The neural basis of e-ective memory therapy in a patient with limbic encephalitis

Microsoft Research Cambridge, 7 JJ Thomson Avenue, Cambridge CB3 0FB, UK.
Journal of neurology, neurosurgery, and psychiatry (Impact Factor: 6.81). 04/2009; 80(11):1202-5. DOI: 10.1136/jnnp.2008.164251
Source: PubMed

ABSTRACT An fMRI study is described in which a postencephalitic woman with amnesia used a wearable camera which takes photographs passively, without user intervention, to record and review recent autobiographical events. "SenseCam" generates hundreds of images which can subsequently be reviewed quickly or one by one.
Memory for a significant event was improved substantially when tested after 4.5 weeks, if the patient viewed SenseCam images of the event every 2 days for 3 weeks. In contrast, after only 3.5 weeks, her memory was at chance levels for a similarly significant event which was reviewed equally often, but using a written diary. During the fMRI scan, the patient viewed images of these two events, plus images of an unrehearsed event and images from a novel "control" event that she had never experienced. There was no difference in behavioural responses or in activation when the unrehearsed and novel conditions were compared. Relative to the written-rehearsed condition, successful recognition of the images in the SenseCam-rehearsed condition was associated with activation of frontal and posterior cortical regions associated with normal episodic memory.
SenseCam images may provide powerful cues that trigger the recall and consolidation of stored but inaccessible memories.

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Available from: James Rowe, Sep 28, 2015
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    • "More advanced lifelog devices such as the SenseCam or Autographer, can record visual lifelogs where images and/or video from a first person (wearer) viewpoint can capture more detail about the wearer's daily activities. Such visual lifelogs can support more advanced applications other than health monitoring including memory recall for people with early-stage dementia [2], diet monitoring, smoking cessation, or even some job-specific lifelogs for example from medical practitioners. All of these applications of lifelogging, and most others, are based around accessing the very recent past from the lifelog and accessing discrete units of that past, corresponding to events and as such, most lifelogs are structured in a manner that reflects the way the brain is believed to store memories, i.e. based around events. "
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    ABSTRACT: Lifelogging is the ambient, continuous digital recording of a person's everyday activities for a variety of possible applications. Much of the work to date in lifelogging has focused on developing sensors, capturing information, processing it into events and then supporting event-based access to the lifelog for applications like memory recall, behaviour analysis or similar. With the recent arrival of aggregating platforms such as Apple's HealthKit, Microsoft's HealthVault and Google's Fit, we are now able to collect and aggregate data from lifelog sensors, to centralize the management of data and in particular to search for and detect patterns of usage for individuals and across populations. In this paper, we present a framework that detects both low-level and high-level periodicity in lifelog data, detecting hidden patterns of which users would not otherwise be aware. We detect periodicities of time series using a combination of correlograms and periodograms, using various signal processing algorithms. Periodicity detection in lifelogs is particularly challenging because the lifelog data itself is not always continuous and can have gaps as users may use their lifelog devices intermittingly. To illustrate that periodicity can be detected from such data, we apply periodicity detection on three lifelog datasets with varying levels of completeness and accuracy.
    IEEE BIBM 2014; 11/2014
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    • "SenseCam review can facilitate recollection in normal healthy individuals (Sellen et al., 2007) and in patients with significant or mild memory impairments, with secondary benefits for confidence and well-being (Berry et al., 2007; Browne et al., 2011). An fMRI study of a patient with limbic encephalitis showed that successful recognition following SenseCam rehearsal, compared to unrehearsed and control conditions, activated cortical regions known to be involved in normal episodic memory (Berry et al., 2009). Healthy students also show increased activity in key brain regions supporting memory when viewing SenseCam traces (St. "
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    ABSTRACT: SenseCam review has been shown to promote and sustain subsequent access to memories that might otherwise remain inaccessible. While SenseCam review facilitates recollection for personally experienced events, we know little about the boundary conditions under which this operates and about how underlying processing mechanisms can be optimally recruited to offset memory impairments of the sort that occur in dementia. This paper considers some of these issues with a view to targeting future research that not only clarifies our evolving body of theory about how memory works, but also informs about how memory-assistive technologies for patients might be employed to maximal effect. We begin by outlining key factors that are known to influence recollection. We then examine variability in the decline of memory function both in normal ageing and in dementia. Attention is drawn to similarities in the recollection deficits associated with depression and dementia, and we suggest that this may reflect shared underlying mechanisms. We conclude by discussing how one particular theoretical rationale can be intersected with key SenseCam capabilities to define priorities for ongoing and future SenseCam research.
    Memory 10/2011; 19(7):758-67. DOI:10.1080/09658211.2010.533180 · 2.09 Impact Factor
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    • "The simple finger-touch interaction is also suitable for novice computer users [3]. These aspects suggest that touchscreen browsers would be an ideal form of interaction for SenseCam users, many of whom are older or have cognitive impairments [4]. To date a touchscreen interface using this method has not yet been explored. "
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    ABSTRACT: In this paper we describe the design considerations for a touchscreen visual lifelog browser. Visual lifelogs are large collections of photographs which represent a person's experiences. Lifelogging devices, such as the wearable camera known as SenseCam, can record thousands of images per day. Utilizing the approach of event segmentation to organize and present these images, we have designed an interface to present lifelog collections for touchscreen interaction, thus increasing accessibility for users.
    Proceedings of the 1st International Conference on Multimedia Retrieval, ICMR 2011, Trento, Italy, April 18 - 20, 2011; 01/2011
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