Anxiety Depression

Mood Disorders

Mood disorders are currently ranked as one of the major disease categories worldwide. According to the World Health Organization, depression, the most common mood disorder, affects an estimated 350 million people of all ages. The various classifications of mood disorder each display symptoms and signs whose origins and biological substrates are only partly understood.

One of the major challenges with studying affective disorders is efficient and timely disease diagnosis and the development of more efficient pharmacological and non-pharmacological treatments.

In the research community, it is particularly difficult to study and develop treatments for mood disorders because animal models often do not share comparable behavioral/physiological signs or such disease symptoms do not mimic the human condition in a satisfactory manner.

Because of these limitations, scientists have tried to model and treat only a few of the symptoms that are present both in humans and in animal models. Some of the most robust and objectively measurable symptoms (also known as biomarkers) are represented by alterations of physiological parameters such as heart rate or body temperature.

A detailed study of these biomarkers can better clarify the biological substrates, and temporal dynamics of the disease, and help identify better treatments.

Parameters & Behavior:

Physiologic biomarkers for a better translational approach for mood disorder models are:

  • Autonomic nervous system dysregulation at the level of the heart, e.g. heart rate variability (HRV) changes 1,2( HRV)
  • Aberrant EEG patterns in sleep stages3 (changes in frequency component/sleep deprivation) (Sleep)
  • Changes in thermoregulatory mechanisms 4(hyperregulation of the thermoregulatory center)è (Thermoregulation)


Using DSI devices in the animal models and combining these data with behavioral observations may offer improved temporal resolution that is needed to create objective markers that will help identify novel gene/drug candidates

Small Animal Implantable Telemetry System – The system is composed of receiver plates (placed below the cage). The signals are then routed through a matrix (MX2) interface into a PC for real time signal collection using network standards (Router and Switch).

Learn more about mouse and small animal telemetry specifications from DSI.

System image

Large Animal Implantable Telemetry System (PhysioTel Digital) – The system is composed of receiver plates placed in the cage that allow group housing of animals and larger cages. The signal are then routed through a matrix interface into a PC for real time signal collection using network standards (Router and Switch).

Learn more about large animal telemetry specifications from DSI.

Hardwired Monitoring System – DSI’s hardwired solutions provide a minimally invasive method to offer continuous measurement (EEG, EMG, EOG, etc.) during central nervous system studies with small animals.  Hardwired solutions allow the use of a tether solution to monitor up to 12 EEG/EMG channels with higher input bandwidths (0.05 Hz to 20 kHz).    

A typical setup includes the use of electrodes, wires, and commutators (researcher’s choice). Wires on the other end of the commutator are connected to DSI's BIO12POD. With the use of digital signal conditioners/amplifiers, brain (EEG) or muscle (EMG) signals are brought into DSI’s Ponemah software platform.

Learn more about Signal Conditioners and accessory PODS from DSI.


Anipill Temperature Monitoring – Anipill is a simple and portable system that automatically collects temparature in a variety of housing environments.

Learn more about Anipill Temperature Implants from DSI.


NeuroScore Software – After data acquisition has taken place, DSI’s NeuroScore™ software can be used to efficiently analyze chronic data sets common to neuroscience studies.  This modular platform offers sleep scoring, seizure detection, video synchronization, and batch processing capabilities. 

Learn more about NeuroScore software from DSI.

Neuroscore, Sleep Scoring, Rodent Sleep Scoring, cns software


Sgoifo, A., Carnevali, L., Alfonso Mde, L. & Amore, M. Autonomic dysfunction and heart rate variability in depression. Stress 18, 343-352, doi:10.3109/10253890.2015.1045868 (2015).

Viviani, D. et al. Oxytocin selectively gates fear responses through distinct outputs from the central amygdala. Science 333, 104-107, doi:10.1126/science.1201043 (2011).

Alenina, N. et al. Growth retardation and altered autonomic control in mice lacking brain serotonin. Proc Natl Acad Sci U S A 106, 10332-10337, doi:10.1073/pnas.0810793106 (2009).

Pattij, T. et al. Autonomic changes associated with enhanced anxiety in 5-HT(1A) receptor knockout mice. Neuropsychopharmacology 27, 380-390, doi:10.1016/S0893-133X(02)00317-2 (2002).