Development and initial assessment of a new paradigm for assessing cognitive and motor inhibition: The bimodal virtual-reality Stroop

Abstract

Assessing and predicting inhibition in adults is a common assignment for clinicians. However, there is no single measure of inhibition that is complete, sensitive and enjoyable. The main goal of this study was to develop a virtual reality neuropsychological task (the bimodal VR-Stroop) capable of measuring both cognitive (control of internal and external interference) and motor inhibition (a go no-go paradigm with reaction time variation, commission errors and omissions). Preliminary data obtained with 71 healthy adult participants confirmed that the VR-Stroop is capable of eliciting the Stroop effect with bimodal stimuli. Initial validation data also suggested that measures of the VR-Stroop significantly correlate with measures of the Elevator counting with distracters, the Continuous Performance Task (CPT-II), and the Stop-it task. Finally, regression analyses indicated that commission errors and variability of reaction times at the VR-Stroop were significantly predicted by scores of the Elevator task and the CPT-II. These preliminary results suggest that the VR-Stroop is an interesting measure of cognitive and motor inhibition for adults, although confirmatory investigations are warranted.

Introduction

Lack of inhibition (or impulsivity) is among the most common manifestations of mental disorder diagnoses (APA, 2000, Moeller et al., 2001). It is also one of the most common behaviors assessed by clinicians (e.g. Lezak et al., 2004). Yet, available measures of inhibition/impulsivity are often considered unsatisfactory or incomplete as they are associated with low sensitivity and poor predictive value, especially among clinical populations (e.g. with psychiatric and/or neurological impairments; Mathias et al., 2008, Moeller et al., 2001, Reynolds et al., 2006). The main goal of this study was to develop a single, yet more complete, assessment of inhibition/impulsivity using virtual reality.

A first factor explaining the difficulties of measuring inhibition/impulsivity is the traditional use of questionnaires and verbal self-reports (e.g. the Barratt Impulsivity Scale; Patton et al., 1995; the I₇ subscale, Eysenck et al., 1985; the UPPS impulsive behavioral scale, Whiteside et al., 2005). Results from these measures depend heavily on the collaboration and comprehension of the examinee, which is not always attainable in certain clinical settings (e.g. forensic and general psychiatry). Also, questionnaires tend to reflect long term traits of impulsivity (as opposed to acute states), and their results often fail to correlate with those of direct (behavioral) measures of acute impulsivity (e.g. Gerbing et al., 1987, Reynolds et al., 2006, Horn et al., 2003). Thus, computerized assessments are better suited to evaluate acute states of inhibition/impulsivity, especially among clinical populations (e.g. Mathias et al., 2008, Moeller et al., 2001).

A second factor explaining the difficulties of developing a satisfying measure of inhibition/impulsivity is the relative complexity of the constructs. Different clinical and research backgrounds, ranging from experimental psychology (e.g. Logan and Cowan, 1984, Patton et al., 1995), to adult psychiatry (e.g. Moeller et al., 2001), and developmental psychology (e.g. Nigg, 2000, Barkley, 1997) offered different theoretical accounts of inhibition and its corollary, impulsivity. Thus, several subtypes of both inhibition (e.g. behavioral vs. cognitive, intentional vs. non intentional, interference control vs. dyscontrol, Nigg, 2000; behavioral vs. interference control vs. cognitive, Kipp, 2005), and impulsivity have been proposed during the past half century (e.g. motor, attentional, and unplanning; Barratt, 1965, Patton et al., 1995; lack of inhibitory control, low decision time, sensation seeking and low persistence; Buss and Plomin, 1975; urgency, lack of premeditation, lack of perseverance and sensation seeking; Whiteside and Lynam, 2001). Overall, however, direct measures (i.e. behavioral) of inhibition and impulsivity are known to either assess cognitive inhibition or motor control (e.g. White et al., 1994). It would be best to develop a task capable of measuring both cognitive inhibition and motor control.

Cognitive inhibition is sometime viewed as the capacity to inhibit access of irrelevant material in working memory (a rather higher-order capacity directly associated with executive functioning; Kipp, 2005), or decision-making capacities (more closely associated with risk taking and/or thrill seeking; e.g. Bechara and van der Linden, 2005). Most commonly, cognitive inhibition is considered as the capacity to control interference from external (environmental) or internal (e.g. intrusive thoughts) stimuli (e.g. Kipp, 2005). In that sense, interference control is a process that helps maintaining attention focussed on a task in spite of distracters. Thus, the best would be to measure both type of interference with the same task. With virtual reality (VR), it is relatively simple to assess external interference with introduction of surrounding distracters within the environment. External distracters (auditory and/or visual elements) render the task environment more sensitive and more ecologically valid than traditional settings (Adams et al., 2009, Nolin et al., 2009). Moreover, distracters provoke head movements, allowing a better detection of subtle deficits among clinical populations (Nolin et al., 2009, Nolin et al., 2012). Therefore, a main advantage of virtual neuropsychological tasks is to evaluate skills and abilities in an environment that appears more sensitive and similar to the real world (e.g. Matheis et al., 2007). As for control of internal interference, it is best measured with the Stroop task, the most widely used assessment of cognitive inhibition and interference control for adults (e.g. MacLeod and MacDonald, 2000, Strauss et al., 2006). That task is based on the classic Stroop effect (Stroop, 1935, MacLeod, 1991), related with the normal habit of automatically reading a written word. When the name of a color and the ink color of the name differ (e.g. the word BLUE is written in red) and a person must name only the ink color, either his/her response time or the number of errors (or both) increase compared to trials where the name and its ink matched. Because inhibition assessments are much more numerous for children than adults (e.g. Simpson and Riggs, 2005, Korkman et al., 1998, Manly et al., 1999; see Lezak et al., 2004 for a compendium), and the Stroop effect is stronger in adults than children (being based on reading automaticity; e.g. MacLeod, 1991), a virtual environment adapted for adults with measures based on the Stroop effect was chosen. Pairing environmental distracters with the Stroop measure, it becomes possible to assess interference control for both external and internal stimuli. Thus, a single instrument could measure both motor impulsivity and cognitive impulsivity. Another virtual reality Stroop task with distracters was recently developed by Parsons et al. (2011), although the Stroop stimuli are unimodal (visual only), and the environments are different (Iraqi/Afghani war zones for army veterans). Using unimodal stimulus presentation implies that at least three different response keys are needed (three different colors). In this study, a VR-Stroop assessment with bimodal stimuli was developed to integrate a measure of motor control, which implies a single response key (go/no-go reaction times). Moreover, a regular environment has to be used to improve environmental ecological validity for the general population.

Motor control is generally viewed as the capacity to physically and voluntarily withhold a prepotent or ongoing motor response (e.g. Evenden, 1999, Dougherty et al., 2009). Motor control is best evaluated with computerized measures, which are generally based on go no-go paradigms (e.g. CPT-II, Conners et al., 2003; the TOVA, Leark et al., 2007; The Stop-it task; Verbruggen et al., 2008). The most commonly used variable for motor control assessment is the commission error, a reactive act performed with low reaction time and reflection, associated with low impulse control, high risk taking tendencies, poor decision making, low gratification delay capacities and weak resistance to temptation (e.g. Kipp, 2005, White et al., 1994). Motor inhibition and commission errors are closely dependent upon integrity of brain circuits involving the lower parts of the frontal lobes (e.g. Bechara and van der Linden, 2005, Horn et al., 2003). Another interesting approach with go no-go paradigms is to consider intra-individual (and intra-test) variability of reaction times, which is associated with certain types of neurological conditions such as Attentional Deficit and Hyperactivity Disorder (ADHD and the so-called sluggish cognitive tempo; e.g. Carlson and Mann, 2002).

Go no-go paradigms might also be used to indirectly assess the capacity of inhibition processes with stop-signal tasks (Verbruggen et al., 2008). The Stop-it task in particular allows to determine the time required between a visual go signal and a auditory no-go signal for an individual to withhold a response, which corresponds to the Stop-Signal Reaction Time (SSRT), an index of inhibition capacities (Logan and Cowan, 1984, Logan et al., 1997, Verbruggen et al., 2008). The Stop-it is generally considered as the best measure of motor inhibition (e.g. Nolan et al., 2011). It is also worth noting that good performances at the Stop-it activate brain regions that are not identical (they only partially overlap) with those associated with good performances at the CPT-II (Swick et al., 2011). Thus, these tasks are not measuring exactly the same construct and might be used concurrently.

The main problem with go no-go paradigms is their notorious tediousness and monotony for the examinee. First, they were generally developed to assess vigilance (the capacity to maintain attention focussed for a relatively long period of time), rendering the assessment long (up to 20 min) and boring. Second, the ecological validity and interest for their environments (typically Xs and Os appearing on a black screen of a computer in a quiet experimental room) are particularly low. The use of virtual reality should vastly improve these aspects of the assessment.

Finally, there are important differences between the concepts and measurements of interference control (as measured with the Stroop), and motor impulsivity (as measured with go no-go paradigms; e.g. Perugini et al., 2000, van Mourik et al., 2005). Given that associations between the Stroop effect and other types of inhibition capacities might be weak (e.g. Heflin et al., 2011), it would be interesting to develop a task capable of measuring more than one subtype of inhibition/impulsivity.

The first objective of this study was to confirm that a Stroop effect might be elicited with a VR task based on bimodal stimuli. The main goal was to develop a single impulsivity measure assessing control of internal interference (Stroop effect), control of external interference (environmental distracters), and motor inhibition (simple reaction times based on a go-no go paradigm). A third goal of this study was to conduct a first-step convergent validation of the VR task with a small group of participants and traditional impulsivity measures.