Showing papers in "Frontiers in Human Neuroscience in 2015"
TL;DR: It is demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies.
Abstract: Recent studies have suggested that the brain’s structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface; (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website (http://www.nitrc.org/projects/gretna/).
884 citations
TL;DR: A new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, is introduced and compared with the mental model theory and the causal model theory.
Abstract: Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani, Barbey, & Johnson-Laird, 2014) and the causal model theory (Sloman, Barbey, & Hotaling, 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people’s ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed.
788 citations
TL;DR: In this paper, the most common brain areas for fNIRS-based BCI are the primary motor cortex and prefrontal cortex, and the motor imagery tasks were preferred to motor execution tasks since possible proprioceptive feedback could be avoided.
Abstract: A brain-computer interface (BCI) is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing the peripheral nervous system, provide a means of communication for people suffering from severe motor disabilities or in a persistent vegetative state. In this paper, brain-signal generation tasks, noise removal methods, feature extraction/selection schemes, and classification techniques for fNIRS-based BCI are reviewed. The most common brain areas for fNIRS BCI are the primary motor cortex and the prefrontal cortex. In relation to the motor cortex, motor imagery tasks were preferred to motor execution tasks since possible proprioceptive feedback could be avoided. In relation to the prefrontal cortex, fNIRS showed a significant advantage due to no hair in detecting the cognitive tasks like mental arithmetic, music imagery, emotion induction, etc. In removing physiological noise in fNIRS data, band-pass filtering was mostly used. However, more advanced techniques like adaptive filtering, independent component analysis, multi optodes arrangement, etc. are being pursued to overcome the problem that a band-pass filter cannot be used when both brain and physiological signals occur within a close band. In extracting features related to the desired brain signal, the mean, variance, peak value, slope, skewness, and kurtosis of the noised-removed hemodynamic response were used. For classification, the linear discriminant analysis method provided simple but good performance among others: support vector machine, hidden Markov model, artificial neural network, etc. fNIRS will be more widely used to monitor the occurrence of neuro-plasticity after neuro-rehabilitation and neuro-stimulation. Technical breakthroughs in the future are expected via bundled-type probes, hybrid EEG-fNIRS BCI, and through the detection of initial dips.
715 citations
TL;DR: The study demonstrated the feasibility of the auditoryBCI with healthy users and stresses the importance of training with auditory multiclass BCIs, especially for potential end-users of BCI with disease.
Abstract: Brain-computer interfaces (BCIs) can serve as muscle independent communication aids. Persons, who are unable to control their eye muscles (e.g., in the completely locked-in state) or have severe visual impairments for other reasons, need BCI systems that do not rely on the visual modality. For this reason, BCIs that employ auditory stimuli were suggested. In this study, a multiclass BCI spelling system was implemented that uses animal voices with directional cues to code rows and columns of a letter matrix. To reveal possible training effects with the system, 11 healthy participants performed spelling tasks on 2 consecutive days. In a second step, the system was tested by a participant with amyotrophic lateral sclerosis (ALS) in two sessions. In the first session, healthy participants spelled with an average accuracy of 76% (3.29 bits/min) that increased to 90% (4.23 bits/min) on the second day. Spelling accuracy by the participant with ALS was 20% in the first and 47% in the second session. The results indicate a strong training effect for both the healthy participants and the participant with ALS. While healthy participants reached high accuracies in the first session and second session, accuracies for the participant with ALS were not sufficient for satisfactory communication in both sessions. More training sessions might be needed to improve spelling accuracies. The study demonstrated the feasibility of the auditory BCI with healthy users and stresses the importance of training with auditory multiclass BCIs, especially for potential end-users of BCI with disease.
481 citations
TL;DR: The present review highlights the potential of virtual reality environments for enhanced ecological validity in the clinical, affective, and social neurosciences with growing interest in contextually embedded stimuli that can constrain participant interpretations of cues about a target’s internal states.
Abstract: An essential tension can be found between researchers interested in ecological validity and those concerned with maintaining experimental control. Research in the human neurosciences often involves the use of simple and static stimuli lacking many of the potentially important aspects of real world activities and interactions. While this research is valuable, there is a growing interest in the human neurosciences to use cues about target states in the real world via multimodal scenarios that involve visual, semantic, and prosodic information. These scenarios should include dynamic stimuli presented concurrently or serially in a manner that allows researchers to assess the integrative processes carried out by perceivers over time. Furthermore, there is growing interest in contextually embedded stimuli that can constrain participant interpretations of cues about a target’s internal states. Virtual reality environments proffer assessment paradigms that combine the experimental control of laboratory measures with emotionally engaging background narratives to enhance affective experience and social interactions. The present review highlights the potential of virtual reality environments for enhanced ecological validity in the clinical, affective, and social neurosciences.
410 citations
TL;DR: A conceptualization based on Bayesian causal inference is proposed for addressing how the authors' nervous system could infer whether an object belongs to their own body, using multisensory, sensorimotor, and semantic information, and how this can account for several experimental findings.
Abstract: Which is my body and how do I distinguish it from the bodies of others, or from objects in the surrounding environment? The perception of our own body and more particularly our sense of body ownership is taken for granted. Nevertheless, experimental findings from body ownership illusions (BOIs), show that under specific multisensory conditions, we can experience artificial body parts or fake bodies as our own body parts or body, respectively. The aim of the present paper is to discuss how and why BOIs are induced. We review several experimental findings concerning the spatial, temporal, and semantic principles of crossmodal stimuli that have been applied to induce BOIs. On the basis of these principles, we discuss theoretical approaches concerning the underlying mechanism of BOIs. We propose a conceptualization based on Bayesian causal inference for addressing how our nervous system could infer whether an object belongs to our own body, using multisensory, sensorimotor, and semantic information, and we discuss how this can account for several experimental findings. Finally, we point to neural network models as an implementational framework within which the computational problem behind BOIs could be addressed in the future.
362 citations
TL;DR: This research demonstrates that stress, anxiety, and other kinds of emotion can profoundly influence key elements of cognition, including selective attention, working memory, and cognitive control, and suggests that widely held beliefs about the key constituents of ‘the emotional brain’ and “the cognitive brain” are fundamentally flawed.
Abstract: Recent years have witnessed the emergence of powerful new tools for assaying the brain and a remarkable acceleration of research focused on the interplay of emotion and cognition. This work has begun to yield new insights into fundamental questions about the nature of the mind and important clues about the origins of mental illness. In particular, this research demonstrates that stress, anxiety, and other kinds of emotion can profoundly influence key elements of cognition, including selective attention, working memory, and cognitive control. Often, this influence persists beyond the duration of transient emotional challenges, partially reflecting the slower molecular dynamics of catecholamine and hormonal neurochemistry. In turn, circuits involved in attention, executive control, and working memory contribute to the regulation of emotion. The distinction between the ‘emotional’ and the ‘cognitive’ brain is fuzzy and context-dependent. Indeed, there is compelling evidence that brain territories and psychological processes commonly associated with cognition, such as the dorsolateral prefrontal cortex and working memory, play a central role in emotion. Furthermore, putatively emotional and cognitive regions influence one another via a complex web of connections in ways that jointly contribute to adaptive and maladaptive behavior. This work demonstrates that emotion and cognition are deeply interwoven in the fabric of the brain, suggesting that widely held beliefs about the key constituents of ‘the emotional brain’ and ‘the cognitive brain’ are fundamentally flawed. We conclude by outlining several strategies for enhancing future research. Developing a deeper understanding of the emotional-cognitive brain is important, not just for understanding the mind but also for elucidating the root causes of its disorders.
279 citations
TL;DR: There is converging evidence that proprioceptive training can yield meaningful improvements in somatosensory and sensorimotor function, and initial evidence suggesting that propriaceptive training induces cortical reorganization, reinforcing the notion that proprieceptive training is a viable method for improving sensorim motor function.
Abstract: Objective: Numerous reports advocate that training of the proprioceptive sense is a viable behavioral therapy for improving impaired motor function. However, there is little agreement of what constitutes proprioceptive training and how effective it is. We therefore conducted a comprehensive, systematic review of the available literature in order to provide clarity to the notion of training the proprioceptive system. Methods: Four major scientific databases were searched. The following criteria were subsequently applied: 1) A quantified pre and post-treatment measure of proprioceptive function. 2) An intervention or training program believed to influence or enhance proprioceptive function. 3) Contained at least one form of treatment or outcome measure that is indicative of somatosensory function. From a total of 1284 articles, 51 studies fulfilled all criteria and were selected for further review. Results: Overall, proprioceptive training resulted in an average improvement of 52% across all outcome measures. Applying muscle vibration above 30Hz for longer durations (i.e., min vs. sec) induced outcome improvements of up to 60%. Joint position and target reaching training consistently enhanced joint position sense (up to 109%) showing an average improvement of 48%. Cortical stroke was the most studied disease entity but no clear evidence indicated that proprioceptive training is differentially beneficial across the reported diseases. Conclusions: There is converging evidence that proprioceptive training can yield meaningful improvements in somatosensory and sensorimotor function. However, there is a clear need for further work. Those forms of training utilizing both passive and active movements with and without visual feedback tended to be most beneficial. There is also initial evidence suggesting that proprioceptive training induces cortical reorganization, reinforcing the notion that proprioceptive training is a viable method for improving sensorimotor function.
256 citations
TL;DR: The objective of this article is to advance the science of automaticity of walking by consolidating evidence and identifying gaps in knowledge regarding: (a) functional significance ofautomaticity; (b) neurophysiology of automaticITY; (c) measurement of automaticities; (d) mechanistic factors that compromise automaticity; and (e) strategies for rehabilitation of automaticality.
Abstract: Automaticity is a hallmark feature of walking in adults who are healthy and well-functioning. In the context of walking, ‘automaticity’ refers to the ability of the nervous system to successfully control typical steady state walking with minimal use of attention-demanding executive control resources. Converging lines of evidence indicate that walking deficits and disorders are characterized in part by a shift in the locomotor control strategy from healthy automaticity to compensatory executive control. This is potentially detrimental to walking performance, as an executive control strategy is not optimized for locomotor control. Furthermore, it places excessive demands on a limited pool of executive reserves. The result is compromised ability to perform basic and complex walking tasks and heightened risk for adverse mobility outcomes including falls. Strategies for rehabilitation of automaticity are not well defined, which is due to both a lack of systematic research into the causes of impaired automaticity and to a lack of robust neurophysiological assessments by which to gauge automaticity. These gaps in knowledge are concerning given the serious functional implications of compromised automaticity. Therefore, the objective of this article is to advance the science of automaticity of walking by consolidating evidence and identifying gaps in knowledge regarding: a) functional significance of automaticity; b) neurophysiology of automaticity; c) measurement of automaticity; d) mechanistic factors that compromise automaticity; and e) strategies for rehabilitation of automaticity.
255 citations
TL;DR: Evidence suggests that a rT MS-induced magnetic field should be considered a separate physical factor that can be impactful at the subatomic level and that rTMS is capable of significantly altering the reactivity of molecules (radicals) and that these factors underlie the therapeutic benefits of therapy with TMS.
Abstract: Transcranial magnetic stimulation (TMS) is an effective method used to diagnose and treat many neurological disorders. Although repetitive TMS (rTMS) has been used to treat a variety of serious pathological conditions including stroke, depression, Parkinson's disease, epilepsy, pain, and migraines, the pathophysiological mechanisms underlying the effects of long-term TMS remain unclear. In the present review, the effects of rTMS on neurotransmitters and synaptic plasticity are described, including the classic interpretations of TMS effects on synaptic plasticity via long-term potentiation (LTP) and long-term depression (LTD). We also discuss the effects of rTMS on the genetic apparatus of neurons, glial cells and the prevention of neuronal death. The neurotrophic effects of rTMS on dendritic growth and sprouting and neurotrophic factors are described, including change in brain-derived neurotrophic factor (BDNF) concentration under the influence of rTMS. Also, non-classical effects of TMS related to biophysical effects of magnetic fields are described, including the quantum effects, the magnetic spin effects, genetic magnetoreception, the macromolecular effects of TMS, and the electromagnetic theory of consciousness. Finally, we discuss possible interpretations of TMS effects according to dynamical systems theory. Evidence suggests that a rTMS-induced magnetic field should be considered a separate physical factor that can be impactful at the subatomic level and that rTMS is capable of significantly altering the reactivity of molecules (radicals). It is thought that these factors underlie the therapeutic benefits of therapy with TMS. Future research on these mechanisms will be instrumental to the development of more powerful and reliable TMS treatment protocols.
242 citations
TL;DR: This perspective paper presents a framework for measuring treatment effects on dual-task interference, specifically taking into account the interactions between the two tasks and how this can provide information on whether overall dual- task capacity has improved or a different attentional strategy has been adopted.
Abstract: The relevance of dual-task walking to everyday ambulation is widely acknowledged, and numerous studies have demonstrated that dual-task interference can significantly impact recovery of functional walking in people with neurological disorders. The magnitude and direction of dual-task interference is influenced by the interaction between the two tasks, including how individuals spontaneously prioritize their attention. Therefore, to accurately interpret and characterize dual-task interference and identify changes over time, it is imperative to evaluate single and dual-task performance in both tasks, as well as the tasks relative to each other. Yet, reciprocal dual-task effects are frequently ignored. The purpose of this perspective paper is to present a framework for measuring treatment effects on dual-task interference, specifically taking into account the interactions between the two tasks and how this can provide information on whether overall dual-task capacity has improved or a different attentional strategy has been adopted. In discussing the clinical implications of using this framework, we provide specific examples of using this method and provide some explicit recommendations for research and clinical practice.
TL;DR: Precise computer-based measurements of SRT latencies show that processing speed is as fast in contemporary populations as in the Victorian era, and that age-related increases in S RT latencies are due primarily to slowed motor output.
Abstract: Simple reaction time (SRT), the minimal time needed to respond to a stimulus, is a basic measure of processing speed. SRTs were first measured by Francis Galton in the 19th century who reported visual SRT latencies below 190 ms in young subjects. However, recent large-scale studies have reported substantially increased SRT latencies that differ markedly in different laboratories, in part due to timing delays introduced by computer hardware and software used for SRT measurement. We developed a calibrated and temporally-precise SRT paradigm to analyze the factors that influence SRT latencies in a paradigm where visual stimuli were presented to the left or right hemifield at varying stimulus onset asynchronies (SOAs). Experiment 1 examined a community sample of 1469 subjects ranging in age from 18 to 65. Mean SRT latencies were short (231 ms, 213 ms when corrected for hardware delays) and increased significantly with age (0.55 ms/year), but were unaffected by sex or education. As in previous studies, SRTs were prolonged at shorter SOAs and were slightly faster for stimuli presented in the visual field contralateral to the responding hand. Stimulus detection time (SDT) was estimated by subtracting movement-initiation time, measured in a speeded finger-tapping test, from SRTs. SDT latencies averaged 131 ms and were unaffected by age. Experiment 2 tested 189 subjects ranging in age from 18 to 82 years in a different laboratory using a larger range of SOAs. Both SRTs and SDTs were slightly prolonged (by 7 ms). SRT latencies increased with age while SDT latencies did not. Precise computer-based measurements of SRT latencies show that processing speed is as fast in contemporary populations as in those from the Victorian era and that age-related increases in SRT latencies are due primarily to slowed motor output.
TL;DR: Methods and models for investigating the neuronal and cognitive-affective bases of literary reading together with pertinent results from studies on poetics, text processing, emotion, or neuroaesthetics are discussed and outline current challenges and future perspectives.
Abstract: A long tradition of research including classical rhetoric, aesthetics and poetics theory, formalism and structuralism, as well as current perspectives in (neuro)cognitive poetics has investigated structural and functional aspects of literature reception. Despite a wealth of literature published in specialised journals like Poetics, however, still little is known about how the brain processes and creates literary and poetic texts. Still, such stimulus material might be suited better than other genres for demonstrating the complexities with which our brain constructs the world in and around us, because it unifies thought and language, music and imagery in a clear, manageable way, most often with play, pleasure, and emotion (Schrott & Jacobs, 2011). In this paper, I discuss methods and models for investigating the neuronal and cognitive-affective bases of literary reading together with pertinent results from studies on poetics, text processing, emotion, or neuroaesthetics, and outline current challenges and future perspectives.
TL;DR: It is suggested that failure of network up- and down-regulation dynamics may provide neuronal underpinnings for cognitive impairments seen in many mental disorders, such as, e.g., schizophrenia.
Abstract: In this paper we suggest the existence of a generalized task-related cortical network that is up-regulated whenever the task to be performed requires the allocation of generalized non-specific cognitive resources, independent of the specifics of the task to be performed. We have labeled this general purpose network, the extrinsic mode network (EMN) as complementary to the default mode network (DMN), such that the EMN is down-regulated during periods of task-absence, when the DMN is up-regulated, and vice versa. We conceptualize the EMN as a cortical network for extrinsic neuronal activity, similar to the DMN as being a cortical network for intrinsic neuronal activity. The EMN has essentially a fronto-temporo-parietal spatial distribution, including the inferior and middle frontal gyri, inferior parietal lobule, supplementary motor area, inferior temporal gyrus. We hypothesize that this network is always active regardless of the cognitive task being performed. We further suggest that failure of network up- and down-regulation dynamics may provide neuronal underpinnings for cognitive impairments seen in many mental disorders, such as, e.g., schizophrenia. We start by describing a common observation in functional imaging, the close overlap in fronto-parietal activations in healthy individuals to tasks that denote very different cognitive processes. We now suggest that this is because the brain utilizes the EMN network as a generalized response to tasks that exceeds a cognitive demand threshold and/or requires the processing of novel information. We further discuss how the EMN is related to the DMN, and how a network for extrinsic activity is related to a network for intrinsic activity. Finally, we discuss whether the EMN and DMN networks interact in a common single brain system, rather than being two separate and independent brain systems.
TL;DR: In vivo measure of individual brainstem nuclei in stroke survivors with spasticity using advanced fMRI techniques in the future is probably able to provide direct evidence of pathogenesis of post-stroke spasticy, and the possible role of VST hyperexcitability cannot be ruled out.
Abstract: Spasticity is one of many consequences after stroke It is characterized by a velocity-dependent increase in resistance during passive stretch, resulting from hyperexcitability of the stretch reflex The underlying mechanism of the hyperexcitable stretch reflex, however, remains poorly understood Accumulated experimental evidence has supported supraspinal origins of spasticity, likely from an imbalance between descending inhibitory and facilitatory regulation of spinal stretch reflexes secondary to cortical disinhibition after stroke The excitability of reticulospinal (RST) and vestibulospinal tracts (VSTs) has been assessed in stroke survivors with spasticity using non-invasive indirect measures There are strong experimental findings that support the RST hyperexcitability as a prominent underlying mechanism of post-stroke spasticity This mechanism can at least partly account for clinical features associated with spasticity and provide insightful guidance for clinical assessment and management of spasticity However, the possible role of VST hyperexcitability cannot be ruled out from indirect measures In vivo measure of individual brainstem nuclei in stroke survivors with spasticity using advanced fMRI techniques in the future is probably able to provide direct evidence of pathogenesis of post-stroke spasticity
TL;DR: A causal relationship between the gamma/theta ratio and WM/STM capacity by means of transcranial alternating current stimulation (tACS) was established, with an increase in STM capacity caused by the manipulation of individual theta frequencies.
Abstract: Working memory (WM) and short-term memory (STM) supposedly rely on the phase-amplitude coupling of neural oscillations in the theta and gamma frequency ranges. The ratio between the individually dominant gamma and theta frequencies is believed to determine an individual’s memory capacity. The aim of this study was to establish a causal relationship between the gamma/theta ratio and WM/STM capacity by means of transcranial alternating current stimulation (tACS). To achieve this, tACS was delivered at a frequency below the individual theta frequency. Thereby the individual ratio of gamma to theta frequencies was changed, resulting in an increase of STM capacity. Healthy human participants (N=33) were allocated to two groups, one receiving verum tACS, the other underwent a sham control protocol. The electroencephalogram (EEG) was measured before stimulation and analyzed with regard to the properties of phase-amplitude coupling between theta and gamma frequencies to determine individual stimulation frequencies. After stimulation, EEG was recorded again in order to find after-effects of tACS in the oscillatory features of the EEG. Measures of STM and WM were obtained before, during and after stimulation. Frequency spectra and behavioral data were compared between groups and different measurement phases. The tACS- but not the sham stimulated group showed an increase in STM capacity during stimulation. WM was not affected in either groups. An increase in task-related theta amplitude after stimulation was observed only for the tACS group. These augmented theta amplitudes indicated that the manipulation of individual theta frequencies was successful and caused the increase in STM capacity.
TL;DR: Higher fit individuals who demonstrate better cardiorespiratory functions show faster reaction times and greater cerebral oxygenation in the right inferior frontal gyrus than women with lower fitness levels, suggesting that good cardiorespiratory functions can have a positive impact on cognition, regardless of age.
Abstract: Aim: Many studies have suggested that physical exercise training improves cognition and more selectively executive functions. There is a growing interest to clarify the neurophysiological mechanisms that underlie this effect. The aim of the current study was to evaluate the neurophysiological changes in cerebral oxygenation associated with physical fitness level and executive functions. Method: In this study, 22 younger and 36 older women underwent a maximal graded continuous test (i.e., O2max) in order to classifyassign them into a fitness group (higher vs. lower fit). All participants completed neuropsychological paper and pencil testing and a computerized Stroop task (which contained executive and non-executive conditions) in which the change in pPrefrontal cortex oxygenation change was evaluated in all participants with a near infrared spectroscopy (NIRS). system during a computerized Stroop task (which contains executive and non-executive conditions). Results: Our findings revealed a Fitness x Condition interaction (p < .05) such that higher fit women scored better on measures of executive functions than lower fit women. In comparison to lower fit women, higher fit women had faster reaction times in the switching (executive)Executive condition of the computerized Stroop task. No significant effect was observed ion the non-executive condition of the test and no interactions were found with age. In measures of cerebral oxygenation (ΔHbT and ΔHbO2), we found a main effect of fitness on cerebral oxygenation during the Stroop task such that only high fit women demonstrated a significant increase in the right inferior frontal gyrus. Discussion/Conclusion: Higher fit individuals who demonstrate better cardiorespiratory functions (as measured by O2max) show faster reaction times and greater cerebral oxygenation in the right inferior frontal gyrus than women with lower fitness levels. The lack of interaction with age, suggests that good cardiorespiratory functions
TL;DR: This is the first study to identify evidence for a robust bidirectional link between executive function and physical activity in a large sample of older adults tracked over time.
Abstract: Physically active lifestyles contribute to better executive function. However, it is unclear whether high levels of executive function lead people to be more active. This study uses a large sample and multi-wave data to identify whether a reciprocal association exists between physical activity and executive function. Participants were 4555 older adults tracked across four waves of the English Longitudinal Study of Aging. In each wave executive function was assessed using a verbal fluency test and a letter cancelation task and participants reported their physical activity levels. Fixed effects regressions showed that changes in executive function corresponded with changes in physical activity. In longitudinal multilevel models low levels of physical activity led to subsequent declines in executive function. Importantly, poor executive function predicted reductions in physical activity over time. This association was found to be over 50% larger in magnitude than the contribution of physical activity to changes in executive function. This is the first study to identify evidence for a robust bidirectional link between executive function and physical activity in a large sample of older adults tracked over time.
TL;DR: It is indicated that mental state is closely related to BCI performance, encouraging future development of psychologically adaptive BCIs and showing the sensitivity of underlying class distributions to changes in mental state.
Abstract: Changes in psychological state have been proposed as a cause of variation in brain-computer interface performance, but little formal analysis has been conducted to support this hypothesis. In this study, we investigated the effects of three mental states - fatigue, frustration, and attention - on BCI performance. Twelve able-bodied participants were trained to use a two-class EEG-BCI based on the performance of user-specific mental tasks. Following training, participants completed three testing sessions, during which they used the BCI to play a simple maze navigation game while periodically reporting their perceived levels of fatigue, frustration, and attention. Statistical analysis indicated that there is a significant relationship between frustration and BCI performance while the relationship between fatigue and BCI performance approached significance. BCI performance was 7% lower than average when self-reported fatigue was low and 10% lower than average when self-reported frustration was low. A multivariate analysis of mental state revealed the presence of contiguous regions in mental state space where BCI performance was more accurate than average, suggesting the importance of moderate fatigue for achieving effortless focus on BCI control, frustration as a potential motivating factor, and attention as a compensatory mechanism to increasing frustration. Finally, a visual analysis showed the sensitivity of underlying class distributions to changes in mental state. Collectively, these results indicate that mental state is closely related to BCI performance, encouraging future development of psychologically adaptive BCIs.
TL;DR: Findings reject the hypothesis that mental fatigue exacerbates central fatigue induced by whole-body endurance exercise and confirm previous findings thatmental fatigue does not reduce the capacity of the central nervous system to recruit the working muscles.
Abstract: It has been shown that the mental fatigue induced by prolonged self-regulation increases perception of effort and reduces performance during subsequent endurance exercise. However, the physiological mechanisms underlying these negative effects of mental fatigue are unclear. The primary aim of this study was to test the hypothesis that mental fatigue exacerbates central fatigue induced by whole-body endurance exercise. Twelve subjects performed 30 min of either an incongruent Stroop task to induce a condition of mental fatigue or a congruent Stroop task (control condition) in a random and counterbalanced order. Both cognitive tasks (CTs) were followed by a whole-body endurance task (ET) consisting of 6 min of cycling exercise at 80% of peak power output measured during a preliminary incremental test. Neuromuscular function of the knee extensors was assessed before and after CT, and after ET. Rating of perceived exertion (RPE) was measured during ET. Both CTs did not induce any decrease in maximal voluntary contraction (MVC) torque (p = 0.194). During ET, mentally fatigued subjects reported higher RPE (mental fatigue 13.9 ± 3.0, control 13.3 ± 3.2, p = 0.044). ET induced a similar decrease in MVC torque (mental fatigue -17 ± 15%, control -15 ± 11%, p = 0.001), maximal voluntary activation level (mental fatigue -6 ± 9%, control -6 ± 7%, p = 0.013) and resting twitch (mental fatigue -30 ± 14%, control -32 ± 10%, p < 0.001) in both conditions. These findings reject our hypothesis and confirm previous findings that mental fatigue does not reduce the capacity of the central nervous system to recruit the working muscles. The negative effect of mental fatigue on perception of effort does not reflect a greater development of either central or peripheral fatigue. Consequently, mentally fatigued subjects are still able to perform maximal exercise, but they are experiencing an altered performance during submaximal exercise due to higher-than-normal perception of effort.
TL;DR: Why and howSad music can become pleasurable is considered and a framework to account for how listening to sad music can lead to positive feelings is offered, contending that this effect hinges on correcting an ongoing homeostatic imbalance.
Abstract: Sadness is generally seen as a negative emotion, a response to distressing and adverse situations. In an aesthetic context, however, sadness is often associated with some degree of pleasure, as suggested by the ubiquity and popularity, throughout history, of music, plays, films and paintings with a sad content. Here, we focus on the fact that music regarded as sad is often experienced as pleasurable. Compared to other art forms, music has an exceptional ability to evoke a wide-range of feelings and is especially beguiling when it deals with grief and sorrow. Why is it, then, that while human survival depends on preventing painful experiences, mental pain often turns out to be explicitly sought through music? In this article we consider why and how sad music can become pleasurable. We offer a framework to account for how listening to sad music can lead to positive feelings, contending that this effect hinges on correcting an ongoing homeostatic imbalance. Sadness evoked by music is found pleasurable (1) when it is perceived as non-threatening; (2) when it is aesthetically pleasing; and (3) when it produces psychological benefits such as mood regulation, and empathic feelings, caused, for example, by recollection of and reflection on past events. We also review neuroimaging studies related to music and emotion and focus on those that deal with sadness. Further exploration of the neural mechanisms through which stimuli that usually produce sadness can induce a positive affective state could help the development of effective therapies for disorders such as depression, in which the ability to experience pleasure is attenuated.
TL;DR: A systematic review of all studies that related the resection of HFO-generating areas to postsurgical outcome found that automated detection and application of a detection threshold in order to detect channels with a frequent occurrence of H FOs is important to yield a marker that could be useful in presurgical evaluation.
Abstract: High frequency oscillations (HFOs) are estimated as a potential marker for epileptogenicity. Current research strives for valid evidence that these HFOs could aid the delineation of the to-be resected area in patients with refractory epilepsy and improve surgical outcomes. In the present meta-analysis, we evaluated the relation between resection of regions from which HFOs can be detected and outcome after epilepsy surgery. We conducted a systematic review of all studies that related the resection of HFO-generating areas to postsurgical outcome. We related the outcome (seizure freedom) to resection ratio, that is, the ratio between the number of channels on which HFOs were detected and, among these, the number of channels that were inside the resected area. We compared the resection ratio between seizure free and not seizure free patients. In total, 11 studies were included. In 10 studies, ripples (80-200 Hz) were analyzed, and in 7 studies, fast ripples (>200 Hz) were studied. We found comparable differences (dif) and largely overlapping confidence intervals (CI) in resection ratios between outcome groups for ripples (dif=0.18; CI: 0.10-0.27) and fast ripples (dif=0.17; CI: 0.01-0.33). Subgroup analysis showed that automated detection (dif=0.22; CI: 0.03-0.41) was comparable to visual detection (dif=0.17; CI: 0.08-0.27). Considering frequency of HFOs (dif=0.24; CI: 0.09-0.38) was related more strongly to outcome than considering each electrode that was showing HFOs (dif=0.15; CI=0.03-0.27). The effect sizes found in the meta-analysis are small but significant. Automated detection and application of a detection threshold in order to detect channels with a frequent occurrence of HFOs is important to yield a marker that could be useful in presurgical evaluation. In order to compare studies with different methodological approaches, detailed and standardized reporting is warranted.
TL;DR: The findings indicate that the connectivity-neurofeedback training can cause long-term changes in intrinsic connectivity and that intrinsic networks can be shaped by experience-driven modulation of regional correlation.
Abstract: Motor or perceptual learning is known to influence functional connectivity between brain regions and induce short-term changes in the intrinsic functional networks revealed as correlations in slow blood-oxygen-level dependent (BOLD) signal fluctuations. However, no cause-and-effect relationship has been elucidated between a specific change in connectivity and a long-term change in global networks. Here, we examine the hypothesis that functional connectivity (i.e., temporal correlation between two regions) is increased and preserved for a long time when two regions are simultaneously activated or deactivated. Using the connectivity-neurofeedback training paradigm, subjects successfully learned to increase the correlation of activity between the lateral parietal and primary motor areas, regions that belong to different intrinsic networks and negatively correlated before training under the resting conditions. Furthermore, whole-brain hypothesis-free analysis as well as functional network analyses demonstrated that the correlation in the resting state between these areas as well as the correlation between the intrinsic networks that include the areas increased for at least 2 months. These findings indicate that the connectivity-neurofeedback training can cause long-term changes in intrinsic connectivity and that intrinsic networks can be shaped by experience-driven modulation of regional correlation.
TL;DR: This technique allows us to study neuroplasticity of the human brain in a reversible manner and to modulate plasticity-related functions such as memory or learning, which critically depend on neuroplasticsity, in healthy and clinical populations.
Abstract: Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation technique that has been reintroduced in the last decade and is now mainly used as a cognitive modulator in human neuroscience research. tDCS delivers a weak direct current (usually up to 2 mA) over the scalp and creates a constant electric field in the brain which can lead to acute alterations of the excitability of cortical areas by its subthreshold depolarizing or hyperpolarizing effects on neuronal resting membrane potentials (Nitsche and Paulus, 2000). Beyond these acute effects, stimulation for some minutes results in neuroplastic after-effects, which can last for over 1 h after stimulation (Nitsche and Paulus, 2001). With repeated usage, longer lasting effects can be induced, which are in the range of late-phase plasticity (Monte-Silva et al., 2013). The neuroplastic effects resemble LTP- and LTD-like plasticity of glutamatergic synapses (Liebetanz et al., 2002; Nitsche et al., 2003a). Therefore, this technique allows us to study neuroplasticity of the human brain in a reversible manner and to modulate plasticity-related functions such as memory or learning, which critically depend on neuroplasticity, in healthy and clinical populations.
Traditionally, one or more surface-positive (anode) and negative (cathode) electrodes are used to deliver current; one is positioned over the target area and the other one is put over another cranial (intracephalic) or extracranial (extracephalic) region of the body. These electrodes are usually called active and reference electrode respectively. However, these terms can be technically improper and should be replaced with other terms such as “target” and “return” electrodes, because the size and the place of a return electrode have an impact on its effects and thus it might not be physiologically inert. The return electrode can contribute directly—and not only via determination of electrical field orientation—to physiological effects when put over the cranium as well (Brunoni et al., 2012). Several studies have also shown antagonistic effects of stimulation on visual cortex (Antal et al., 2004; Accornero et al., 2007) and motor cortex (Nitsche and Paulus, 2000) dependent on return electrode position. In any case, the position of the return electrode will affect electrical field orientation, which is critical for the efficacy, and direction of the effects (Bikson et al., 2010; Kabakov et al., 2012). In both—extracephalic and intracephalic conditions—positive (cathode) and negative (anode) poles are conventionally physiologically distinguished according to their effects on excitability of the brain. Basically, cathodal stimulation has hyperpolarizing effects, which lead to inhibition of cortical activity, while anodal stimulation has excitatory effects (Nitsche et al., 2003b, 2008). It should be worth noting that although every neuron undergoes hyperpolarizing and depolarizing, the physiological effect depends more on axonal/soma polarization (Arlotti et al., 2012), hence the physical and physiological aspects can be dissociated. General effects on excitability, which were obtained primarily in the human motor cortex, might also switch, turning from excitatory to inhibitory or vice versa, dependent on stimulation parameters such as intensity, and duration (Batsikadze et al., 2013; Monte-Silva et al., 2013), and position of the return electrode (Antal et al., 2004; Accornero et al., 2007). With a rise in prevalence of studies using tDCS, protocols have become more complex and varieties of tDCS montages were introduced and are used in different labs. Despite this extending diversity of tDCS electrode montages, to our best knowledge, there is no consensus among researchers in this field on a systematic framework for categorizing electrode montages in a unified way. In this short article, we propose a framework for categorization of tDCS montages according to physical characteristics. This categorization is based on published studies until October 2014. Our main motivation to propose this framework is to unify the classifications of electrode montages in a simple way; there are nevertheless several other advantages of this categorization. First, different montages that are used to target a specific brain area such as dorsolateral prefrontal cortex (DLPFC) could have different effects; therefore providing a unified classification enables us to take these differences into account. Furthermore, this classification gives us a chance to explore other novel potentials for electrode montages that so far have remained untouched. Lastly, a unified systematic framework will be helpful for presenting study methods and for extracting data for systematic reviews and meta-analyses in a more practical way.
TL;DR: It is shown that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response, which allows us to detect and discriminate errors of different origin in an event-locked manner.
Abstract: When a person recognizes an error during a task, an error-related potential (ErrP) can be measured as response. It has been shown that ErrPs can be automatically detected in tasks with time-discrete feedback, which is widely applied in the field of Brain-Computer Interfaces (BCIs) for error correction or adaptation. However, there are only a few studies that concentrate on ErrPs during continuous feedback. With this study, we wanted to answer three different questions: (i) Can ErrPs be measured in electroencephalography (EEG) recordings during a task with continuous cursor control? (ii) Can ErrPs be classified using machine learning methods and is it possible to discriminate errors of different origins? (iii) Can we use EEG to detect the severity of an error? To answer these questions, we recorded EEG data from 10 subjects during a video game task and investigated two different types of error (execution error, due to inaccurate feedback; outcome error, due to not achieving the goal of an action). We analyzed the recorded data to show that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response. This allows us to detect and discriminate errors of different origin in an event-locked manner. By utilizing the error-related spectral response, we show that also a continuous, asynchronous detection of errors is possible. Although the detection of error severity based on EEG was one goal of this study, we did not find any significant influence of the severity on the EEG.
TL;DR: An emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity is highlighted, and Multivariate Cross-Classification (MVCC) is called, which has been important in establishing correspondences among neural patterns across cognitive domains.
Abstract: Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application.
TL;DR: This work outlines the bottom-up neurophysiological and top-down neurocognitive mechanisms hypothesized to be at play in YBP, and proposes a comprehensive theoretical framework from which testable hypotheses can be formulated.
Abstract: During recent decades numerous yoga-based practices (YBP) have emerged in the West, with their aims ranging from fitness gains to therapeutic benefits and spiritual development. Yoga is also beginning to spark growing interest within the scientific community, and yoga-based interventions have been associated with measureable changes in physiological parameters, perceived emotional states, and cognitive functioning. Yoga-based interventions typically involve a combination of postures or movement sequences, conscious regulation of the breath, and various techniques to improve attentional focus. However, so far little if any research has attempted to deconstruct the role of these different component parts in order to better understand their respective contribution to the effect of YBP. A clear operational definition of yoga-based therapeutic interventions for scientific purposes, as well as a comprehensive theoretical framework from which testable hypotheses can be formulated, is therefore needed. Here we propose such a framework, and outline the bottom-up neurophysiological and top-down neurocognitive mechanisms hypothesized to underlie the effects of YBP.
TL;DR: Results provide evidence that mindfulness is associated with iFC between DMN and SN and suggest that ongoing interactions among central intrinsic brain networks link with the ability to attend to current experience without judgment.
Abstract: Mindfulness is attention to present moment experience without judgment Mindfulness practice is associated with brain activity in areas overlapping with the default mode, salience, and central executive networks (DMN, SN, CEN) We hypothesized that intrinsic functional connectivity (iFC; ie, synchronized ongoing activity) across these networks is associated with mindfulness scores After 2 weeks of daily 20 min attention to breath training, healthy participants were assessed by mindfulness questionnaires and resting-state functional MRI Independent component analysis (ICA) of imaging data revealed networks of interest, whose activity time series defined inter-network intrinsic functional connectivity (inter-iFC) by temporal correlation Inter-iFC between subnetworks of the DMN and SN-and inter-iFC between subnetworks of the SN and left CEN at trend-was correlated with mindfulness scores Additional control analyses about visual networks' inter-iFC support the specificity of our findings Results provide evidence that mindfulness is associated with iFC between DMN and SN Data suggest that ongoing interactions among central intrinsic brain networks link with the ability to attend to current experience without judgment
TL;DR: A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool and identified specific measures and analysis methods that may be most suitable as fieldable diagnostic tools.
Abstract: Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: 1. Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. 2. ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are nondisclosing. 3. The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including nonlinear dynamical analysis, complexity measures, analysis of causal interactions, graph theory and information dynamics. 4. and 5. are too long to include here
TL;DR: Age-related eye-movement changes as measured in the laboratory only partly resemble those in the real world, and the importance of validity for natural situations when studying the impact of aging on real-life performance is highlighted.
Abstract: The effects of aging on eye movements are well studied in the laboratory. Increased saccade latencies or decreased smooth-pursuit gain are well established findings. The question remains whether these findings are influenced by the rather untypical environment of a laboratory; that is, whether or not they transfer to the real world. We measured 34 healthy participants between the age of 25 and 85 during two everyday tasks in the real world: (I) walking down a hallway with free gaze, (II) visual tracking of an earth-fixed object while walking straight-ahead. Eye movements were recorded with a mobile light-weight eye tracker, the EyeSeeCam (ESC). We find that age significantly influences saccade parameters. With increasing age, saccade frequency, amplitude, peak velocity, and mean velocity are reduced and the velocity/amplitude distribution as well as the velocity profile become less skewed. In contrast to laboratory results on smooth pursuit, we did not find a significant effect of age on tracking eye-movements in the real world. Taken together, age-related eye-movement changes as measured in the laboratory only partly resemble those in the real world. It is well-conceivable that in the real world additional sensory cues, such as head-movement or vestibular signals, may partially compensate for age-related effects, which, according to this view, would be specific to early motion processing. In any case, our results highlight the importance of validity for natural situations when studying the impact of aging on real-life performance.