Linking brain and behavior states in Zebrafish Larvae locomotion using hidden Markov models

doi:10.1371/journal.pcbi.1013762

Linking brain and behavior states in Zebrafish Larvae locomotion using hidden Markov models

Fig 6

Generative ability of HMM models and trajectory reconstruction from neural HMMs:

(a,b,c) Pipeline to convert neuronal activity to swim trajectory. (a) ARTR activity is first converted to the most likely sequence of forward/left/right hidden states using the Viterbi algorithm on the Neuronal Hidden Markov Models (N-HMM). (Example empirical ARTR activity at 26°C). (b) Time is then re-scaled using the scaling factor identified in Fig 5, and sampled based on the empirical distribution of inter-bout intervals . Bout-angle sequences are then sampled based on the Behavioral Hidden Markov Models (B-HMM). (c) Swim trajectories are constructed for each bout sequence by sampling the bout distances d_n from the empirical distribution. An example trajectory generated from the empirical neuronal activity at 26°C is shown. Point color corresponds to bout type (left, right, forward), and point size corresponds to inter-bout interval. (d,b,e) Pipeline to convert N-HMM-generated state sequences to swim trajectories. (d) The N-HMM is first sampled to generate a sequence of forward/left/right internal states. The sequence is then temporally rescaled and sampled as before (see panel b). (e) Swim trajectories are constructed as before (see panel c). An example N-HMM-generated trajectory at 26°C is shown. (f) Distributions of reorientation angles , inter-bout intervals , and bout distances d_n; for the aggregated multiple-fish trajectories (gray), trajectories generated from B-HMM (black), and generated from N-HMM (blue); at 22°C. (g) Mean Square Reorientation (MSR) accumulated after q bouts for aggregated multiple-fish trajectories (normal : grey, shuffled : red dashed), single-fish long trajectories (green), and trajectories generated from N-HMM (blue). For both long and N-HMM-generated trajectories, we show the mean and standard deviation over all individuals (solid line and band). (see S7 Fig for individual trajectories and all temperatures) (h) MSR at q = 10 bouts, with mean (horizontal bars) and standard deviation (vertical bars).

doi: https://doi.org/10.1371/journal.pcbi.1013762.g006