Dian Lu (Lyu 吕)
Postdoctoral Scholar, Neurology and Neurological Sciences
Bio
Dian received her Master's degree in Cognitive Neurosciences from University College London, and her Ph.D. in Clinical Neurosciences from the University of Cambridge. Her previous work focused on default-mode-network functional connectivity and inter-network interactions across different brain states. She is interested in consciousness studies involving self-related cognition using intracranial EEG and electrical stimulation and precision mapping of anatomy and function by leveraging computational modeling.
Community and International Work
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International volunteer with the non-governmental organization (NGO) Program, the west bank of Palestine
Partnering Organization(s)
Holy Land Trust
Populations Served
people
Location
International
Ongoing Project
No
Opportunities for Student Involvement
Yes
Research Interests
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Brain and Learning Sciences
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Diversity and Identity
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Equity in Education
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Higher Education
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Philosophy
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Psychology
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Sociology
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Special Education
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Technology and Education
All Publications
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Causal evidence for the processing of bodily self in the anterior precuneus.
Neuron
2023
Abstract
To probe the causal importance of the human posteromedial cortex (PMC) in processing the sense of self, we studied a rare cohort of nine patients with electrodes implanted bilaterally in the precuneus, posterior cingulate, and retrosplenial regions with a combination of neuroimaging, intracranial recordings, and direct cortical stimulations. In all participants, the stimulation of specific sites within the anterior precuneus (aPCu) caused dissociative changes in physical and spatial domains. Using single-pulse electrical stimulations and neuroimaging, we present effective and resting-state connectivity of aPCu hot zone with the rest of the brain and show that they are located outside the boundaries of the default mode network (DMN) but connected reciprocally with it. We propose that the function of this subregion of the PMC is integral to a range of cognitive processes that require the self's physical point of reference, given its location within a spatial environment.
View details for DOI 10.1016/j.neuron.2023.05.013
View details for PubMedID 37295420
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Intrinsic brain dynamics in the Default Mode Network predict involuntary fluctuations of visual awareness
NATURE COMMUNICATIONS
2022; 13 (1): 6923
Abstract
Brain activity is intrinsically organised into spatiotemporal patterns, but it is still not clear whether these intrinsic patterns are functional or epiphenomenal. Using a simultaneous fMRI-EEG implementation of a well-known bistable visual task, we showed that the latent transient states in the intrinsic EEG oscillations can predict upcoming involuntarily perceptual transitions. The critical state predicting a dominant perceptual transition was characterised by the phase coupling between the precuneus (PCU), a key node of the Default Mode Network (DMN), and the primary visual cortex (V1). The interaction between the lifetime of this state and the PCU- > V1 Granger-causal effect is correlated with the perceptual fluctuation rate. Our study suggests that the brain's endogenous dynamics are phenomenologically relevant, as they can elicit a diversion between potential visual processing pathways, while external stimuli remain the same. In this sense, the intrinsic DMN dynamics pre-empt the content of consciousness.
View details for DOI 10.1038/s41467-022-34410-6
View details for Web of Science ID 000883836600042
View details for PubMedID 36376303
View details for PubMedCentralID PMC9663583
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A Precuneal Causal Loop Mediates External and Internal Information Integration in the Human Brain
JOURNAL OF NEUROSCIENCE
2021; 41 (48): 9944-9956
Abstract
Human brains interpret external stimuli based on internal representations. One untested hypothesis is that the default-mode network (DMN), widely considered responsible for internally oriented cognition, can decode external information. Here, we posit that the unique structural and functional fingerprint of the precuneus (PCu) supports a prominent role for the posterior part of the DMN in this process. By analyzing the imaging data of 100 participants performing two attention-demanding tasks, we found that the PCu is functionally divided into dorsal and ventral subdivisions. We then conducted a comprehensive examination of their connectivity profiles and found that at rest, both the ventral PCu (vPCu) and dorsal PCu (dPCu) are mainly connected with the DMN but also are differentially connected with internally oriented networks (IoN) and externally oriented networks (EoN). During tasks, the double associations between the v/dPCu and the IoN/EoN are correlated with task performance and can switch depending on cognitive demand. Furthermore, dynamic causal modeling (DCM) revealed that the strength and direction of the effective connectivity (EC) between v/dPCu is modulated by task difficulty in a manner potentially dictated by the balance of internal versus external cognitive demands. Our study provides evidence that the posterior medial part of the DMN may drive interactions between large-scale networks, potentially allowing access to stored representations for moment-to-moment interpretation of an ever-changing environment.SIGNIFICANCE STATEMENT The default-mode network (DMN) is widely known for its association with internalized thinking processes, e.g., spontaneous thoughts, which is the most interesting but least understood component in human consciousness. The precuneus (PCu), a posteromedial DMN hub, is thought to play a role in this, but a mechanistic explanation has not yet been established. In this study we found that the associations between ventral PCu (vPCu)/dorsal PCu (dPCu) subdivisions and internally oriented network (IoN)/externally oriented network (EoN) are flexibly modulated by cognitive demand and correlate with task performance. We further propose that the recurrent causal connectivity between the ventral and dorsal PCu supports conscious processing by constantly interpreting external information based on an internal model, meanwhile updating the internal model with the incoming information.
View details for DOI 10.1523/JNEUROSCI.0647-21.2021
View details for Web of Science ID 000726786900008
View details for PubMedID 34675087
View details for PubMedCentralID PMC8638689