allensdk.brain_observatory.behavior.behavior_ophys_session module

class allensdk.brain_observatory.behavior.behavior_ophys_session.BehaviorOphysSession(api=None, eye_tracking_z_threshold: float = 3.0, eye_tracking_dilation_frames: int = 2)

Bases: allensdk.brain_observatory.session_api_utils.ParamsMixin

Represents data from a single Visual Behavior Ophys imaging session. Can be initialized with an api that fetches data, or by using class methods from_lims and from_nwb_path.

average_projection

2D image of the microscope field of view, averaged across the experiment :rtype: pandas.DataFrame

cache_clear(self) → None

Convenience method to clear the api cache, if applicable.

cell_specimen_table

Cell roi information organized into a dataframe; index is the cell roi ids. :rtype: pandas.DataFrame

corrected_fluorescence_traces

The motion-corrected fluorescence traces organized into a dataframe; index is the cell roi ids. :rtype: pandas.DataFrame

deserialize_image(self, sitk_image)

Convert SimpleITK image returned by the api to an Image class:

Args:

sitk_image (SimpleITK image): image object returned by the api

Returns

img (allensdk.brain_observatory.behavior.image_api.Image)

dff_traces

Traces of dff organized into a dataframe; index is the cell roi ids. :rtype: pandas.DataFrame

eye_tracking

A dataframe containing ellipse fit parameters for the eye, pupil and corneal reflection (cr). Fits are derived from tracking points from a DeepLabCut model applied to video frames of a subject’s right eye. Raw tracking points and raw video frames are not exposed by the SDK.

Notes: - All columns starting with ‘pupil_’ represent ellipse fit parameters

relating to the pupil.

• All columns starting with ‘eye_’ represent ellipse fit parameters relating to the eyelid.
• All columns starting with ‘cr_’ represent ellipse fit parameters relating to the corneal reflection, which is caused by an infrared LED positioned near the eye tracking camera.
• All positions are in units of pixels.
• All areas are in units of pixels^2
• All values are in the coordinate space of the eye tracking camera, NOT the coordinate space of the stimulus display (i.e. this is not gaze location), with (0, 0) being the upper-left corner of the eye-tracking image.
• The ‘likely_blink’ column is True for any row (frame) where the pupil fit failed OR eye fit failed OR an outlier fit was identified.
• All ellipse fits are derived from tracking points that were output by a DeepLabCut model that was trained on hand-annotated data frome a subset of imaging sessions on optical physiology rigs.
• Raw DeepLabCut tracking points are not publicly available.

Return type:pandas.DataFrame

classmethod from_lims(ophys_experiment_id: int, eye_tracking_z_threshold: float = 3.0, eye_tracking_dilation_frames: int = 2) → 'BehaviorOphysSession'

classmethod from_nwb_path(nwb_path: str, **api_kwargs: Any) → 'BehaviorOphysSession'

get_average_projection(self)

Returns an image whose values are the average obtained values at each pixel of the ophys movie over time.

Returns:

allensdk.brain_observatory.behavior.image_api.Image:

array-like interface to max projection image data and metadata

get_cell_specimen_ids(self)

get_cell_specimen_indices(self, cell_specimen_ids)

get_dff_traces(self, cell_specimen_ids=None)

get_max_projection(self)

Returns an image whose values are the maximum obtained values at each pixel of the ophys movie over time.

Returns:

allensdk.brain_observatory.behavior.image_api.Image:

array-like interface to max projection image data and metadata

get_performance_metrics(self, engaged_trial_reward_rate_threshold=2)

get_reward_rate(self)

get_roi_masks(self, cell_specimen_ids=None)

Obtains boolean masks indicating the location of one or more cell’s ROIs in this session.

Parameters:

cell_specimen_ids : array-like of int, optional

ROI masks for these cell specimens will be returned. The default behavior is to return masks for all cell specimens.

Returns:

result : xr.DataArray

dimensions are:

• cell_specimen_id : which cell’s roi is described by this mask?
• row : index within the underlying image
• column : index within the image

values are 1 where an ROI was present, otherwise 0.

get_rolling_performance_df(self)

get_segmentation_mask_image(self)

Returns an image with value 1 if the pixel was included in an ROI, and 0 otherwise

Returns:

allensdk.brain_observatory.behavior.image_api.Image:

array-like interface to segmentation_mask image data and metadata

licks

A dataframe containing lick timestamps. :rtype: pandas.DataFrame

max_projection

2D max projection image. :rtype: allensdk.brain_observatory.behavior.image_api.Image

metadata

Dictionary of session-specific metadata. :rtype: dict

motion_correction

A dataframe containing trace data used during motion correction computation :rtype: pandas.DataFrame

ophys_experiment_id

Unique identifier for this experimental session. :rtype: int

ophys_timestamps

Timestamps associated with frames captured by the microscope :rtype: numpy.ndarray

rewards

A dataframe containing timestamps of delivered rewards. :rtype: pandas.DataFrame

running_data_df

Dataframe containing various signals used to compute running speed :rtype: pandas.DataFrame

running_speed

Running speed of mouse. NamedTuple with two fields

timestamps : numpy.ndarray

Timestamps of running speed data samples

values : np.ndarray

Running speed of the experimental subject (in cm / s).

Return type:allensdk.brain_observatory.running_speed.RunningSpeed

segmentation_mask_image

An image with pixel value 1 if that pixel was included in an ROI, and 0 otherwise :rtype: allensdk.brain_observatory.behavior.image_api.Image

stimulus_presentations

Table whose rows are stimulus presentations (i.e. a given image, for a given duration, typically 250 ms) and whose columns are presentation characteristics. :rtype: pandas.DataFrame

stimulus_templates

A dictionary containing the stimulus images presented during the session keys are data set names, and values are 3D numpy arrays. :rtype: dict

stimulus_timestamps

Timestamps associated with stimulus presentations on the monitor (corrected for monitor delay). :rtype: numpy.ndarray

task_parameters

A dictionary containing parameters used to define the task runtime behavior. :rtype: dict

trials

A dataframe containing behavioral trial start/stop times, and trial data :rtype: pandas.DataFrame