances in neuroscience and applying its technical methods, such as neuroimaging, have provided the possibility to make an objective exploration of how architecture affects users? brain reactions. This study aims to objectify the effects of spatial characteristics of architectural settings on the brain?s responses and the users? approach-avoidance behavior. Therefore, to determine the regional activation of the nervous system responsible for emotions and approach-avoidance behavior, participants? brains were scanned with functional magnetic resonance imaging while looking at photographs of architectural spaces. Results showed that the pleasant and unpleasant spaces activate the brain structures involved in positive and negative emotions. Additionally, pleasant and unpleasant spaces were more likely to elicit inter and exit decisions and activate the brain?s regions engaged in approach and avoidance decisions.

Unsupervised Joint Domain Adaptation for Decoding Brain Cognitive States From tfMRI Images.

Recent advances in large model and neuroscience have enabled exploration of the mechanism of brain activity by using neuroimaging data. Brain decoding is one of the most promising researches to further understand the human cognitive function. However, current methods excessively depends on high-quality labeled data, which brings enormous expense of collection and annotation of neural images by experts. Besides, the performance of cross-individual decoding suffers from inconsistency in data distribution caused by individual variation and different collection equipments. To address mentioned above issues, a Join Domain Adapative Decoding (JDAD) framework is proposed for unsupervised decoding specific brain cognitive state related to behavioral task. Based on the volumetric feature extraction from task-based functional Magnetic Resonance Imaging (tfMRI) data, a novel objective loss function is designed by the combination of joint distribution regularizer, which aims to restrict the distance of both the conditional and marginal probability distribution of labeled and unlabeled samples. Experimental results on the public Human Connectome Project (HCP) S1200 dataset show that JDAD achieves superior performance than other prevalent methods, especially for fine-grained task with 11.5%-21.6% improvements of decoding accuracy. The learned 3D features are visualized by Grad-CAM to build a combination with brain functional regions, which provides a novel path to learn the function of brain cortex regions related to specific cognitive task in group level.

Integrative learning in the lens of meta-learned models of cognition: Impacts on animal and human learning outcomes

Abstract This commentary examines the synergy between meta-learned models of cognition and integrative learning in enhancing animal and human learning outcomes. It highlights three integrative learning modes – holistic integration of parts, top-down reasoning, and generalization with in-depth analysis – and their alignment with meta-learned models of cognition. This convergence promises significant advances in educational practices, artificial intelligence, and cognitive neuroscience, offering a novel perspective on learning and cognition.

Biomimetic learning of hand gestures in a humanoid robot.

Hand gestures are a natural and intuitive form of communication, and integrating this communication method into robotic systems presents significant potential to improve human-robot collaboration. Recent advances in motor neuroscience have focused on replicating human hand movements from synergies also known as movement primitives. Synergies, fundamental building blocks of movement, serve as a potential strategy adapted by the central nervous system to generate and control movements. Identifying how synergies contribute to movement can help in dexterous control of robotics, exoskeletons, prosthetics and extend its applications to rehabilitation. In this paper, 33 static hand gestures were recorded through a single RGB camera and identified in real-time through the MediaPipe framework as participants made various postures with their dominant hand. Assuming an open palm as initial posture, uniform joint angular velocities were obtained from all these gestures. By applying a dimensionality reduction method, kinematic synergies were obtained from these joint angular velocities. Kinematic synergies that explain 98% of variance of movements were utilized to reconstruct new hand gestures using convex optimization. Reconstructed hand gestures and selected kinematic synergies were translated onto a humanoid robot, Mitra, in real-time, as the participants demonstrated various hand gestures. The results showed that by using only few kinematic synergies it is possible to generate various hand gestures, with 95.7% accuracy. Furthermore, utilizing low-dimensional synergies in control of high dimensional end effectors holds promise to enable near-natural human-robot collaboration.

A Brief Analysis of the Puzzle of Consciousness

The challenging problem of consciousness, or more traditionally the mind-body problem, continues to maintain its vitality and importance despite all philosophical theories and advances in neuroscience, artificial intelligence and technology. The problem of consciousness has been addressed by both philosophers and scientists from ancient times to the present. In the most general sense, the problem of consciousness, also known as the hard problem, is the problem of how subjective mental states arise from a physical piece of meat. The main purpose of this article is to present a categorical and explanatory analysis of this puzzle of consciousness, which is still important today. For this purpose, first of all, the definitions of the concept of consciousness in the literature will be examined in depth. Afterwards, the characteristics of consciousness that are untamed for science, which turns it into the hard problem for us, will be touched upon, and the puzzle of consciousness will be explained with Chalmers' distinction between easy problems and the hard problem of consciousness. Finally, it is aimed to complete this explanatory analysis on the puzzle of consciousness by making a categorical distinction between traditional solution-oriented approaches to the problem of consciousness.

Gestalt's Perspective on Insight: A Recap Based on Recent Behavioral and Neuroscientific Evidence.

The Gestalt psychologists' theory of insight problem-solving was based on a direct parallelism between perceptual experience and higher-order forms of cognition (e.g., problem-solving). Similarly, albeit not exclusively, to the sudden recognition of bistable figures, these psychologists contended that problem-solving involves a restructuring of one's initial representation of the problem's elements, leading to a sudden leap of understanding phenomenologically indexed by the "Aha!" feeling. Over the last century, different scholars have discussed the validity of the Gestalt psychologists' perspective, foremost using the behavioral measures available at the time. However, in the last two decades, scientists have gained a deeper understanding of insight problem-solving due to the advancements in cognitive neuroscience. This review aims to provide a retrospective reading of Gestalt theory based on the knowledge accrued by adopting novel paradigms of research and investigating their neurophysiological correlates. Among several key points that the Gestalt psychologists underscored, we focus specifically on the role of the visual system in marking a discrete switch of knowledge into awareness, as well as the perceptual experience and holistic standpoints. While the main goal of this paper is to read the previous theory in light of new evidence, we also hope to initiate an academic discussion and encourage further research about the points we raise.

Efficient functional localization of language regions in the brain

Important recent advances in the cognitive neuroscience of language have been made using functional localizers to demarcate language-selective regions in individual brains. Although single-subject localizers offer insights that are unavailable in classic group analyses, they require additional scan time that imposes costs on investigators and participants. In particular, the unique practical challenges of scanning children and other special populations has led to less adoption of localizers for neuroimaging research with these theoretically and clinically important groups. Here, we examined how measurements of the spatial extent and functional response profiles of language regions are affected by the duration of an auditory language localizer. We compared how parametrically smaller amounts of data collected from one scanning session affected (i) consistency of group-level whole-brain parcellations, (ii) functional selectivity of subject-level activation in individually defined functional regions of interest (fROIs), (iii) sensitivity and specificity of subject-level whole-brain and fROI activation, and (iv) test-retest reliability of subject-level whole-brain and fROI activation. For many of these metrics, the localizer duration could be reduced by 50-75% while preserving the stability and reliability of both the spatial extent and functional response profiles of language areas. These results indicate that, for most measures relevant to cognitive neuroimaging studies, the brain's language network can be localized just as effectively with 3.5 min of scan time as it can with 12 min. Minimizing the time required to reliably localize the brain's language network allows more effective localizer use in situations where each minute of scan time is particularly precious.

Modeling Brain Representations of Words' Concreteness in Context Using GPT-2 and Human Ratings.

The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented opportunities to study the human brain in action as language is read and understood. Recent contextualized language models seem to be able to capture homonymic meaning variation ("bat", in a baseball vs. a vampire context), as well as more nuanced differences of meaning-for example, polysemous words such as "book", which can be interpreted in distinct but related senses ("explain a book", information, vs. "open a book", object) whose differences are fine-grained. We study these subtle differences in lexical meaning along the concrete/abstract dimension, as they are triggered by verb-noun semantic composition. We analyze functional magnetic resonance imaging (fMRI) activations elicited by Italian verb phrases containing nouns whose interpretation is affected by the verb to different degrees. By using a contextualized language model and human concreteness ratings, we shed light on where in the brain such fine-grained meaning variation takes place and how it is coded. Our results show that phrase concreteness judgments and the contextualized model can predict BOLD activation associated with semantic composition within the language network. Importantly, representations derived from a complex, nonlinear composition process consistently outperform simpler composition approaches. This is compatible with a holistic view of semantic composition in the brain, where semantic representations are modified by the process of composition itself. When looking at individual brain areas, we find that encoding performance is statistically significant, although with differing patterns of results, suggesting differential involvement, in the posterior superior temporal sulcus, inferior frontal gyrus and anterior temporal lobe, and in motor areas previously associated with processing of concreteness/abstractness.

Shatavadhan Could Imply A New State of Consciousness

Recent advances in neurosciences and an attempt to explain properties of consciousness has opened new frontiers to understand the properties of consciousness from various perspectives like quantum biology, neurophysiology, neuropsychology, quantum physics, computer science and several other disciplines. Here we describe a state of consciousness known as Shatvadhan. Shatvadhan in Jainism means one hundred states of extraordinary attention of the brain. In this state a person will listen or observe one hundred questions of different types from one hundred persons or more for over a period of say 2-3 hours without break and without using any paper or pen or electronic device. This is a demonstration of extraordinary memory to retain and recall questions and their answers in same sequence, reverse sequence or random sequences involving complex questions. This appears to represent a new state of consciousness which involves demonstration of extra ordinary memory, highly sequential ordering of memory, recalling, remembering sequences also in which memories of events are stored, simultaneous storing information from different sense organs and others. This also involves mathematical computations which are done in parts in different activities and simultaneous observations of pictures and listening of audio sounds. It appears that this process represents a new state of consciousness mostly found in saints who are highly advanced in the process of spiritual development. An analysis of this may provide new avenues of thought regarding storage and recalling mechanism of memory in the human brain. It may also involve non-local information transfer in the brain through quantum holography and similar mechanism.

Comprehensive anatomical study of meningeal arteries in dromedaries

This study provides a detailed, in-depth analysis of the anatomy, topography, and branching patterns of the meningeal arteries in dromedary camels, a subject that has not previously been thoroughly studied in animals, providing insight into the intricate biological adaptations that allow them to survive in harsh environments. By precisely examining 20 heads obtained from freshly slaughtered dromedaries, we revealed the origins and topologies of the rostral, middle, and caudal meningeal arteries using advanced casting techniques for precise rendering. Our findings indicate that the rostral meningeal artery derives from the external ethmoidal artery and primarily supplies the rostrodorsal region of the frontal lobe. The middle meningeal artery provides blood to approximately two-thirds of the brain meninges. The caudal meningeal artery is derived from the occipital artery and supplies the meninges covering the cerebellum, caudal part of the falx cerebri, and tentorium cerebelli. Significantly, our study revealed the presence of accessory branches originating from the rostral epidural rete mirabile, a finding not previously described in the existing literature. These branches supply the meninges of the frontal and lateral regions of the frontal lobes. This novel study advances our understanding of the meningeal arteries in dromedaries and has significant implications for advancements in veterinary neuroscience.

Usia Pertanggungjawaban Pidana Anak dalam Perspektif Neurolaw

Due to recent discoveries and technological advancements in neuroscience, we can gain a deeper understanding of the human brain that significantly impact juvenile criminal law, particularly concerning children's behavior and ability to regulate impulsive behavior. This study aims to analyze the current age of criminal responsibility in the Indonesian legal system using a neurolaw perspective that considers cognitive neuroscience and legal theory. The research utilizes normative legal research methodology with a statute approach and a neuroscience approach. The data obtained from literature research is then analyzed conceptually. The study results indicate that the age of criminal responsibility for children in Indonesia is 12 years; however, it has not yet reached 18 years. According to the neurolaw perspective, brain development within this age range is not fully matured and continues to undergo behavioral changes. This research implies the urgency of revising regulations regarding the age of criminal responsibility for children in Indonesia, considering the discoveries in neuroscience. Using a neurolaw perspective can encourage changes in legal policies that pay more attention to neurological factors in assessing juvenile criminal responsibility. As far as the law governs human behavior, the brain plays a crucial role in controlling that behavior. Therefore, a better understanding of the brain will lead to better and fairer laws.

Dual Residency Training in Neurology and Psychiatry: History and Current Practice.

In the early 20th century, neurology training included more experience in psychiatry, and psychiatry training included more training in neurology than what is currently required. After World War I, the increased need for differential diagnosis of what might now be called functional neurological disorders resulted in the military encouraging combined residency training in neurology and psychiatry and the promulgation of the term "neuropsychiatry" for this specialty. Thirty-six percent of physicians certified by the American Board of Psychiatry and Neurology in its first decade (1935-1945) held certification in both neurology and psychiatry. However, the term neuropsychiatry gradually became used interchangeably with general psychiatry-to distinguish it from psychoanalysis-and lost its specificity. It is widely held that the popularity of psychoanalysis resulted in psychiatrists perceiving less need for neurological knowledge, and inclusion of neurology content in psychiatry training decreased. Dual residency training programs in neurology and psychiatry began to increase in popularity again in the 1980s as advances in neuroscience, neuroimaging, and pharmacology, paired with the growth of behavioral neurology, laid the foundation for meaningful practice of neuropsychiatry. The author surveyed 207 physicians who graduated from both a neurology and psychiatry residency and 18 current trainees in combined neuropsychiatry residency programs to collect information on their current practice, academic activity, and opinions about their training. The response rate was 64%. Respondents' attitudes toward the value of their dual neurology and psychiatry training were overwhelmingly positive. Reasons for the lack of growth of combined residency programs in neurology and psychiatry are examined.

Unveiling the Neuroscientific Underpinnings of Mood and Anxiety Disorders

Depression and anxiety are two of the most prevalent mental health disorders worldwide, affecting millions of individuals across various age groups, and social categories. While the origins of these disorders are complex and multifaceted, recent advancements in Neuroscience provide valuable insights into the underlying mechanisms that contribute to the development and maintenance of mood and anxiety disorders. This review delves into the intricate interplay of neurobiological factors involved in these mental disorders, shedding light on the neural pathways, neurotransmitters, and structural/functional circuit changes that contribute to their manifestations. A special focus is given on new and upcoming insights in Neuroscience that emerge from a deeper understanding of the complex interplay of biological and environmental factors that takes place at a multi-scale level, from genes to behaviors.

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing.

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

Improving social reward responsivity and social connectedness in psychotherapies for late-life depression: Engage & Connect as an example

Psychotherapies are effective in reducing late-life depression. Yet, about half of patients remain depressed at treatment end. Advances in neuroscience can inform simplified interventions that target key brain networks impacted by depression. Behavioral activation therapies that increase social connectedness may improve social reward responsivity and alter abnormalities of the Positive Valence System (PVS). Engage & Connect is an example for a scalable and simple neuroscience-informed psychotherapy, aimed to improve PVS functions and social reward responsivity by increasing engagement in rewarding social activities. Interventions that improve social reward responsivity can be promising first-line treatments for late-life depression in the community.

Future medicine: from molecular pathways to the collective intelligence of the body.

The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems that offer numerous interfaces to their physiological and anatomical problem-solving capacities. We briefly review data suggesting that the multiscale competency of living forms affords a new path for biomedicine that exploits the innate collective intelligence of tissues and organs. The concept of tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. We sketch a roadmap towards 'somatic psychiatry' by using advances in bioelectricity and behavioral neuroscience to design methods that induce self-repair of structure and function. Relaxing the assumption that cellular control mechanisms are static, exploiting powerful concepts from cybernetics, behavioral science, and developmental biology may spark definitive solutions to current biomedical challenges.

New Advances in Social Cognitive Neuroscience

Social cognitive neuroscience, as an important branch of the field of neuroscience, studies the cognitive, emotional and interactive processes of individuals in social environments. In recent years, with the continuous development of neuroscience, social cognitive research has been progressing steadily. This paper discusses the latest research progress in the field of social cognitive neuroscience from the perspective of neuroscience, covering the mechanism of emotional disorders and cognitive decision making, and brain imaging of social cognitive neuroscience. These advances not only deepen our understanding of social cognition, but also provide new ideas for the intervention and treatment of social cognitive disorders.

On the origin and evolution of the dual oscillator model underlying the photoperiodic clockwork in the suprachiasmatic nucleus.

Decades have now passed since Colin Pittendrigh first proposed a model of a circadian clock composed of two coupled oscillators, individually responsive to the rising and setting sun, as a flexible solution to the challenge of behavioral and physiological adaptation to the changing seasons. The elegance and predictive power of this postulation has stimulated laboratories around the world in searches to identify and localize such hypothesized evening and morning oscillators, or sets of oscillators, in insects, rodents, and humans, with experimental designs and approaches keeping pace over the years with technological advances in biology and neuroscience. Here, we recount the conceptual origin and highlight the subsequent evolution of this dual oscillator model for the circadian clock in the mammalian suprachiasmatic nucleus; and how, despite our increasingly sophisticated view of this multicellular pacemaker, Pittendrigh's binary conception has remained influential in our clock models and metaphors.

PAIN THRESHOLD PARADOX IN SCHIZOPHRENIA: A NARRATIVE REVIEW BASED ON THE LASTEST NEUROSCIENCE.

Pain is one of the basic defense responses of living organisms. Although the threshold for pain perception varies from person to person, there is no doubt that pain reduces a person's quality of life. Assessing the subjective experience of pain is especially important in the treatment of patients with schizophrenia. In light of recent advances in neuroscience, we discuss pain thresholds in patients with schizophrenia. A narrative review of pain thresholds in patients with schizophrenia was conducted. We electronically searched the PubMed and Google Scholar databases for articles in English with "pain," "schizophrenia," "neural circuits," and "neurotransmitters" in the title or abstract, for the period January 2000 through June 2022. A seemingly contradictory phenomenon has been noted with regard to pain thresholds in patients with schizophrenia. One phenomenon is a high pain threshold for nociceptive stimuli, and the other is a low pain threshold in chronic pain. As a result, a pain threshold paradox has been observed. Many schizophrenia patients appear to have an excess of dopamine in the mesolimbic system, which stimulates both the descending pain inhibitory pathway and the salience network. As a result, a pain threshold paradox has been observed, in which the threshold for acute nociceptive pain is high and the threshold for chronic pain is low.