A Lifetime-based Garbage Collector for LISP Systems on General-Purpose Computers

Garbage collector performance in LISP systems on custom hardware has been substantially improved by the adoption of lifetime-based garbage collection techniques. To date, however, successful lifetime-based garbage collectors have required special-purpose hardware, or at least privileged access to data structures maintained by the virtual memory system. I present here a lifetime-based garbage collector requiring no special-purpose hardware or virtual memory system support, and discuss its performance.

Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally.

Functional neuroimaging of autobiographical memory.

Functional neuroimaging studies of autobiographical memory have grown dramatically in recent years. These studies are important because they can investigate the neural correlates of processes that are difficult to study using laboratory stimuli, including: (i) complex constructive processes, (ii) recollective qualities of emotion and vividness, and (iii) remote memory retrieval. Constructing autobiographical memories involves search, monitoring and self-referential processes that are associated with activity in separable prefrontal regions. The contributions of emotion and vividness have been linked to the amygdala and visual cortex respectively. Finally, there is evidence that recent and remote autobiographical memories might activate the hippocampus equally, which has implications for memory-consolidation theories. The rapid development of innovative methods for eliciting personal memories in the scanner provides the opportunity to delve into the functional neuroanatomy of our personal past.

Neural networks supporting autobiographical memory retrieval in posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) affects the functional recruitment and connectivity between neural regions during autobiographical memory (AM) retrieval that overlap with default and control networks. Whether such univariate changes relate to potential differences in the contributions of the large-scale neural networks supporting cognition in PTSD is unknown. In the present functional MRI study, we employed independent-component analysis to examine the influence of the engagement of neural networks during the recall of personal memories in a PTSD group (15 participants) as compared to non-trauma-exposed healthy controls (14 participants). We found that the PTSD group recruited similar neural networks when compared to the controls during AM recall, including default-network subsystems and control networks, but group differences emerged in the spatial and temporal characteristics of these networks. First, we found spatial differences in the contributions of the anterior and posterior midline across the networks, and of the amygdala in particular, for the medial temporal subsystem of the default network. Second, we found temporal differences within the medial prefrontal subsystem of the default network, with less temporal coupling of this network during AM retrieval in PTSD relative to controls. These findings suggest that the spatial and temporal characteristics of the default and control networks potentially differ in a PTSD group versus healthy controls and contribute to altered recall of personal memory.

Age-related effects on the neural correlates of autobiographical memory retrieval.

Older adults recall less episodically rich autobiographical memories (AM), however, the neural basis of this effect is not clear. Using functional MRI, we examined the effects of age during search and elaboration phases of AM retrieval. Our results suggest that the age-related attenuation in the episodic richness of AMs is associated with difficulty in the strategic retrieval processes underlying recovery of information during elaboration. First, age effects on AM activity were more pronounced during elaboration than search, with older adults showing less sustained recruitment of the hippocampus and ventrolateral prefrontal cortex (VLPFC) for less episodically rich AMs. Second, there was an age-related reduction in the modulation of top-down coupling of the VLPFC on the hippocampus for episodically rich AMs. In sum, the present study shows that changes in the sustained response and coupling of the hippocampus and prefrontal cortex (PFC) underlie age-related reductions in episodic richness of the personal past.

Dynamic neural networks supporting memory retrieval.

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) medial prefrontal cortex (PFC) network, associated with self-referential processes, 2) medial temporal lobe (MTL) network, associated with memory, 3) frontoparietal network, associated with strategic search, and 4) cingulooperculum network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior.

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.

The spatiotemporal dynamics of autobiographical memory: neural correlates of recall, emotional intensity, and reliving.

We sought to map the time course of autobiographical memory retrieval, including brain regions that mediate phenomenological experiences of reliving and emotional intensity. Participants recalled personal memories to auditory word cues during event-related functional magnetic resonance imaging (fMRI). Participants pressed a button when a memory was accessed, maintained and elaborated the memory, and then gave subjective ratings of emotion and reliving. A novel fMRI approach based on timing differences capitalized on the protracted reconstructive process of autobiographical memory to segregate brain areas contributing to initial access and later elaboration and maintenance of episodic memories. The initial period engaged hippocampal, retrosplenial, and medial and right prefrontal activity, whereas the later period recruited visual, precuneus, and left prefrontal activity. Emotional intensity ratings were correlated with activity in several regions, including the amygdala and the hippocampus during the initial period. Reliving ratings were correlated with activity in visual cortex and ventromedial and inferior prefrontal regions during the later period. Frontopolar cortex was the only brain region sensitive to emotional intensity across both periods. Results were confirmed by time-locked averages of the fMRI signal. The findings indicate dynamic recruitment of emotion-, memory-, and sensory-related brain regions during remembering and their dissociable contributions to phenomenological features of the memories.

Co-activation of the amygdala, hippocampus and inferior frontal gyrus during autobiographical memory retrieval.

Functional MRI was used to investigate the role of medial temporal lobe and inferior frontal lobe regions in autobiographical recall. Prior to scanning, participants generated cue words for 50 autobiographical memories and rated their phenomenological properties using our autobiographical memory questionnaire (AMQ). During scanning, the cue words were presented and participants pressed a button when they retrieved the associated memory. The autobiographical retrieval task was interleaved in an event-related design with a semantic retrieval task (category generation). Region-of-interest analyses showed greater activation of the amygdala, hippocampus, and right inferior frontal gyrus during autobiographical retrieval relative to semantic retrieval. In addition, the left inferior frontal gyrus showed a more prolonged duration of activation in the semantic retrieval condition. A targeted correlational analysis revealed pronounced functional connectivity among the amygdala, hippocampus, and right inferior frontal gyrus during autobiographical retrieval but not during semantic retrieval. These results support theories of autobiographical memory that hypothesize co-activation of frontotemporal areas during recollection of episodes from the personal past.

When Working Memory and Attention Compete: Characterizing the Dynamic Interdependence between our Mental Workspace and External Environment

All of us are taxed with juggling our inner mental lives with immediate external task demands. For many years, the temporary maintenance of internal information was considered to be handled by a dedicated working memory (WM) system. It has recently become increasingly clear, however, that such short-term internal activation interacts with attention focused on external stimuli. It is unclear, however, exactly why these two interact, at what level of processing, and to what degree. Because our internal maintenance and external attention processes co-occur with one another, the manner of their interaction has vast implications for functioning in daily life. The work described here has employed original experimental paradigms combining WM and attention task elements, functional magnetic resonance imaging (fMRI) to illuminate the associated neural processes, and transcranial magnetic stimulation (TMS) to clarify the causal substrates of attentional brain function. These studies have examined a mechanism that might explain why (and when) the content of WM can involuntarily capture visual attention. They have, furthermore, tested whether fundamental attentional selection processes operate within WM, and whether they are reciprocal with attention. Finally, they have illuminated the neural consequences of competing attentional demands. The findings indicate that WM shares representations, operating principles, and cognitive resources with externally-oriented attention.

Parallel mesh partitioning on distributed memory systems

The problem of deriving parallel mesh partitioning algorithms for mapping unstructured meshes to parallel computers is discussed in this chapter. In itself this raises a paradox - we seek to find a high quality partition of the mesh, but to compute it in parallel we require a partition of the mesh. In fact, we overcome this difficulty by deriving an optimisation strategy which can find a high quality partition even if the quality of the initial partition is very poor and then use a crude distribution scheme for the initial partition. The basis of this strategy is to use a multilevel approach combined with local refinement algorithms. Three such refinement algorithms are outlined and some example results presented which show that they can produce very high global quality partitions, very rapidly. The results are also compared with a similar multilevel serial partitioner and shown to be almost identical in quality. Finally we consider the impact of the initial partition on the results and demonstrate that the final partition quality is, modulo a certain amount of noise, independent of the initial partition.

Abnormal Functional Connectivity of Hippocampus During Episodic Memory Retrieval Processing Network in Amnestic Mild Cognitive Impairment.

BACKGROUND: Functional connectivity magnetic resonance imaging technique has revealed the importance of distributed network structures in higher cognitive processes in the human brain. The hippocampus has a key role in a distributed network supporting memory encoding and retrieval. Hippocampal dysfunction is a recurrent finding in memory disorders of aging such as amnestic mild cognitive impairment (aMCI) in which learning- and memory-related cognitive abilities are the predominant impairment. The functional connectivity method provides a novel approach in our attempts to better understand the changes occurring in this structure in aMCI patients. METHODS: Functional connectivity analysis was used to examine episodic memory retrieval networks in vivo in twenty 28 aMCI patients and 23 well-matched control subjects, specifically between the hippocampal structures and other brain regions. RESULTS: Compared with control subjects, aMCI patients showed significantly lower hippocampus functional connectivity in a network involving prefrontal lobe, temporal lobe, parietal lobe, and cerebellum, and higher functional connectivity to more diffuse areas of the brain than normal aging control subjects. In addition, those regions associated with increased functional connectivity with the hippocampus demonstrated a significantly negative correlation to episodic memory performance. CONCLUSIONS: aMCI patients displayed altered patterns of functional connectivity during memory retrieval. The degree of this disturbance appears to be related to level of impairment of processes involved in memory function. Because aMCI is a putative prodromal syndrome to Alzheimer's disease (AD), these early changes in functional connectivity involving the hippocampus may yield important new data to predict whether a patient will eventually develop AD.

Altered long-range alpha-band synchronization during visual short-term memory retention in children born very preterm

Children born very preterm, even when intelligence is broadly normal, often experience selective difficulties in executive function and visual-spatial processing. Development of structural cortical connectivity is known to be altered in this group, and functional magnetic resonance imaging (fMRI) evidence indicates that very preterm children recruit different patterns of functional connectivity between cortical regions during cognition. Synchronization of neural oscillations across brain areas has been proposed as a mechanism for dynamically assigning functional coupling to support perceptual and cognitive processing, but little is known about what role oscillatory synchronization may play in the altered neurocognitive development of very preterm children. To investigate this, we recorded magnetoencephalographic (MEG) activity while 7-8 year old children born very preterm and age-matched full-term controls performed a visual short-term memory task. Very preterm children exhibited reduced long-range synchronization in the alpha-band during visual short-term memory retention, indicating that cortical alpha rhythms may play a critical role in altered patterns functional connectivity expressed by this population during cognitive and perceptual processing. Long-range alpha-band synchronization was also correlated with task performance and visual-perceptual ability within the very preterm group, indicating that altered alpha oscillatory mechanisms mediating transient functional integration between cortical regions may be relevant to selective problems in neurocognitive development in this vulnerable population at school age.

Optical quantum memory for polarization qubits with V-type three-level atoms

We investigate an optical quantum memory scheme with V-type three-level atoms based on the controlled reversible inhomogeneous broadening (CRIB) technique. We theoretically show the possibility to store and retrieve a weak light pulse interacting with the two optical transitions of the system. This scheme implements a quantum memory for a polarization qubit - a single photon in an arbitrary polarization state - without the need of two spatially separated two-level media, thus offering the advantage of experimental compactness overcoming the limitations due to mismatching and unequal efficiencies that can arise in spatially separated memories. The effects of a relative phase change between the atomic levels, as well as of phase noise due to, for example, the presence of spurious electric and magnetic fields are analyzed.