# Wired to Rest - Neural Architecture of Sleep States
Lakshman Abhilash

## Experimental Preparation

**System and materials.**

The primary experimental platform in this module is the Drosophila
Activity Monitor (DAM) system, manufactured by [Trikinetics
Inc.](https://trikinetics.com) (Waltham, MA).

1.  Individual adult flies are loaded into 5mm glass tubes containing
    sucrose-agar food at one end and sealed at the other with a small
    piece of white yarn, which permits gas exchange while preventing the
    flies from escaping.
    1)  Sucrose-agar food can be made using the following recipe. For
        125mL of food, mix the following in a 1000mL conical flask:
        1)  *125mL de-ionized water.*
        2)  *2.5g Bactoagar.*
        3)  *5g of sucrose.*
    2)  Microwave the mixture until completely dissolved. The solution
        should be transparent and have a yellow/golden color. Keep an
        eye to avoid spills.
    3)  Pour the mixture into a glass petri-dish. Make bundles of
        locomotor tubes with ~35 tubes per bundle. *Note. These tubes
        must be 65mm long and have a diameter of 5mm.*
    4)  These bundles are then dipped into the glass petri-dish with the
        media. Food rises up the tubes through capillary action.
2.  Each loaded tube is inserted into a DAM monitor, which houses 32
    tubes arranged in a grid, with a single infrared (IR) beam passing
    transversally through each tube.
3.  The DAM monitors are then connected to a recording computer as per
    instructions from [Trikinetics Inc](https://trikinetics.com).

**Experimental logic.**

Every time a fly interrupts its beam, the event is registered by the
recording computer as a unit of locomotor activity, binned in 1-minute
intervals across the full duration of the experiment. This is an elegant
example of engineering in service of biology: a highly reliable,
automated system capable of resolving the fine temporal structure of
behavioral regulation across large numbers of animals simultaneously.

**Protocol design.**

The experimental protocol spans 14 days and is structured in two phases
that together allow circadian and homeostatic regulation of sleep to be
dissected independently.

1.  Days 1 to 4 (entrainment): Monitors are placed in a controlled
    environment (an incubator) under a 12:12 Light:Dark (LD) cycle and
    25 degrees Celsius. The external light-dark cycle entrains flies’
    circadian clocks and provides the temporal reference necessary to
    assess sleep bout timing, phase, and proxies of sleep depth,
    analogous to how polysomnography or wearable consumer devices infer
    sleep-stage architecture from continuous physiological recordings in
    humans.
2.  Days 5 to 14 (free-running): Monitors are transferred to constant
    darkness (DD). This is done by switching the environment in the
    incubator without disturbing the monitors. In the absence of
    environmental timing cues, the free-running, endogenously driven
    circadian regulation of sleep states can be isolated and quantified
    without the confound of environmental influence.

This LD-to-DD transition is a foundational paradigm in chronobiology,
giving students direct, hands-on experience with one of the most
powerful experimental strategies for separating clock-driven from
environmentally modulated behavioral outputs in a concrete application
of controlled experimental design, as foregrounded in NGSS practices.

## Classroom Execution

**Scale.**

The scale of data generated in this module is itself a central feature
of the learning experience. A classroom of 30 students, each setting up
one monitor, can collectively record behavioral data from up to 960
flies across 14 days. With activity logged every minute for each animal
over this period, the class generates nearly 20 million data points
(19,353,600, to be precise).

**From raw data to analysis.**

Rather than treating this volume as an obstacle, the module uses it as a
window into the realities of modern systems neuroscience, where
large-scale data collection and computational analysis are
indispensable. Students are introduced to pipelines that make this
tractable on a standard laptop:

1.  ***Quality control:*** Raw data files are first processed through
    [DAMScan](https://trikinetics.com), quality-control software by
    Trikinetics that identifies and flags recording errors, dropped
    readings, and anomalous entries, producing clean datasets ready for
    analysis.
2.  ***Analysis:*** Students then use
    *\[phaseR\]*(https://github.com/abhilashlakshman/phaseR), an
    open-source analytical tool developed specifically for quantifying
    *Drosophila* sleep states and their circadian and homeostatic
    regulation.
    1)  Through *phaseR*, students compute sleep duration, bout number
        and architecture (proxies for sleep depth and homeostatic
        drive),
    2)  and the period and robustness of free-running circadian rhythms
        in sleep states.
    3)  Detailed protocols for *phaseR* can be found
        [here](https://github.com/abhilashlakshman/phaseR/blob/main/phaseR_UserManual_v01.html).
        Note. Download the HTML file to your local computer and open it
        on any web browser.
    4)  The R package for most functions used in *phaseR* can be found
        [here](https://cran.r-project.org/web/packages/phase/index.html)
        on CRAN. An example dataset is part of the package which
        students can use.

**What students take from this.**

1.  Engagement with this computational workflow prompts students to
    think carefully about
    1)  the statistical properties of data,
    2)  the assumptions underlying quantitative methods,
    3)  what different measures do and do not capture,
    4)  and how inferential choices shape scientific conclusions.
2.  By interpreting longitudinal, high-throughput behavioral datasets,
    students develop
    1)  quantitative reasoning,
    2)  computational analysis,
    3)  and evidence-based argumentation skills.

The module thus cultivates not only technical fluency but epistemic
awareness, an understanding of the relationship between data, models,
and claims that are essential to rigorous scientific reasoning.

Situated within the broader curriculum, this module connects
developmental origin and synaptic connectivity explored in other modules
to observable behavior, reinforcing the integrative, NGSS-aligned
approach of inquiry-driven experimentation and evidence-based reasoning
that runs throughout the pedagogical sequence.