Syntactic processing in bilinguals: an fNIRS study

The study of the neural basis of syntactic processing has greatly benefited from neuroimaging techniques. Research on syntactic processing in bilinguals has used a variety of techniques, including mainly functional magnetic resonance imaging (fMRI) and event-related potentials (ERP). This paper reports on a functional near-infrared spectroscopy (fNIRS) study on syntactic processing in highly proficient young adult speakers of Portuguese (mother tongue) (L1) and French (second language) (L2). They made a syntactic judgment of visually presented sentences, which either did or did not contain noun-verb agreement violations. The results showed that syntactic processing in both languages resulted in significant activation in anterior frontal regions of the left hemisphere and in the temporal superior posterior areas of the right hemisphere, with a more prominent activation for L2 in some areas. These findings corroborate previously reported neuroimaging evidence, showing the suitability of fNIRS for the study of syntactic processing in the bilingual brain.     

A brief review on the use of functional near-infrared spectroscopy (fNIRS) for language imaging studies in human newborns and adults

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have a time resolution of 1-10 Hz, a depth sensitivity of about 1.5 cm, and a spatial resolution of about 1 cm. The goal of this brief review is to report infants, children and adults fNIRS language studies. Since 1998, 60 studies have been published on cortical activation in the brain’s classic language areas in children/adults as well as newborns using fNIRS instrumentations of different complexity. In addition, the basic principles of fNIRS including features, strengths, advantages, and limitations are summarized in terms that can be understood even by non specialists. Future prospects of fNIRS in the field of language processing imaging are highlighted.     

Contribution of NIRS to the study of prefrontal cortex for verbal fluency in aging

Healthy aging is characterized by a number of changes on brain structure and function. Several neuroimaging studies have shown an age-related reduction in hemispheric asymmetry on various cognitive tasks, a phenomenon captured by Cabeza (2002) in the Hemispheric Asymmetry Reduction in Older Adults (HAROLD) model. Although this phenomenon is supported by a range of neuroimaging data on memory and inhibitory processes, there is little evidence concerning changes in hemispheric asymmetry for language processing, and particularly word retrieval, which is assessed with verbal fluency task (VFT). This study aimed to investigate the age-related changes in cerebral oxygenation in the prefrontal cortex for both letter and category VFT, varying the complexity of the criteria (i.e., degree of productivity) and using near-infrared spectroscopy (NIRS). Sixteen younger and 16 older adults participated in this study. For both VF conditions, participants were instructed to pronounce as many nouns as possible as a function of high-productivity (e.g., “animals” or “L”) or low-productivity (e.g., “flowers” or “V”) criteria. Behavioral data (i.e., accuracy responses) showed comparable performance in younger and older adults for both VF conditions. However, NIRS data showed more reduced activation (i.e., significantly reduced increase in [O₂Hb] and reduced decrease in [HHb]) in older than younger adults for both VFT. In addition, a bilateral effect was found for both groups, suggesting that VFT requires both executive and language functions. The results are discussed in the context of the current theories of aging.     

Mind matters: A narrative review on affective state-dependency in non-invasive brain stimulation

Variability in findings related to non-invasive brain stimulation (NIBS) have increasingly been described as a result of differences in neurophysiological state. Additionally, there is some evidence suggesting that individual differences in psychological states may correlate with the magnitude and directionality of effects of NIBS on the neural and behavioural level. In this narrative review, it is proposed that the assessment of baseline affective states can quantify non-reductive properties which are not readily accessible to neuroscientific methods. Particularly, affective-related states are theorized to correlate with physiological, behavioural and phenomenological effects of NIBS. While further systematic research is needed, baseline psychological states are suggested to provide a complementary cost-effective source of information for understanding variability in NIBS outcomes. Implementing measures of psychological state may potentially contribute to increasing the sensitivity and specificity of results in experimental and clinical NIBS studies.     

Old processes,new perspectives: Familiarity is correlated with (not independent of) recollection and is more (not equally) variable for targets than for lures

According to dual-process models of memory, recognition is subserved by two processes: recollection and familiarity. Many variants of these models assume that recollection and familiarity make stochastically independent contributions to performance in recognition tasks and that the variance of the familiarity signal is equal for targets and for lures. Here, we challenge these ‘common-currency’ assumptions. Using a model-comparison approach, featuring the Continuous Dual Process (CDP; Wixted & Mickes, 2010) model as the protagonist, we show that when these assumptions are relaxed, the model’s fits to individual participants’ data improve. Furthermore, our analyses reveal that across items, recollection and familiarity show a positive correlation. Interestingly, this across-items correlation was dissociated from an across-participants correlation between the sensitivities of these processes. We also find that the familiarity signal is significantly more variable for targets than for lures. One striking theoretical implication of these findings is that familiarity—rather than recollection, as most models assume—may be the main contributor responsible for one of the most influential findings of recognition memory, that of subunit zROC slopes. Additionally, we show that erroneously adopting the common-currency assumptions, introduces severe biases to estimates of recollection and familiarity.     

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.     

Empirical Bayes Derivative Estimates

Abstract

A dynamic system is a set of interacting elements characterized by changes occurring over time. The estimation of derivatives is a mainstay for exploring dynamics of constructs, particularly when the dynamics are complicated or unknown. The presence of measurement error in many social science constructs frequently results in poor estimates of derivatives, as even modest proportions of measurement error can compound when estimating derivatives. Given the overlap in the specification of latent differential equation models and latent growth curve models, and the equivalence of latent growth curve models and mixed models under some conditions, derivatives could be estimated from estimates of random effects. This article proposes a new method for estimating derivatives based on calculating the Empirical Bayes estimates of derivatives from a mixed model. Two simulations compare four derivative estimation methods: Generalized Local Linear Approximation, Generalized Orthogonal Derivative Estimates, Functional Data Analysis, and the proposed Empirical Bayes Derivative Estimates. The simulations consider two data collection scenarios: short time series (≤10 observations) from many individuals or occasions, and long individual time series (25–500 observations). A substantive example visualizing the dynamics of intraindividual positive affect time series is also presented.     

Towards modern post-coma care based on neuroscientific evidence

BackgroundUnderstanding the mechanisms underlying human consciousness is pivotal to improve the prognostication and treatment of severely brain-injured patients. Consciousness remains an elusive concept and the identification of its neural correlates is an active subject of research, however recent neuroscientific advances have allowed scientists to better characterize disorders of consciousness. These breakthroughs question the historical nomenclature and our current management of post-comatose patients.MethodThis review examines the contribution of consciousness neurosciences to the current clinical management of severe brain injury. It investigates the major impact of consciousness disorders on healthcare systems, the scientific frameworks employed to identify their neural correlates and how evidence-based data from neuroimaging research have reshaped the landscape of post-coma care in recent years.ResultsOur increased ability to detect behavioral and neurophysiological signatures of consciousness has led to significant changes in taxonomy and clinical practice. We advocate for a multimodal framework for the management of severely brain-injured patients based on precision medicine and evidence-based decisions, integrating epidemiology, health economics and neuroethics.ConclusionsMajor progress in brain imaging and clinical assessment have opened the door to a new era of post-coma care based on standardized neuroscientific evidence. We highlight its implications in clinical applications and call for improved collaborations between researchers and clinicians to better translate findings to the bedside.     

Durability and generalization of attribution-based feedback following failure: Effects on expectations and behavioral persistence

ObjectiveThis experiment investigated, following perceived failure, the immediate, long-term (i.e., durability), and cross-situational (i.e., generalization) effects of attribution-based feedback on expectations and behavioral persistence.DesignWe used a 3 × 2 (Group × Time) experimental design over seven weeks with attributions, expectations of success, and persistence as dependent measures.Method49 novice participants were randomly assigned to one of three treatment (attributional feedback) groups: (a) functional (i.e., controllable and unstable); (b) dysfunctional (i.e., uncontrollable and stable); or (c) no feedback. Testing involved three sessions, in which participants completed a total of five trials across two performance tasks (golf-putting and dart-throwing). In order to track whether the attributional manipulation conducted within the context of the golf-putting task in Session 2 would generalize to a new situation, participants performed a dart-throwing task in Session 3, and their scores were compared with those recorded at baseline (in Session 1).ResultsAnalysis of pre- and post-intervention measures of attributions, expectations, and persistence revealed that the functional attributional feedback led to more personally controllable attributions following failure in a golf-putting task, together with increases in success expectations and persistence. In contrast, dysfunctional attributional feedback led to more personally uncontrollable and stable attributions following failure, together with lower success expectations and reduced persistence. These effects extended beyond the intervention period, were present up to four weeks post intervention, and were maintained even when participants performed a different (i.e., dart-throwing) task.ConclusionsThe findings demonstrate that attributional feedback effects are durable over time and generalize across situations.     

Unrealistic representations of “the self”: A cognitive neuroscience assessment of anosognosia for memory deficit

Three cognitive components may play a crucial role in both memory awareness and in anosognosia for memory deficit (AMD): (1) a personal data base (PDB), i.e., a memory store that contains “semantic” representations about the self, (2) monitoring processes (MPs) and (3) an explicit evaluation system (EES), or comparator, that assesses and binds the representations stored in the PDB with information obtained from the environment.We compared both the behavior and the functional connectivity (as assessed by resting-state fMRI) of AMD patients with aware patients and healthy controls. We found that AMD is associated with an impoverished PDB, while MPs are necessary to successfully update the PDB.AMD was associated with reduced functional connectivity within both the default-mode network and in a network that includes the left lateral temporal cortex, the hippocampus and the insula. The reduced connectivity between the hippocampus and the insular cortex was correlated with AMD severity.