Elsevier

Neuropharmacology

Volume 52, Issue 1, January 2007, Pages 228-233
Neuropharmacology

A robust automated method to analyze rodent motion during fear conditioning

https://doi.org/10.1016/j.neuropharm.2006.07.028Get rights and content

Abstract

A central question in the study of LTP has been to determine what role it plays in memory formation and storage. One valuable form of learning for addressing this issue is associative fear conditioning. In this paradigm an animal learns to associate a tone and shock, such that subsequent presentation of a tone evokes a fear response (freezing behavior). Recent studies indicate that overlapping cellular processes underlie fear conditioning and LTP. The fear response has generally been scored manually which is both labor-intensive and subject to potential artifacts such as inconsistent or biased results. Here we describe a simple automated method that provides unbiased and rapid analysis of animal motion. We show that measured motion, in units termed significant motion pixels (SMPs), is both linear and robust over a wide range of animal speeds and detection thresholds and scores freezing in a quantitatively similar manner to trained human observers. By comparing the frequency distribution of motion during baseline periods and to the response to fox urine (which causes unconditioned fear), we suggest that freezing and non-freezing are distinct behaviors. Finally, we show how this algorithm can be applied to a fear conditioning paradigm yielding information on long and short-term associative memory as well as habituation. This automated analysis of fear conditioning will permit a more rapid and accurate assessment of the role of LTP in memory.

Introduction

Knowledge about long-term potentiation (LTP) has advanced tremendously over the last few decades. This increased understanding has occurred at the molecular, cellular and behavioral levels of analyses. Perhaps one of the most important issues raised by the initial discovery of LTP was its relation to learning and memory (Morris, 2003). This relation has been examined using a number of different experimental paradigms (Martin et al., 2000). One behavioral paradigm, associative fear conditioning (Fanselow and Poulos, 2005, LeDoux, 2000, Maren, 2005, Rodrigues et al., 2004), has been used with considerable success as it affords a number of advantages. In this form of learning, an animal is exposed to an initially neutral conditioned stimulus (CS; generally a tone) temporally associated with an aversive unconditioned stimulus (US; usually an electrical shock). Subsequent presentations of the CS elicit an array of defensive responses, collectively referred to as conditioned fear. Behavioral freezing, defined as the absence of all non-respiratory movements, is perhaps the most widely studied conditioned fear response (Blanchard and Blanchard, 1969, Fanselow, 1980).

The advantages of this behavior, specifically in addressing the question regarding its relationship to LTP, are numerous. First, the anatomical circuitry underlying the acquisition and expression of this behavior is fairly well established (Blair et al., 2001, LeDoux, 2000, Maren, 2001). Thus, one can predict which synaptic contacts should undergo LTP during learning (Bauer et al., 2002, Lamprecht et al., 2006, Rumpel et al., 2005, Schafe et al., 2000, Schafe et al., 2005) (for review see (Maren and Quirk, 2004, Rodrigues et al., 2004)). Second, the conditioning is quite brief; typically one to five tone-shock pairings are used, which mimics to some extent the LTP inducing protocols. Third, the memory is long lasting (weeks to months), as with LTP. And last, the behavioral output, freezing, is quite robust.

One drawback of this paradigm is that the behavioral output has typically been measured by human observers. This often requires multiple independent observations and is susceptible to potential bias. Furthermore, other potentially important behavioral measures, such as motion, are generally not scored. Although significant progress in automation of the analysis has been described (Contarino et al., 2002, Fitch et al., 2002, Marchand et al., 2003, Takahashi, 2004, Anagnostaras et al., 2000), these algorithms have some drawbacks. For instance, several require sophisticated hardware that measure animal movement indirectly (e.g. force-transduction or photobeam interruption). Furthermore others have poor time resolution, produce non-linear results, or only score freezing and not motion. Here we describe a reliable, low-cost method that uses digital cameras and standard speed computers to measure animal motion. The algorithm output displays a linear relation to the motion of an animal. Freezing can be calculated by setting a threshold for motion. However, the percent freezing is quite insensitive to the threshold suggesting that freezing and non-freezing are distinct behaviors. This is further supported by comparing the behavior during unconditioned freezing and baseline behavior.

Section snippets

Animals

Male C57/Bl6*129 hybrid mice, 10 weeks of age, and male Sprague–Dawley rats (250–350 g) were housed on a 12-h light/dark cycle with ad libitum access to water and food. Procedures were performed in strict compliance with the animal use and care guidelines of Cold Spring Harbor Laboratory and New York University.

Behavioral training

The mice were handled and habituated to the conditioning chamber and testing chamber during 5 min for 5 consecutive days. Conditioning was performed in a Mouse Test Cage (18 cm × 18 cm × 30 cm)

Results

We began by asking whether the algorithm could score the motion of a mouse in a qualitative manner. Fig. 1a shows the motion of a mouse in SMPs plotted as a function of time (see Section 2). Two successive frames from the video where the algorithm calculates a high (Fig. 1b1) or low (Fig. 1b2) SMP value are shown, indicating that SMP value does qualitatively correlate with absolution motion.

Next we asked if SMP value was a linear measure of motion. To accomplish this we designed a fake mouse

Discussion

Understanding the relation between LTP and learning and memory is a central issue in the study of plasticity. With a molecular and cellular understanding of LTP we have gained a number of pharmacological and molecular tools that can be applied to the analysis of behavior. While the application of these tools to the study of fear conditioning has led to important findings, further progress in relating LTP to fear memory could be made through the use of automated measures that produce reliable,

References (22)

  • S.G. Anagnostaras et al.

    Computer-assisted behavioral assessment of Pavlovian fear conditioning in mice

    Learn. Mem.

    (2000)
  • E.P. Bauer et al.

    NMDA receptors and L-type voltage-gated calcium channels contribute to long-term potentiation and different components of fear memory formation in the lateral amygdala

    J. Neurosci.

    (2002)
  • H.T. Blair et al.

    Synaptic plasticity in the lateral amygdala: a cellular hypothesis of fear conditioning

    Learn. Mem.

    (2001)
  • R.J. Blanchard et al.

    Crouching as an index of fear

    J. Comp. Physiol. Psychol.

    (1969)
  • M.E. Bouton et al.

    Role of conditioned contextual stimuli in reinstatement of extinguished fear

    J. Exp. Psychol. Anim. Behav. Process.

    (1979)
  • A. Contarino et al.

    Automated assessment of conditioning parameters for context and cued fear in mice

    Learn. Mem.

    (2002)
  • M.S. Fanselow

    Conditioned and unconditional components of post-shock freezing

    Pavlov J. Biol. Sci.

    (1980)
  • M.S. Fanselow et al.

    The neuroscience of mammalian associative learning

    Annu. Rev. Psychol.

    (2005)
  • T. Fitch et al.

    Force transducer-based movement detection in fear conditioning in mice: a comparative analysis

    Hippocampus

    (2002)
  • R. Lamprecht et al.

    Myosin light chain kinase regulates synaptic plasticity and fear learning in the lateral amygdala

    Neuroscience

    (2006)
  • J.E. LeDoux

    Emotion circuits in the brain

    Annu. Rev. Neurosci.

    (2000)
  • Cited by (33)

    • Learning-induced biases in the ongoing dynamics of sensory representations predict stimulus generalization

      2022, Cell Reports
      Citation Excerpt :

      During conditioning, memory and generalization test session, movies were recorded at a frame rate of 2.8 frames per seconds. Movies were analyzed offline based on a similar approach as described previously (Kopec et al., 2007), which provides a rapid and unbiased analysis of animal behavior. In short, the number of ‘significant motion pixels’ (SMP), i.e. pixels which varied by a fixed threshold of gray values, was calculated for all pairs of consecutive frames using a custom MATLAB R2007a or R2019b script (MathWorks).

    • Fox urine exposure induces avoidance behavior in rats and activates the amygdalar olfactory cortex

      2015, Behavioural Brain Research
      Citation Excerpt :

      In the present study, saline-treated rats displayed robust avoidance behavior, i.e. approximately 6% of their time was spent in the quadrant with fox urine (chance level would be 25%). Similar fear-evoking properties of fox urine have been reported several times in fox urine-exposed rats and mice showing higher levels of freezing, suppressed locomotor activity, and elevated c-Fos immunoreactivity in brain regions involved in fear [20,21,26,30,34]. This data, together with our results, indicate that fox urine functions as a predatory signal that reliably induces fear behavior in rodents.

    • Aging redistributes medial prefrontal neuronal excitability and impedes extinction of trace fear conditioning

      2012, Neurobiology of Aging
      Citation Excerpt :

      Post hoc analysis revealed that adult rats exhibited within-session extinction evidenced by a significant decrease in mean freezing across the first 4 CS-alone trials of extinction training (p < 0.01) but middle-aged and aged rats did not (p = 0.91 and p = 0.97, respectively). Note that within-session extinction was assessed across the first 4 CS-alone trials to avoid confounds associated with the interpretation of immobility during subsequent trials of a temporally spaced extinction session (Cain et al., 2003; Kopec et al., 2007). Given that rats with permanent or temporary lesions of the mPFC (Lebrón et al., 2004; Morgan et al., 2003; Quirk et al., 2000; Sierra-Mercado et al., 2006), or disruption of protein synthesis in the mPFC (Santini et al., 2004), have difficulty recalling fear extinction, it is likely that our observed aging-related extinction deficits reflect mPFC dysfunction.

    View all citing articles on Scopus
    1

    These authors contributed equally to this work.

    View full text