The triadic systems model perspective and adolescent risk taking

In this special issue, Ernst (2014) outlines the triadic systems model, which focuses on the balanced interaction among three functional neural systems: the prefrontal cortex (regulation/control), striatum (motivation/approach), and amygdala (emotion/avoidance). Asynchrony in maturation timelines, coupled with less mature connectivity across brain regions, is thought to result in unique vulnerabilities for risk taking during the adolescent age period. Yet, the research evidence linking the triadic systems model to differences in risk taking across adolescence and adulthood is equivocal, and few studies have examined how neural development is associated with real-world behavior. In this commentary, we outline research on adolescent risk taking which highlights the importance of considering trait level and situational conditions when examining associations between neural systems and behavior, as well as the need to adopt a lifespan perspective.     

The minimal self hypothesis

For millennia self has been conjectured to be necessary for consciousness. But scant empirical evidence has been adduced to support this hypothesis. Inconsistent explications of “self” and failure to design apt experiments have impeded progress. Advocates of phenomenological psychiatry, however, have helped explicate “self,” and employed it to explain some psychopathological symptoms. In those studies, “self” is understood in a minimalist sense, sheer “for-me-ness.” Unfortunately, explication of the “minimal self” (MS) has relied on conceptual analysis, and applications to psychopathology have been hermeneutic, allowing for many degrees of interpretive latitude. The result is that MS’s current scientific status is analogous to that of the “atom,” at the time when “atom” was just beginning to undergo transformation from a philosophical to a scientific concept. Fortunately, there is now an opportunity to promote a similar transformation for “MS.” Discovery of the brain’s Default Mode Network (DMN) opened the door to neuroimaging investigations of self. Taking the DMN and other forms of intrinsic activity as a starting point, an empirical foothold can be established, one that spurs experimental research and that enables extension of research into multiple phenomena. New experimental protocols that posit “MS” can help explain phenomena hitherto not thought to be related to self, thereby hastening development of a mature science of self. In particular, targeting phenomena wherein consciousness is lost and recovered, as in some cases of Unresponsive Wakefulness Syndrome (UWS), allow for design of neuroimaging probes that enable detection of MS during non-conscious states. These probes, as well as other experimental protocols applied to NREM Sleep, General Anesthesia (GA), and the waking state, provide some evidence to suggest that not only can self and consciousness dissociate, MS might be a necessary precondition for conscious experience. Finally, these findings have implications for the science of consciousness: it has been suggested that “levels of consciousness” (LoC) is not a legitimate concept for the science of consciousness. But because we have the conceptual and methodological tools with which to refine investigations of MS, we have the means to identify a possible foundation—a bifurcation point—for consciousness, as well as the means by which to measure degrees of distance from that foundation. These neuroimaging investigations of MS position us to better assess whether LoC has a role to play in a mature science of consciousness.     

Russian-language neurosemantics: Clustering of word meaning and sense from oral narratives

This article is a part of a large-scale brain mapping project aimed at finding the relations among semantic categories in oral Russian-language texts and brain activity as measured using functional magnetic resonance imaging (fMRI). The goal of present study in particular is to examine the nature of lexical semantic relations and find an appropriate lexical space, homeomorphic to the activation patterns in the brain. Participants were presented with oral narratives, which described significant social issues from the first-person perspective. Stimuli were annotated using a dictionary and a vector approach. Results show that fMRI signal and clusters of related words have similar patterns of brain activation across participants. Results also show that annotation by a list of features more strongly contributes to prediction of the observed activation patterns. Findings confirm the hypothesis of situational semantic representation in the brain.     

EEG neurofeedback improves cycling time to exhaustion

ObjectiveThe role of the brain in endurance performance is frequently debated; surprisingly, few investigations have attempted to improve endurance performance by directly targeting brain activity. One promising but untested approach to modifying brain activity is electroencephalogram (EEG) neurofeedback. Consequently, our experiment is the first to examine an EEG neurofeedback intervention for whole-body endurance performance.MethodWe adopted a two-part experiment. The first consisted of a randomized parallel controlled design. Forty participants were allocated to three experimental groups; increase relative left cortical activity (NFL), increase relative right (NFR), and passive control (CON). They performed a depleting cognitive task, followed by either six 2-min blocks of EEG neurofeedback training (NFL or NFR) or time-matched videos of the neurofeedback display (CON). Next, they performed a time-to-exhaustion (TTE) test on a cycle-ergometer. We then tested participants of NFL and NFR groups in an additional experimental visit and administered the opposite neurofeedback training within a fully repeated-measures protocol.ResultsEEG neurofeedback modified brain activity as expected. As hypothesized, the NFL group cycled for over 30% longer than the other groups in the parallel controlled design, NFL: 1382 ± 252 s, NFR: 878 ± 167, CON: 963 ± 117 s. We replicated this result in the repeated-measures design where NFL: 1167 ± 831 s performed 11% longer than NFR: 1049 ± 638 s. There were no differences in pre-exercise fatigue, vigor or self-control; area under the curve group-differences for perceived effort were interpreted within a goal persistence framework.ConclusionThe brief EEG neurofeedback intervention elicited greater relative left frontal cortical activity and enhanced endurance exercise performance.     

Transcranial parenchymal sonography in patients with Chronic Disorders of Consciousness: Association with neuroimaging data,and beyond

Differential diagnosis of patients with Chronic Disorders of Consciousness (DoC) is rather challenging, owing to the lack of objective approaches highlighting residual awareness. Sophisticated functional neuroimaging have provided high diagnostic value, but their application in the clinical setting is limited due to their relative complexity, cost, availability and poor collaboration of persons with DoC. By using a specific ultrasound-based methodology, namely Transcranial B-mode Parenchymal Sonography (TCS), it is possible to obtain images of the main parenchymal brain structures. We assessed the TCS abnormalities in three patients with DoC, demonstrating widespread alterations of brain parenchyma morphology that matched to MRI findings and were associated with the degree of consciousness disorders. Thus, TCS might represent a valuable tool for routine assessment and follow-up of brain structures functioning of patients with DoC, potentially helping in differential diagnosis and prognosis.     

Reconciling current approaches to blindsight

After decades of research, blindsight is still a mysterious and controversial topic in consciousness research. Currently, many researchers tend to think of it as an ideal phenomenon to investigate neural correlates of consciousness, whereas others believe that blindsight is in fact a kind of degraded vision rather than “truly blind”. This article considers both perspectives and finds that both have difficulties understanding all existing evidence about blindsight. In order to reconcile the perspectives, we suggest two specific criteria for a good model of blindsight, able to encompass all evidence. We propose that the REF-CON model (Overgaard & Mogensen, 2014) may work as such a model.     

Mental models in the brain: On context-dependent neural correlates of mental models

In this paper, the concept of context-dependent realisation of mental models is introduced and discussed. Literature from neuroscience is discussed showing that different types of mental models can use different types of brain areas. Moreover, it is discussed that the same occurs for the formation and adaptation of mental models and the control of these processes. This makes that it is hard to claim that all mental models use the same brain mechanisms and areas. Instead, the notion of context-dependent realisation is proposed here as a better manner to relate neural correlates to mental models. It is shown in some formal detail how this context-dependent realisation approach can be related to well-known perspectives based on bridge principle realisation and interpretation mapping realisation.     

Brain MR kurtosis imaging study: Contrasting gray and white matter

This paper mainly focuses on characterization of different brain tissues such as White and Gray matter (WM and GM) using the relation between Diffusion Tensor Imaging and Diffusion Kurtosis Imaging parameters. Both Diffusion Tensor Imaging and Diffusion Kurtosis Imaging are the extension of Diffusion Weighted Imaging, which are widely applied for analysing micro fibre structure of human organs non-invasively. Diffusion Tensor Imaging assumes that the water diffusion is in Gaussian nature and Diffusion Kurtosis Imaging accounts the deviation of the Gaussian nature. This study, conducted a correlation and regression analysis between different parametric maps generated from Diffusion Kurtosis Images. For this we have chosen 200 regions of interest pixels drawn from brain MRIs. From the results, it is observed that there is a significant variation in the correlation results between Axial Diffusion and Kurtosis Fractional Anisotropy maps of Gray matter and White matter tissues. This can be employed for enhancing accuracy in MRI segmentation techniques and also as a potential tool for Neuro degenerative disease detection.