Neuroscience Literature Research Articles

Effects of tDCS on the attentional blink revisited: A statistical evaluation of a replication attempt.

The attentional blink (AB) phenomenon reveals a bottleneck of human information processing: the second of two targets is often missed when they are presented in rapid succession among distractors. In our previous work, we showed that the size of the AB can be changed by applying transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (lDLPFC) (London & Slagter, Journal of Cognitive Neuroscience, 33, 756-68, 2021). Although AB size at the group level remained unchanged, the effects of anodal and cathodal tDCS were negatively correlated: if a given individual's AB size decreased from baseline during anodal tDCS, their AB size would increase during cathodal tDCS, and vice versa. Here, we attempted to replicate this finding. We found no group effects of tDCS, as in the original study, but we no longer found a significant negative correlation. We present a series of statistical measures of replication success, all of which confirm that both studies are not in agreement. First, the correlation here is significantly smaller than a conservative estimate of the original correlation. Second, the difference between the correlations is greater than expected due to sampling error, and our data are more consistent with a zero-effect than with the original estimate. Finally, the overall effect when combining both studies is small and not significant. Our findings thus indicate that the effects of lDPLFC-tDCS on the AB are less substantial than observed in our initial study. Although this should be quite a common scenario, null findings can be difficult to interpret and are still under-represented in the brain stimulation and cognitive neuroscience literatures. An important auxiliary goal of this paper is therefore to provide a tutorial for other researchers, to maximize the evidential value from null findings.

Categorical Perception: A Groundwork for Deep Learning.

Classification is one of the major tasks that deep learning is successfully tackling. Categorization is also a fundamental cognitive ability. A well-known perceptual consequence of categorization in humans and other animals, categorical perception, is notably characterized by a within-category compression and a between-category separation: two items, close in input space, are perceived closer if they belong to the same category than if they belong to different categories. Elaborating on experimental and theoretical results in cognitive science, here we study categorical effects in artificial neural networks. We combine a theoretical analysis that makes use of mutual and Fisher information quantities and a series of numerical simulations on networks of increasing complexity. These formal and numerical analyses provide insights into the geometry of the neural representation in deep layers, with expansion of space near category boundaries and contraction far from category boundaries. We investigate categorical representation by using two complementary approaches: one mimics experiments in psychophysics and cognitive neuroscience by means of morphed continua between stimuli of different categories, while the other introduces a categoricality index that, for each layer in the network, quantifies the separability of the categories at the neural population level. We show on both shallow and deep neural networks that category learning automatically induces categorical perception. We further show that the deeper a layer, the stronger the categorical effects. As an outcome of our study, we propose a coherent view of the efficacy of different heuristic practices of the dropout regularization technique. More generally, our view, which finds echoes in the neuroscience literature, insists on the differential impact of noise in any given layer depending on the geometry of the neural representation that is being learned, that is, on how this geometry reflects the structure of the categories.

A compact guide to the systematic review and meta-analysis of the literature in neuroscience

Critical appraisals of the literature may help to increase reproducibility in neuroscience. Systematic reviews and meta-analyses are tools for neuroscientists to critically evaluate a large amount of knowledge in the research field. These methods involve individually simple decisions, which may become complex when considering the whole process. Strategies to organize the planning and implementation of the protocols minimize the workload. Here, we prepared a compact guide to assist neuroscientists willing to perform a systematic review and meta-analysis of the literature in neuroscience.

Are object relations temporal? From the brain’s intrinsic neural timescales over temporo-spatial alignment to object relations

ABSTRACT What are object relations? Otto Kernberg raises this question and addresses it in an excellent way recruiting much of current neuroscientific literature. There is a yet deeper dimension, the brain’s inner time. Inner time means that the brain constructs its own inner timescales: it has various timescales in its neural activity through which it processes external inputs – the external inputs are thus “filtered” through the brain’s various timescales. The brain’s timescales are described as “intrinsic neural timescales” (INT) which can be measured by the degree of the correlation of the signal with itself, i.e. autocorrelation window (ACW). The term window describes it well: the brain has several temporal windows through and by means of which it processes and relates to external inputs which, on the psychodynamic level, surfaces as object relations.

Sex/Gender Differences in Brain Lateralisation and Connectivity.

There is now a significant body of literature concerning sex/gender differences in the human brain. This chapter will critically review and synthesise key findings from several studies that have investigated sex/gender differences in structural and functional lateralisation and connectivity. We argue that while small, relative sex/gender differences reliably exist in lateralisation and connectivity, there is considerable overlap between the sexes. Some inconsistencies exist, however, and this is likely due to considerable variability in the methodologies, tasks, measures, and sample compositions between studies. Moreover, research to date is limited in its consideration of sex/gender-related factors, such as sex hormones and gender roles, that can explain inter-and inter-individual differences in brain and behaviour better than sex/gender alone. We conclude that conceptualising the brain as 'sexually dimorphic' is incorrect, and the terms 'male brain' and 'female brain' should be avoided in the neuroscientific literature. However, this does not necessarily mean that sex/gender differences in the brain are trivial. Future research involving sex/gender should adopt a biopsychosocial approach whenever possible, to ensure that non-binary psychological, biological, and environmental/social factors related to sex/gender, and their interactions, are routinely accounted for.

Implications of nocebo in anaesthesia care.

Nocebo refers to non-pharmacological adverse effects of an intervention. Well-intended procedural warnings frequently function as a nocebo. Both nocebo and placebo are integral to the generation of 'real' treatment effects and their associated 'real' side-effects. They are induced or exacerbated by: context; negative expectancy; and negative conditioning surrounding treatment. Since the late 1990s, the neuroscience literature has repeatedly demonstrated that the nocebo effect is mediated by discrete neurobiological mechanisms and specific physiological modulations. Although no single biological mechanism has been found to explain the nocebo effect, nocebo hyperalgesia is thought to initiate from the dorsal lateral prefrontal cortex subsequently triggering the brain's descending pain modulatory system and other pain regulation pathways. Functional magnetic resonance imaging shows that expectation of increased pain is accompanied by increased neural activity in the hippocampus and midcingulate cortex which is not observed when analgesia is expected. Functional magnetic resonance imaging studies have shown that the anterior cingulate cortex is pivotal in the perception of affective pain evoked by nocebo words. Research has also explored neurotransmitters which mediate the nocebo effect. The neuropeptide cholecystokinin appears to play a key role in the modulation of pain by nocebo. Hyperalgesia generated by nocebo also increases the activity of the hypothalamic-pituitary-adrenal axis as indicated by increases in plasma cortisol. The avoidance or mitigation of nocebo needs to be recognised as a core clinical skill in optimising anaesthesia care. Embracing the evidence around nocebo will allow for phrases such as 'bee sting' and 'sharp scratch' to be thought of as clumsy verbal relics of the past. Anaesthesia as a profession has always prided itself on practicing evidence-based medicine, yet for decades anaesthetists and other healthcare staff have communicated in ways counter to the evidence. The premise of every interaction should be 'primum non nocere' (first, do no harm). Whether the context is research or clinical anaesthesia practice, the nocebo can be ignored no longer.

How Do We Learn Mathematics A Framework for a Theoretical and Practical Model

The purpose of this paper is to propose an effective learning environment for the initial stages of mathematical learning. Basic numerical skills and the objects and actions that trigger those skills are conceptualized as a mathematics-learning environment. We discuss numerical learning mechanism and the basic skills and environments we use to learn numbers briefly within the human cognition system. The three subsystems of number, i.e., exact number system, approximate number system and access to symbol system, are explained with reference to basic number competencies. They are discussed within the framework of "number sense” by drawing evidences from the neuroscience and mathematics education literature. Finally, how to manipulate the components of these subsystems for an effective learning of number is exemplified in a proposed model of mathematical learning environment.

Symposium

Behavioral Addictions: Current State of Research.Conceptual Understanding: The concept of Behavioral addictions has gained momentum in recent scientific studies. Current conceptualization of Behavioral addictions is sharing commonalities and similarities with other forms of addictive disorders. Recent neuroscientific literature supported inclusion of Gambling disorder in DSM 5 manual. Internet use disorder, gaming disorder, exercise addition, sex addiction and shopping addiction have been studied but still need more robust evidence. ICD 11 has specified Gaming disorder among such categories. Challenge also occurs to translate updated neurobiological evidence of Behavioral addictions into developing treatment options.Neurobiology and Genetics aspects of Behavioral addictions: Imaging studies with cognitive tasks reported more consistent results. Neurochemical analysis revealed role of dopaminergic and serotonergic transmission, but results are more equivocal. Genetics data and family history findings show heritability for pathological gambling and individuals with Behavioral addictions have family members with psychopathological issues. For other type of Behavioral addictions, findings are limited and need further research.Phenomenology of Behavioral addictions: Behavioral addictions share characteristics with substance use disorder such as natural history, phenomenology and adverse psychosocial outcomes. The degree to which Behavioral addictions share clinical, genetic, phenomenological and biological features need to be understood. The essential aspect of these addictive behaviors is failure to resist an impulse, drive or temptation to perform an act that produces harmful consequences. Repetitive engagements in these behaviors results in dysfunctionManagement of Behavioral Addictions: Treatment involves both pharmacological and psychological interventions but with varied evidence base. It is important to assess the circumstances that led patient to seek help. Patients with Behavioral addiction struggle because of social, occupational or legal problems. The area of treatment modality for Behavioral addictions needs more robust data and longitudinal studies to develop evidence-based models of care.

Chapter 8 - Visual mental imagery: Inside the mind's eyes

What are mental images needed for? A variety of everyday situations calls for us to plan ahead; one of the clever ways our mind prepares and strategizes our next move is through mental simulation. A powerful tool in running these simulations is visual mental imagery, which can be conceived as a way to activate and maintain an internal representation of the to-be-imagined object, giving rise to predictions. Therefore, under normal conditions imagination is primarily an endogenous process, and only more rarely can mental images be activated exogenously, for example, by means of intracerebral stimulation. A large debate is still ongoing regarding the neural substrates supporting mental imagery, with the neuropsychological and neuroimaging literature agreeing in some cases, but not others. This chapter reviews the neuroscientific literature on mental imagery, and attempts to reappraise the neuropsychological and neuroimaging evidence by drawing a model of mental imagery informed by both structural and functional brain data. Overall, the role of regions in the ventral temporal cortex, especially of the left hemisphere, stands out unequivocally as a key substrate in mental imagery.

Chapter 5 - Neuroplasticity following cochlear implants

The auditory cortex of people with sensorineural hearing loss can be re-afferented using a cochlear implant (CI): a neural prosthesis that bypasses the damaged cells in the cochlea to directly stimulate the auditory nerve. Although CIs are the most successful neural prosthesis to date, some CI users still do not achieve satisfactory outcomes using these devices. To explain variability in outcomes, clinicians and researchers have increasingly focused their attention on neuroscientific investigations that examined how the auditory cortices respond to the electric signals that originate from the CI. This chapter provides an overview of the literature that examined how the auditory cortex changes its functional properties in response to inputs from the CI, in animal models and in humans. We focus first on the basic responses to sounds delivered through electrical hearing and, next, we examine the integrity of two fundamental aspects of the auditory system: tonotopy and processing of binaural cues. When addressing the effects of CIs in humans, we also consider speech-evoked responses. We conclude by discussing to what extent this neuroscientific literature can contribute to clinical practices and help to overcome variability in outcomes.

Ecological validity in exercise neuroscience research: A systematic investigation.

The contribution of cortical processes to adaptive motor behaviour is of great interest in the field of exercise neuroscience. Next to established criteria of objectivity, reliability and validity, ecological validity refers to the concerns of whether measurements and behaviour in research settings are representative of the real world. Because exercise neuroscience investigations using mobile electroencephalography are oftentimes conducted in laboratory settings under controlled environments, methodological approaches may interfere with the idea of ecological validity. This review utilizes an original ecological validity tool to assess the degree of ecological validity in current exercise neuroscience research. A systematic literature search was conducted to identify articles investigating cortical dynamics during goal-directed sports movement. To assess ecological validity, five elements (environment, stimulus, response, body and mind) were assessed on a continuum of artificiality-naturality and simplicity-complexity. Forty-seven studies were included in the present review. Results indicate lowest average ratings for the element of environment. The elements stimulus, body and mind had mediocre ratings, and the element of response had the highest overall ratings. In terms of the type of sport, studies that assessed closed-skill indoor sports had the highest ratings, whereas closed-skill outdoor sports had the lowest overall rating. Our findings identify specific elements that are lacking in ecological validity and areas of improvement in current exercise neuroscience literature. Future studies may potentially increase ecological validity by moving from reductionist, artificial environments towards complex, natural environments and incorporating real-world sport elements such as adaptive responses and competition.

Distributional independent component analysis for diverse neuroimaging modalities.

Recent advances in neuroimaging technologies have provided opportunities to acquire brain images of different modalities for studying human brain organization from both functional and structural perspectives. Analysis of images derived from various modalities involves some common goals such as dimension reduction, denoising, and feature extraction. However, since these modalities have vastly different data characteristics, the current analysis is usually performed using distinct analytical tools that are only suitable for a specific imaging modality. In this paper, we present a Distributional Independent Component Analysis (DICA) that represents a new approach that performs decomposition on the distribution level, providing a unified framework for extracting features across imaging modalities with different scales and representations. When applying DICA to fMRI images, we successfully recover well-established brain functional networks in neuroscience literature, providing empirical validation that DICA delivers neurologically relevant findings. More importantly, we discover several structural network components when applying DICA to DTI images. Through fiber tracking, we find these DICA-derived structural components correspond to several major white fiber bundles. To the best of our knowledge, this is the first time these fiber bundles are successfully identified via blind source separation on single subject DTI images. We also evaluate the performance of DICA as compared with existing ICA methods through extensive simulationstudies.

Can we build a neuroecology of innovativeness similar to that pioneered by David Sherry for spatial memory?

David Sherry's pioneering work on the neuroecology of spatial memory has three characteristics that could inspire studies on other cognitive processes: it was grounded in a robust prior literature in psychology and neuroscience; it identified several natural history contexts in which repeated independent evolution of spatial memory differences had occurred in different clades; it involved a precise cognitive ability with a precise neural substrate. We discuss the application of these three principles to a more domain-general trait-innovation. We argue that targeting the caudolateral nidopallium and its connected areas, favoring problem-solving over reversal learning as an experimental assay, and focusing on situations that involve environmental change, such as urbanization and invasion, can help the study of innovation progress, like the field of spatial memory has since 1989.

An extended state of uncertainty: A snap-shot of expressions of concern in neuroscience

An expression of concern (EoC) alerts readers to new considerations or concerns about a paper, usually at the post-publication stage. Authors and readers are left in a state of uncertainty as they await a resolution. This uncertainty might create a state of stress or anxiety for some authors. The paper's findings may be either validated and confirmed, resolving the EoC, or the paper's validity or loss of integrity is confirmed, leading to an erratum or retraction. Academics wanting to cite a paper to which an EoC is associated might decide not to cite it. If an EoC is reversed, i.e., if the post-publication findings annul the initial concerns, then the authors and journal may suffer a “loss” of citations. Conversely, if concerns are confirmed post-publication, and the EoC develops into a retraction, then any citations that were rewarded while the paper was in a state of uncertainty were rewarded unfairly. In such a case, both author- and journal-based metrics should be adjusted. Using the Retraction Watch database until April 20, 2021, we assessed 20 cases of EoCs in the neuroscience literature to appreciate how EoCs have been processed. After excluding one author-issued EoC, from 19 editor-issued EoCs, 10 were resolved in an average of 220 days while nine remain unresolved. In this article, we suggest the need to make the processes associated with an EoC more visible and transparent to the academic community, allowing editors to make the correct decisions regarding its resolution.

Glutamate: The Master Neurotransmitter and Its Implications in Chronic Stress and Mood Disorders.

This brief review article makes the argument that glutamate is deserving of its newfound attention within the neuroscience literature and that many directions of important research have yet to be explored. Glutamate is an excitatory neurotransmitter with several types of receptors found throughout the central nervous system, and its metabolism is important to maintaining optimal levels within the extracellular space. As such, it is important to memory, cognition, and mood regulation. The mechanisms by which chronic stress affect the glutamatergic system and neuroplasticity are outlined. Several implications for potential pharmacologic and non-pharmacologic interventions are discussed.

Listening in on investors’ thoughts and conversations

A large literature in neuroscience and social psychology shows that humans are wired to be meticulous about how they are perceived by others. In this paper, we propose that impression management considerations can also end up guiding the content that investors transmit via word of mouth and inadvertently lead to the propagation of noise. We analyze server log data from one of the largest investment-related websites in the United States. Consistent with our proposition, we find that investors more frequently share articles that are more suitable for impression management despite such articles less accurately predicting returns. Additional analyses suggest that high levels of sharing can lead to overpricing.

Sleep, Cognition and Cortisol in Addison's Disease: A Mechanistic Relationship.

Sleep is a critical biological process, essential for cognitive well-being. Neuroscientific literature suggests there are mechanistic relations between sleep disruption and memory deficits, and that varying concentrations of cortisol may play an important role in mediating those relations. Patients with Addison’s disease (AD) experience consistent and predictable periods of sub- and supra-physiological cortisol concentrations due to lifelong glucocorticoid replacement therapy, and they frequently report disrupted sleep and impaired memory. These disruptions and impairments may be related to the failure of replacement regimens to restore a normal circadian rhythm of cortisol secretion. Available data provides support for existing theoretical frameworks which postulate that in AD and other neuroendocrine, neurological, or psychiatric disorders, disrupted sleep is an important biological mechanism that underlies, at least partially, the memory impairments that patients frequently report experiencing. Given the literature linking sleep disruption and cognitive impairment in AD, future initiatives should aim to improve patients’ cognitive performance (and, indeed, their overall quality of life) by prioritizing and optimizing sleep. This review summarizes the literature on sleep and cognition in AD, and the role that cortisol concentrations play in the relationship between the two.

Hold-out validation for the assessment of stability and reliability of multivariable regression demonstrated with magnetic resonance imaging of patients with schizophrenia.

Neuroscience studies are very often tasked with identifying measurable differences between two groups of subjects, typically one group with a pathological condition and one group representing control subjects. It is often expected that the measurements acquired for comparing groups are also affected by a variety of additional patient characteristics such as sex, age, and comorbidities. Multivariable regression (MVR) is a statistical analysis technique commonly employed in neuroscience studies to "control for" or "adjust for" secondary effects (such as sex, age, and comorbidities) in order to ensure that the main study findings are focused on actual differences between the groups of interest associated with the condition under investigation. It is common practice in the neuroscience literature to utilize MVR to control for secondary effects; however, at present, it is not typically possible to assess whether the MVR adjustments correct for more error than they introduce. In common neuroscience practice, MVR models are not validated and no attempt to characterize deficiencies in the MVR model is made. In this article, we demonstrate how standard hold-out validation techniques (commonly used in machine learning analyses) that involve repeatedly randomly dividing datasets into training and testing samples can be adapted to the assessment of stability and reliability of MVR models with a publicly available neurological magnetic resonance imaging (MRI) dataset of patients with schizophrenia. Results demonstrate that MVR can introduce measurement error up to 30.06% and, on average across all considered measurements, introduce 9.84% error on this dataset. When hold-out validated MVR does not agree with the results of the standard use of MVR, the use of MVR in the given application is unstable. Thus, this paper helps evaluate the extent to which the simplistic use of MVR introduces study error in neuroscientific analyses with an analysis of patients with schizophrenia.

Moral Psychopharmacology Needs Moral Inquiry: The Case of Psychedelics.

The revival of psychedelic research coincided and more recently conjoined with psychopharmacological research on how drugs affect moral judgments and behaviors. This article makes the case for a moral psychopharmacology of psychedelics that examines whether psychedelics serve as non-specific amplifiers that enable subjects to (re-)connect with their values, or whether they promote specific moral-political orientations such as liberal and anti-authoritarian views, as recent psychopharmacological studies suggest. This question gains urgency from the fact that the return of psychedelics from counterculture and underground laboratories to mainstream science and society has been accompanied by a diversification of their users and uses. We propose bringing the pharmacological and neuroscientific literature into a conversation with historical and anthropological scholarship documenting the full spectrum of moral and political views associated with the uses of psychedelics. This paper sheds new light on the cultural plasticity of drug action and has implications for the design of psychedelic pharmacopsychotherapies. It also raises the question of whether other classes of psychoactive drugs have an equally rich moral and political life.

Phase-locking intermittency induced by dynamical heterogeneity in networks of thermosensitive neurons.

In this work, we study the phase synchronization of a neural network and explore how the heterogeneity in the neurons' dynamics can lead their phases to intermittently phase-lock and unlock. The neurons are connected through chemical excitatory connections in a sparse random topology, feel no noise or external inputs, and have identical parameters except for different in-degrees. They follow a modification of the Hodgkin-Huxley model, which adds details like temperature dependence, and can burst either periodically or chaotically when uncoupled. Coupling makes them chaotic in all cases but each individual mode leads to different transitions to phase synchronization in the networks due to increasing synaptic strength. In almost all cases, neurons' inter-burst intervals differ among themselves, which indicates their dynamical heterogeneity and leads to their intermittent phase-locking. We argue then that this behavior occurs here because of their chaotic dynamics and their differing initial conditions. We also investigate how this intermittency affects the formation of clusters of neurons in the network and show that the clusters' compositions change at a rate following the degree of intermittency. Finally, we discuss how these results relate to studies in the neuroscience literature, especially regarding metastability.