PHASOR: An Open-Source Pipeline for Hidden Markov Model Analysis of Stimulus-Locked Retinal Multielectrode-Array Population Activity
Multielectrode-array recordings of the retina reveal neural population activity at cellular resolution, but relating recurring population states to stimulus timing and single-unit responses requires several linked analysis steps. We present PHASOR (Population HMM Analysis of Stimulus-locked Output in the Retina), a pipeline that combines stimulus-clock alignment, Fourier-based response classification, hidden Markov modeling with Chow-Liu tree emissions, model-order selection, and state visualization. We evaluated the workflow with synthetic populations and demonstrated its use in ten ex vivo recordings from three wild-type retinas (two male, one female) and one male rd1 retina, including 2 Hz full-field sinusoidal stimulation. Across ten synthetic datasets containing seven generative states, selected model orders ranged from seven to nine, with a mean of 7.9, matching the generative count exactly in three of the ten datasets. A representative confusion matrix showed a near one-to-one correspondence between generative and decoded states, with a single additional low-occupancy state, illustrating the distinction between recovering temporal structure and recovering the exact state count. In a representative retinal recording, response classes differed in stimulus phase and contrast dependence, and decoded states differed in occupancy, dwell time, and active-unit composition. Recordings during L-AP4 application, without projected stimulation, and in a photoreceptor-degenerate rd1 retina illustrated changes in the resulting population-state descriptions. PHASOR integrates established analysis methods into a reusable workflow for relating stimulus-associated population activity to functional response classes. The selected states provide a descriptive model of population activity; their number and correspondence to biological assemblies require separate validation.