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Protein Quantification Protocols

Protein Quantification Protocols

Introduction: Quantitative Method

The estimation of proteins via the quantitative method is one of the basic requirements in biochemistry. Proteins, from various perspectives, are substantially more complex than nucleic acids. Thus, it has been hard to give laboratory protocols that can be applied to proteins. The precise quantitation of the amount of protein during the steps of protein preparation is the only valid method to check the overall value of a procedure.

 

LOWRY Protein Quantification

LOWRY protocol has been the most widely used method to estimate the number of proteins in biological samples. Lowry et al. (1940) was the biochemist who developed the reagent. Copper ion in alkali solution pre-treats the proteins followed by the reduction of phosphomolybdate phosphotungstic acid present in the Folin reagent. The end product of this reaction has a blue color.

Note:

  • An aliquot of the protein-free buffer in the same volume as the protein-containing sample has to be taken as blank as a control.
  • A couple of standards with different amounts of protein between 0 and 100 µg should be measured in each analysis since the reaction conditions may differ from experiment to experiment and the standard curve is not linear.
Solutions/Reagents:
  • 20 g Na2CO3 (anhydrous) in 1000 ml 0.1 N NaOH
    • Anhydrous Sodium Carbonate (Used in the dilution of reagents – [amazon link=”B07MC64C66″ link_icon=”amazon” /])
    • Sodium Hydroxide Reagent (For the dilution of reagents – [amazon link=”B00AUAB0HC” link_icon=”amazon” /] )
  • 1g CuSO4 · 5H2O in 100 ml ddH2O
    • Copper (II) Sulfate (A chemical perfect for use in any biochemistry lab – [amazon link=”B07JD2C6TW” link_icon=”amazon” /] )
    • Distilled Water (Used in the dilution of reagents – [amazon link=”B07MFS5Z3L” link_icon=”amazon” /] )
  • 2g potassium-sodium tartrate in 100 ml ddH2O
    • Potassium Sodium Tartrate( It is a common precipitant in protein crystallography and maintains cupric ions in solution at an alkaline pH – [amazon link=”B07MJDDXWW” link_icon=”amazon” /])
  • mix 1 vol. B and 1 vol. C, and then add 50 vol. A
  • Folin–Ciocalteu’s phenol reagent (stock), 1 + 1 diluted with ddH2O
    • Folin–Ciocalteu’s phenol reagent(Reagent used in LOWRY method – [amazon link=”B07MJDGBT9″ link_icon=”amazon” /] )
  • Standard 5.0 mg/ml ovalbumin or BSA, 0.1% SDS (w/v) in ddH2O
    • Bovine Serum Albumin (BSA) (It is used as a protein concentration standard in lab experiments – [amazon link=”B07MC644FT” link_icon=”amazon” /] )
Preparation of Reagents
  1. Dissolve 0.4 gm cupric sulfate (5x hydrated) in 20 ml water, 20 gm sodium carbonate in 260 ml water, and 0.2 gm sodium potassium tartrate in 20 ml water. Prepare the copper reagent by mixing all three solutions.
  2. Prepare the solution of sodium dodecyl sulfate (SDS): 100 ml of a 1% solution (1 gm/100 ml)
  3. Prepare a solution of NaOH: 1 M (4 gm/100 ml)
  4. Mix 1 part NaOH with 3 parts copper reagent and 1 part SDS for the 2x Lowry concentrate. Warm the solution to 37 degrees if a white precipitate forms, and discard if there is a black precipitate.
  5. Mix 10 ml 2 N Folin reagent with 90 ml water to prepare 0.2 N Folin reagent.
Experiment Protocol

This protocol is slightly modified, with respect to the original paper by Lowry, to work with smaller volumes.

Step 1:

Start the dilution of samples to an estimated 0.025-0.25 mg/ml with buffer. It is better to prepare a range of 2-3 dilutions spanning an order of magnitude if the concentration can’t be estimated.  Prepare 400 microliters each dilution.

Step 2:

Prepare a reference of 400 microliters buffer. Prepare standards by adding 40-400 microliters to 13 x 100 mm tubes from 0.25 mg/ml bovine serum albumin + buffer to bring volume to 400 microliters/tube.

Step 3:

After adding 400 microliters of 2x Lowry concentrate, mix it thoroughly, and incubate at room temp. 10 min.

Step 4:

Add 0.2 N 200 microliters Folin reagent very quickly, and vortex immediately. Complete mixing of the reagent must be achieved rapidly to avoid decomposition of the reagent before it reacts with protein. Incubate for 30 min. more at room temperature.

Step 5:

Use polystyrene or glass cuvettes to read the absorbances at 750 nm and after centrifugation, use an aliquot for protein determination.

Comments/Conclusion:

Recording of absorbances should be done within 10 minutes of each other for this modified procedure. This modification is more sensitive to protein than the original and less sensitive to interfering agents. Proteins with an abnormally low or high percentage of tryptophan, tyrosine, or cysteine residues will give high or low errors, respectively.

 

Introduction and Principle: Modification by SARGENT

This modification method by Sargent (1985) is also used in the quantification of proteins. The principle of this method includes a 50-fold increase in sensitivity with respect to the Lowry standard protocol. It is possible to estimate 0.1– 1 µg protein and 4–40 µg/ml, respectively.

Solutions/Reagents:
  • 20 mM CuSO4, 40 mM citric acid, 0.1 mM EDTA
    • Copper (II) Sulfate (A chemical perfect for use in any biochemistry lab – [amazon link=”B07JD2C6TW” link_icon=”amazon” /] )
    • Citric Acid (It is an intermediate in the citric acid cycle, which occurs in the metabolism of all aerobic organisms – [amazon link=”B00EYFKKZC” link_icon=”amazon” /] )
    • Ethylenediaminetetraacetic acid (EDTA) (Water-soluble solid used to prepare solutions – [amazon link=”B07MJDDPQK” link_icon=”amazon” /])
  • 4 M Na2CO3, 0.32 M NaOH
    • Anhydrous Sodium Carbonate (To make the dilute solutions – [amazon link=”B07MC64C66″ link_icon=”amazon” /] )
    • Sodium Hydroxide Reagent (For the dilution of reagents – [amazon link=”B00AUAB0HC” link_icon=”amazon” /])
  • mix 1 vol. freshly prepared A with 25 vol. freshly prepared B
  • Folin–Ciacalteu’s phenol reagent (stock), 1 + 1 diluted with ddH2O
    • Folin & Ciocalteu’s Phenol Reagent (Reagent used in LOWRY method – [amazon link=”B07MJDGBT9″ link_icon=”amazon” /])
  • 60 µg/ml malachite green in 0.1 M sodium maleate buffer, pH 6.0, 1 mM EDTA
    • Malachite Green (Chemical for general purpose lab and used as a staining agent – [amazon link=”B07JMMQJ3J” link_icon=”amazon” /] )
    • Ethylenediaminetetraacetic acid (EDTA) (Water-soluble solid used to prepare solutions – [amazon link=”B07MJDDPQK” link_icon=”amazon” /] )
Preparation of Reagents
  1. Prepare a 20 mM solution of copper sulfate and a 40mM solution of citric acid in 0.1 mM EDTA. It is recommended to make samples, blank, and standards at least in duplicates.
  2. Prepare a 0.40 M solution of sodium carbonate
  3. Prepare a 0.32 M solution of NaOH
  4. Prepare 0.2 N Folin reagent by mixing 10 ml 2 N Folin reagent with 90 ml of water
  5. Prepare 60 µg/ml malachite green in 0.1 M sodium maleate buffer
Experiment Protocol

Step 1:

Start the dilution of samples to an estimated 0.025-0.25 mg/ml with buffer. It is better to prepare a range of 2-3 dilutions spanning an order of magnitude if the concentration can’t be estimated.  Prepare 400 microliters for each dilution.

Step 2:

Prepare a reference of 400 microliters buffer and add 400 microliters of 2x Lowry concentrate, mix thoroughly, and incubate at room temp. 10 min.

Step 3:

Add 0.2 N 200 microliters Folin reagent very quickly, and vortex immediately. Complete mixing of the reagent must be achieved rapidly to avoid decomposition of the reagent before it reacts with protein. Incubate for 30 min. more at room temperature.

Step 4:

Extract the samples twice with 1 ml ethyl ether each. After centrifugation remove the ether by aspiration; remove the remaining ether in the aqueous phase with a SpeedVac.

Step 5:

Now add Soln. E, i.e. Malachite green and note the observations.

Comments/Conclusion:

Measure the absorbances at 690 nm immediately after the addition of solution E and prepare the standard curve in the range between 0 and 1 µg BSA.

 

Introduction and Principle: Micromethod on Microtest Plates

The microassay method is used for samples with low protein concentrations. The 96 well plate assay is used to perform the Lowry assay in a plate format.

Solutions/Reagents:
  • 20 g Na2CO3 (anhydrous) in 1000 ml 0.1 N NaOH
    • Anhydrous Sodium Carbonate (To make the dilute solutions -[amazon link=”B07MC64C66″ link_icon=”amazon” /] )
    • Sodium Hydroxide Reagent (For the dilution of reagents – [amazon link=”B00AUAB0HC” link_icon=”amazon” /])
  • 0g CuSO4 · 5H2O in 100 ml ddH2O
    • Copper (II) Sulfate (A chemical perfect for use in any biochemistry lab – [amazon link=”B07JD2C6TW” link_icon=”amazon” /])
    • Distilled Water (Used in the dilution of reagents – [amazon link=”B07MFS5Z3L” link_icon=”amazon” /] )
  • 0g potassium-sodium tartrate (Seignette salt) in 100 ml ddH2O
    • Potassium Sodium Tartrate (It is a common precipitant in protein crystallography and maintains cupric ions in solution at an alkaline pH – [amazon link=”B07MJDDXWW” link_icon=”amazon” /] )
  • mix 1 vol. B and 1 vol. C, and then add 50 vol. A
  • Folin–Ciocalteu’s phenol reagent (stock), 1 + 1 diluted with ddH2O
    • Folin & Ciocalteu’s Phenol Reagent (Reagent used in LOWRY method – [amazon link=”B07MJDGBT9″ link_icon=”amazon” /] )
  • Standard 2.0 mg/ml BSA in 0.1 N NaOH (stable at 2–8 ◦C for several months)
    • Bovine Serum Albumin (BSA) (It is used as a protein concentration standard in lab experiments – [amazon link=”B07MC644FT” link_icon=”amazon” /] )
Preparation of Reagents

Start the dilution of the sample with NaOH to a final concentration of about 0.1 moles NaOH and to an amount of protein within the measuring range.

Experiment Protocol

Step 1:

Pipette 40 µl of each unknown (25 µl) and standard sample replicate into a microplate well. The same buffer that was used in the samples will be used for the diluents.

Step 2:

After adding 200 µl of freshly prepared Lowry Assay Mix, immediately mix the microplate for 30 seconds.

Step 3:

For exactly 10 minutes, incubate the microplate at room temperature.

Step 4:

After adding 20 µl of freshly prepared Lowry Working Solution to each well, immediately mix the microplate for 30 seconds.

Step 5:

Incubate 30 min at room temperature. Measure the absorbance at 620nm-660 nm on a plate reader.

Comments/Conclusion:

If all the samples are read at the same time, the absorbance will not change significantly. The Lowry assay is not an endpoint assay, so samples will change in absorbance if too much time elapses between sample readings. During the reading of samples, i.e. less than 10 minutes, the typical time that elapses does not ordinarily result in significant changes in absorbance.

 

Introduction and Principle: Protein Determination in the Presence of Interfering Substances

The Lowry protein assay is a susceptible but profoundly nonspecific procedure.  The standard Lowry protein assay has been adjusted so that protein can be measured in the presence of interfering chemicals. The method depends on the observation that in the presence of 125 ìg/ml of Na-deoxycholate, bovine serum albumin (5—50 ìg) is reproducibly precipitated (90–104%) by 6% trichloroacetic acid. Interference by glycerol, sucrose, EDTA, Tris—HCl, and Tricine can be eliminated. If the NaCl concentration is adjusted to 1 m, the protein samples containing carrier ampholytes can also be assayed.

Solutions/Reagents:
  • 15% sodium deoxycholate (w/v) in ddH2O Solutions/Reagents
    • Sodium Deoxycholate (It is an ionic detergent for solubilizing and isolating membrane-bound proteins in an active state – [amazon link=”B0771S29QQ” link_icon=”amazon” /])
    • Distilled Water (Used in the dilution of reagents – [amazon link=”B07MFS5Z3L” link_icon=”amazon” /] )
  • 72% trichloroacetic acid (w/v) in ddH2O
    • Trichloroacetic Acid (It is widely used in biochemistry for the precipitation of macromolecules such as proteins – [amazon link=”B07F5MKR4Q” link_icon=”amazon” /])
  • 1% CuSO4 (w/v) in ddH2O
    • Copper (II) Sulfate (A chemical perfect for use in any biochemistry lab – [amazon link=”B07JD2C6TW” link_icon=”amazon” /] )
  • 2% sodium-potassium tartrate (w/v) in ddH2O
    • Potassium Sodium Tartrate (It is a common precipitant in protein crystallography and maintains cupric ions in solution at an alkaline pH – [amazon link=”B07MJDDXWW” link_icon=”amazon” /] )
  • 3.4% sodium carbonate (anhydrous) (w/v) in 0.2 N NaOH
    • Anhydrous Sodium Carbonate (To make the dilute solutions – [amazon link=”B07MC64C66″ link_icon=”amazon” /])
    • Sodium Hydroxide Reagent (For the dilution of reagents – [amazon link=”B00AUAB0HC” link_icon=”amazon” /] )
  • 10% SDS (w/v) in ddH2O
    • 10% SDS (Sodium Dodecyl Sulfate) (It is a detergent that is used to denature proteins – [amazon link=”B017MX7EXI” link_icon=”amazon” /] )
  • Mix just before using Soln. C, D, E, and F in a ratio of 1:1:28:10
  • Folin–Ciocalteu’s phenol reagent (stock), diluted 1 + 3 with ddH2O
    • Folin–Ciocalteu’s phenol reagent (Reagent used in LOWRY method – [amazon link=”B07MJDGBT9″ link_icon=”amazon” /] )
Preparation of Reagents and Experiment Protocol:

Step 1:

Dilute 5 to 100 µg of protein and standard, respectively, with ddH2O to 1.0 ml.

Step 2:

After that, add 0.1 ml of Soln. A.

Step 3:

After a further 10 min at RT add 0.1 ml of Soln. B. After mixing the solution well, place the samples for centrifugation with 3000 × g at RT 15 min later.

Step 4:

Now resolve the precipitate in 1.0 ml ddH2O, and then add 1.0 ml Soln. G.

Step 5:

Now the precipitate should be resolved entirely. After further 10 minutes add 0.5 ml of Soln. H, mix well and read the absorbances at 700 nm 30–45 minutes later.

Comments/Conclusion:

In the presence of 125 μg/ml of Na-deoxycholate at 700 nm, bovine serum albumin (5—50 μg) is reproducibly precipitated (90–104%) by 6% trichloroacetic acid.

 

References
  1. Lowry, OH., NJ, Rosbrough., AL, Farr., and RJ, Randall. J. (1951). Protein measurement with the Folin phenol reagent. Biol. Chem;193(1):265-75.
  2. Sargent, MG. (1987). Fiftyfold amplification of the Lowry protein assay. Anal Biochem; 163(2):476-81.
  3. Oosta, GM., Mathewson, NS., Catravas, GN. (1978). Optimization of Folin–Ciocalteu Reagent concentration in an automated Lowry protein assay. Anal Biochem; 89(1):31-4.
  4. Stoscheck, CM. (1990). Quantitation of protein. Methods Enzymol. 182:50-68.
  5. Hartree, EF. (1972). Determination of protein: a modification of the Lowry method that gives a linear photometric response. Anal Biochem; 48(2):422-7.
  6. Bradford, MM. (1976). A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem;72:248-54.

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Introduction

In behavioral neuroscience, the Open Field Test (OFT) remains one of the most widely used assays to evaluate rodent models of affect, cognition, and motivation. It provides a non-invasive framework for examining how animals respond to novelty, stress, and pharmacological or environmental manipulations. Among the test’s core metrics, the percentage of time spent in the center zone offers a uniquely normalized and sensitive measure of an animal’s emotional reactivity and willingness to engage with a potentially risky environment.

This metric is calculated as the proportion of time spent in the central area of the arena—typically the inner 25%—relative to the entire session duration. By normalizing this value, researchers gain a behaviorally informative variable that is resilient to fluctuations in session length or overall movement levels. This makes it especially valuable in comparative analyses, longitudinal monitoring, and cross-model validation.

Unlike raw center duration, which can be affected by trial design inconsistencies, the percentage-based measure enables clearer comparisons across animals, treatments, and conditions. It plays a key role in identifying trait anxiety, avoidance behavior, risk-taking tendencies, and environmental adaptation, making it indispensable in both basic and translational research contexts.

Whereas simple center duration provides absolute time, the percentage-based metric introduces greater interpretability and reproducibility, especially when comparing different animal models, treatment conditions, or experimental setups. It is particularly effective for quantifying avoidance behaviors, risk assessment strategies, and trait anxiety profiles in both acute and longitudinal designs.

What Does Percentage of Time in the Centre Measure?

This metric reflects the relative amount of time an animal chooses to spend in the open, exposed portion of the arena—typically defined as the inner 25% of a square or circular enclosure. Because rodents innately prefer the periphery (thigmotaxis), time in the center is inversely associated with anxiety-like behavior. As such, this percentage is considered a sensitive, normalized index of:

  • Exploratory drive vs. risk aversion: High center time reflects an animal’s willingness to engage with uncertain or exposed environments, often indicative of lower anxiety and a stronger intrinsic drive to explore. These animals are more likely to exhibit flexible, information-gathering behaviors. On the other hand, animals that spend little time in the center display a strong bias toward the safety of the perimeter, indicative of a defensive behavioral state or trait-level risk aversion. This dichotomy helps distinguish adaptive exploration from fear-driven avoidance.

  • Emotional reactivity: Fluctuations in center time percentage serve as a sensitive behavioral proxy for changes in emotional state. In stress-prone or trauma-exposed animals, decreased center engagement may reflect hypervigilance or fear generalization, while a sudden increase might indicate emotional blunting or impaired threat appraisal. The metric is also responsive to acute stressors, environmental perturbations, or pharmacological interventions that impact affective regulation.

  • Behavioral confidence and adaptation: Repeated exposure to the same environment typically leads to reduced novelty-induced anxiety and increased behavioral flexibility. A rising trend in center time percentage across trials suggests successful habituation, reduced threat perception, and greater confidence in navigating open spaces. Conversely, a stable or declining trend may indicate behavioral rigidity or chronic stress effects.

  • Pharmacological or genetic modulation: The percentage of time in the center is widely used to evaluate the effects of pharmacological treatments and genetic modifications that influence anxiety-related circuits. Anxiolytic agents—including benzodiazepines, SSRIs, and cannabinoid agonists—reliably increase center occupancy, providing a robust behavioral endpoint in preclinical drug trials. Similarly, genetic models targeting serotonin receptors, GABAergic tone, or HPA axis function often show distinct patterns of center preference, offering translational insights into psychiatric vulnerability and resilience.

Critically, because this metric is normalized by session duration, it accommodates variability in activity levels or testing conditions. This makes it especially suitable for comparing across individuals, treatment groups, or timepoints in longitudinal studies.

A high percentage of center time indicates reduced anxiety, increased novelty-seeking, or pharmacological modulation (e.g., anxiolysis). Conversely, a low percentage suggests emotional inhibition, behavioral avoidance, or contextual hypervigilance. reduced anxiety, increased novelty-seeking, or pharmacological modulation (e.g., anxiolysis). Conversely, a low percentage suggests emotional inhibition, behavioral avoidance, or contextual hypervigilance.

Behavioral Significance and Neuroscientific Context

1. Emotional State and Trait Anxiety

The percentage of center time is one of the most direct, unconditioned readouts of anxiety-like behavior in rodents. It is frequently reduced in models of PTSD, chronic stress, or early-life adversity, where animals exhibit persistent avoidance of the center due to heightened emotional reactivity. This metric can also distinguish between acute anxiety responses and enduring trait anxiety, especially in longitudinal or developmental studies. Its normalized nature makes it ideal for comparing across cohorts with variable locomotor profiles, helping researchers detect true affective changes rather than activity-based confounds.

2. Exploration Strategies and Cognitive Engagement

Rodents that spend more time in the center zone typically exhibit broader and more flexible exploration strategies. This behavior reflects not only reduced anxiety but also cognitive engagement and environmental curiosity. High center percentage is associated with robust spatial learning, attentional scanning, and memory encoding functions, supported by coordinated activation in the prefrontal cortex, hippocampus, and basal forebrain. In contrast, reduced center engagement may signal spatial rigidity, attentional narrowing, or cognitive withdrawal, particularly in models of neurodegeneration or aging.

3. Pharmacological Responsiveness

The open field test remains one of the most widely accepted platforms for testing anxiolytic and psychotropic drugs. The percentage of center time reliably increases following administration of anxiolytic agents such as benzodiazepines, SSRIs, and GABA-A receptor agonists. This metric serves as a sensitive and reproducible endpoint in preclinical dose-finding studies, mechanistic pharmacology, and compound screening pipelines. It also aids in differentiating true anxiolytic effects from sedation or motor suppression by integrating with other behavioral parameters like distance traveled and entry count (Prut & Belzung, 2003).

4. Sex Differences and Hormonal Modulation

Sex-based differences in emotional regulation often manifest in open field behavior, with female rodents generally exhibiting higher variability in center zone metrics due to hormonal cycling. For example, estrogen has been shown to facilitate exploratory behavior and increase center occupancy, while progesterone and stress-induced corticosterone often reduce it. Studies involving gonadectomy, hormone replacement, or sex-specific genetic knockouts use this metric to quantify the impact of endocrine factors on anxiety and exploratory behavior. As such, it remains a vital tool for dissecting sex-dependent neurobehavioral dynamics.
The percentage of center time is one of the most direct, unconditioned readouts of anxiety-like behavior in rodents. It is frequently reduced in models of PTSD, chronic stress, or early-life adversity. Because it is normalized, this metric is especially helpful for distinguishing between genuine avoidance and low general activity.

Methodological Considerations

  • Zone Definition: Accurately defining the center zone is critical for reliable and reproducible data. In most open field arenas, the center zone constitutes approximately 25% of the total area, centrally located and evenly distanced from the walls. Software-based segmentation tools enhance precision and ensure consistency across trials and experiments. Deviations in zone parameters—whether due to arena geometry or tracking inconsistencies—can result in skewed data, especially when calculating percentages.

     

  • Trial Duration: Trials typically last between 5 to 10 minutes. The percentage of time in the center must be normalized to total trial duration to maintain comparability across animals and experimental groups. Longer trials may lead to fatigue, boredom, or habituation effects that artificially reduce exploratory behavior, while overly short trials may not capture full behavioral repertoires or response to novel stimuli.

     

  • Handling and Habituation: Variability in pre-test handling can introduce confounds, particularly through stress-induced hypoactivity or hyperactivity. Standardized handling routines—including gentle, consistent human interaction in the days leading up to testing—reduce variability. Habituation to the testing room and apparatus prior to data collection helps animals engage in more representative exploratory behavior, minimizing novelty-induced freezing or erratic movement.

     

  • Tracking Accuracy: High-resolution tracking systems should be validated for accurate, real-time detection of full-body center entries and sustained occupancy. The system should distinguish between full zone occupancy and transient overlaps or partial body entries that do not reflect true exploratory behavior. Poor tracking fidelity or lag can produce significant measurement error in percentage calculations.

     

  • Environmental Control: Uniformity in environmental conditions is essential. Lighting should be evenly diffused to avoid shadow bias, and noise should be minimized to prevent stress-induced variability. The arena must be cleaned between trials using odor-neutral solutions to eliminate scent trails or pheromone cues that may affect zone preference. Any variation in these conditions can introduce systematic bias in center zone behavior. Use consistent definitions of the center zone (commonly 25% of total area) to allow valid comparisons. Software-based segmentation enhances spatial precision.

Interpretation with Complementary Metrics

Temporal Dynamics of Center Occupancy

Evaluating how center time evolves across the duration of a session—divided into early, middle, and late thirds—provides insight into behavioral transitions and adaptive responses. Animals may begin by avoiding the center, only to gradually increase center time as they habituate to the environment. Conversely, persistently low center time across the session can signal prolonged anxiety, fear generalization, or a trait-like avoidance phenotype.

Cross-Paradigm Correlation

To validate the significance of center time percentage, it should be examined alongside results from other anxiety-related tests such as the Elevated Plus Maze, Light-Dark Box, or Novelty Suppressed Feeding. Concordance across paradigms supports the reliability of center time as a trait marker, while discordance may indicate task-specific reactivity or behavioral dissociation.

Behavioral Microstructure Analysis

When paired with high-resolution scoring of behavioral events such as rearing, grooming, defecation, or immobility, center time offers a richer view of the animal’s internal state. For example, an animal that spends substantial time in the center while grooming may be coping with mild stress, while another that remains immobile in the periphery may be experiencing more severe anxiety. Microstructure analysis aids in decoding the complexity behind spatial behavior.

Inter-individual Variability and Subgroup Classification

Animals naturally vary in their exploratory style. By analyzing percentage of center time across subjects, researchers can identify behavioral subgroups—such as consistently bold individuals who frequently explore the center versus cautious animals that remain along the periphery. These classifications can be used to examine predictors of drug response, resilience to stress, or vulnerability to neuropsychiatric disorders.

Machine Learning-Based Behavioral Clustering

In studies with large cohorts or multiple behavioral variables, machine learning techniques such as hierarchical clustering or principal component analysis can incorporate center time percentage to discover novel phenotypic groupings. These data-driven approaches help uncover latent dimensions of behavior that may not be visible through univariate analyses alone.

Total Distance Traveled

Total locomotion helps contextualize center time. Low percentage values in animals with minimal movement may reflect sedation or fatigue, while similar values in high-mobility subjects suggest deliberate avoidance. This metric helps distinguish emotional versus motor causes of low center engagement.

Number of Center Entries

This measure indicates how often the animal initiates exploration of the center zone. When combined with percentage of time, it differentiates between frequent but brief visits (indicative of anxiety or impulsivity) versus fewer but sustained center engagements (suggesting comfort and behavioral confidence).

Latency to First Center Entry

The delay before the first center entry reflects initial threat appraisal. Longer latencies may be associated with heightened fear or low motivation, while shorter latencies are typically linked to exploratory drive or low anxiety.

Thigmotaxis Time

Time spent hugging the walls offers a spatial counterbalance to center metrics. High thigmotaxis and low center time jointly support an interpretation of strong avoidance behavior. This inverse relationship helps triangulate affective and motivational states.

Applications in Translational Research

  • Drug Discovery: The percentage of center time is a key behavioral endpoint in the development and screening of anxiolytic, antidepressant, and antipsychotic medications. Its sensitivity to pharmacological modulation makes it particularly valuable in dose-response assessments and in distinguishing therapeutic effects from sedative or locomotor confounds. Repeated trials can also help assess drug tolerance and chronic efficacy over time.
  • Genetic and Neurodevelopmental Modeling: In transgenic and knockout models, altered center percentage provides a behavioral signature of neurodevelopmental abnormalities. This is particularly relevant in the study of autism spectrum disorders, ADHD, fragile X syndrome, and schizophrenia, where subjects often exhibit heightened anxiety, reduced flexibility, or altered environmental engagement.
  • Hormonal and Sex-Based Research: The metric is highly responsive to hormonal fluctuations, including estrous cycle phases, gonadectomy, and hormone replacement therapies. It supports investigations into sex differences in stress reactivity and the behavioral consequences of endocrine disorders or interventions.
  • Environmental Enrichment and Deprivation: Housing conditions significantly influence anxiety-like behavior and exploratory motivation. Animals raised in enriched environments typically show increased center time, indicative of reduced stress and greater behavioral plasticity. Conversely, socially isolated or stimulus-deprived animals often show strong center avoidance.
  • Behavioral Biomarker Development: As a robust and reproducible readout, center time percentage can serve as a behavioral biomarker in longitudinal and interventional studies. It is increasingly used to identify early signs of affective dysregulation or to track the efficacy of neuromodulatory treatments such as optogenetics, chemogenetics, or deep brain stimulation.
  • Personalized Preclinical Models: This measure supports behavioral stratification, allowing researchers to identify high-anxiety or low-anxiety phenotypes before treatment. This enables within-group comparisons and enhances statistical power by accounting for pre-existing behavioral variation. Used to screen anxiolytic agents and distinguish between compounds with sedative vs. anxiolytic profiles.

Enhancing Research Outcomes with Percentage-Based Analysis

By expressing center zone activity as a proportion of total trial time, researchers gain a metric that is resistant to session variability and more readily comparable across time, treatment, and model conditions. This normalized measure enhances reproducibility and statistical power, particularly in multi-cohort or cross-laboratory designs.

For experimental designs aimed at assessing anxiety, exploratory strategy, or affective state, the percentage of time spent in the center offers one of the most robust and interpretable measures available in the Open Field Test.

Explore high-resolution tracking solutions and open field platforms at

References

  • Prut, L., & Belzung, C. (2003). The open field as a paradigm to measure the effects of drugs on anxiety-like behaviors: a review. European Journal of Pharmacology, 463(1–3), 3–33.
  • Seibenhener, M. L., & Wooten, M. C. (2015). Use of the open field maze to measure locomotor and anxiety-like behavior in mice. Journal of Visualized Experiments, (96), e52434.
  • Crawley, J. N. (2007). What’s Wrong With My Mouse? Behavioral Phenotyping of Transgenic and Knockout Mice. Wiley-Liss.
  • Carola, V., D’Olimpio, F., Brunamonti, E., Mangia, F., & Renzi, P. (2002). Evaluation of the elevated plus-maze and open-field tests for the assessment of anxiety-related behavior in inbred mice. Behavioral Brain Research, 134(1–2), 49–57.

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