Temporal and spatial gait characteristics of transfemoral amputees fitted with osseointegrated fixation: preliminary data

The conventional method of attachment of prosthesis involves on a socket. A new method relying on osseointegrated fixation is emerging. It has significant prosthetic benefits. Only a few studies demonstrated the biomechanical benefits. The ultimate aim of this study was to characterise the functional outcome of transfemoral amputees fitted with osseointegrated fixation, which can be assess through temporal and spatial gait characteristics. The specific objective of this preliminary study was to present the key temporal and spatial gait characteristics.

Polysynaptic potentials within the lateral amygdala networks as indicators of reverberatory activity

Synaptic plasticity in the lateral amygdala (LA) may underlie auditory fear conditioning. Hebb postulated that sustained activity in reverberating cellular ensembles can facilitate temporal coincidence detection. Our anatomical data show that LA neurons have extensive local axon collaterals that are topographically organized and that could provide the anatomical basis for reverberatory activity...

Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging

Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

Temporal and environmental influences on the vocal behaviour of a nocturnal bird

Temporal and environmental variation in vocal activity can provide information on avian behaviour and call function not available to short-term experimental studies. Intersexual differences in this variation can provide insight into selection effects. Yet factors influencing vocal behaviour have not been assessed in many birds, even those monitored by acoustic methods. This applies to the New Zealand kiwi (Apterygidae), for which call censuses are used extensively in conservation monitoring, yet which have poorly understood acoustic ecology. We investigated little spotted kiwi Apteryx owenii vocal behaviour over 3 yr, measuring influences on vocal activity in both sexes from time of night, season, weather conditions and lunar cycle. We tested hypotheses that call rate variation reflects call function, foraging efficiency, historic predation risk and variability in sound transmission, and that there are inter-sexual differences in call function. Significant seasonal variation showed that vocalisations were important in kiwi reproduction, and inter-sexual synchronisation of call rates indicated that contact, pair-bonding or resource defence were key functions. All weather variables significantly affected call rates, with elevated calling during increased humidity and ground moisture indicating a relation between vocal activity and foraging conditions. A significant decrease in calling activity on cloudy nights, combined with no moonlight effect, suggests an impact of light pollution in this species. These influences on vocal activity provide insight into kiwi call function, have direct consequences for conservation monitoring of kiwi, and have wider implications in understanding vocal behaviour in a range of nocturnal birds

Oscillatory brain activity in memory disorders

Neuronal oscillations are thought to underlie interactions between distinct brain regions required for normal memory functioning. This study aimed at elucidating the neuronal basis of memory abnormalities in neurodegenerative disorders. Magnetoencephalography (MEG) was used to measure oscillatory brain signals in patients with Alzheimer s disease (AD), a neurodegenerative disease causing progressive cognitive decline, and mild cognitive impairment (MCI), a disorder characterized by mild but clinically significant complaints of memory loss without apparent impairment in other cognitive domains. Furthermore, to help interpret our AD/MCI results and to develop more powerful oscillatory MEG paradigms for clinical memory studies, oscillatory neuronal activity underlying declarative memory, the function which is afflicted first in both AD and MCI, was investigated in a group of healthy subjects. An increased temporal-lobe contribution coinciding with parieto-occipital deficits in oscillatory activity was observed in AD patients: sources in the 6 12.5 Hz range were significantly stronger in the parieto-occipital and significantly weaker in the right temporal region in AD patients, as compared to MCI patients and healthy elderly subjects. Further, the auditory steady-state response, thought to represent both evoked and induced activity, was enhanced in AD patients, as compared to controls, possibly reflecting decreased inhibition in auditory processing and deficits in adaptation to repetitive stimulation with low relevance. Finally, the methodological study revealed that successful declarative encoding and retrieval is associated with increases in occipital gamma and right hemisphere theta power in healthy unmedicated subjects. This result suggests that investigation of neuronal oscillations during cognitive performance could potentially be used to investigate declarative memory deficits in AD patients. Taken together, the present results provide an insight on the role of brain oscillatory activity in memory function and memory disorders.

Unpacking the perceived opportunity to misbehave: The influence of spatio-temporal and social dimensions on consumer misbehavior

Purpose This study aims to use opportunity as a theoretical lens to investigate how the spatio-temporal and social dimensions of the consumption environment create perceived opportunities for consumers to misbehave. Design/methodology/approach Drawing on routine activity theory and social impact theory, the authors use two experiments to demonstrate that spatio-temporal and social dimensions can explain consumer theft in retail settings. Findings Study 1 reveals mixed empirical support for the basic dimensions of routine activity theory, which posits that the opportunity to thieve is optimised when a motivated offender, suitable target and the absence of a capable formal guardian transpire in time and space. Extending the notion of guardianship, Study 2 tests social impact theory and shows that informal guardianship impacts the likelihood of theft under optimal routine activity conditions. Originality/value The study findings highlight important implications for academicians and retail managers: rather than focusing on the uncontrollable characteristics of thieving offenders, more controllable spatio-temporal and social factors of the retail environment can be actively monitored and manipulated to reduce perceived opportunities for consumer misbehaviour.

A hidden Markov model approach for determining vessel activity from vessel monitoring system data.

Many fisheries worldwide have adopted vessel monitoring systems (VMS) for compliance purposes. An added benefit of these systems is that they collect a large amount of data on vessel locations at very fine spatial and temporal scales. This data can provide a wealth of information for stock assessment, research, and management. However, since most VMS implementations record vessel location at set time intervals with no regard to vessel activity, some methodology is required to determine which data records correspond to fishing activity. This paper describes a probabilistic approach, based on hidden Markov models (HMMs), to determine vessel activity. A HMM provides a natural framework for the problem and, by definition, models the intrinsic temporal correlation of the data. The paper describes the general approach that was developed and presents an example of this approach applied to the Queensland trawl fishery off the coast of eastern Australia. Finally, a simulation experiment is presented that compares the misallocation rates of the HMM approach with other approaches.

Temporal and spatial patterns of soil water extraction and drought resistance among genotypes of a perennial C-4 grass

The objective of this study was to investigate patterns of soil water extraction and drought resistance among genotypes of bermudagrass (Cynodon spp.) a perennial C-4 grass. Four wild Australian ecotypes (1-1, 25a1, 40-1, and 81-1) and four cultivars (CT2, Grand Prix, Legend, and Wintergreen) were examined in field experiments with rainfall excluded to monitor soil water extraction at 30-190 cm depths. In the study we defined drought resistance as the ability to maintain green canopy cover under drought. The most drought resistant genotypes (40-1 and 25a1) maintained more green cover (55-85% vs 5-10%) during water deficit and extracted more soil water (120-160 mm vs 77-107 mm) than drought sensitive genotypes, especially at depths from 50 to 110 cm, though all genotypes extracted water to 190 cm. The maintenance of green cover and higher soil water extraction were associated with higher stomatal conductance, photosynthetic rate and relative water content. For all genotypes, the pattern of water use as a percentage of total water use was similar across depth and time We propose the observed genetic variation was related to different root characteristics (root length density, hydraulic conductivity, root activity) although shoot sensitivity to drying soil cannot be ruled out.

Activity recognition using binary tree SVM

This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

Role of Temperature in the Biological Activity of a Boreal Forest

In northern latitudes, temperature is the key factor driving the temporal scales of biological activity, namely the length of the growing season and the seasonal efficiency of photosynthesis. The formation of atmospheric concentrations of biogenic volatile organic compounds (BVOCs) are linked to the intensity of biological activity. However, interdisciplinary knowledge of the role of temperature in the biological processes related to the annual cycle and photosynthesis and atmospheric chemistry is not fully understood. The aim of this study was to improve understanding of the role of temperature in these three interlinked areas: 1) onset of growing season, 2) photosynthetic efficiency and 3) BVOC air concentrations in a boreal forest. The results present a cross-section of the role of temperature on different spatial (southern northern boreal), structural (tree forest stand - forest) and temporal (day-season- year) scales. The fundamental status of the Thermal Time model in predicting the onset of spring recovery was confirmed. However, it was recommended that sequential models would be more appropriate tools when the onset of the growing season is estimated under a warmer climate. A similar type of relationship between photosynthetic efficiency and temperature history was found in both southern and northern boreal forest stands. This result draws attention to the critical question of the seasonal efficiency of coniferous species to emit organic compounds under a warmer climate. New knowledge about the temperature dependence of the concentrations of biogenic volatile organic compounds in a boreal forest stand was obtained. The seasonal progress and the inter-correlation of BVOC concentrations in ambient air indicated a link to biological activity. Temperature was found to be the main driving factor for the concentrations. However, in addition to temperature, other factors may play a significant role here, especially when the peak concentrations are studied. There is strong evidence that the spring recovery and phenological events of many plant species have already advanced in Europe. This study does not fully support this observation. In a boreal forest, changes in the annual cycle, especially the temperature requirement in winter, would have an impact on the atmospheric BVOC composition. According to this study, more joint phenological and BVOC field observations and laboratory experiments are still needed to improve these scenarios.

Temporal associations in fig-wasp-ant interactions: diel and phenological patterns

In a complex multitrophic plant-animal interaction system in which there are direct and indirect interactions between species, comprehending the dynamics of these multiple partners is very important for an understanding of how the system is structured. We investigated the plant Ficus racemosa L. (Moraceae) and its community of obligatory mutualistic and parasitic fig wasps (Hymenoptera: Chalcidoidea) that develop within the fig inflorescence or syconium, as well as their interaction with opportunistic ants. We focused on temporal resource partitioning among members of the fig wasp community over the development cycle of the fig syconia during which wasp oviposition and development occur and we studied the activity rhythm of the ants associated with this community. We found that the seven members of the wasp community partitioned their oviposition across fig syconium development phenology and showed interspecific variation in activity across the day-night cycle. The wasps presented a distinct sequence in their arrival at fig syconia for oviposition, with the parasitoid wasps following the galling wasps. Although fig wasps are known to be largely diurnal, we documented night oviposition in several fig wasp species for the first time. Ant activity on the fig syconia was correlated with wasp activity and was dependent on whether the ants were predatory or trophobiont-tending species; only numbers of predatory ants increased during peak arrivals of the wasps.

A new method for modulating the activity of parvalbumin-positive neurons and cerebellar Purkinje cells in vivo

Neurons can be divided into various classes according to their location, morphology, neurochemical identity and electrical properties. They form complex interconnected networks with precise roles for each cell type. GABAergic neurons expressing the calcium-binding protein parvalbumin (Pv) are mainly interneurons, which serve a coordinating function. Pv-cells modulate the activity of principal cells with high temporal precision. Abnormalities of Pv-interneuron activity in cortical areas have been linked to neuropsychiatric illnesses such as schizophrenia. Cerebellar Purkinje cells are known to be central to motor learning. They are the sole output from the layered cerebellar cortex to deep cerebellar nuclei. There are still many open questions about the precise role of Pv-neurons and Purkinje cells, many of which could be answered if one could achieve rapid, reversible cell-type specific modulation of the activity of these neurons and observe the subsequent changes at the whole-animal level. The aim of these studies was to develop a novel method for the modulation of Pv-neurons and Purkinje cells in vivo and to use this method to investigate the significance of inhibition in these neuronal types with a variety of behavioral experiments in addition to tissue autoradiography, electrophysiology and immunohistochemistry. The GABA(A) receptor γ2 subunit was ablated from Pv-neurons and Purkinje cells in four separate mouse lines. Pv-Δγ2 mice had wide-ranging behavioral alterations and increased GABA-insensitive binding indicative of an altered GABA(A) receptor composition, particularly in midbrain areas. PC-Δγ2 mice experienced little or no motor impairment despite the lack of inhibition in Purkinje cells. In Pv-Δγ2-partial rescue mice, a reversal of motor and cognitive deficits was observed in addition to restoration of the wild-type γ2F77 subunit to the reticular nucleus of thalamus and the cerebellar molecular layer. In PC-Δγ2-swap mice, zolpidem sensitivity was restored to Purkinje cells and the administration of systemic zolpidem evoked a transient motor impairment. On the basis of these results, it is concluded that this new method of cell-type specific modulation is a feasible way to modulate the activity of selected neuronal types. The importance of Purkinje cells to motor control supports previous studies, and the crucial involvement of Pv-neurons in a range of behavioral modalities is confirmed.

Transition in subicular burst firing neurons from epileptiform activity to suppressed state by feedforward inhibition

The subiculum, a para-hippocampal structure positioned between the cornu ammonis 1 subfield and the entorhinal cortex, has been implicated in temporal lobe epilepsy in human patients and in animal models of epilepsy. The structure is characterized by the presence of a significant population of burst firing neurons that has been shown previously to lead epileptiform activity locally. Phase transitions in epileptiform activity in neurons following a prolonged challenge with an epileptogenic stimulus has been shown in other brain structures, but not in the subiculum. Considering the importance of the subicular burst firing neurons in the propagation of epileptiform activity to the entorhinal cortex, we have explored the phenomenon of phase transitions in the burst firing neurons of the subiculum in an in vitro rat brain slice model of epileptogenesis. Whole-cell patch-clamp and extracellular field recordings revealed a distinct phenomenon in the subiculum wherein an early hyperexcitable state was followed by a late suppressed state upon continuous perfusion with epileptogenic 4-aminopyridine and magnesium-free medium. The suppressed state was characterized by inhibitory post-synaptic potentials in pyramidal excitatory neurons and bursting activity in local fast-spiking interneurons at a frequency of 0.1-0.8Hz. The inhibitory post-synaptic potentials were mediated by GABA(A) receptors that coincided with excitatory synaptic inputs to attenuate action potential discharge. These inhibitory post-synaptic potentials ceased following a cut between the cornu ammonis 1 and subiculum. The suppression of epileptiform activity in the subiculum thus represents a homeostatic response towards the induced hyperexcitability. Our results suggest the importance of feedforward inhibition in exerting this homeostatic control.

Dynamics of history-dependent epidemics in temporal networks

The structural properties of temporal networks often influence the dynamical processes that occur on these networks, e.g., bursty interaction patterns have been shown to slow down epidemics. In this paper, we investigate the effect of link lifetimes on the spread of history-dependent epidemics. We formulate an analytically tractable activity-driven temporal network model that explicitly incorporates link lifetimes. For Markovian link lifetimes, we use mean-field analysis for computing the epidemic threshold, while the effect of non-Markovian link lifetimes is studied using simulations. Furthermore, we also study the effect of negative correlation between the number of links spawned by an individual and the lifetimes of those links. Such negative correlations may arise due to the finite cognitive capacity of the individuals. Our investigations reveal that heavy-tailed link lifetimes slow down the epidemic, while negative correlations can reduce epidemic prevalence. We believe that our results help shed light on the role of link lifetimes in modulating diffusion processes on temporal networks.