Working Memories for Storage and Recall of Arbitrary Temporal Sequences

A working memory model is described that is capable of storing and recalling arbitrary temporal sequences of events, including repeated items. These memories encode the invariant temporal order of sequential events that may be presented at widely differing speeds, durations, and interstimulus intervals. This temporal order code is designed to enable all possible groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system.

A Neural Network Model of Spatio-Temporal Pattern Recognition, Recall and Timing

This paper describes the design of a self~organizing, hierarchical neural network model of unsupervised serial learning. The model learns to recognize, store, and recall sequences of unitized patterns, using either short-term memory (STM) or both STM and long-term memory (LTM) mechanisms. Timing information is learned and recall {both from STM and from LTM) is performed with a learned rhythmical structure. The network, bearing similarities with ART (Carpenter & Grossberg 1987a), learns to map temporal sequences to unitized patterns, which makes it suitable for hierarchical operation. It is therefore capable of self-organizing codes for sequences of sequences. The capacity is only limited by the number of nodes provided. Selected simulation results are reported to illustrate system properties.

Store Working Memory Networks for Storage and Recall of Arbitrary Temporal Sequences

Neural network models of working memory, called Sustained Temporal Order REcurrent (STORE) models, are described. They encode the invariant temporal order of sequential events in short term memory (STM) in a way that mimics cognitive data about working memory, including primacy, recency, and bowed order and error gradients. As new items are presented, the pattern of previously stored items is invariant in the sense that, relative activations remain constant through time. This invariant temporal order code enables all possible groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system. Such a competence is needed to design self-organizing temporal recognition and planning systems in which any subsequence of events may need to be categorized in order to to control and predict future behavior or external events. STORE models show how arbitrary event sequences may be invariantly stored, including repeated events. A preprocessor interacts with the working memory to represent event repeats in spatially separate locations. It is shown why at least two processing levels are needed to invariantly store events presented with variable durations and interstimulus intervals. It is also shown how network parameters control the type and shape of primacy, recency, or bowed temporal order gradients that will be stored.

Soft sediment ecology of Lough Hyne Marine Reserve - spatial and temporal patterns

Distribution of soft sediment benthic fauna and the environmental factors affecting them were studied, to investigate changes across spatial and temporal scales. Investigations took place at Lough Hyne Marine Reserve using a range of methods. Data on the sedimentation rates of organic and inorganic matter were collected at monthly intervals for one year at a number of sites around the Lough, by use of vertical midwater-column sediment traps. Sedimentation of these two fractions were not coupled; inorganic matter sedimentation depended on hydrodynamic and weather factors, while the organic matter sedimentation was more complex, being dependent on biological and chemical processes in the water column. The effects of regular hypoxic episodes on benthic fauna due to a natural seasonal thermocline were studied in the deep Western Trough, using camera-equipped remotely-operated vehicle to follow transects, on a three-monthly basis over one year. In late summer, the area below the thermocline of the Western Trough was devoid of visible fauna. Decapod crustaceans were the first taxon to make use of ameliorating oxygen conditions in autumn, by darting below the thermocline depth, most likely to scavenge. This was indicated by tracks that they left on the surface of the Trough floor. Some species, most noticeably Fries’ goby Lesueurigobius friesii, migrated below the thermocline depth when conditions were normoxic and established semi-permanent burrows. Their population encompassed all size classes, indicating that this habitat was not limited to juveniles of this territorial species. Recolonisation by macrofauna and burrowing megafauna was studied during normoxic conditions, from November 2009 to May 2010. Macrofauna displayed a typical post-disturbance pattern of recolonisation with one species, the polychaete Scalibregma inflatum, occurring at high abundance levels in March 2010. In May, this population had become significantly reduced and a more diverse community was established. The abundance of burrowing infauna comprising decapods crabs and Fries’ gobies, was estimated by identifying and counting their distinctive burrow structures. While above the summer thermocline depth, burrow abundance increased in a linear fashion, below the thermocline depth a slight reduction of burrow abundance occurred in May, when oxygen conditions deteriorated again. The majority of the burrows occurring in May were made by Fries’ gobies, which are thought to encounter low oxygen concentrations in their burrows. Reduction in burrow abundance of burrowing shrimps Calocaris macandreae and Callianassa subterranea (based on descriptions of burrow structures from the literature), from March to May, might be related to their reduced activity in hypoxia, leading to loss of structural burrow maintenance. Spatial and temporal changes to macrofaunal assemblage structures were studied seasonally for one year across 5 sites in the Lough and subject to multivariate statistical analysis. Assemblage structures were significantly correlated with organic matter levels in the sediment, the amounts of organic matter settling out of the water column one month before macrofaunal sampling took place as well as current speed and temperature. This study was the first to investigate patterns and processes in the Lough soft sediment ecology across all 3 basins on a temporal and spatial scale. An investigation into the oceanographic aspects of the development, behaviour and break-down of the summer thermocline of Lough Hyne was performed in collaboration with researchers from other Irish institutions.

Variability in north temperate dung beetle assemblages at different spatial and temporal scales

This study examined the spatial and temporal variability of dung beetle assemblages across a variety of scales e.g. from the between-pad scale (examining the effects of dung size and type) to larger spatial scales encompassing southern Ireland. Dung beetle assemblage structure as sampled by dung pad cohort samples and dung baited pitfall trapping were compared. Generally, the rank order of abundance of dung beetle species was significantly correlated between pitfall catches and cohort pad samples. Across different dung sizes, in both pitfall catches and cohort pad samples, the relative abundance of species was frequently significantly different, but the rank order of abundance of dung beetle was usually significantly correlated. Considerable variations in pitfall catches at temporal scales of a few days appeared to be closely related to weather conditions and rotational grazing. However, despite considerable variation in absolute abundances between consecutive days of sampling, assemblage structure typically remained very similar. The relationship between dung pad size and dung beetle colonisation was investigated. In field experiments in which pads of different sizes (0.25 L, 0.5 L, 1.0 L and 1.5 L) were artificially deposited, there was a positive relationship between pad size and both biomass and number of beetles colonising dung pads and pitfall traps. In addition, with one exception, the field experiments indicated a general positive relationship between dung pad size and biomass density (dung beetle biomass per unit dung volume). A laboratory experiment indicated that pat residence times of A. rufipes were significantly correlated with dung pad size. Investigation of naturally-deposited cow dung pads in the field also indicated that both larval numbers and densities were significantly correlated with dung pad size. These results were discussed in the context of theory related to aggregation and coexistence of species, and resource utilisation by organisms in ephemeral, patchy resources. The colonisation by dung beetles of dung types from native herbivores (sheep, horse and cow) was investigated in field experiments. There were significant differences between the dung types in the chemical parameters measured, and there were significant differences in abundances of dung beetles colonising the dung types. Sheep dung was typically the preferred dung type. Data from these field experiments, and from published literature, indicated that dung beetle species can display dung type preferences, in terms of comparisons of both absolute and relative abundances. In addition, data from laboratory experiments indicate that both Aphodius larval production and pat residence times tended to be higher in those dung types which were preferred by adult Aphodius in the colonisation experiments. Data from dung-baited pitfall trapping (from this and another study) at several sites (up to 180 km distant) and over a number of years (between 1991 and 1996) were used to investigate spatial and temporal variation in dung beetle assemblage structure and composition (Aphodius, Sphaeridium and Geotrupes) across a range of scales in southern Ireland. Species richness levels, species composition and rank order of abundances were very similar between the assemblages. The temporal variability between seasons within any year exceeded temporal variability between years. DCA ordinations indicated that there was a similar level of variability between assemblage structure from the between-field (~1km) to regional (~180 km) spatial scales, and between year (6 years) temporal scales. At the biogeographical spatial scale, analysis of data from the literature indicated that there was considerable variability at this scale, largely due to species turnover.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Temporal variations of IEEE 802.11b signal strengths in an in-building environment

Recent popularity of the IEEE 802.11b Wireless Local Area Networks (WLANs) in a host of current-day applications has instigated a suite of research challenges. The 802.11b WLANs are highly reliable and wide spread. In this work, we study the temporal characteristics of RSSI in the real-working environment by conducting a controlled set of experiments. Our results indicate that a significant variability in the RSSI can occur over time. Some of this variability in the RSSI may be due to systematic causes while the other component can be expressed as stochastic noise. We present an analysis of both these aspects of RSSI. We treat the moving average of the RSSI as the systematic causes and the noise as the stochastic causes. We give a reasonable estimate for the moving average to compute the noise accurately. We attribute the changes in the environment such as the movement of people and the noise associated with the NIC circuitry and the network access point as causes for this variability. We find that the results of our analysis are of primary importance to active research areas such as location determination of users in a WLAN. The techniques used in some of the RF-based WLAN location determination systems, exploit the characteristics of the RSSI presented in this work to infer the location of a wireless client in a WLAN. Thus our results form the building blocks for other users of the exact characteristics of the RSSI.

The evolutionary origins of human patience: temporal preferences in chimpanzees, bonobos, and human adults.

To make adaptive choices, individuals must sometimes exhibit patience, forgoing immediate benefits to acquire more valuable future rewards [1-3]. Although humans account for future consequences when making temporal decisions [4], many animal species wait only a few seconds for delayed benefits [5-10]. Current research thus suggests a phylogenetic gap between patient humans and impulsive, present-oriented animals [9, 11], a distinction with implications for our understanding of economic decision making [12] and the origins of human cooperation [13]. On the basis of a series of experimental results, we reject this conclusion. First, bonobos (Pan paniscus) and chimpanzees (Pan troglodytes) exhibit a degree of patience not seen in other animals tested thus far. Second, humans are less willing to wait for food rewards than are chimpanzees. Third, humans are more willing to wait for monetary rewards than for food, and show the highest degree of patience only in response to decisions about money involving low opportunity costs. These findings suggest that core components of the capacity for future-oriented decisions evolved before the human lineage diverged from apes. Moreover, the different levels of patience that humans exhibit might be driven by fundamental differences in the mechanisms representing biological versus abstract rewards.

Adaptive temporal compressive sensing for video

This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to realtime implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems. © 2013 IEEE.

Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.

Exposure to influenza viruses is necessary, but not sufficient, for healthy human hosts to develop symptomatic illness. The host response is an important determinant of disease progression. In order to delineate host molecular responses that differentiate symptomatic and asymptomatic Influenza A infection, we inoculated 17 healthy adults with live influenza (H3N2/Wisconsin) and examined changes in host peripheral blood gene expression at 16 timepoints over 132 hours. Here we present distinct transcriptional dynamics of host responses unique to asymptomatic and symptomatic infections. We show that symptomatic hosts invoke, simultaneously, multiple pattern recognition receptors-mediated antiviral and inflammatory responses that may relate to virus-induced oxidative stress. In contrast, asymptomatic subjects tightly regulate these responses and exhibit elevated expression of genes that function in antioxidant responses and cell-mediated responses. We reveal an ab initio molecular signature that strongly correlates to symptomatic clinical disease and biomarkers whose expression patterns best discriminate early from late phases of infection. Our results establish a temporal pattern of host molecular responses that differentiates symptomatic from asymptomatic infections and reveals an asymptomatic host-unique non-passive response signature, suggesting novel putative molecular targets for both prognostic assessment and ameliorative therapeutic intervention in seasonal and pandemic influenza.

Coded aperture compressive temporal imaging.

We use mechanical translation of a coded aperture for code division multiple access compression of video. We discuss the compressed video's temporal resolution and present experimental results for reconstructions of > 10 frames of temporal data per coded snapshot.

The reminiscence bump in the temporal distribution of the best football players of all time: Pelé, Cruijff or Maradona?

The reminiscence bump is the tendency to recall more autobiographical memories from adolescence and early adulthood than from adjacent lifetime periods. In this online study, the robustness of the reminiscence bump was examined by looking at participants' judgements about the quality of football players. Dutch participants (N = 619) were asked who they thought the five best players of all time were. The participants could select the names from a list or enter the names when their favourite players were not on the list. Johan Cruijff, Pelé, and Diego Maradona were the three most often mentioned players. Participants frequently named football players who reached the midpoint of their career when the participants were adolescents (mode = 17). The results indicate that the reminiscence bump can also be identified outside the autobiographical memory domain.

The temporal distribution of autobiographical memory: changes in reliving and vividness over the life span do not explain the reminiscence bump.

When autobiographical memories are elicited with word cues, personal events from middle childhood to early adulthood are overrepresented compared to events from other periods. It is, however, unclear whether these memories are also associated with greater recollection. In this online study, we examined whether autobiographical memories from adolescence and early adulthood are recollected more than memories from other lifetime periods. Participants rated personal events that were elicited with cue words on reliving or vividness. Consistent with previous studies, most memories came from the period in which the participants were between 6 and 20 years old. The memories from this period were not relived more or recalled more vividly than memories from other lifetime periods, suggesting that they do not involve more recollection. Recent events had higher levels of reliving and vividness than remote events, and older adults reported a stronger recollective experience than younger adults.

The short and long of it: neural correlates of temporal-order memory for autobiographical events.

Previous functional neuroimaging studies of temporal-order memory have investigated memory for laboratory stimuli that are causally unrelated and poor in sensory detail. In contrast, the present functional magnetic resonance imaging (fMRI) study investigated temporal-order memory for autobiographical events that were causally interconnected and rich in sensory detail. Participants took photographs at many campus locations over a period of several hours, and the following day they were scanned while making temporal-order judgments to pairs of photographs from different locations. By manipulating the temporal lag between the two locations in each trial, we compared the neural correlates associated with reconstruction processes, which we hypothesized depended on recollection and contribute mainly to short lags, and distance processes, which we hypothesized to depend on familiarity and contribute mainly to longer lags. Consistent with our hypotheses, parametric fMRI analyses linked shorter lags to activations in regions previously associated with recollection (left prefrontal, parahippocampal, precuneus, and visual cortices), and longer lags with regions previously associated with familiarity (right prefrontal cortex). The hemispheric asymmetry in prefrontal cortex activity fits very well with evidence and theories regarding the contributions of the left versus right prefrontal cortex to memory (recollection vs. familiarity processes) and cognition (systematic vs. heuristic processes). In sum, using a novel photo-paradigm, this study provided the first evidence regarding the neural correlates of temporal-order for autobiographical events.

Spatial imagery preserves temporal order.

Line drawings were presented in either a spatial or a nonspatial format. Subjects recalled each of four sets of 24 items in serial order. Amount recalled in the correct serial order and sequencing errors were scored. In Experiment 1 items appeared either in consecutive locations of a matrix or in one central location. Subjects who saw the items in different locations made fewer sequencing errors than those who saw each item in a central location, but serial recall levels for these two conditions did not differ. When items appeared in nonconsecutive locations in Experiment 2, the advantage of the spatial presentation on sequencing errors disappeared. Experiment 3 included conditions in which both the consecutive and nonconsecutive spatial formats were paired with retrieval cues that either did or did not indicate the sequence of locations in which the items had appeared. Spatial imagery aided sequencing when, and only when, the order of locations in which the stimuli appeared could be reconstructed at retrieval.