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dc.contributor.authorPalma, Jesse T.en_US
dc.date.accessioned2018-10-25T12:51:44Z
dc.date.issued2012
dc.date.submitted2012
dc.identifier.otherb38910792
dc.identifier.urihttps://hdl.handle.net/2144/31593
dc.descriptionThesis (Ph.D.)--Boston Universityen_US
dc.descriptionPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.en_US
dc.description.abstractRecurrent networks in which neurons interact with their neighboring cells are ubiquitous in the brain, where they enable a diverse set of transformations during perception, cognition, emotion, and action. It has been known since the 1970's how the choice of feedback signal functions within rate-based recurrent on-center off-surround networks can control the transformation of input patterns into activity patterns that are stored in short term memory, and eventually learned in long term memory. A sigmoid signal function may, in particular, control a quenching threshold below which inputs are suppressed as noise and above which they may be contrast-enhanced before the pattern is stored. The threshold and slope of the sigmoid signal function determine the degree of noise suppression and contrast enhancement. This dissertation analyses how sigmoid signal functions may be shaped and controlled in biophysically realistic spiking neurons. Combinations of fast, medium, and slow after-hyperpolarization (AHP) currents, and their modulation by acetylcholine (ACh), can control sigmoid signal threshold and slope. Simulations demonstrate how these changes in signaling impact pattern processing by recurrent on-center off-surround circuits. The results include network connectivity that is global, distance-dependent, and interneuron-mediated. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 milliseconds or longer after stimulus termination, then resolve to no stored pattern, or to winner-take-all stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition, while strengthening excitation causes more winners when the network stabilizes. These dynamics are sensitive to changes in AHP currents due to ACh influx, namely a decrease in the threshold and an increase in the slope of the transfer function. The effect can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of winners, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by basal forebrain circuits may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract information, as predicted by Adaptive Resonance Theory.en_US
dc.language.isoen_US
dc.publisherBoston Universityen_US
dc.titleSigmoid signaling and pattern processing by spiking cortical circuits: after-hyperpolarization currents, acetylcholine, and recurrent competitive dynamicsen_US
dc.typeThesis/Dissertationen_US
dc.description.embargo2031-01-01
etd.degree.nameDoctor of Philosophyen_US
etd.degree.leveldoctoralen_US
etd.degree.disciplineNeuroscienceen_US
etd.degree.grantorBoston Universityen_US
dc.identifier.barcode11719032087258
dc.identifier.mmsid99196056940001161


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