title: A robust and biologically plausible spike pattern recognition network.
abstract: The neural mechanisms that enable recognition of spiking patterns in the brain are currently unknown. This is especially relevant in sensory systems, in which the brain has to detect such patterns and recognize relevant stimuli by processing peripheral inputs; in particular, it is unclear how sensory systems can recognize time-varying stimuli by processing spiking activity. Because auditory stimuli are represented by time-varying fluctuations in frequency content, it is useful to consider how such stimuli can be recognized by neural processing. Previous models for sound recognition have used preprocessed or low-level auditory signals as input, but complex natural sounds such as speech are thought to be processed in auditory cortex, and brain regions involved in object recognition in general must deal with the natural variability present in spike trains. Thus, we used neural recordings to investigate how a spike pattern recognition system could deal with the intrinsic variability and diverse response properties of cortical spike trains. We propose a biologically plausible computational spike pattern recognition model that uses an excitatory chain of neurons to spatially preserve the temporal representation of the spike pattern. Using a single neural recording as input, the model can be trained using a spike-timing-dependent plasticity-based learning rule to recognize neural responses to 20 different bird songs with >98% accuracy and can be stimulated to evoke reverse spike pattern playback. Although we test spike train recognition performance in an auditory task, this model can be applied to recognize sufficiently reliable spike patterns from any neuronal system.
authors.affiliation: Hearing Research Center, Department of Biomedical Engineering, and Center for Biodynamics, Boston University, Boston, Massachusetts 02215, USA.
authors.forename: Eric
authors.initials: E
authors.lastname: Larson
authors.forename: Ben P
authors.initials: BP
authors.lastname: Perrone
authors.forename: Kamal
authors.initials: K
authors.lastname: Sen
authors.forename: Cyrus P
authors.initials: CP
authors.lastname: Billimoria
mesh_terms: D000161:Acoustic Stimulation / Q000379:methods*; D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001303:Auditory Cortex / Q000502:physiology*; D046369:Finches; D007858:Learning / Q000502:physiology; D008297:Male; D009415:Nerve Net / Q000502:physiology*; D021641:Recognition, Psychology / Q000502:physiology*; D014828:Vocalization, Animal / Q000502:physiology