Dataset Information

A Model of Fast Hebbian Spike Latency Normalization.

ABSTRACT: Hebbian changes of excitatory synapses are driven by and enhance correlations between pre- and postsynaptic neuronal activations, forming a positive feedback loop that can lead to instability in simulated neural networks. Because Hebbian learning may occur on time scales of seconds to minutes, it is conjectured that some form of fast stabilization of neural firing is necessary to avoid runaway of excitation, but both the theoretical underpinning and the biological implementation for such homeostatic mechanism are to be fully investigated. Supported by analytical and computational arguments, we show that a Hebbian spike-timing-dependent metaplasticity rule, accounts for inherently-stable, quick tuning of the total input weight of a single neuron in the general scenario of asynchronous neural firing characterized by UP and DOWN states of activity.

SUBMITTER: Einarsson H

PROVIDER: S-EPMC5430963 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Model of Fast Hebbian Spike Latency Normalization.

Einarsson Hafsteinn H Gauy Marcelo M MM Lengler Johannes J Steger Angelika A

Frontiers in computational neuroscience 20170515

Hebbian changes of excitatory synapses are driven by and enhance correlations between pre- and postsynaptic neuronal activations, forming a positive feedback loop that can lead to instability in simulated neural networks. Because Hebbian learning may occur on time scales of seconds to minutes, it is conjectured that some form of fast stabilization of neural firing is necessary to avoid runaway of excitation, but both the theoretical underpinning and the biological implementation for such homeost ...[more]

PMID: 28555102

Similar Datasets

Project description:Anecdotal evidence suggests that unfamiliar languages sound faster than one's native language. Empirical evidence for this impression has, so far, come from explicit rate judgments. The aim of the present study was to test whether such perceived rate differences between native and foreign languages (FLs) have effects on implicit speech processing. Our measure of implicit rate perception was "normalization for speech rate": an ambiguous vowel between short /a/ and long /a:/ is interpreted as /a:/ following a fast but as /a/ following a slow carrier sentence. That is, listeners did not judge speech rate itself; instead, they categorized ambiguous vowels whose perception was implicitly affected by the rate of the context. We asked whether a bias towards long /a:/ might be observed when the context is not actually faster but simply spoken in a FL. A fully symmetrical experimental design was used: Dutch and German participants listened to rate matched (fast and slow) sentences in both languages spoken by the same bilingual speaker. Sentences were followed by non-words that contained vowels from an /a-a:/ duration continuum. Results from Experiments 1 and 2 showed a consistent effect of rate normalization for both listener groups. Moreover, for German listeners, across the two experiments, foreign sentences triggered more /a:/ responses than (rate matched) native sentences, suggesting that foreign sentences were indeed perceived as faster. Moreover, this FL effect was modulated by participants' ability to understand the FL: those participants that scored higher on a FL translation task showed less of a FL effect. However, opposite effects were found for the Dutch listeners. For them, their native rather than the FL induced more /a:/ responses. Nevertheless, this reversed effect could be reduced when additional spectral properties of the context were controlled for. Experiment 3, using explicit rate judgments, replicated the effect for German but not Dutch listeners. We therefore conclude that the subjective impression that FLs sound fast may have an effect on implicit speech processing, with implications for how language learners perceive spoken segments in a FL.

Dataset Information

A Model of Fast Hebbian Spike Latency Normalization.

Publications

A Model of Fast Hebbian Spike Latency Normalization.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets