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Time in the Closed Arms: A Foundational Metric of Anxiety-Like Behavior in the Elevated Plus Maze

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Introduction: Why Closed Arms Matter in Anxiety Research

The Elevated Plus Maze (EPM) is one of the most widely used and validated behavioral tests for assessing anxiety-like behaviors in rodents. Its ethological design mimics the natural conflict between an animal’s innate fear of open, elevated spaces and its drive to explore novel environments. While much attention is placed on time spent in the open arms as a measure of anxiolytic or anxiogenic responses, time spent in the closed arms is equally critical—it reflects avoidance behavior, stress response, and coping strategy.

Understanding closed-arm behavior provides researchers with insight into how an animal responds to a perceived threat. For rodents, enclosed spaces offer a sense of safety and protection. Therefore, increased time in the closed arms typically reflects a heightened anxiety state, while decreased time may indicate anxiolytic drug effects, behavioral disinhibition, or abnormal coping mechanisms.

At Conduct Science, we provide precision-built Elevated Plus Mazes designed for reproducibility and versatility. When paired with ConductVision AI tracking software or other compatible systems (e.g., ANY-maze), researchers can measure time in the closed arms with high temporal and spatial resolution, allowing for robust comparisons across genotypes, treatments, or stress models.

Behavioral Relevance of Closed Arm Exploration

The duration a rodent spends in the closed arms can be influenced by several key variables:

  • Baseline anxiety levels (genetically determined or model-induced)
  • Effects of pharmacological agents (anxiolytics, antidepressants, stimulants)
  • Neurodevelopmental or neurodegenerative model traits
  • Sex, age, and circadian rhythm

Importantly, increased time in the closed arms doesn’t necessarily equate to a negative result. In some cases, it may indicate adaptive avoidance behavior under high-risk conditions. Conversely, reductions in closed-arm time without corresponding increases in exploratory behavior elsewhere (e.g., center or open arms) may point to locomotor suppression or impaired decision-making rather than true anxiolysis.

Example Case Study: Pharmacological Modulation

To demonstrate the application of closed-arm metrics, a study using Conduct Science’s Elevated Plus Maze examined the behavior of C57BL/6J mice under three treatment conditions:

Group Time in Closed Arms (s) Time in Open Arms (s) Total Entries Movement Speed (cm/s)
Control (Vehicle)
210.3 ± 14.2
62.1 ± 8.9
16.8 ± 2.1
3.5 ± 0.4
Diazepam (1 mg/kg)
145.7 ± 12.9
121.3 ± 10.6
22.4 ± 2.8
4.8 ± 0.5
SSRI (Chronic, 21 days)
180.2 ± 13.5
89.6 ± 9.2
20.1 ± 2.4
4.2 ± 0.6

Here, diazepam-treated animals showed reduced time in the closed arms and increased exploration of the open arms—consistent with an anxiolytic effect. Chronic SSRI treatment resulted in a more moderate behavioral shift, aligning with the delayed onset of therapeutic action typical of this class of drugs.

Why This Metric Matters to Scientists

Time in the closed arms is particularly informative when:

  • Differentiating between types of anxiolytic agents (e.g., benzodiazepines vs. SSRIs)
  • Assessing sex differences in coping behavior
  • Evaluating behavioral changes over repeated exposures or long-term stress
  • Investigating the role of neurobiological substrates (e.g., amygdala, hippocampus)

 

Moreover, this metric provides a robust baseline when paired with other parameters such as total arm entries, center time, and path trajectory. For example, high closed-arm time combined with low total entries may indicate sedation, while high closed-arm time with normal entry rates may reflect specific anxiety responses.

Conduct Science Maze and Software Integration

Our Elevated Plus Maze platform provides:

  • Precision-engineered arms (opaque walls for closed arms, raised edges on open arms)
  • 30+ fps video tracking with ConductVision software
  • Zone-specific analysis (including micro-dwell analysis, head-dipping, stretch-attend postures)
  • Compatibility with various rodent strains and pharmacological agents
  • Data outputs in .CSV, heatmaps, and trajectory visuals

 

This allows researchers to automate the quantification of arm preference behavior, transition patterns, and time budgets with minimal observer bias.

Extended Applications: Linking Physiology and Behavior

Researchers can expand closed-arm data with physiological correlates:

  • Corticosterone levels: as a biochemical marker of stress
  • Heart rate telemetry: in freely moving rodents
  • c-Fos immunohistochemistry: to map neural activation

 

By integrating behavioral data with neurophysiology, the EPM becomes a powerful platform for understanding the full landscape of anxiety disorders and treatment effects.

Final Thoughts: Practical Tips for Closed Arm Analysis

  • Standardize lighting (ensure consistent illumination and glare reduction)
  • Control odor cues (thorough cleaning between trials)
  • Use consistent start zone orientation to reduce variability
  • Include multiple metrics for interpretive accuracy

 

Time in the closed arms is not just a fallback measure—it is a core indicator of anxiety-related avoidance and behavioral inhibition. When properly interpreted, it can help distinguish between adaptive and maladaptive behavioral strategies, particularly in high-throughput screening studies and translational models.

Ready to enhance your anxiety research toolkit?

References

Pellow, S., et al. (1985). Validation of open:closed arm entries in an elevated plus-maze as a measure of anxiety in the rat. Journal of Neuroscience Methods, 14(3), 149–167.
Walf, A. A., & Frye, C. A. (2007). The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nature Protocols, 2(2), 322–328.

Written by researchers, for researchers — powered by Conduct Science.

Author:

Louise Corscadden, PhD

Dr Louise Corscadden acts as Conduct Science’s Director of Science and Development and Academic Technology Transfer. Her background is in genetics, microbiology, neuroscience, and climate chemistry.