Reference: Input Fields

Note: A formal definition of the input structure is provided as a json-schema definition, see the /v3/schema endpoint. Any structural discrepancies between the following table and the json-schema definition indicates an error in this table, the json-schema is definitive.

Required

Note: these first 4 top level fields must be specified in every query.

Input Field	Value/s	Description
`batch_label`	Required: Yes – API will return an error if no value is provided. Default: None Format: Any string, up to 255 characters. Example: `"batch_label": "group_1"`	A label to identify batches of related queries in a single upload that should be collated for return. This is relevant when files are uploaded using a web-browser. It allows you to submit a file with an array of queries but get an individual email of links for each group having a common `batch_label`.
`person_ID`	Required: Yes – API will return an error if no value is provided. Default: None Format: Any string, up to 255 characters. Example: `"person_ID": "Bobby42"`	A label to identify the person (eg. in a roster) that a query relates to.
`start_time`	Required: Yes – API will return an error if no value is provided. Default: None. Format: - Sydney Models: `YYYY-MM-DD'T'hh:mm:ss+hh:mm` - Other Models: `YYYY-MM-DD'T'hh:mm:ss+hh:mm` Example: - Sydney Models: `"start_time": "2021-02-16T00:00:00+10:00"` - Other Models: `"start_time": "2021-02-16T08:00:00+10:00"`	Start-time of the protocol Model evaluation and returned results begin at this date-time. Note: Default initial conditions are configured for the simulation of Sydney models to begin at `00:00:00`, and for non-Sydney models to begin at `08:00:00`. So, it is an error to specify start-times other than these without also specifying non-default initial conditions.
`time_zone`	Required: Yes – API will return an error if no value is provided. Default: None. Format: String, one of a fixed set Example: `"time_zone": "Australia/Brisbane"`	Time-Zone of the Start-time of the protocol IANA time-zones

Common

Note: none of the top level fields here are required, that is, if you do not need them simply do not include them, however, once you specify a top-level field with sub-fields (eg. forced_wake), then most of its sub-fields are required.

Input Field	Value/s	Description
`evaluation_type`	Required: No Default: `predictions` Format: String, one of a fixed set Select From: `predictions` `recommendations` Example: `"evaluation_type": "predictions"`	Defines how the model should be evaluated. Specifically, whether it should be run a single time to generate predictions, or multiple times to identify recommendations that optimise a desired sleep or alertness property. See `optimisation_objective` .
`optimisation_objective`	Required: No Default: `average-alertness` Format: String, one of a fixed set Select From: `total-sleep-time` `minimum-alertness` `average-alertness` Example: `"optimisation_objective": "total-sleep-time"`	For `evaluation_type: "recommendations"`, this field specifies the optimisation objective for the recommendation algorithm. Currently, three options are supported: Maximise `total-sleep-time`; Maximise the `minimum-alertness` during shift and commute; and Maximise the `average-alertness` during shift and commute.
`output_set`	Required: No Default: `default`; `recommendations-default` Format: String, one of a fixed set Select From: `default` `default-raster` `recommendations-default` `recommendations-raster` `sleep` `sleep-raster` `continuation` `continuation-raster` `alertnessCRC-new` `scheduling-old` `scheduling-new` `custom` Example: `"output_set": "sleep"`	Defines output measures and format. Note: See the listing of Predefined Output-Sets and the Output descriptions for more detail. Note: The `custom` option does not actually correspond to a predefined `output_set`. It instead indicates that the `output_config` field will be provided to specify a custom configuration for the desired output. See the Custom output-config field.
`forced_wake` Note: while `forced_wake` is not required, if provided then most sub-fields are required.	Required: No Default: None Format: An object containing 6 fields: `label`; `start_time`; `end_time`; `lead_duration`; `lag_duration` and `time_zone`. As described in the following rows	Periods of time with forced wakefulness. Can be periods of sleep deprivation in a clinical or experimental setting, or work shifts and social commitments in real world settings.
`forced_wake` `label`	Required: Yes Default: None Format: Any string, up to 255 characters. Examples: `shift`; `day-shift`; `social`; `advanced-basket-weaving-class`.	A string to identify a particular type of forced wake. Any value can be used, however, those with `shift` as a sub-part are used to identify time periods relevant to the calculation of some types of output.
`forced_wake` `start_time`	Required: Yes Default: None Format: Array of date-time strings, `YYYY-MM-DD'T'hh:mm:ss+hh:mm` Example: `"start_time": ["2020-01-22T22:00:00+10:00"]`	Start time/s of this type of forced-wake. Note: must have a matching entry in the `forced_wake` `end_time` field.
`forced_wake` `end_time`	Required: Yes Default: None Format: Array of date-time strings, `YYYY-MM-DD'T'hh:mm:ss+hh:mm` Example: `"end_time": ["2020-01-23T07:30:00+10:00"]`	End time/s of this type of forced-wake. Note: must have a matching entry in the `forced_wake` `start_time` field.
`forced_wake` `lead_duration`	Required: Yes Default: None Format: A single number, hours. Example: `"lead_duration": 0.5`	Duration (hours) required before forced-wake event, the time-interval implied by this duration is also treated as forced-wake, eg. Commute time to work.
`forced_wake` `lag_duration`	Required: Yes Default: None Format: A single number, hours. Example: `"lag_duration": 0.5`	Duration (hours) required after forced-wake event, the time-interval implied by this duration is also treated as forced-wake, eg. Commute time from work.
`forced_wake` `time_zone`	Required: No Default: Time-Zone Specified for initial time-zone. Format: String, one of a fixed set Example: `"time_zone": "Australia/Brisbane"`	Time-Zone of these forced-wakes IANA time-zones Note: if omitted the top level time-zone is assumed to apply to these date-times.
`light` Note: while `light` is not required, if provided then most sub-fields are required.	Required: No Default: None Format: An object containing 5 fields: `label`; `start_time`; `end_time`; `photopic_lux`; and `time_zone`. As described in the following rows	Specific light information can be provided as coarsely as a single value for an entire simulation, by referenced time-intervals, such as an average value during shift, or as fine grained as minute-by-minute values (eg as recorded by a worn light meter). Any value provided here replaces the built-in diurnal light-profile at the specified time.
`light` `label`	Required: Yes Default: None Format: Any string, up to 255 characters. Examples: `shift`; `day-shift`; `social`; `advanced-basket-weaving-class`.	Identifies the light intervals. When explicit `start_time` and `end_time` are specified as empty arrays, `[]`, this label is used to identify the intervals to which the specified `photopic_lux` applies, and so must match a forced_wake label.
`light` `start_time`	Required: Yes Default: None Format: Array of date-time strings, `YYYY-MM-DD'T'hh:mm:ss+hh:mm` Example: `"start_time": ["2020-01-22T22:00:00+10:00"]`	Start time/s of Note: must have a matching entry in the `light` `end_time` field.
`light` `end_time`	Required: Yes Default: None Format: Array of date-time strings, `YYYY-MM-DD'T'hh:mm:ss+hh:mm` Example: `"end_time": ["2020-01-23T07:30:00+10:00"]`	End time/s of Note: must have a matching entry in the `light` `start_time` field.
`light` `photopic_lux`	Required: Yes Default: `[250]` Format: An array of numbers, either a single entry or `[lux1, lux2,...,luxn]`, where `n` is the number of arrays in `light_start` and `light_end`. Values must be between `0` and `100000`. Example: `"photopic_lux": [13, 1981.0121, 42.77]`	White-light illuminance in lux.
`light` `time_zone`	Required: No Default: Time-Zone Specified for initial time-zone. Format: String, one of a fixed set Example: `"time_zone": "Australia/Brisbane"`	Time-Zone of these forced-wakes IANA time-zones Note: if omitted the top level time-zone is assumed to apply to these date-times.

Custom Output

The field described here is for requesting custom output, ie, when setting output_set: "custom".

Input Field	Value/s	Description
`output_config` Note: `output_config` is required when `output_set: "custom"`	Required: No Default: None Format: An object containing 11 fields: `data_format`; `figure_format`; `time_format`; `duration_format`; `time_series`; `instants`; `instant_samples`; `intervals`; `interval_samples`; `durations`; and `figures`. As described in the following rows	Object for configuring customised output.
`output_config` `data_format`	Required: No Default: `json` Format: String, one of a fixed set Select From: `json` `TODO(SAK): mat` Example: `"data_format": "json"`	File Format for Data Output
`output_config` `time_format`	Required: No Default: `date-time` Format: String, one of a fixed set Select From: `date-time` `date-time-local` `seconds` `minutes` `hours` `day` Example: `"time_format": "minutes"`	Format used for date-time output. The format is specified as one of six predefined types and governs the format the output is written. The `date-time` and `date-time-local` return date-time strings, the first in the time-zone of the initial `start_time`, while local sets time-zone based on the time-zone of the most recent preceding date-time input, eg forced-wake, light, etc. The duration types (`seconds`, `minutes`, etc) are durations in the specified units relative to the initial `start_time`.
`output_config` `duration_format`	Required: No Default: `minutes` Format: String, one of a fixed set Select From: `seconds` `minutes` `hours` `days` Example: `"duration_format": "hours"`	Format (Units) Used for Duration Output The format is specified as one of four predefined types and governs the units used when durations are output. The duration types (`seconds`, `minutes`, etc) are durations in the specified units relative to the initial `start_time`.
`output_config` `figure_format`	Required: No Default: `png` Format: String, one of a fixed set Select From: `png` `jpg` `tiff` `eps` `svg` `fig` Example: `"figure_format": "svg"`	File Format for the Figure Output The format is specified as one of the predefined types and governs the file format used when saving figures.
`output_config` `time_series`	Required: No Default: `None` Format: Array of Objects, with fields: Fields: `interval` String, one of a fixed set `sampling_period` Number [minutes] `measure` String, one of a fixed set `statistic` String, one of a fixed set Example: `"time_series": [{"interval": "simulation", "sampling_period": 30, "statistic": "value", "measure": "melatonin-urine"}]`	An array time-series specification objects. For each required time-series (periodically sampled measure), an object specifying the time-`interval` to sample from, the `sampling_period`, the name of the `measure` to be sampled, and the `statistic` used to accumulate values at the `sampling_period`. For supported `interval`s, `measure`s, and `statistics`, see examples elsewhere in this documentation and the json-schema definition.
`output_config` `instant_samples`	Required: No Default: `None` Format: Array of Objects, with fields: Fields: `interval` String, one of a fixed set `instant` String, one of a fixed set `measure` String, one of a fixed set Example: `"instant_samples": [{"interval": "simulation", "instant": "sleep-start", "measure": "melatonin-urine"}]`	Data Sampled at Specific Time-Instants. For each required instant-sample (aperiodically sampled measure), an object specifying the time-`interval` to sample from, the name of the `measure` to be sampled, and the time-`instant`s at which to sample.
`output_config` `interval_samples`	Required: No Default: `None` Format: Array of Objects, with fields: Fields: `interval` String, one of a fixed set `measure` String, one of a fixed set `statistic` String, one of a fixed set Example: `"interval_samples": [{"interval": "forced-wake", "statistic": "max", "measure": "vPVTL"}]`	Data Sampled within Time-Intervals. Interval-samples are used to return a single value for each instance of the specified interval. For each required interval-sample, an object specifying the time-interval to sample from, the name of the `measure` to be sampled, and the `statistic` used to accumulate values over each instance of the requested `interval`.
`output_config` `instants`	Required: No Default: `None` Format: Array of Objects, with fields: Fields: `interval` String, one of a fixed set `label` String, one of a fixed set For `label`, Select From: `midnight` `forced-wake-start` `forced-wake-start-shift` `pre-forced-wake-start` `pre-forced-wake-start-shift` `forced-wake-end` `forced-wake-end-shift` `post-forced-wake-end` `post-forced-wake-end-shift` `sleep-start` `sleep-end` `wake-start` `wake-end` `alertness-level-green-start` `alertness-level-green-end` `alertness-level-yellow-start` `alertness-level-yellow-end` `alertness-level-red-start` `alertness-level-red-end` `core-body-temperature-minimum` `core-body-temperature-local-minima` `core-body-temperature-local-maxima` `melatonin-synthesis-onset` `melatonin-synthesis-cease` `melatonin-dlmo-sthilaire` `melatonin-dlmo-khalsa` `melatonin-peak-dijk` `melatonin-urine-peak` `melatonin-urine-local-minima` `melatonin-urine-local-maxima` `melatonin-saliva-local-minima` `melatonin-saliva-local-maxima` `melatonin-saliva-dlmo` `melatonin-plasma-local-minima` `melatonin-plasma-local-maxima` `melatonin-plasma-dlmo` `melatonin-synthesis-active-start` `melatonin-synthesis-active-end` `melatonin-synthesis-inactive-start` `melatonin-synthesis-inactive-end` Example: `"instants": [{"interval": "wake", "label": "alertness-level-red-start"}]`	Time-Instants Note: any instants requested for instant-samples are included implicitly, so you only need to specify required timing output not already implicitly included.
`output_config` `intervals`	Required: No Default: `None` Format: Array of Strings, from a fixed set Select From: `simulation` `forced-wake` `forced-wake-shift` `pre-post-forced-wake` `pre-post-forced-wake-shift` `pre-forced-wake` `pre-forced-wake-shift` `post-forced-wake` `post-forced-wake-shift` `sleep-opportunity` `sleep` `wake` `alertness-level-green` `alertness-level-yellow` `alertness-level-red` `melatonin-synthesis-active` `melatonin-synthesis-inactive` Example: `"intervals": ["sleep", "sleep-opportunity"]`	An array interval specification strings. Note: any intervals requested for time-series instant-samples or interval-samples are included implicitly, so there is no need to specify implicitly included intervals again here.
`output_config` `durations`	Required: No Default: `None` Format: Array of Objects, with fields: Fields: `interval` String, one of a fixed set `state` String, one of a fixed set Example: `"durations": [{"interval": "sleep"}, {"interval":"sleep-opportunity"}, {"interval": "wake", "state": "alertness-level-red"}]`	For each required duration, an object specifying the time-interval for which the duration is wanted. Optionally, a state can be specified, with the duration for that state within the interval being returned.
`output_config` `figures`	Required: No Default: Format: Array of Strings, from a fixed set Select From: `raster-outputs` `raster-inputs` Example: `"figures": "raster-outputs"`	Figures to Generate.

Advanced

The fields listed here are primarily of use for advanced use-cases such as individualising model predictions and recommendations.

Input Field	Value/s	Description
`V_initial`	Required: No Default: Values corresponding to being rested and entrained to local light-dark cycle. Format: Array of numbers, model dependent `phillips_2010`, `postnova_2016` [`lVLPO(t0)`, `lMA(t0)`, `CIRC_X(t0)`, `CIRC_XC(t0)`, `CIRC_N(t0)`, `lH(t0)`, `WEFFORT(t0)`] `sydney_crc_2017` [`lVLPO(t0)`, `lMA(t0)`, `CIRC_X(t0)`, `CIRC_XC(t0)`, `CIRC_N(t0)`, `lH(t0)`, `P(t0)`, `Pmin(t0)`, `WEFFORT(t0)`] `mccauley_2013` [`p(t0)`, `u(t0)`, `kappa(t0)`] `rajdev_2013` [`S(t0)`, `Debt(t0)`] `ingre_2014` [`S(t0)`, `C(t0)`, `U(t0)`, `W(t0)`] `phillips_2017` [`A_tot(t0)`, `R_tot(t0)`] `johnson_2004` [`P(t0)`, `M(t0)`]	Initial values for model variables. This corresponds to the assumed state of the person at the beginning of a simulation. For Sydney models the default initial values are for state at midnight (`00:00:00`). For other models it is state at `08:00:00`.
`duration_days`	Required: No Default: See descriptions. Format: Single number, days. Maximum allowed via the API is `14`. Example: `"duration_days": 5.5`	Duration of simulation in days. Used to extend the models evaluation beyond the time period of the provided context, eg., forced-wake times. When evaluating a model for predictions, the duration defaults to the time between `start_time` and midnight at the end of the last day for which explicit times were provided. For recommendations the default end is the final explicitly provided time. If a provided `duration_days` is smaller than these respective values then it is ignored. But, if it is longer, the simulation will be run from `start_time` to `start_time` + `duration_days`.

Research

The fields listed here are primarily of use for research purposes, they generally should not be modified unless you know what you’re doing.

Input Field	Value/s	Description
`model`	Required: No Default: `sydney_crc_2017` Format: String, one of a fixed set Select From: `postnova_2016` `sydney_crc_2017` `phillips_2010` `mccauley_2013` `rajdev_2013` `phillips_2017` `ingre_2014` `johnson_2004` Example: `model: "postnova_2016"`	Specifies which model of sleep-wake and alertness should be evaluated. See the Models section of the user guide for more detail. If you are unsure, stick with the default. That is, do NOT specify a model.
`sleep_opportunity` Note: while `sleep_opportunity` is not required, if provided then most sub-fields are required.	Required: (model dependent) Sydney: No other: Yes Format: An object containing 3 fields: `start_time`; `end_time`; and `time_zone`. As described in the following rows	Specify time-intervals of sleep-opportunity Inverse of, and overrides, forced-wake. For Sydney models, which predict sleep times, it is strongly preferred to specify context in terms of forced-wake only. For models that do not predict sleep, this field is required for specifying sleep.
`sleep_opportunity` `start_time`	Required: Yes Default: None Format: Array of date-time strings, `YYYY-MM-DD'T'hh:mm:ss+hh:mm` Example: `"start_time":["2020-01-22T22:00:00+10:00"]`	Start time/s of sleep opportunities/episodes. Note: Implies forced-wake at all other time. Note: For non-Sydney models if no sleep times are specified the model is always awake. Note: must have a matching entry in the `sleep_opportunity` `end_time` field.
`sleep_opportunity` `end_time`	Required: Yes Default: None Format: Array of date-time strings, `YYYY-MM-DD'T'hh:mm:ss+hh:mm` Example: `"end_time":["2020-01-23T07:30:00+10:00"]`	End time/s of Note: Implies forced-wake at all other time. Note: For non-Sydney models if no sleep times are specified the model is always awake. Note: must have a matching entry in the `sleep_opportunity` `start_time` field.
`sleep_opportunity` `time_zone`	Required: No Default: Time-Zone Specified for initial time-zone. Format: String, one of a fixed set Example: `time_zone: "Australia/Brisbane"`	Time-Zone of these sleep-opportunity IANA time-zones Note: if omitted the top level time-zone is assumed to apply to these date-times.
`simulation_sampling_period_minutes`	Required: No Default: `1` minute Format: Single number, minimum `1`, maximum `15`.	Simulation sample period in minutes.
`ambient_light`	Required: No Default: `default` Format: String, one of a fixed set Select From: `default` `local` Example: `ambient_light: "local"`	Specifies the form of ambient/background lighting to use. The `default` option, which can be omitted as it is in effect by default, is the only option experimentally validated. It provides fixed day/night light levels between 08:00 and 20:00. The ‘local’ option sets a profile with sunrise and sunset times based on time-zone and date. Any lighting provided by the ‘light’ input field overrides this background profile. Note: Only affects models that incorporate light into their predictions.

Only Sydney-Groups Models

The following input fields are only applicable to the Sydney models.

Note: The parameters listed below are just those that are considered to be somewhat safe to modify, however, all model parameters (more than just the few listed below) are accessible following a similar pattern.

Input Field	Value/s	Description
`model_parameters`	Required: No Default: None Format: `model_parameters` is itself a `json` object with sub-fields: `pars`; `homeostatic`; `time_constants`; `circ`; and `task_shift`.	Used to override default values used for a model’s parameters. Individual sub-fields are described in the following rows.
`model_parameters` `pars` `A_v`	Required: No Default: `{"Av":-10.3}` Format: `pars` is a `json` object, its sub-field `A_v` is a single number Example: `"pars":{"Av":-10.3}`	Combined external influences on the VLPO, units: mV. Main effect on sleep onset time, total sleep time, and phase angle.
`model_parameters` `homeostatic` `nu_Hm`	Required: No Default: `{"nu_Hm": 4.57}` Format: `homeostatic` is a `json` object, its sub-field `nu_Hm` is a single number Example: `"homeostatic":{"nu_Hm":4.57}`	Connection strength from the MA to H, units: mV. Main effect on sleep onset time and phase angle
`model_parameters` `time_constants` `tau_H`	Required: No Default: `{"tau_H": 212400}` Format: `time_constants` is a `json` object, its sub-field `tau_H` is a single number Example: `"time_constants":{"tau_H":212400.0}`	Time constant of the homeostatic drive, units: seconds. The default value corresponds to 59.0 hours. Main effect on sleep onset time and phase angle
`model_parameters` `circ` `tau_C`	Required: No Default: `{"tau_C":87120.0}` Format: `circ` is a `json` object, its sub-field `tau_C` is a single number Example: `"circ":{"tau_C":87120.0}`	Endogenous circadian period, units: seconds. The default value corresponds to 24.2 hours Main effect on circadian period, sleep onset time, and phase angle
`model_parameters` `task_shift` `shift` _ `V_WE` This parameter is added as a trial only and does not exist in published models. Note: not validated against data.	Required: No Default: `{"shift": {"V_WE": 1.0}}` Format: `task_shift` is a `json` object, its sub-field `shift` is a `json` object, and `shift`’s sub-field `V_WE` is a single number. Example: `"task_shift":{"shift":{"V_WE": 1.0}}`	Multiplicative scaling applied to the actual value of `V_WE` during shifts. Can be used to simulate effects of task during shift on alertness. Should only be used if the task is expected to affect sleep times post task as well as alertness during task. Main effect on the homeostatic drive during shifts. This changes model dynamics, so sleep times after shifts will be affected as well. The default of 1.0 corresponds to no scaling of `V_WE` during shift.
`processing_parameters`	Required: No Default: None Format: `processing_parameters` is a `json` object with sub-field `task_shift`.	Used to override default values used for post processing of a model’s output. Individual sub-fields are described in the following rows.
`processing_parameters` `task_shift` `vPVTL` `theta_0` NOTE: trailing character is zero. This parameter is added as a trial only and does not exist in published models. Note: not validated against data.	Required: No Default: `{"vPVTL":{"theta_0": 1.0}}` Format: `task_shift` is a `json` object, its sub-field `vPVTL` is a `json` object, and `vPVTL`’s sub-field `theta_0` is a single number. Example: `"theta_0": 1.0` `"task_shift":{"vPVTL":{"theta_0": 1.0}}`	Multiplicative scaling applied to the bias term of the regression model used to calculate vPVTL from the homeostatic and circadian outputs during shifts. The only effect is on vPVTL output during shifts. Decrease of `theta_0` leads to an increase of vPVTL on shifts by a set constant value. It does not affect vPVTL outside of shifts. Recommended for simple simulations of effects of task on alertness.
`processing_parameters` `task_shift` `vPVTL` `theta_H` This parameter is added as a trial only and does not exist in published models. Note: not validated against data.	Required: No Default: `{"vPVTL":{"theta_H": 1.0}}` Format: `task_shift` is a `json` object, its sub-field `vPVTL` is a `json` object, and `vPVTL`’s sub-field `theta_H` is a single number. Example: `"theta_H": 1.0` `"task_shift":{"vPVTL":{"theta_H": 1.0}}`	Multiplicative scaling applied to the homeostatic term of vPVTL during shifts. The only effect is on vPVTL output during shifts. Increase of `theta_H` leads to an increase of vPVTL on shifts with the effect proportional to H. It does not affect vPVTL outside of shifts. Recommended for simple simulations of effects of task on alertness, together with or instead of `theta_0`.
`processing_parameters` `task_shift` `vPVTL` `theta_C` This parameter is added as a trial only and does not exist in published models. Note: not validated against data.	Required: No Default: `{"vPVTL":{"theta_C": 1.0}}` Format: `task_shift` is a `json` object, its sub-field `vPVTL` is a `json` object, and `vPVTL`’s sub-field `theta_C` is a single number. Example: `"theta_C": 1.0` `"task_shift":{"vPVTL":{"theta_C": 1.0}}`	Multiplicative scaling applied to the circadian term of vPVTL during shifts. The only effect is on vPVTL output during shifts. Increase of `theta_C` leads to a decrease of vPVTL on shifts with the effect proportional to C. It does not affect vPVTL outside of shifts.

Research Notes

Access to model parameters:

The models have been validated for group average predictions and for default parameter values only. Thus, at this stage use of the default model parameters is advised for real-world applications of the models. However, if users choose to change model parameters, it is up to them to ensure that the change is appropriate for the problem at hand.
Changes of model_parameters will affect sleep dynamics as described for each parameter. The changes will propagate to changes in all alertness measures because alertness depends on the homeostatic and circadian drives and both are affected by sleep times (effects on the circadian drive are indirect via changes in light profile due to sleep).
All other model parameters described in Postnova et al., 2018 can be made available through the API but are not recommended to be changed by users. The parameters listed in the table above are the ones that are best suited to simulate inter individual variability. For example, see Skeldon et al. 2015 for ideas of how effects of ageing on sleep can be simulated in models of this type

Effects of task during shifts:

Simulation of the effects of task on performance has not yet been validated against data. So, even though a prototype implementation is made available via the task_shift parameters, it is not yet advised for use in real world applications. The group processing_parameters should be used as a first choice to introduce effects of task on vPVTL during shifts. This will change the performance during shifts but won’t otherwise affect model dynamics. An alternative implementation of the effect of task on performance is via model_parameters.task_shift.shift.V_WE. This implementation should only be used when changes in sleep are expected due to different tasks. This may also have longer term effects of dynamics post-shifts.