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BrainMap: Making Sense of Time in the Human Mind
July 8, 2020
Virginie van Wassenhove, Ph.D., Research Director, Université Paris-Sud, France
Late 2008, she moved to NeuroSpin (France) to build NeuroSpin MEG and her research group. The Cognition & Brain Dynamics lab mostly uses psychophysics and time-resolved neuroimaging to study temporal cognition, with the understanding, that humans’ conceptualization of time may dramatically affect how we conceive of the mind and brain. The neural mechanisms supporting temporal cognition remain debated considering they do not encompass a unitary brain function. Temporal cognition in humans is a composite of psychological realities ranging from the individuation and ordering of events to the feeling that time passes, that things exist for a while (duration) or that we can mentally travel time. Several difficulties stand in the way of understanding psychological time: subjective temporalities emerge from the perspective of the brain – the generator, actuator and observer of events – and not that of the external observer (the experimenter). The psychological time arrow, taken as our sense of past-to-future, is a convenient metaphor for how allo- and egocentric temporal cognitive maps may help the capacity to mentally travel time, namely the capacity to generate a chronology of events suiting narratives. The ability to introspect about one’s timing productions (temporal metacognition) will further illustrate that time is “represented”, thus coded, and that the variability of timing is also constitutive of temporal representations. Altogether, these recent findings go beyond our classic notions of temporal perception as duration and focus on the endogenous generation of high-level temporalities may yield abstract and intelligible representations of time in the human mind.
Virginie van Wassenhove is a CEA and INSERM Research Director at NeuroSpin, France. She received her PhD in Neurosciences and Cognitive Sciences at the University of Maryland (College Park, USA in 2004). Her thesis proposed the Analysis-by-Synthesis as a generative predictive coding framework for the integration of audiovisual speech in the human brain.
In 2005, she joined the UCSF to study auditory and multisensory learning and plasticity with MEG. In 2006, she relocated to a dual position at UCLA and at Caltech to work on multiple projects that included implicit statistical learning, time perception, gesture communication, and interpersonal interactions.
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