DOI: 10.5061/dryad.xsj3tx9q6
title: Data from: Slow cortical dynamics generate context processing and novelty detection

description: The cortex amplifies responses to novel stimuli, compared to those
 elicited by redundant stimuli—a function key to efficiently processing
 sensory information and building predictive models of the environment.
 Novelty detection is measured by the “Mismatch Negativity” (MMN) signal,
 the reduction of which represents the best functional biomarker of
 schizophrenia. To better understand the circuit mechanisms of novelty
 detection, we used an auditory “oddball” paradigm and two-photon calcium
 imaging to measure responses to simple and complex stimuli in neuronal
 populations across the mouse auditory cortex. Stimulus statistics and
 complexity generated differences in neural response profiles across
 contexts and auditory cortical subregions. At the population level,
 neuronal ensembles separately and reliably encoded basic auditory
 features, as well as temporal context. Interestingly, stimuli-evoked
 responses were particularly long-lasting, persisting after the stimuli
 ended and affecting responses to future stimuli. These slow network
 dynamics encoded stimulus history and temporal context, generating novelty
 detection. Recurrent neural network models trained on the oddball task
 exhibited slow network dynamics and recapitulated the biological data,
 including context selectivity, MMN, and stimulus-specific adaptation. We
 conclude that the slow dynamics of recurrent cortical networks underlies
 temporal processing of stimuli, a canonical computation that gives rise to
 context-specific encoding and novelty detection.
description: Methods of data collection, preprocessing, and analysis are
 described in detail in the associated article Data was
 collected with two-photon calcium imaging in the Auditory Cortex of awake
 mice that were head fixed and moving on a circular treadmil. Mice were
 presented with auditory oddball stimuli, and many standards control
 variation. Raw data were motion corrected, and regions of interest (ROIs)
 corresponding to cells were demixed with CaImAn. The demixed data is
 provided here.
description: # Slow cortical dynamics generate context processing and novelty detection
 [https://doi.org/10.5061/dryad.xsj3tx9q6](https://doi.org/10.5061/dryad.xsj3tx9q6) ## Description of the data and file structure Each .zip file contains all datasets from a single mouse. Mice *M1* - *M10* ("*missmatch*") are oddball data that were used for Figures 1, 2, 3A-3F. Mice *M226*, *M4264*, *M4265*, *M4266*, *M4371*, *M4372* are variable ISI experiments ("*echo*") used for Figures 3 H-3J.  Each "M" file contains all the datasets collected from the given mouse. Each dataset contains processed calcium imaging data within files ending with "_results_cnmf_sort.mat", along with stimulus and imaging information within files ending with "_processed_data.mat". Finally, "*AC_data_list.csv*" file contains additional information about datasets and mice. Extended details about the experimental methods and analysis are described in detail in the attached publication. Extended descriptions for data files: "**_results_cnmfsort.mat*": files containing processed calcium imaging data. Data was motion corrected with modified Suite2P motion correction, and single neuron traces were demixed using the CaImAn pipeline. After demixing, individual cells were selected using signal-to-noise (SNR) metrics with a custom code (*caiman_sorter*). Below listed are key variables needed for data analysis * *est*: raw CaImAn outputs (documentation [https://caiman.readthedocs.io/en/latest/](https://caiman.readthedocs.io/en/latest/)) * *A*: neuronal spatial components corresponding to regions of interest (ROIs) in calcium imaging data * *C*: neuronal temporal components * *YrA*: temporal residual components. Raw calcium imaging traces are reconstructed with C + YrA * *b*: spatial background components * *f*: temporal background components * *proc*: additional parameters after sorting caiman outputs from *est* via the *caiman_sorter* GUI * *idx_components*: list of indexes containing the selected components from est.A, est.C, est.YrA, etc. * *idx_components_bad*: list of discarded components * *SNR2_vals*: computed SNR values with a more stable algorithms that one in CaImAn, and used for selection * *deconv*: contains deconvolved traces for all CaImAn extracted components using one of the three algorthms (smooth_dfdt (default), foopsi, MCMC) * *smooth_dfdt*: simple algorithm that uses smoothed, rectified first derivative to infer the neuronal firing rate from the raw caclium imaging traces * *S*: trace of deconvolved firing rate proxy data * *ops*: contains parameters used for CaImAn and postprocessing * *init_params_caiman*: contains CaImAm parameters * *eval_params2**:* parameters used for cell selection in *caiman_sorter* GUI * *deconv*: contains deconvolution parameters * *smooth_dfdt.params.gauss_kernel_sigma*: standard deviation of gaussian smoothing kernel during deconvolution "**_processed_data.mat*": files containing input stimulus information, imaging parameters, and recorded behavior (locomotion). * *data*: contains stimulus information data * *frame_data*: imaging parameters * *volume_period*: volume imaging period for each dataset (number of planes*frame period) * *frame_period*: frame imaging period * *frame_times_mpl*: times of each frame, for both single plane or multiplane data * *stim_params*: contains data on oddball parameters * *MMN_freq*: index of frequencies used for oddball * *stim_duration*: stimulus duration * *isi*: interstimulus interval duration * *trials*: number of trials in oddball * *start_freq*: in Hz, the first and lowest frequency * *increase_factor*: octave difference between frequencies * *num_freqs*: number of total frequencies * *stim_times_frame**: the times of each stimulus in terms of frame index* * *stim_times_volt*: the times of each stimulus in terms of ms * *volt_data_binned*: voltage data recorded with microscope containing raw stimulus times, locomotion, etc. * ops: parameters used for processing stimulus information data "**_registration_cmnf.mat*": files containing spatial registration information to map the same cells recorded across datasets from the same field of view (FOV). These were not used in any of the analysis published, but are included here nevertheless. The FOV number for each dataset is listed in the "*AC_data_list.csv*" file, in the "FOV" column. * *A_list*: cell containing all input spatial footprints "*A*" from corresponding datasets. * *fname_list*: list of dataset names for the corresponding FOV * reg_out: cell containing the outputs of registration * idx1: combined "A" file across datasets where all unique spatial footprints have unique indexes. * idx2: array containing registration information, where each row is a unique footprint, with its contents containing the indexes of those same footprints from the input datasets. * "*AC_data_list.csv*": file contains additional information about datasets and mice.  "n/a" values in the "*AC_data_list.csv*" file correspond to "data not available" because it was not recorded. Extended details on experiments and analysis are provided in the attached manuscript, and accompanying code in the GitHub libraries linked below. ## Code/software Widefield mapping analysis: [https://github.com/shymkivy/AC_mapping_analysis](https://github.com/shymkivy/AC_mapping_analysis) Caiman_sorter cell selection GUI : [https://github.com/shymkivy/caiman_sorter](https://github.com/shymkivy/caiman_sorter) Motion correction: [https://github.com/shymkivy/motion_corr_YS](https://github.com/shymkivy/motion_corr_YS) Two photon data analysis: [https://github.com/shymkivy/AC_2p_analysis](https://github.com/shymkivy/AC_2p_analysis) Spatial registration of 2p datasets to widefield [https://github.com/shymkivy/register_2p_to_wf](https://github.com/shymkivy/register_2p_to_wf) RNN model: [https://github.com/shymkivy/RNN](https://github.com/shymkivy/RNN) External pipelines: [CaImAn](https://github.com/flatironinstitute/CaImAn) [Suite2P](https://github.com/MouseLand/suite2p)