ResearchPad - brain-mapping https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Functional magnetic resonance imaging of the trail-making test in older adults]]> https://www.researchpad.co/article/elastic_article_13819 The trail-making test (TMT) is a popular neuropsychological test, which is used extensively to measure cognitive impairment associated with neurodegenerative disorders in older adults. Behavioural performance on the TMT has been investigated in older populations, but there is limited research on task-related brain activity in older adults. The current study administered a naturalistic version of the TMT to a healthy older-aged population in an MRI environment using a novel, MRI-compatible tablet. Functional MRI was conducted during task completion, allowing characterization of the brain activity associated with the TMT. Performance on the TMT was evaluated using number of errors and seconds per completion of each link. Results are reported for 36 cognitively healthy older adults between the ages of 52 and 85. Task-related activation was observed in extensive regions of the bilateral frontal, parietal, temporal and occipital lobes as well as key motor areas. Increased age was associated with reduced brain activity and worse task performance. Specifically, older age was correlated with decreased task-related activity in the bilateral occipital, temporal and parietal lobes. These results suggest that healthy older aging significantly affects brain function during the TMT, which consequently may result in performance decrements. The current study reveals the brain activation patterns underlying TMT performance in a healthy older aging population, which functions as an important, clinically-relevant control to compare to pathological aging in future investigations.

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<![CDATA[Thalamic, cortical, and amygdala involvement in the processing of a natural sound cue of danger]]> https://www.researchpad.co/article/elastic_article_7872 When others stop and silence ensues, animals respond as if threatened. This study highlights the brain areas involved in listening to the dangerous silence.

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<![CDATA[Resting state networks of the canine brain under sevoflurane anaesthesia]]> https://www.researchpad.co/article/N0f88adec-494f-4799-9601-5a30499e23df

Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has become an established technique in humans and reliably determines several resting state networks (RSNs) simultaneously. Limited data exist about RSN in dogs. The aim of this study was to investigate the RSNs in 10 healthy beagle dogs using a 3 tesla MRI scanner and subsequently perform group-level independent component analysis (ICA) to identify functionally connected brain networks. Rs-fMRI sequences were performed under steady state sevoflurane inhalation anaesthesia. Anaesthetic depth was titrated to the minimum level needed for immobilisation and mechanical ventilation of the patient. This required a sevoflurane MAC between 0.8 to 1.2. Group-level ICA dimensionality of 20 components revealed distributed sensory, motor and higher-order networks in the dogs’ brain. We identified in total 7 RSNs (default mode, primary and higher order visual, auditory, two putative motor-somatosensory and one putative somatosensory), which are common to other mammals including humans. Identified RSN are remarkably similar to those identified in awake dogs. This study proves the feasibility of rs-fMRI in anesthetized dogs and describes several RSNs, which may set the basis for investigating pathophysiological characteristics of various canine brain diseases.

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<![CDATA[The impact of body posture on intrinsic brain activity: The role of beta power at rest]]> https://www.researchpad.co/article/N65f7a4e6-ac5f-46ef-91d2-3d4de84bb5d0

Tying the hands behind the back has detrimental effects on sensorimotor perceptual tasks. Here we provide evidence that beta band oscillatory activity in a resting state condition might play a crucial role in such detrimental effects. EEG activity at rest was measured from thirty young participants (mean age = 24.03) in two different body posture conditions. In one condition participants were required to keep their hands freely resting on the table. In the other condition, participants’ hands were tied behind their back. Increased beta power was observed in the left inferior frontal gyrus during the tied hands condition compared to the free hands condition. A control experiment ruled out alternative explanations for observed change in beta power, including muscle tension. Our findings provide new insights on how body postural manipulations impact on perceptual tasks and brain activity.

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<![CDATA[A novel visual ranking system based on arterial spin labeling perfusion imaging for evaluating perfusion disturbance in patients with ischemic stroke]]> https://www.researchpad.co/article/N32085c18-73a0-407b-8668-9d011597efb2

We developed a visual ranking system by combining the parenchymal perfusion deficits (PPD) and hyperintense vessel signals (HVS) on arterial spin labeling (ASL) imaging. This study aimed to assess the performance of this ranking system by correlating with subtypes classified based on dynamic susceptibility contrast (DSC) imaging for evaluating the perfusion disturbance observed in patients with ischemic stroke. 32 patients with acute or subacute infarcts detected by DSC imaging were reviewed. Each patient’s brain was divided into 12 areas. ASL ranks were defined by the presence (+) or absence (-) of PPD/HVS as follows; I:–/–, II:–/+, III: +/+, and IV: +/–. DSC imaging findings were categorized based on cerebral blood flow (CBF) and time to peak (TTP) as normal (normal CBF/TTP), mismatched (normal CBF/delayed TTP), and matched (decreased CBF/delayed TTP). Two reviewers rated perfusion abnormalities in the total of 384 areas. The four ASL ranks correlated well with the DSC subtypes (Spearman’s r = 0.82). The performance of ASL ranking system was excellent as indicated by the area under the curve value of 0.94 using either matched or mismatched DSC subtype as the gold standard and 0.97 using only the matched DSC subtype as the gold standard. The two methods were in good-to-excellent agreement (maximum κ-values, 0.86). Inter-observer agreement was excellent (κ-value, 0.98). Although the number of patients was small and the number of dropouts was high, our proposed, ASL-based visual ranking system represented by PPD and HVS provides good, graded estimates of perfusion disturbance that agree well with those obtained by DSC perfusion imaging.

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<![CDATA[Executive task-based brain function in children with type 1 diabetes: An observational study]]> https://www.researchpad.co/article/Nd7290b0a-e9f9-4731-9f28-e7228fa093e0

Background

Optimal glycemic control is particularly difficult to achieve in children and adolescents with type 1 diabetes (T1D), yet the influence of dysglycemia on the developing brain remains poorly understood.

Methods and findings

Using a large multi-site study framework, we investigated activation patterns using functional magnetic resonance imaging (fMRI) in 93 children with T1D (mean age 11.5 ± 1.8 years; 45.2% female) and 57 non-diabetic (control) children (mean age 11.8 ± 1.5 years; 50.9% female) as they performed an executive function paradigm, the go/no-go task. Children underwent scanning and cognitive and clinical assessment at 1 of 5 different sites. Group differences in activation occurring during the contrast of “no-go > go” were examined while controlling for age, sex, and scan site. Results indicated that, despite equivalent task performance between the 2 groups, children with T1D exhibited increased activation in executive control regions (e.g., dorsolateral prefrontal and supramarginal gyri; p = 0.010) and reduced suppression of activation in the posterior node of the default mode network (DMN; p = 0.006). Secondary analyses indicated associations between activation patterns and behavior and clinical disease course. Greater hyperactivation in executive control regions in the T1D group was correlated with improved task performance (as indexed by shorter response times to correct “go” trials; r = −0.36, 95% CI −0.53 to −0.16, p < 0.001) and with better parent-reported measures of executive functioning (r values < −0.29, 95% CIs −0.47 to −0.08, p-values < 0.007). Increased deficits in deactivation of the posterior DMN in the T1D group were correlated with an earlier age of T1D onset (r = −0.22, 95% CI −0.41 to −0.02, p = 0.033). Finally, exploratory analyses indicated that among children with T1D (but not control children), more severe impairments in deactivation of the DMN were associated with greater increases in hyperactivation of executive control regions (T1D: r = 0.284, 95% CI 0.08 to 0.46, p = 0.006; control: r = 0.108, 95% CI −0.16 to 0.36, p = 0.423). A limitation to this study involves glycemic effects on brain function; because blood glucose was not clamped prior to or during scanning, future studies are needed to assess the influence of acute versus chronic dysglycemia on our reported findings. In addition, the mechanisms underlying T1D-associated alterations in activation are unknown.

Conclusions

These data indicate that increased recruitment of executive control areas in pediatric T1D may act to offset diabetes-related impairments in the DMN, ultimately facilitating cognitive and behavioral performance levels that are equivalent to that of non-diabetic controls. Future studies that examine whether these patterns change as a function of improved glycemic control are warranted.

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<![CDATA[Tracking the brain in myotonic dystrophies: A 5-year longitudinal follow-up study]]> https://www.researchpad.co/article/5c8accf4d5eed0c4849903d9

Objectives

The aim of this study was to examine the natural history of brain involvement in adult-onset myotonic dystrophies type 1 and 2 (DM1, DM2).

Methods

We conducted a longitudinal observational study to examine functional and structural cerebral changes in myotonic dystrophies. We enrolled 16 adult-onset DM1 patients, 16 DM2 patients, and 17 controls. At baseline and after 5.5 ± 0.4 years participants underwent neurological, neuropsychological, and 3T-brain MRI examinations using identical study protocols that included voxel-based morphometry and diffusion tensor imaging. Data were analyzed by (i) group comparisons between patients and controls at baseline and follow-up, and (ii) group comparisons using difference maps (baseline–follow-up in each participant) to focus on disease-related effects over time.

Results

We found minor neuropsychological deficits with mild progression in DM1 more than DM2. Daytime sleepiness was restricted to DM1, whereas fatigue was present in both disease entities and stable over time. Comparing results of cross-sectional neuroimaging analyses at baseline and follow-up revealed an unchanged pattern of pronounced white matter alterations in DM1. There was mild additional gray matter reduction in DM1 at follow-up. In DM2, white matter reduction was of lesser extent, but there were some additional alterations at follow-up. Gray matter seemed unaffected in DM2. Intriguingly, longitudinal analyses using difference maps and comparing them between patients and controls did not reveal any significant differences of cerebral changes over time between patients and controls.

Conclusion

The lack of significant disease-related progression of gray and white matter involvement over a period of five years in our cohort of DM1 and DM2 patients suggests either a rather slowly progressive process or even a stable course of cerebral changes in middle-aged adult-onset patients. Being the first longitudinal neuroimaging trial in DM1 and DM2, this study provides useful additional information regarding the natural history of brain involvement.

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<![CDATA[Adaptive multi-degree of freedom Brain Computer Interface using online feedback: Towards novel methods and metrics of mutual adaptation between humans and machines for BCI]]> https://www.researchpad.co/article/5c89771ad5eed0c4847d2469

This paper proposes a novel adaptive online-feedback methodology for Brain Computer Interfaces (BCI). The method uses ElectroEncephaloGraphic (EEG) signals and combines motor with speech imagery to allow for tasks that involve multiple degrees of freedom (DoF). The main approach utilizes the covariance matrix descriptor as feature, and the Relevance Vector Machines (RVM) classifier. The novel contributions include, (1) a new method to select representative data to update the RVM model, and (2) an online classifier which is an adaptively-weighted mixture of RVM models to account for the users’ exploration and exploitation processes during the learning phase. Instead of evaluating the subjects’ performance solely based on the conventional metric of accuracy, we analyze their skill’s improvement based on 3 other criteria, namely the confusion matrix’s quality, the separability of the data, and their instability. After collecting calibration data for 8 minutes in the first run, 8 participants were able to control the system while receiving visual feedback in the subsequent runs. We observed significant improvement in all subjects, including two of them who fell into the BCI illiteracy category. Our proposed BCI system complements the existing approaches in several aspects. First, the co-adaptation paradigm not only adapts the classifiers, but also allows the users to actively discover their own way to use the BCI through their exploration and exploitation processes. Furthermore, the auto-calibrating system can be used immediately with a minimal calibration time. Finally, this is the first work to combine motor and speech imagery in an online feedback experiment to provide multiple DoF for BCI control applications.

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<![CDATA[Cyborg groups enhance face recognition in crowded environments]]> https://www.researchpad.co/article/5c89773bd5eed0c4847d2790

Recognizing a person in a crowded environment is a challenging, yet critical, visual-search task for both humans and machine-vision algorithms. This paper explores the possibility of combining a residual neural network (ResNet), brain-computer interfaces (BCIs) and human participants to create “cyborgs” that improve decision making. Human participants and a ResNet undertook the same face-recognition experiment. BCIs were used to decode the decision confidence of humans from their EEG signals. Different types of cyborg groups were created, including either only humans (with or without the BCI) or groups of humans and the ResNet. Cyborg groups decisions were obtained weighing individual decisions by confidence estimates. Results show that groups of cyborgs are significantly more accurate (up to 35%) than the ResNet, the average participant, and equally-sized groups of humans not assisted by technology. These results suggest that melding humans, BCI, and machine-vision technology could significantly improve decision-making in realistic scenarios.

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<![CDATA[A comparison study of anxiety in children undergoing brain MRI vs adults undergoing brain MRI vs children undergoing an electroencephalogram]]> https://www.researchpad.co/article/5c9902cbd5eed0c484b985cc

Background

Magnetic resonance imaging (MRI) of the brain in children and adolescents is a well-established method in both clinical practice and in neuroscientific research. This practice is sometimes viewed critically, as MRI scans might expose minors (e.g. through scan-associated fears) to more than the legally permissible “minimal burden”. While there is evidence that a significant portion of adults undergoing brain MRI scans experience anxiety, data on anxiety in children and adolescents undergoing brain MRI scans is rare. This study therefore aimed to examine the prevalence and level of anxiety in children and adolescents who had MRI scans of the brain, and to compare the results to adults undergoing brain MRI scans, and to children and adolescents undergoing electroencephalography (EEG; which is usually regarded a “minimal burden”).

Method

Participants were 57 children and adolescents who had a brain MRI scan (MRI-C; mean age 12.9 years), 28 adults who had a brain MRI scan (MRI-A; mean age 43.7 years), and 66 children and adolescents undergoing EEG (EEG-C; mean age 12.9 years). Anxiety was assessed on the subjective (situational anxiety) and on the physiological level (arousal), before and after the respective examination.

Results

More than 98% of children and adolescents reported no or only minimal fear during the MRI scan. Both pre- and post-examination, the MRI-C and the MRI-A groups did not differ significantly with respect to situational anxiety (p = 0.262 and p = 0.374, respectively), and to physiological arousal (p = 0.050, p = 0.472). Between the MRI-C and the EEG-C group, there were also no significant differences in terms of situational anxiety (p = 0.525, p = 0.875), or physiological arousal (p = 0.535, p = 0.189). Prior MRI experience did not significantly influence subjective or physiological anxiety parameters.

Conclusions

In this study, children and adolescents undergoing a brain MRI scan did not experience significantly more anxiety than those undergoing an EEG, or adults undergoing MRI scanning. Therefore, a general exclusion of minors from MRI research studies does not appear reasonable.

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<![CDATA[Electrophysiological correlates of concept type shifts]]> https://www.researchpad.co/article/5c8823b9d5eed0c484638ef4

A recent semantic theory of nominal concepts by Löbner [1] posits that–due to their inherent uniqueness and relationality properties–noun concepts can be classified into four concept types (CTs): sortal, individual, relational, functional. For sortal nouns the default determination is indefinite (a stone), for individual nouns it is definite (the sun), for relational and functional nouns it is possessive (his ear, his father). Incongruent determination leads to a concept type shift: his father (functional concept: unique, relational)–a father (sortal concept: non-unique, non-relational). Behavioral studies on CT shifts have demonstrated a CT congruence effect, with congruent determiners triggering faster lexical decision times on the subsequent noun than incongruent ones [2, 3]. The present ERP study investigated electrophysiological correlates of congruent and incongruent determination in German noun phrases, and specifically, whether the CT congruence effect could be indexed by such classic ERP components as N400, LAN or P600. If incongruent determination affects the lexical retrieval or semantic integration of the noun, it should be reflected in the amplitude of the N400 component. If, however, CT congruence is processed by the same neuronal mechanisms that underlie morphosyntactic processing, incongruent determination should trigger LAN or/and P600. These predictions were tested in two ERP studies. In Experiment 1, participants just listened to noun phrases. In Experiment 2, they performed a wellformedness judgment task. The processing of (in)congruent CTs (his sun vs. the sun) was compared to the processing of morphosyntactic and semantic violations in control conditions. Whereas the control conditions elicited classic electrophysiological violation responses (N400, LAN, & P600), CT-incongruences did not. Instead they showed novel concept-type specific response patterns. The absence of the classic ERP components suggests that CT-incongruent determination is not perceived as a violation of the semantic or morphosyntactic structure of the noun phrase.

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<![CDATA[Introducing chaotic codes for the modulation of code modulated visual evoked potentials (c-VEP) in normal adults for visual fatigue reduction]]> https://www.researchpad.co/article/5c897745d5eed0c4847d28a9

Code modulated Visual Evoked Potentials (c-VEP) based BCI studies usually employ m-sequences as a modulating codes for their broadband spectrum and correlation property. However, subjective fatigue of the presented codes has been a problem. In this study, we introduce chaotic codes containing broadband spectrum and similar correlation property. We examined whether the introduced chaotic codes could be decoded from EEG signals and also compared the subjective fatigue level with m-sequence codes in normal subjects. We generated chaotic code from one-dimensional logistic map and used it with conventional 31-bit m-sequence code. In a c-VEP based study in normal subjects (n = 44, 21 females) we presented these codes visually and recorded EEG signals from the corresponding codes for their four lagged versions. Canonical correlation analysis (CCA) and spatiotemporal beamforming (STB) methods were used for target identification and comparison of responses. Additionally, we compared the subjective self-declared fatigue using VAS caused by presented m-sequence and chaotic codes. The introduced chaotic code was decoded from EEG responses with CCA and STB methods. The maximum total accuracy values of 93.6 ± 11.9% and 94 ± 14.4% were achieved with STB method for chaotic and m-sequence codes for all subjects respectively. The achieved accuracies in all subjects were not significantly different in m-sequence and chaotic codes. There was significant reduction in subjective fatigue caused by chaotic codes compared to the m-sequence codes. Both m-sequence and chaotic codes were similar in their accuracies as evaluated by CCA and STB methods. The chaotic codes significantly reduced subjective fatigue compared to the m-sequence codes.

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<![CDATA[Population dynamics and entrainment of basal ganglia pacemakers are shaped by their dendritic arbors]]> https://www.researchpad.co/article/5c65dcf2d5eed0c484dec628

The theory of phase oscillators is an essential tool for understanding population dynamics of pacemaking neurons. GABAergic pacemakers in the substantia nigra pars reticulata (SNr), a main basal ganglia (BG) output nucleus, receive inputs from the direct and indirect pathways at distal and proximal regions of their dendritic arbors, respectively. We combine theory, optogenetic stimulation and electrophysiological experiments in acute brain slices to ask how dendritic properties impact the propensity of the various inputs, arriving at different locations along the dendrite, to recruit or entrain SNr pacemakers. By combining cable theory with sinusoidally-modulated optogenetic activation of either proximal somatodendritic regions or the entire somatodendritic arbor of SNr neurons, we construct an analytical model that accurately fits the empirically measured somatic current response to inputs arising from illuminating the soma and various portions of the dendritic field. We show that the extent of the dendritic tree that is illuminated generates measurable and systematic differences in the pacemaker’s phase response curve (PRC), causing a shift in its peak. Finally, we show that the divergent PRCs correctly predict differences in two major features of the collective dynamics of SNr neurons: the fidelity of population responses to sudden step-like changes in inputs; and the phase latency at which SNr neurons are entrained by rhythmic stimulation, which can occur in the BG under both physiological and pathophysiological conditions. Our novel method generates measurable and physiologically meaningful spatial effects, and provides the first empirical demonstration of how the collective responses of SNr pacemakers are determined by the transmission properties of their dendrites. SNr dendrites may serve to delay distal striatal inputs so that they impinge on the spike initiation zone simultaneously with pallidal and subthalamic inputs in order to guarantee a fair competition between the influence of the monosynaptic direct- and polysynaptic indirect pathways.

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<![CDATA[Noninvasive vagus nerve stimulation alters neural response and physiological autonomic tone to noxious thermal challenge]]> https://www.researchpad.co/article/5c6dca21d5eed0c48452a80d

The mechanisms by which noninvasive vagal nerve stimulation (nVNS) affect central and peripheral neural circuits that subserve pain and autonomic physiology are not clear, and thus remain an area of intense investigation. Effects of nVNS vs sham stimulation on subject responses to five noxious thermal stimuli (applied to left lower extremity), were measured in 30 healthy subjects (n = 15 sham and n = 15 nVNS), with fMRI and physiological galvanic skin response (GSR). With repeated noxious thermal stimuli a group × time analysis showed a significantly (p < .001) decreased response with nVNS in bilateral primary and secondary somatosensory cortices (SI and SII), left dorsoposterior insular cortex, bilateral paracentral lobule, bilateral medial dorsal thalamus, right anterior cingulate cortex, and right orbitofrontal cortex. A group × time × GSR analysis showed a significantly decreased response in the nVNS group (p < .0005) bilaterally in SI, lower and mid medullary brainstem, and inferior occipital cortex. Finally, nVNS treatment showed decreased activity in pronociceptive brainstem nuclei (e.g. the reticular nucleus and rostral ventromedial medulla) and key autonomic integration nuclei (e.g. the rostroventrolateral medulla, nucleus ambiguous, and dorsal motor nucleus of the vagus nerve). In aggregate, noninvasive vagal nerve stimulation reduced the physiological response to noxious thermal stimuli and impacted neural circuits important for pain processing and autonomic output.

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<![CDATA[Information integration in large brain networks]]> https://www.researchpad.co/article/5c65dcadd5eed0c484dec021

An outstanding problem in neuroscience is to understand how information is integrated across the many modules of the brain. While classic information-theoretic measures have transformed our understanding of feedforward information processing in the brain’s sensory periphery, comparable measures for information flow in the massively recurrent networks of the rest of the brain have been lacking. To address this, recent work in information theory has produced a sound measure of network-wide “integrated information”, which can be estimated from time-series data. But, a computational hurdle has stymied attempts to measure large-scale information integration in real brains. Specifically, the measurement of integrated information involves a combinatorial search for the informational “weakest link” of a network, a process whose computation time explodes super-exponentially with network size. Here, we show that spectral clustering, applied on the correlation matrix of time-series data, provides an approximate but robust solution to the search for the informational weakest link of large networks. This reduces the computation time for integrated information in large systems from longer than the lifespan of the universe to just minutes. We evaluate this solution in brain-like systems of coupled oscillators as well as in high-density electrocortigraphy data from two macaque monkeys, and show that the informational “weakest link” of the monkey cortex splits posterior sensory areas from anterior association areas. Finally, we use our solution to provide evidence in support of the long-standing hypothesis that information integration is maximized by networks with a high global efficiency, and that modular network structures promote the segregation of information.

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<![CDATA[Motor skill learning induces brain network plasticity: A diffusion-tensor imaging study]]> https://www.researchpad.co/article/5c648cf2d5eed0c484c81b6f

Motor skills and the acquisition of brain plasticity are important topics in current research. The development of non-invasive white matter imaging technology, such as diffusion-tensor imaging and the introduction of graph theory make it possible to study the effects of learning skills on the connection patterns of brain networks. However, few studies have characterized the brain network topological features of motor skill learning, especially open skill. Given the need to interact with environmental changes in real time, we hypothesized that the brain network of high-level open-skilled athletes had higher transmission efficiency and stronger interaction in attention, visual and sensorimotor networks. We selected 21 high-level basketball players and 25 ordinary individuals as control subjects, collected their DTI data, built a network of brain structures, and used graph theory to analyze and compare the network properties of the two groups at global and regional levels. In addition, we conducted a correlation analysis on the training years of high-level athletes and brain network nodal parameters on the regional level to assess the relationship between brain network topological characteristics and skills learning. We found that on the global-level, the brain network of high-level basketball players had a shorter path length, small-worldness, and higher global efficiency. On the regional level, the brain nodes of the high-level athletes had nodal parameters that were significantly higher than those of control groups, and were mainly distributed in the visual network, the default mode network, and the attention network. The changes in brain node parameters were significantly related to the number of training years.

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<![CDATA[Enhancing activation in the right temporoparietal junction using theta-burst stimulation: Disambiguating between two hypotheses of top-down control of behavioral mimicry]]> https://www.researchpad.co/article/5c57e659d5eed0c484ef2cf5

Whereas previous research has focused on the role of the rTPJ when consciously inhibiting mimicry, we test the role of the rTPJ on mimicry within a social interaction, during which mimicking occurs nonconsciously. We wanted to determine whether higher rTPJ activation always inhibits the tendency to imitate (regardless of the context) or whether it facilitates mimicry during social interactions (when mimicking is an adaptive response). Participants received either active or sham intermittent theta-burst stimulation (iTBS: a type of stimulation that increases cortical activation) to the rTPJ. Next, we measured how much participants mimicked the hair and face touching of another person. Participants in the active stimulation condition engaged in significantly less mimicry than those in the sham stimulation condition. This finding suggests that even in a context in which mimicking is adaptive, rTPJ inhibits mimicry rather than facilitating it, supporting the hypothesis that rTPJ enhances representations of self over other regardless of the goals within a given context.

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<![CDATA[Predicting neurological recovery with Canonical Autocorrelation Embeddings]]> https://www.researchpad.co/article/5c58d654d5eed0c484031bb6

Early prediction of the potential for neurological recovery after resuscitation from cardiac arrest is difficult but important. Currently, no clinical finding or combination of findings are sufficient to accurately predict or preclude favorable recovery of comatose patients in the first 24 to 48 hours after resuscitation. Thus, life-sustaining therapy is often continued for several days in patients whose irrecoverable injury is not yet recognized. Conversely, early withdrawal of life-sustaining therapy increases mortality among patients who otherwise might have gone on to recover. In this work, we present Canonical Autocorrelation Analysis (CAA) and Canonical Autocorrelation Embeddings (CAE), novel methods suitable for identifying complex patterns in high-resolution multivariate data often collected in highly monitored clinical environments such as intensive care units. CAE embeds sets of datapoints onto a space that characterizes their latent correlation structures and allows direct comparison of these structures through the use of a distance metric. The methodology may be particularly suitable when the unit of analysis is not just an individual datapoint but a dataset, as for instance in patients for whom physiological measures are recorded over time, and where changes of correlation patterns in these datasets are informative for the task at hand.

We present a proof of concept to illustrate the potential utility of CAE by applying it to characterize electroencephalographic recordings from 80 comatose survivors of cardiac arrest, aiming to identify patients who will survive to hospital discharge with favorable functional recovery. Our results show that with very low probability of making a Type 1 error, we are able to identify 32.5% of patients who are likely to have a good neurological outcome, some of whom have otherwise unfavorable clinical characteristics. Importantly, some of these had 5% predicted chance of favorable recovery based on initial illness severity measures alone. Providing this information to support clinical decision-making could motivate the continuation of life-sustaining therapies for these patients.

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<![CDATA[Nitrogen gas produces less behavioural and neurophysiological excitation than carbon dioxide in mice undergoing euthanasia]]> https://www.researchpad.co/article/5c5ca2bcd5eed0c48441e9d5

Carbon dioxide (CO2) is one of the most commonly used gas euthanasia agents in mice, despite reports of aversion and nociception. Inert gases such as nitrogen (N2) may be a viable alternative to carbon dioxide. Here we compared behavioural and electrophysiological reactions to CO2 or N2 at either slow fill or rapid fill in C57Bl/6 mice undergoing gas euthanasia. We found that mice euthanised with CO2 increased locomotor activity compared to baseline, whereas mice exposed to N2 decreased locomotion. Furthermore, mice exposed to CO2 showed significantly more vertical jumps and freezing episodes than mice exposed to N2. We further found that CO2 exposure resulted in increased theta:delta of the EEG, a measure of excitation, whereas the N2 decreased theta:delta. Differences in responses were not oxygen-concentration dependent. Taken together, these results demonstrate that CO2 increases both behavioural and electrophysiological excitation as well as producing a fear response, whereas N2 reduces behavioural activity and central neurological depression and may be less aversive although still produces a fear response. Further studies are required to evaluate N2 as a suitable euthanasia agent for mice.

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<![CDATA[A neural hallmark of auditory implicit learning is altered in older adults]]> https://www.researchpad.co/article/5c5b5256d5eed0c4842bc694

Temporal regularities in the environment are often learned implicitly. In an auditory target-detection paradigm using EEG, Jongsma and colleagues (2006) showed that the neural response to these implicit regularities results in a reduction of the P3-N2 complex. Here, we utilized the same paradigm, this time in both young and old participants, to determine if this EEG signature of implicit learning was altered with age. Behaviorally, both groups of participants showed similar benefits for the presence of temporal regularity, with faster and more accurate responses given when the auditory targets were presented in a temporally regular vs. random pattern. In the brain, the younger adults showed the expected decrease in amplitude of this complex for regular compared to irregular trials. Older adults, in contrast, showed no difference in the amplitude of the P3-N2 complex between the irregular and regular condition. These data suggest that, although auditory implicit learning may be behaviorally spared in aging, older adults are not using the same neural substrates as younger adults to achieve this.

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