443 research outputs found

    When Do Objects Become Landmarks? A VR Study of the Effect of Task Relevance on Spatial Memory

    Get PDF
    We investigated how objects come to serve as landmarks in spatial memory, and more specifically how they form part of an allocentric cognitive map. Participants performing a virtual driving task incidentally learned the layout of a virtual town and locations of objects in that town. They were subsequently tested on their spatial and recognition memory for the objects. To assess whether the objects were encoded allocentrically we examined pointing consistency across tested viewpoints. In three experiments, we found that spatial memory for objects at navigationally relevant locations was more consistent across tested viewpoints, particularly when participants had more limited experience of the environment. When participants’ attention was focused on the appearance of objects, the navigational relevance effect was eliminated, whereas when their attention was focused on objects’ locations, this effect was enhanced, supporting the hypothesis that when objects are processed in the service of navigation, rather than merely being viewed as objects, they engage qualitatively distinct attentional systems and are incorporated into an allocentric spatial representation. The results are consistent with evidence from the neuroimaging literature that when objects are relevant to navigation, they not only engage the ventral “object processing stream”, but also the dorsal stream and medial temporal lobe memory system classically associated with allocentric spatial memory

    An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes

    Get PDF
    For the analysis of neuronal cooperativity, simultaneously recorded extracellular signals from neighboring neurons need to be sorted reliably by a spike sorting method. Many algorithms have been developed to this end, however, to date, none of them manages to fulfill a set of demanding requirements. In particular, it is desirable to have an algorithm that operates online, detects and classifies overlapping spikes in real time, and that adapts to non-stationary data. Here, we present a combined spike detection and classification algorithm, which explicitly addresses these issues. Our approach makes use of linear filters to find a new representation of the data and to optimally enhance the signal-to-noise ratio. We introduce a method called “Deconfusion” which de-correlates the filter outputs and provides source separation. Finally, a set of well-defined thresholds is applied and leads to simultaneous spike detection and spike classification. By incorporating a direct feedback, the algorithm adapts to non-stationary data and is, therefore, well suited for acute recordings. We evaluate our method on simulated and experimental data, including simultaneous intra/extra-cellular recordings made in slices of a rat cortex and recordings from the prefrontal cortex of awake behaving macaques. We compare the results to existing spike detection as well as spike sorting methods. We conclude that our algorithm meets all of the mentioned requirements and outperforms other methods under realistic signal-to-noise ratios and in the presence of overlapping spikes

    Spared unconscious influences of spatial memory in diencephalic amnesia

    Get PDF
    Spatial memory is crucial to our daily lives and in part strongly depends on automatic, implicit memory processes. This study investigates the neurocognitive basis of conscious and unconscious influences of object–location memory in amnesic patients with Korsakoff’s syndrome (N = 23) and healthy controls (N = 18) using a process-dissociation procedure in a computerized spatial memory task. As expected, the patients performed substantially worse on the conscious memory measures but showed even slightly stronger effects of unconscious influences than the controls. Moreover, a delayed test administered after 1 week revealed a strong decline in conscious influences in the patients, while unconscious influences were not affected. The presented results suggest that conscious and unconscious influences of spatial memory can be clearly dissociated in Korsakoff’s syndrome

    Relationship Contexts as Sources of Socialization: An Exploration of Intimate Partner Violence Experiences of Economically Disadvantaged African American Adolescents

    Get PDF
    Intimate partner violence (IPV) among African Americans is a serious public health concern. Research suggest that African Americans adolescents, particularly those from economically disadvantaged communities, are at heightened risk for experiencing and perpetrating dating violence compared to youth from other racial and ethnic groups. In the present study, we examined different relationship contexts that are sources of IPV socialization. Semi-structured interviews were conducted with 22 economically disadvantaged African American adolescents. Content analysis yielded five relationship contexts through which the participants witnessed, experienced, and perpetrated IPV: (a) adolescents’ own dating relationships (64%), (b) siblings and extended family members (e.g., cousins, aunts, uncles) (59%), (c) parent-partners (27%), (d) friends (23%), and (e) neighbors (18%). Adolescents also frequently described IPV in their own dating relationships and in parent-partner relationships as mutual. Moreover, they appeared to minimize the experience of IPV in their own relationships. Efforts to reduce rates of IPV among economically disadvantaged African American adolescents should consider these relational contexts through which adolescents are socialized with regards to IPV and adolescents’ beliefs about mutual violence in relationships. Results highlight the importance of culturally relevant prevention and intervention programs that consider these relationship contexts

    The Neural Representation of Prospective Choice during Spatial Planning and Decisions

    Get PDF
    We are remarkably adept at inferring the consequences of our actions, yet the neuronal mechanisms that allow us to plan a sequence of novel choices remain unclear. We used functional magnetic resonance imaging (fMRI) to investigate how the human brain plans the shortest path to a goal in novel mazes with one (shallow maze) or two (deep maze) choice points. We observed two distinct anterior prefrontal responses to demanding choices at the second choice point: one in rostrodorsal medial prefrontal cortex (rd-mPFC)/superior frontal gyrus (SFG) that was also sensitive to (deactivated by) demanding initial choices and another in lateral frontopolar cortex (lFPC), which was only engaged by demanding choices at the second choice point. Furthermore, we identified hippocampal responses during planning that correlated with subsequent choice accuracy and response time, particularly in mazes affording sequential choices. Psychophysiological interaction (PPI) analyses showed that coupling between the hippocampus and rd-mPFC increases during sequential (deep versus shallow) planning and is higher before correct versus incorrect choices. In short, using a naturalistic spatial planning paradigm, we reveal how the human brain represents sequential choices during planning without extensive training. Our data highlight a network centred on the cortical midline and hippocampus that allows us to make prospective choices while maintaining initial choices during planning in novel environments

    Neural Correlates of Visual Motion Prediction

    Get PDF
    Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities

    Non-invasive cardiac imaging techniques and vascular tools for the assessment of cardiovascular disease in type 2 diabetes mellitus

    Get PDF
    Cardiovascular disease is the major cause of mortality in type 2 diabetes mellitus. The criteria for the selection of those asymptomatic patients with type 2 diabetes who should undergo cardiac screening and the therapeutic consequences of screening remain controversial. Non-invasive techniques as markers of atherosclerosis and myocardial ischaemia may aid risk stratification and the implementation of tailored therapy for the patient with type 2 diabetes. In the present article we review the literature on the implementation of non-invasive vascular tools and cardiac imaging techniques in this patient group. The value of these techniques as endpoints in clinical trials and as risk estimators in asymptomatic diabetic patients is discussed. Carotid intima–media thickness, arterial stiffness and flow-mediated dilation are abnormal long before the onset of type 2 diabetes. These vascular tools are therefore most likely to be useful for the identification of ‘at risk’ patients during the early stages of atherosclerotic disease. The additional value of these tools in risk stratification and tailored therapy in type 2 diabetes remains to be proven. Cardiac imaging techniques are more justified in individuals with a strong clinical suspicion of advanced coronary heart disease (CHD). Asymptomatic myocardial ischaemia can be detected by stress echocardiography and myocardial perfusion imaging. The more recently developed non-invasive multi-slice computed tomography angiography is recommended for exclusion of CHD, and can therefore be used to screen asymptomatic patients with type 2 diabetes, but has the associated disadvantages of high radiation exposure and costs. Therefore, we propose an algorithm for the screening of asymptomatic diabetic patients, the first step of which consists of coronary artery calcium score assessment and exercise ECG
    corecore