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Annemarie Wolff

4 papers in the library · 411 citations · publishing 2015-2022

Papers

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Temporal continuity of self: Long autocorrelation windows mediate self-specificity

Neuroimage May 11, 2022 David Smith, Annemarie Wolff, Angelika Wolman et al. 40 citations

The self is characterized by an intrinsic temporal component consisting in continuity across time. On the neural level, this temporal continuity manifests in the brain's intrinsic neural timescales (INT) that can be measured by the autocorrelation window (ACW). Recent EEG studies reveal a relationship between resting state ACW and self-consciousness. However, it remains unclear whether ACW...

Temporal integration as “common currency” of brain and self‐scale‐free activity in resting‐stateEEGcorrelates with temporal delay effects on self‐relatedness

Human Brain Mapping July 22, 2020 Ivar R. Kolvoort, Soren Wainio-Theberge, Annemarie Wolff et al. 92 citations

The self is a multifaceted phenomenon that integrates information and experience across multiple time scales. How temporal integration on the psychological level of the self is related to temporal integration on the neuronal level remains unclear. To investigate temporal integration on the psychological level, we modified a well-established self-matching paradigm by inserting temporal delays....

The temporal signature of self: Temporal measures of resting‐state EEG predict self‐consciousness

Human Brain Mapping October 4, 2018 Annemarie Wolff, Daniel A. di Giovanni, Javier Gómez‐Pilar et al. 135 citations

The self is the core of our mental life. Previous investigations have demonstrated a strong neural overlap between self-related activity and resting state activity. This suggests that information about self-relatedness is encoded in our brain's spontaneous activity. The exact neuronal mechanisms of such "rest-self containment," however, remain unclear. The present EEG study investigated...

How are different neural networks related to consciousness?

Annals of Neurology August 20, 2015 Pengmin Qin, Xuehai Wu, Zirui Huang et al. 144 citations

OBJECTIVE: We aimed to investigate the roles of different resting-state networks in predicting both the actual level of consciousness and its recovery in brain injury patients. METHODS: We investigated resting-state functional connectivity within different networks in patients with varying levels of consciousness: unresponsive wakefulness syndrome (UWS; n = 56), minimally conscious state (MCS;...