A Clinical Trial to Validate Event-Related Potential Markers of Alzheimer\u27s Disease in Outpatient Settings

INTRODUCTION: We investigated whether event-related potentials (ERP) collected in outpatient settings and analyzed with standardized methods can provide a sensitive and reliable measure of the cognitive deficits associated with early Alzheimer\u27s disease (AD). METHODS: A total of 103 subjects with probable mild AD and 101 healthy controls were recruited at seven clinical study sites. Subjects were tested using an auditory oddball ERP paradigm. RESULTS: Subjects with mild AD showed lower amplitude and increased latency for ERP features associated with attention, working memory, and executive function. These subjects also had decreased accuracy and longer reaction time in the target detection task associated with the ERP test. DISCUSSION: Analysis of ERP data showed significant changes in subjects with mild AD that are consistent with the cognitive deficits found in this population. The use of an integrated hardware/software system for data acquisition and automated data analysis methods make administration of ERP tests practical in outpatient settings

Informed perspectives on human annotation using neural signals

In this work we explore how neurophysiological correlates related to attention and perception can be used to better understand the image-annotation task. We explore the nature of the highly variable labelling data often seen across annotators. Our results indicate potential issues with regard to ‘how well’ a person manually annotates images and variability across annotators. We propose such issues arise in part as a result of subjectively interpretable instructions that may fail to elicit similar labelling behaviours and decision thresholds across participants. We find instances where an individual’s annotations differ from a group consensus, even though their EEG (Electroencephalography) signals indicate in fact they were likely in consensus with the group. We offer a new perspective on how EEG can be incorporated in an annotation task to reveal information not readily captured using manual annotations alone. As crowd-sourcing resources become more readily available for annotation tasks one can reconsider the quality of such annotations. Furthermore, with the availability of consumer EEG hardware, we speculate that we are approaching a point where it may be feasible to better harness an annotators time and decisions by examining neural responses as part of the process. In this regard, we examine strategies to deal with inter-annotator sources of noise and correlation that can be used to understand the relationship between annotators at a neural level

P3 amplitude reductions are associated with shared variance between internalizing and externalizing psychopathology

P3 amplitude reductions, commonly elicited in oddball paradigms, have been associated with both internalizing (e.g., depression and anxiety) and externalizing problems (e.g., substance use, aggression, and impulsivity). Recent factor analytic models have focused on the shared variance between internalizing and externalizing problems as a potentially important separable psychopathology construct (a general psychopathology factor, or p‐factor). To assess neurophysiological markers of this shared variance, we examined P3 amplitude to target and novel stimuli in an undergraduate sample with a range of internalizing and externalizing problems. Participants (N = 125) completed a rotated heads visual oddball paradigm, with IAPS pictures serving as infrequent novel stimuli. Results replicated P3 amplitude reduction relative to both target and novel stimuli separately for internalizing and externalizing problems, and found that the shared variance across internalizing and externalizing was significantly related to lower P3 amplitude to novels, targets, and a factor score of target and novel P3 measures. The present results are consistent with the interpretation that a general or shared problem behavior factor accounts for much of the associations between reduced P3 amplitude and internalizing and externalizing problems.There is a need for biological measures that can index emerging models of the shared variance between internalizing and externalizing problems (cf. general psychopathology factor, or p‐factor), to provide approaches for assessing the biological systems underlying these models. The current study found support for the idea that a general or shared problem behavior factor contributes to P3 amplitude reductions observed separately for internalizing and externalizing behaviors. This supports an inference that some biological systems are sensitive to processes associated with a shared problem behavior factor.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155993/1/psyp13618_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155993/2/psyp13618.pd

Cognitive control in belief-laden reasoning during conclusion processing: An ERP study

Belief bias is the tendency to accept conclusions that are compatible with existing beliefs more frequently than those that contradict beliefs. It is one of the most replicated behavioral findings in the reasoning literature. Recently, neuroimaging studies using functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) have provided a new perspective and have demonstrated neural correlates of belief bias that have been viewed as supportive of dual-process theories of belief bias. However, fMRI studies have tended to focus on conclusion processing, while ERPs studies have been concerned with the processing of premises. In the present research, the electrophysiological correlates of cognitive control were studied among 12 subjects using high-density ERPs. The analysis was focused on the conclusion presentation phase and was limited to normatively sanctioned responses to valid–believable and valid–unbelievable problems. Results showed that when participants gave normatively sanctioned responses to problems where belief and logic conflicted, a more positive ERP deflection was elicited than for normatively sanctioned responses to nonconflict problems. This was observed from −400 to −200 ms prior to the correct response being given. The positive component is argued to be analogous to the late positive component (LPC) involved in cognitive control processes. This is consistent with the inhibition of empirically anomalous information when conclusions are unbelievable. These data are important in elucidating the neural correlates of belief bias by providing evidence for electrophysiological correlates of conflict resolution during conclusion processing. Moreover, they are supportive of dual-process theories of belief bias that propose conflict detection and resolution processes as central to the explanation of belief bias

Reptile Embryos Lack the Opportunity to Thermoregulate by Moving within the Egg

Historically, egg-bound reptile embryos were thought to passively thermoconform to the nest environment. However, recent observations of thermal taxis by embryos of multiple reptile species have led to the widely discussed hypothesis that embryos behaviorally thermoregulate. Because temperature affects development, such thermoregulation could allow embryos to control their fate far more than historically assumed. We assessed the opportunity for embryos to behaviorally thermoregulate in nature by examining thermal gradients within natural nests and eggs of the common snapping turtle (Chelydra serpentina; which displays embryonic thermal taxis) and by simulating thermal gradients within nests across a range of nest depths, egg sizes, and soil types. We observed little spatial thermal variation within nests, and thermal gradients were poorly transferred to eggs. Furthermore, thermal gradients sufficiently large and constant for behavioral thermoregulation were not predicted to occur in our simulations. Gradients of biologically relevant magnitude have limited global occurrence and reverse direction twice daily when they do exist, which is substantially faster than embryos can shift position within the egg. Our results imply that reptile embryos will rarely, if ever, have the opportunity to behaviorally thermoregulate by moving within the egg. We suggest that embryonic thermal taxis instead represents a play behavior, which may be adaptive or selectively neutral, and results from the mechanisms for behavioral thermoregulation in free-living stages coming online prior to hatching

Imaging the functional connectivity of the Periaqueductal Gray during genuine and sham electroacupuncture treatment

Background Electroacupuncture (EA) is currently one of the most popular acupuncture modalities. However, the continuous stimulation characteristic of EA treatment presents challenges to the use of conventional functional Magnetic Resonance Imaging (fMRI) approaches for the investigation of neural mechanisms mediating treatment response because of the requirement for brief and intermittent stimuli in event related or block designed task paradigms. A relatively new analysis method, functional connectivity fMRI (fcMRI), has great potential for studying continuous treatment modalities such as EA. In a previous study, we found that, compared with sham acupuncture, EA can significantly reduce Periaqueductal Gray (PAG) activity when subsequently evoked by experimental pain. Given the PAG's important role in mediating acupuncture analgesia, in this study we investigated functional connectivity with the area of the PAG we previously identified and how that connectivity was affected by genuine and sham EA. Results Forty-eight subjects, who were randomly assigned to receive either genuine or sham EA paired with either a high or low expectancy manipulation, completed the study. Direct comparison of each treatment mode's functional connectivity revealed: significantly greater connectivity between the PAG, left posterior cingulate cortex (PCC), and precuneus for the contrast of genuine minus sham; significantly greater connectivity between the PAG and right anterior insula for the contrast of sham minus genuine; no significant differences in connectivity between different contrasts of the two expectancy levels. Conclusions Our findings indicate the intrinsic functional connectivity changes among key brain regions in the pain matrix and default mode network during genuine EA compared with sham EA. We speculate that continuous genuine EA stimulation can modify the coupling of spontaneous activity in brain regions that play a role in modulating pain perception.National Center for Complementary and Alternative Medicine (U.S.) (PO1-AT002048)National Center for Complementary and Alternative Medicine (U.S.) (R01AT005280)National Center for Complementary and Alternative Medicine (U.S.) (R21AT00949)National Center for Complementary and Alternative Medicine (U.S.) (KO1AT003883)National Center for Complementary and Alternative Medicine (U.S.) (R21AT004497)National Center for Complementary and Alternative Medicine (U.S.) (K24AT004095)National Center for Research Resources (U.S.) (Clinical Research Center Biomedical Imaging Core, M01-RR-01066)National Center for Research Resources (U.S.) (Clinical Research Center Biomedical Imaging Core, UL1 RR025758-01)National Center for Research Resources (U.S.) (Center for Functional Neuroimaging Technologies, P41RR14075

Learning from M/EEG data with variable brain activation delays

International audienceMagneto- and electroencephalography (M/EEG) measure the electromagnetic signals produced by brain activity. In order to address the issue of limited signal-to-noise ratio (SNR) with raw data, acquisitions consist of multiple repetitions of the same experiment. An important challenge arising from such data is the variability of brain activations over the repetitions. It hinders statistical analysis such as prediction performance in a supervised learning setup. One such confounding variability is the time offset of the peak of the activation, which varies across repetitions. We propose to address this misalignment issue by explicitly modeling time shifts of different brain responses in a classification setup. To this end, we use the latent support vector machine (LSVM) formulation, where the latent shifts are inferred while learning the classifier parameters. The inferred shifts are further used to improve the SNR of the M/EEG data, and to infer the chronometry and the sequence of activations across the brain regions that are involved in the experimental task. Results are validated on a long term memory retrieval task, showing significant improvement using the proposed latent discriminative method