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INSIGHT

@FET_Insight

Investigates Neural Replicator Hypothesis & Darwinian neurodynamics, from cell cultures & human psychology, to robotics & language communication

Katılım Nisan 2015
11 Takip Edilen23 Takipçiler
INSIGHT
INSIGHT@FET_Insight·
Awesome interview by our project coordinator Eörs Szathmáry - about the impact of INSIGHT to the advancement of research on neurodynamics and its applications on robotics!👇 ec.europa.eu/digital-single…
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We focus on how language evolves, what does the brain need and what social patterns are required @lucsteels @FET_Insight
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Undergraduates get involved with multielectrode array recording expts for third-year projects @FET_Insight
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Trying to discover the (neuro-)computational processes that build and maintain linguistic structures @lucsteels @FET_Insight
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This paper introduces the Syntax Game, a language game for exploring the origins of syntactic structure @FET_Insight
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The Syntax Game is a variant of the Naming Game but introduces more complex semantics @FET_Insight
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The Syntax Game is a minimal language game for exploring how grammar can arise in a population of agents @FET_Insight
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The Syntax Game is a game of reference similar to the Naming Game that studies syntax emergence @FET_Insight
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The paper explored the hypothesis that usage-based grammar learning can be modelled as an insight problem solving process @FET_Insight
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The advantage of a simpler system is that the minimal characteristics of a language learner become more starkly visible @FET_Insight
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The activity of a network of neurons trained to encode a time interval can be used to train a naive network @FET_Insight
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Sussex use micro-electrode arrays to store defined time intervals between activity of two neuronal populations @FET_Insight
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Sussex train one set of hippocampal neurons to fire at a defined time interval after another set @FET_Insight
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Structural synaptic plasticity is a mechanism that allows exploring a complex fitness landscape @hpvladar @FET_Insight
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Strongly couple neurons with structural synaptic plasticity can lead to self-organised criticality! @hpvladar @FET_Insight
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Strategies to build language can't use machine learning techniques bc lang is incremental and no training corpus available @FET_Insight
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Selection of novel variation within brains plays an active role in learning and thinking @hpvladar @FET_Insight
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Search and impasse stages recur several times for the majority of participants during a classic insight task @fedoranna @FET_Insight
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Replicator equations show that learning and evolvability can be viewed as the same phenomenon @hpvladar @FET_Insight
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Reflex learning provides a kind of mutation which facilitates the replication of the whole behavioural phase space @FET_Insight
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