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SUMMARY:Computational Neuroscience Journal Club - Rodrigo Echeveste (CBL)
DTSTART:20170504T150000Z
DTEND:20170504T160000Z
UID:TALK72494@talks.cam.ac.uk
CONTACT:Daniel McNamee
DESCRIPTION:Rodrigo Echeveste will cover:\n\n* Dynamic hidden states under
 lying working-memory-guided behavior\n* Michael J Wolff\, Janina Jochim\, 
 Elkan G Akyürek\, Mark G Stokes\n* Nature Neuroscience (April 2017)\n* ht
 tps://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.4546.html\n\nAbst
 ract:\nRecent theoretical models propose that working memory is mediated b
 y rapid transitions in 'activity-silent' neural states (for example\, shor
 t-term synaptic plasticity). According to the dynamic coding framework\, s
 uch hidden state transitions flexibly configure memory networks for memory
 -guided behavior and dissolve them equally fast to allow forgetting. We de
 veloped a perturbation approach to measure mnemonic hidden states in an el
 ectroencephalogram. By 'pinging' the brain during maintenance\, we show th
 at memory-item-specific information is decodable from the impulse response
 \, even in the absence of attention and lingering delay activity. Moreover
 \, hidden memories are remarkably flexible: an instruction cue that direct
 s people to forget one item is sufficient to wipe the corresponding trace 
 from the hidden state. In contrast\, temporarily unattended items remain r
 obustly coded in the hidden state\, decoupling attentional focus from cue-
 directed forgetting. Finally\, the strength of hidden-state coding predict
 s the accuracy of working-memory-guided behavior\, including memory precis
 ion.
LOCATION:Cambridge University Engineering Department\, CBL\, BE-438 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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