897 resultados para Sensory modifier
Resumo:
Patients with idiopathic small fibre neuropathy (ISFN) have been shown to have significant intraepidermal nerve fibre loss and an increased prevalence of impaired glucose tolerance (IGT). It has been suggested that the dysglycemia of IGT and additional metabolic risk factors may contribute to small nerve fibre damage in these patients. Twenty-five patients with ISFN and 12 aged-matched control subjects underwent a detailed evaluation of neuropathic symptoms, neurological deficits (Neuropathy deficit score (NDS); Nerve Conduction Studies (NCS); Quantitative Sensory Testing (QST) and Corneal Confocal Microscopy (CCM)) to quantify small nerve fibre pathology. Eight (32%) patients had IGT. Whilst all patients with ISFN had significant neuropathic symptoms, NDS, NCS and QST except for warm thresholds were normal. Corneal sensitivity was reduced and CCM demonstrated a significant reduction in corneal nerve fibre density (NFD) (Pb0.0001), nerve branch density (NBD) (Pb0.0001), nerve fibre length (NFL) (Pb0.0001) and an increase in nerve fibre tortuosity (NFT) (Pb0.0001). However these parameters did not differ between ISFN patients with and without IGT, nor did they correlate with BMI, lipids and blood pressure. Corneal confocal microscopy provides a sensitive non-invasive means to detect small nerve fibre damage in patients with ISFN and metabolic abnormalities do not relate to nerve damage.
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Study Design: Case Study Series.---------- Introduction: Restriction of forearm rotation may be required for effective management and rehabilitation of the upper limb after trauma.---------- Purpose of the Study: To compare the effectiveness of four splints in restricting forearm rotation.---------- Methods: Muenster, Sugartong, antipronation distal radioulnar joint (DRUJ), and standard wrist splints were fabricated for five healthy participants. Active range of motion (AROM) in forearm pronation and supination was measured with a goniometer for each splint, at the initial point of sensory feedback and during exertion of maximal force.---------- Results: Repeated-measures analysis of variance indicated significant differences between splints for all four AROM measures. Post hoc paired t-tests showed that the Sugartong splint was significantly more restrictive in pronation than the Muenster splint. The antipronation DRUJ splint provided significantly greater restriction in pronation than the standard wrist splint. No splints immobilized the forearm completely.---------- Conclusions: The Sugartong splint is recommended for maximal restriction in pronation, but individual patient characteristics require consideration in splint choice.
Resumo:
Drivers are known to be optimistic about their risk of crash involvement, believing that they are less likely to be involved in a crash than other drivers. However, little comparative research has been conducted among other road users. In addition, optimism about crash risk is conceptualised as applying only to an individual’s assessment of his or her personal risk of crash involvement. The possibility that the self-serving nature of optimism about safety might be generalised to the group-level as a cyclist or a pedestrian, i.e., becoming group-serving rather than self-serving, has been overlooked in relation to road safety. This study analysed a subset of data collected as part of a larger research project on the visibility of pedestrians, cyclists and road workers, focusing on a set of questionnaire items administered to 406 pedestrians, 838 cyclists and 622 drivers. The items related to safety in various scenarios involving drivers, pedestrians and cyclists, allowing predictions to be derived about group differences in agreement with items based on the assumption that the results would exhibit group-serving bias. Analysis of the responses indicated that specific hypotheses about group-serving interpretations of safety and responsibility were supported in 22 of the 26 comparisons. When the nine comparisons relevant to low lighting conditions were considered separately, seven were found to be supported. The findings of the research have implications for public education and for the likely acceptance of messages which are inconsistent with current assumptions and expectations of pedestrians and cyclists. They also suggest that research into group-serving interpretations of safety, even for temporary roles rather than enduring groups, could be fruitful. Further, there is an implication that gains in safety can be made by better educating road users about the limitations of their visibility and the ramifications of this for their own road safety, particularly in low light.
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Fatigue has been recognised as the primary contributing factor in approximately 15% of all fatal road crashes in Australia. To develop effective countermeasures for managing fatigue, this study investigates why drivers continue to drive when sleepy, and driver perceptions and behaviours in regards to countermeasures. Based on responses from 305 Australian drivers, it was identified that the major reasons why these participants continued to drive when sleepy were: wanting to get to their destination; being close to home; and time factors. Participants’ perceptions and use of 18 fatigue countermeasures were investigated. It was found that participants perceived the safest strategies, including stopping and sleeping, swapping drivers and stopping for a quick nap, to be the most effective countermeasures. However, it appeared that their knowledge of safe countermeasures did not translate into their use of these strategies. For example, although the drivers perceived stopping for a quick nap to be an effective countermeasure, they reported more frequent use of less safe methods such as stopping to eat or drink and winding down the window. This finding suggests that, while practitioners should continue educating drivers, they may need a greater focus on motivating drivers to implement safe fatigue countermeasures.
Resumo:
A number of advanced driver assistance systems (ADAS) are currently being released on the market, providing safety functions to the drivers such as collision avoidance, adaptive cruise control or enhanced night-vision. These systems however are inherently limited by their sensory range: they cannot gather information from outside this range, also called their “perceptive horizon”. Cooperative systems are a developing research avenue that aims at providing extended safety and comfort functionalities by introducing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications to the road actors. This paper presents the problematic of cooperative systems, their advantages and contributions to road safety and exposes some limitations related to market penetration, sensors accuracy and communications scalability. It explains the issues of how to implement extended perception, a central contribution of cooperative systems. The initial steps of an evaluation of data fusion architectures for extended perception are exposed.
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Level crossing crashes have been shown to result in enormous human and financial cost to society. According to the Australian Transport Safety Bureau (ATSB) [5] a total of 632 Railway Level crossing (RLX) collisions, between trains and road vehicles, occurred in Australia between 2001 and June 2009. The cost of RLX collisions runs into the tens of millions of dollars each year in Australia [6]. In addition, loss of life and injury are commonplace in instances where collisions occur. Based on estimates that 40% of rail related fatalities occur at level crossings [12], it is estimated that 142 deaths between 2001 and June 2009 occurred at RLX. The aim of this paper is to (i) summarise crash patterns in Australia, (ii) review existing international ITS interventions to improve level crossing and (iii) highlights open human factors research related issues. Human factors (e.g., driver error, lapses or violations) have been evidenced as a significant contributing factor in RLX collisions, with drivers of road vehicles particularly responsible for many collisions. Unintentional errors have been found to contribute to 46% of RLX collisions [6] and appear to be far more commonplace than deliberate violations. Humans have been found to be inherently inadequate at using the sensory information available to them to facilitate safe decision-making at RLX and tend to underestimate the speed of approaching large objects due to the non-linear increases in perceived size [6]. Collisions resulting from misjudgements of train approach speed and distance are common [20]. Thus, a fundamental goal for improved RLX safety is the provision of sufficient contextual information to road vehicle drivers to facilitate safe decision-making regarding crossing behaviours.
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The human knee acts as a sophisticated shock absorber during landing movements. The ability of the knee to perform this function in the real world is remarkable given that the context of the landing movement may vary widely between performances. For this reason, humans must be capable of rapidly adjusting the mechanical properties of the knee under impact load in order to satisfy many competing demands. However, the processes involved in regulating these properties in response to changing constraints remain poorly understood. In particular, the effects of muscle fatigue on knee function during step landing are yet to be fully explored. Fatigue of the knee muscles is significant for 2 reasons. First, it is thought to have detrimental effects on the ability of the knee to act as a shock absorber and is considered a risk factor for knee injury. Second, fatigue of knee muscles provides a unique opportunity to examine the mechanisms by which healthy individuals alter knee function. A review of the literature revealed that the effect of fatigue on knee function during landing has been assessed by comparing pre and postfatigue measurements, with fatigue induced by a voluntary exercise protocol. The information is limited by inconsistent results with key measures, such as knee stiffness, showing varying results following fatigue, including increased stiffness, decreased stiffness or failure to detect any change in some experiments. Further consideration of the literature questions the validity of the models used to induce and measure fatigue, as well as the pre-post study design, which may explain the lack of consensus in the results. These limitations cast doubt on the usefulness of the available information and identify a need to investigate alternative approaches. Based on the results of this review, the aims of this thesis were to: • evaluate the methodological procedures used in validation of a fatigue model • investigate the adaptation and regulation of post-impact knee mechanics during repeated step landings • use this new information to test the effects of fatigue on knee function during a step-landing task. To address the aims of the thesis, 3 related experiments were conducted that collected kinetic, kinematic and electromyographic data from 3 separate samples of healthy male participants. The methodologies involved optoelectronic motion capture (VICON), isokinetic dynamometry (System3 Pro, BIODEX) and wireless surface electromyography (Zerowire, Aurion, Italy). Fatigue indicators and knee function measures used in each experiment were derived from the data. Study 1 compared the validity and reliability of repetitive stepping and isokinetic contractions with respect to fatigue of the quadriceps and hamstrings. Fifteen participants performed 50 repetitions of each exercise twice in randomised order, over 4 sessions. Sessions were separated by a minimum of 1 week’s rest, to ensure full recovery. Validity and reliability depended on a complex interaction between the exercise protocol, the fatigue indicator, the individual and the muscle of interest. Nevertheless, differences between exercise protocols indicated that stepping was less effective in eliciting valid and reliable changes in peak power and spectral compression, compared with isokinetic exercise. A key finding was that fatigue progressed in a biphasic pattern during both exercises. The point separating the 2 phases, known as the transition point, demonstrated superior between-test reliability during the isokinetic protocol, compared with stepping. However, a correction factor should be used to accurately apply this technique to the study of fatigue during landing. Study 2 examined alterations in knee function during repeated landings, with a different sample (N =12) performing 60 consecutive step landing trials. Each landing trial was separated by 1-minute rest periods. The results provided new information in relation to the pre-post study design in the context of detecting adjustments in knee function during landing. First, participants significantly increased or decreased pre-impact muscle activity or post-impact mechanics despite environmental and task constraints remaining unchanged. This is the 1st study to demonstrate this effect in healthy individuals without external feedback on performance. Second, single-subject analysis was more effective in detecting alterations in knee function compared to group-level analysis. Finally, repeated landing trials did not reduce inter-trial variability of knee function in some participants, contrary to assumptions underpinning previous studies. The results of studies 1 and 2 were used to modify the design of Study 3 relative to previous research. These alterations included a modified isokinetic fatigue protocol, multiple pre-fatigue measurements and singlesubject analysis to detect fatigue-related changes in knee function. The study design incorporated new analytical approaches to investigate fatiguerelated alterations in knee function during landing. Participants (N = 16) were measured during multiple pre-fatigue baseline trial blocks prior to the fatigue model. A final block of landing trials was recorded once the participant met the operational fatigue definition that was identified in Study 1. The analysis revealed that the effects of fatigue in this context are heavily dependent on the compensatory response of the individual. A continuum of responses was observed within the sample for each knee function measure. Overall, preimpact preparation and post-impact mechanics of the knee were altered with highly individualised patterns. Moreover, participants used a range of active or passive pre-impact strategies to adapt post-impact mechanics in response to quadriceps fatigue. The unique patterns identified in the data represented an optimisation of knee function based on priorities of the individual. The findings of these studies explain the lack of consensus within the literature regarding the effects of fatigue on knee function during landing. First, functional fatigue protocols lack validity in inducing fatigue-related changes in mechanical output and spectral compression of surface electromyography (sEMG) signals, compared with isokinetic exercise. Second, fatigue-related changes in knee function during landing are confounded by inter-individual variation, which limits the sensitivity of group-level analysis. By addressing these limitations, the 3rd study demonstrated the efficacies of new experimental and analytical approaches to observe fatigue-related alterations in knee function during landing. Consequently, this thesis provides new perspectives into the effects of fatigue in knee function during landing. In conclusion: • The effects of fatigue on knee function during landing depend on the response of the individual, with considerable variation present between study participants, despite similar physical characteristics. • In healthy males, adaptation of pre-impact muscle activity and postimpact knee mechanics is unique to the individual and reflects their own optimisation of demands such as energy expenditure, joint stability, sensory information and loading of knee structures. • The results of these studies should guide future exploration of adaptations in knee function to fatigue. However, research in this area should continue with reduced emphasis on the directional response of the population and a greater focus on individual adaptations of knee function.
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OBJECTIVE: The accurate quantification of human diabetic neuropathy is important to define at-risk patients, anticipate deterioration, and assess new therapies. ---------- RESEARCH DESIGN AND METHODS: A total of 101 diabetic patients and 17 age-matched control subjects underwent neurological evaluation, neurophysiology tests, quantitative sensory testing, and evaluation of corneal sensation and corneal nerve morphology using corneal confocal microscopy (CCM). ---------- RESULTS: Corneal sensation decreased significantly (P = 0.0001) with increasing neuropathic severity and correlated with the neuropathy disability score (NDS) (r = 0.441, P < 0.0001). Corneal nerve fiber density (NFD) (P < 0.0001), nerve fiber length (NFL), (P < 0.0001), and nerve branch density (NBD) (P < 0.0001) decreased significantly with increasing neuropathic severity and correlated with NDS (NFD r = −0.475, P < 0.0001; NBD r = −0.511, P < 0.0001; and NFL r = −0.581, P < 0.0001). NBD and NFL demonstrated a significant and progressive reduction with worsening heat pain thresholds (P = 0.01). Receiver operating characteristic curve analysis for the diagnosis of neuropathy (NDS >3) defined an NFD of <27.8/mm2 with a sensitivity of 0.82 (95% CI 0.68–0.92) and specificity of 0.52 (0.40–0.64) and for detecting patients at risk of foot ulceration (NDS >6) defined a NFD cutoff of <20.8/mm2 with a sensitivity of 0.71 (0.42–0.92) and specificity of 0.64 (0.54–0.74). ---------- CONCLUSIONS: CCM is a noninvasive clinical technique that may be used to detect early nerve damage and stratify diabetic patients with increasing neuropathic severity. Established diabetic neuropathy leads to pain and foot ulceration. Detecting neuropathy early may allow intervention with treatments to slow or reverse this condition (1). Recent studies suggested that small unmyelinated C-fibers are damaged early in diabetic neuropathy (2–4) but can only be detected using invasive procedures such as sural nerve biopsy (4,5) or skin-punch biopsy (6–8). Our studies have shown that corneal confocal microscopy (CCM) can identify early small nerve fiber damage and accurately quantify the severity of diabetic neuropathy (9–11). We have also shown that CCM relates to intraepidermal nerve fiber loss (12) and a reduction in corneal sensitivity (13) and detects early nerve fiber regeneration after pancreas transplantation (14). Recently we have also shown that CCM detects nerve fiber damage in patients with Fabry disease (15) and idiopathic small fiber neuropathy (16) when results of electrophysiology tests and quantitative sensory testing (QST) are normal. In this study we assessed corneal sensitivity and corneal nerve morphology using CCM in diabetic patients stratified for the severity of diabetic neuropathy using neurological evaluation, electrophysiology tests, and QST. This enabled us to compare CCM and corneal esthesiometry with established tests of diabetic neuropathy and define their sensitivity and specificity to detect diabetic patients with early neuropathy and those at risk of foot ulceration.
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To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments.
Resumo:
Objective: To investigate how age-related declines in vision (particularly contrast sensitivity), simulated using cataract-goggles and low-contrast stimuli, influence the accuracy and speed of cognitive test performance in older adults. An additional aim was to investigate whether declines in vision differentially affect secondary more than primary memory. Method: Using a fully within-subjects design, 50 older drivers aged 66-87 years completed two tests of cognitive performance - letter matching (perceptual speed) and symbol recall (short-term memory) - under different viewing conditions that degraded visual input (low-contrast stimuli, cataract-goggles, and low-contrast stimuli combined with cataract-goggles, compared with normal viewing). However, presentation time was also manipulated for letter matching. Visual function, as measured using standard charts, was taken into account in statistical analyses. Results: Accuracy and speed for cognitive tasks were significantly impaired when visual input was degraded. Furthermore, cognitive performance was positively associated with contrast sensitivity. Presentation time did not influence cognitive performance, and visual gradation did not differentially influence primary and secondary memory. Conclusion: Age-related declines in visual function can impact on the accuracy and speed of cognitive performance, and therefore the cognitive abilities of older adults may be underestimated in neuropsychological testing. It is thus critical that visual function be assessed prior to testing, and that stimuli be adapted to older adults' sensory capabilities (e.g., by maximising stimuli contrast).
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The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.
Resumo:
Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.
Resumo:
Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.
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Participatory sensing enables collection, processing, dissemination and analysis of environmental sensory data by ordinary citizens, through mobile devices. Researchers have recognized the potential of participatory sensing and attempted applying it to many areas. However, participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data quality has become a significant issue. This study proposes using reputation management to classify the gathered data and provide useful information for campaign organizers and data analysts to facilitate their decisions.
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The relationship between neuronal acuity and behavioral performance was assessed in the barn owl (Tyto alba), a nocturnal raptor renowned for its ability to localize sounds and for the topographic representation of auditory space found in the midbrain. We measured discrimination of sound-source separation using a newly developed procedure involving the habituation and recovery of the pupillary dilation response. The smallest discriminable change of source location was found to be about two times finer in azimuth than in elevation. Recordings from neurons in its midbrain space map revealed that their spatial tuning, like the spatial discrimination behavior, was also better in azimuth than in elevation by a factor of about two. Because the PDR behavioral assay is mediated by the same circuitry whether discrimination is assessed in azimuth or in elevation, this difference in vertical and horizontal acuity is likely to reflect a true difference in sensory resolution, without additional confounding effects of differences in motor performance in the two dimensions. Our results, therefore, are consistent with the hypothesis that the acuity of the midbrain space map determines auditory spatial discrimination.