Even low alcohol concentrations affect obstacle avoidance reactions in healthy senior individuals

<p>Abstract</p> <p>Background</p> <p>Alcohol is a commonly used social drug and driving under influence is a well-established risk factor for traffic accidents<abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. To improve road safety, legal limits are set for blood alcohol concentration (BAC) and driving, usually at 0.05% (most European countries) or 0.08% (most US states, Canada and UK). In contrast, for walking there are no legal limits, yet there are numerous accounts of people stumbling and falling after drinking. Alcohol, even at these low concentrations, affects brain function and increases fall risk. An increased fall risk has been associated with impaired obstacle avoidance skills. Low level BACs are likely to affect obstacle avoidance reactions during gait, since the brain areas that are presumably involved in these reactions have been shown to be influenced by alcohol. Therefore we investigated the effect of low to moderate alcohol consumption on such reactions.</p> <p>Thirteen healthy senior individuals (mean(SD) age: 61.5(4.4) years, 9 male) were subjected to an obstacle avoidance task on a treadmill after low alcohol consumption. Fast stepping adjustments were required to successfully avoid suddenly appearing obstacles. Response times and amplitudes of the m. biceps femoris, a prime mover, as well as avoidance failure rates were assessed.</p> <p>Findings</p> <p>After the first alcoholic drink, 12 of the 13 participants already had slower responses. Without exception, all participants' biceps femoris response times were delayed after the final alcoholic drink (avg ± sd:180 ± 20 ms; <it>p </it>< 0.001) compared to when participants were sober (156 ± 16 ms). Biceps femoris response times were significantly delayed from BACs of 0.035% onwards and were strongly associated with increasing levels of BAC (<it>r </it>= 0.6; <it>p </it>< 0.001). These delays had important behavioural consequences. Chances of hitting the obstacle were doubled with increased BACs.</p> <p>Conclusions</p> <p>The present results clearly show that even with BACs considered to be safe for driving, obstacle avoidance reactions are inadequate, late, and too small. This is likely to contribute to an increased fall risk. Therefore we suggest that many of the alcohol-related falls are the result of the disruptive effects of alcohol on the online corrections of the ongoing gait pattern when walking under challenging conditions.</p

The Effects of Chronic Sleep Deprivation on Sustained Attention: A Study of Brain Dynamic Functional Connectivity

It is estimated that about 35-40% of adults in the U.S. suffer from insufficient sleep. Chronic sleep deprivation has become a prevalent phenomenon because of contemporary lifestyle and work-related factors. Sleep deprivation can reduce the capabilities and efficiency of attentional performance by impairing perception, increasing effort to maintain concentration, as well as introducing vision disturbance. Thus, it is important to understand the neural mechanisms behind how chronic sleep deprivation impairs sustained attention. In recent years, more attention has been paid to the study of the integration between anatomically distributed and functionally connected brain regions. Functional connectivity has been widely used to characterize brain functional integration, which measures the statistical dependency between neurophysiological events of the human brain. Further, evidence from recent studies has shown the non-stationary nature of brain functional connectivity, which may reveal more information about the human brain. Thus, the objective of this thesis is to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic functional connectivity. A modified spatial cueing paradigm was used to assess human sustained attention in rested wakefulness and chronic sleep deprivation conditions. Partial least squares approach was applied to distinguish brain functional connectivity for the experimental conditions. With the integration of a sliding-window approach, dynamic patterns of brain functional connectivity were identified in two experimental conditions. The brain was modeled as a series of dynamic functional networks in each experimental condition. Graph theoretic analysis was performed to investigate the dynamic properties of brain functional networks, using network measures of clustering coefficient and characteristics path length. In the chronic sleep deprivation condition, a compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed. Specifically, a highly clustered organization of brain functional networks was illustrated with a large clustering coefficient. This organization suggested that brain utilizes more connections to maintain attention in the chronic sleep deprivation condition. A smaller impact of clustering coefficient variation on characteristics path lengths indicated an ineffective adaptability of brain functional networks in the chronic sleep deprivation condition. In the rested wakefulness condition, brain functional networks showed the small-world topology in general, with the average small-world topology index larger than one. Small-world topology was identified as an optimal network structure with the balance between local information processing and global integration. Given the fluctuating values of the index over time, small-world brain networks were observed in most cases, indicating an effective adaptability of the human brain to maintain the dominance of small-world networks in the rested wakefulness condition. On the contrary, given that the average small-world topology index was smaller than one, brain functional networks generally exhibited random network structure. From the perspective of dynamic functional networks, even though there were few cases showing small-world brain networks, brain functional networks failed to maintain the dominance of small-world topology in the chronic sleep deprivation condition. In conclusion, to the best of our knowledge this thesis was the first to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic brain functional connectivity. A compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed in the chronic sleep deprivation condition. Furthermore, chronic sleep deprivation impaired sustained attention by reducing the effectiveness of brain functional networks\u27 adaptability, resulting in the disrupted dominance of small-world brain networks

Dopaminergic Modulation of a Fast Visuomotor Pathway in Parkinson\u27s Disease

Parkinson’s disease (PD) is associated with reduced dopaminergic (DA) input to the dorsal striatum (DS). This study investigated the role of DA in modulating automatic, stimulus-driven reactions by assessing contextual control of stimulus-locked responses (SLRs) in 10 PD patients off and on DA medication. The SLR is the rapid recruitment of limb muscles that drives the arm towards suddenly appearing stimuli. Participants reached away from (anti-reach) or towards (pro-reach) a target on a screen, depending on instruction appearing 500 or 1000ms before target appearance. Modulation of SLRs was assessed by comparing SLR magnitude on anti- and pro-reach trials using surface electrodes. We predicted patients would exhibit less control of the SLR while off medication, especially with only 500ms of instruction. Patients modulated the SLR less with 500ms of instruction, but there was no effect of medication state, suggesting modulation of the SLR is independent of DA input to the DS

How Acute and Chronic Alcohol Consumption Affects Brain Networks: Insights from Multimodal Neuroimaging

Background— Multimodal imaging combining 2 or more techniques is becoming increasingly important because no single imaging approach has the capacity to elucidate all clinically relevant characteristics of a network. Methods— This review highlights recent advances in multimodal neuroimaging (i.e., combined use and interpretation of data collected through magnetic resonance imaging [MRI], functional MRI, diffusion tensor imaging, positron emission tomography, magnetoencephalography, MR perfusion, and MR spectroscopy methods) that leads to a more comprehensive understanding of how acute and chronic alcohol consumption affect neural networks underlying cognition, emotion, reward processing, and drinking behavior. Results— Several innovative investigators have started utilizing multiple imaging approaches within the same individual to better understand how alcohol influences brain systems, both during intoxication and after years of chronic heavy use. Conclusions— Their findings can help identify mechanism-based therapeutic and pharmacological treatment options, and they may increase the efficacy and cost effectiveness of such treatments by predicting those at greatest risk for relapse

Discovering Motor Phenotypes in Autism Spectrum Disorder: A Cross-Syndrome Approach

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with a behavioral phenotype characterized by persistent deficits in social communication and social interaction accompanied by restricted, repetitive patterns of behaviors, interests, or activities. Currently in the US, approximately 2.5% of children have a diagnosis of ASD. The etiology of ASD is complex, however the disorder does have a strong genetic basis. Specific genetic mutations can lead to neuroanatomical and neurophysiological changes during development resulting in a behavioral phenotype that falls along the ASD spectrum and may result in a diagnosis of ASD. The severity of ASD-specific behaviors falls on a continuum and co-occurring psychiatric disorders are common – adding to the complexity of the disorder. In addition to specific gene mutations implicated in the diagnosis of ASD, specific brain regions are also implicated in ASD that are different from those observed in other common neurodevelopmental disorders – such as Attention-Deficit Hyperactivity Disorder. Studying the neuroanatomical footprint of ASD is a relatively new area of research fueled by the desire to bridge the gap between brain structure and function. Several brain regions implicated in the core social/communication deficits and repetitive behaviors associated with ASD are also involved in various aspects of motor control. These brain areas include cortical regions such as the primary motor cortex (M1), primary somatosensory cortex (S1), inferior parietal lobule (IPL), and subcortical structures that include the cerebellum and basal ganglia. These neuroanatomical findings are bolstered by several studies detailing a wide range of motor deficits in children and adults with ASD. Therefore, studying motor control may provide another means to study the neurological underpinnings of ASD. However, the meaningfulness of nearly all studies detailing motor control deficits in children with ASD is limited due to comparisons limited to a single typically developing (TD) control group. Therefore, the specificity of motor deficits in children with ASD is not well understood since intellectual and behavioral deficits – not specific to children with ASD – may also contribute to the observed motor deficits between children with ASD and TD controls. To overcome this limitation, the current dissertation project employs a cross-syndrome design that includes two additional clinical control groups of children with Fetal Alcohol Spectrum Disorder (FASD) and Attention-Deficit Hyperactivity Disorder (ADHD) with similar intellectual and behavioral impairments as children with ASD. Utilizing this novel approach, motor deficits specific to children with ASD may be identified, allowing for the generation of new hypotheses about the neurological underpinnings of ASD. To bridge the gap between neuroscience and motor control in the study of ASD it is important to understand what findings from both fields of research reveal about ASD. Therefore, an extensive literature review (Chapter 1) is warranted to orient the reader to what is currently known about the underlying neurology and motor deficits associated with ASD. To detail the progression of knowledge about the neuroanatomical deficits associated with ASD, the literature review will funnel from general to more specific findings from animal-models of ASD and human patient studies. Following the neuroanatomical review, a detailed overview of findings from motor control studies on individuals with ASD will be reviewed and discussed in relation to the key neuroanatomical findings in children with ASD. The overall purpose of this dissertation was to identify motor features specifically impaired in children with ASD using a cross-syndrome design. This dissertation explores the three different motor tasks that previous studies have shown to be impaired in children with ASD compared to TD controls. To examine the specificity of previously observed deficits, motor features were extracted from: (1) a precision-grip force tracking task; (2) a postural maintenance task; and (3) a manual dexterity task and compared between children with ASD and children with FASD, ADHD, and TD controls. The first study (Chapter 2) examines group differences in isometric precision-grip static force output features in children with ASD, FASD, ADHD, and TD controls. In this study, grip-force output was maintained at 15% of maximal voluntary contraction (MVC) and no group differences were observed for: (1) relative force accuracy; (2) relative variability; (3) complexity; or (4) frequency structure of the force signal. However, the relative proportion of low frequency oscillations (0-1 Hz) was significantly associated with force accuracy, variability, and complexity in the ASD-group only. In the second study (Chapter 3), dynamic force control features were examined using a ramp-up (0-25% MVC) and ramp-down (25-0% MVC) task. Compared to the TD group, the children with ASD demonstrated significantly: (1) greater relative error during ramp-up and ramp-down; (2) lower ramp-up force-complexity; and (3) greater relative error during transition between ramp-up and ramp-down phases. In the third study (Chapter 4), postural sway features during quiet stance and unipedal stance time were examined. Compared to the FASD, ADHD, and TD groups, the children with ASD demonstrated significantly: (1) greater postural sway area and (2) mediolateral (ML) sway magnitude. Furthermore, children with ASD group demonstrated significantly greater anteroposterior (AP) sway velocity between the TD and FASD groups, and lower ML sway complexity compared to the FASD group only. For unipedal stance, TD children had greater stance times compared to all clinical groups. However, postural sway area was associated with unipedal stance times only in the ASD group. In the fourth study (Chapter 5), manual dexterity of the dominant and non-dominant was examined. Children in the ASD group showed significantly: (1) worse dominant hand dexterity compared to TD controls and (2) worse non-dominant hand dexterity compared to children in the FASD and TD groups. Finally, hand performance asymmetry was significantly lower children with FASD than children without FASD. In summary, this dissertation uses a cross-syndrome approach to identify motor features specifically impaired in children with ASD. Throughout the dissertation, several ASD-specific motor features were identified that align with current knowledge of neuroanatomical deficits associated with ASD. Furthermore, identification of ASD-specific motor features using biomechanics techniques may provide a means to quantitatively study the effects of various pharmacological, behavioral, and non-invasive brain stimulation interventions in clinical settings. Therefore, studying the motor system in children with ASD may have clinical importance due to challenges in quantifying changes in behaviors associated with ASD. In this dissertation, several ASD-specific motor features are identified that can be measured quickly in clinical settings. Further research is required to examine the clinical utility of quantitative motor testing in children with ASD

Contributions of the striatum to learning, motivation, and performance: an associative account

It has long been recognized that the striatum is composed of distinct functional sub-units that are part of multiple cortico-striatal-thalamic circuits. Contemporary research has focused on the contribution of striatal sub-regions to three main phenomena: learning of associations between stimuli, actions and rewards; selection between competing response alternatives; and motivational modulation of motor behavior. Recent proposals have argued for a functional division of the striatum along these lines, attributing, for example, learning to one region and performance to another. Here, we consider empirical data from human and animal studies, as well as theoretical notions from both the psychological and computational literatures, and conclude that striatal sub-regions instead differ most clearly in terms of the associations being encoded in each region