Using a symptom-based approach, we found that pathological liars have abnormally increased prefrontal white matter (Reference Yang, Raine and LenczYang et al, 2005). It was suggested that this increase may represent a predisposition to lying. In this study it is hypothesised that pathological liars will show structural abnormalities particularly in the dorsolateral, prefrontal and orbitofrontal cortex.

METHOD

Participants were taken from a total sample of 108 community volunteers drawn from five temporary employment agencies in Los Angeles (Reference Raine, Lencz and BihrleRaine et al, 2000). The three groups consisted of 10 people with a history of repeated lying (‘liars’), 20 normal controls who had neither antisocial personality disorder nor a history of pathological lying, and 14 ‘antisocial’ controls matched for antisocial behaviours but with no history of pathological lying. Participants were defined as pathological liars if they fulfilled criteria for: pathological lying on the Psychopathy Checklist–Revised (PCL–R; Reference HareHare, 1991); or conning/manipulative behaviour on the PCL–R; or deceitfulness for DSM–IV antisocial personality disorder (American Psychiatric Association, 1994), or malingering (for details see Reference Yang, Raine and LenczYang et al, 2005). Of the 10 liars in this study, 5 were classified as malingerers. Full informed, written consent was obtained from all participants in accordance with institutional review board procedures. Five brain volumes from the original sample (Reference Yang, Raine and LenczYang et al, 2005) could not be segmented owing to irretrievable corruption on data storage. Missing data were relatively evenly distributed across groups, with two from the liar group, two from the antisocial control group and one from the normal control group.

Structural MRI was carried out on a 1.5-Telsa Philips S15/ACS (Selton, Connecticut, USA) scanner using three-dimensional T₁-weighted gradient-echo scans (for detals see Reference Yang, Raine and LenczYang et al, 2005). All image data-sets were processed with a series of preparatory steps before manual delineation of prefrontal subregions (Sowell et al, Reference Sowell, Thompson and Holmes1999, Reference Sowell, Thompson and Rex2002). First, all images were anonymised to exclude personal information. Second, non-brain tissue and the cerebellum were removed from the brain volume, and signal intensity inhomogeneities were corrected (Reference Sled and PikeSled & Pike, 1998). Third, fully automated tissue segmentation was applied and brain voxels were automatically classified as gray matter, white matter, or cerebrospinal fluid using a validated partial volume correction method (Reference Shattuck, Sandor-Leahy and SchaperShattuck et al, 2001). Finally, a spherical mesh surface was created using a three-dimensional active surface algorithm to facilitate identification of anatomical boundaries (Reference MacDonald, Avis, Evans and RobbMacDonald et al, 1994).

The parcellation of the prefrontal lobe into four subregions for each hemisphere followed the methods of Ballmaier et al (Reference Ballmaier, Toga and Blanton2004). A three-dimensional shape representation and coronal two-dimensional MRI scan of the segmentation of the prefrontal cortex of one of the participants are shown in the data supplement to the online version of this paper. All anatomical delineations were conducted by two research assistants trained by Y.Y. Unlike gray matter subregions, which are clearly defined by sulcal landmarks, white matter delineations are arbitrary and the segmentation results should be viewed as estimated volumes. To assess interrater reliability, all anatomical regions were delineated on ten randomly chosen image data-sets; intraclass correlation coefficients ranged between 0.90 and 0.97 for gray matter and white matter in all four frontal subregions. Each of the eight subregional volumes was divided by total intracranial volume to account for potential differences in individual brain size. Since there was a lack of hemisphere effect, white matter volumes from two hemispheres were averaged to create a mean regional volume.

RESULTS

A multivariate analysis of variance (ANOVA) showed a main group effect for whole-brain-corrected white matter volume in prefrontal regions (i.e. inferior frontal, middle frontal, orbitofrontal and superior frontal cortices); F(8, 78) 4.19, P=0.001, η²=0.29). Groups differed in the volume of white matter in the inferior (F(2, 41)=11.09, P=0.001), middle (F(2, 41)=7.05, P=0.003) and orbitofrontal cortex (F(2, 41)=6.87, P=0.001), with increased white matter in liars. However, a trend towards lower white matter volume was found in the superior frontal cortices for liars (F(2, 41)=0.42, P=0.66). Liars showed significantly increased white matter in inferior, middle and orbitofrontal cortex compared with both antisocial controls (P=0.001, P=0.004, and P=0.006, respectively) and normal controls (P=0.001, P=0.005, and P=0.001 respectively; Fig. 1). No difference was found for gray matter volume in the four subregions (F(8, 78) =0.54, P=0.82).

DISCUSSION

Following our previous finding of a prefrontal white matter increase in people who lie, cheat and manipulate others (Reference Yang, Raine and LenczYang et al, 2005), this study found pathological liars to have increased white matter volumes in some prefrontal subregions, particularly orbitofrontal cortex (22–26% increase), inferior frontal cortex (32–36% increase) and middle frontal cortex (28–32% increase) compared with both antisocial and normal controls. An important exception was that no white matter increase was found for the superior frontal cortices. Such an increase might be expected based on findings of an fMRI study in which activation of superior frontal cortices was found during a deception task involving motor responses (Reference Langleben, Schroeder and MaldjianLangleben et al, 2002). In contrast, one study using a potentially more realistic lying task involving a verbal response found prefrontal activation specifically in ventrolateral and orbitofrontal cortex, but not superior frontal cortices (Reference Spence, Hunter and FarrowSpence et al, 2004). Moreover, these nonsuperior frontal regions are most frequently shown to be activated by deception tasks (e.g. Reference Spence, Hunter and FarrowSpence et al, 2004; Reference Langleben, Loughead and BilkerLangleben et al, 2005; Reference Phan, Magalhaes and ZiemlewiczPhan et al, 2005). This may in part explain why we observed white matter increases in the ventral (orbitofrontal cortex), ventrolateral (inferior frontal cortex) and inferior aspect of dorsolateral (middle frontal cortex), but not superior dorsolateral (superior frontal cortices), frontal regions in the liar group.

Fig. 1 Whole-brain-corrected prefrontal white matter volumes in the inferior frontal cortex (IFC), middle frontal cortex (MFC), orbitofrontal cortex (OFC), and superior frontal cortex (SFC) in pathological liars (▪), normal controls (□) and antisocial controls (APD, ▒). Vertical lines indicate the standard error of the mean.

One interpretation of the white matter increases in the ventral and lateral nonsuperior frontal regions could be that a pre-existing variation in prefrontal structure may predispose individuals to engage in pathological lying. Alternatively, several studies have argued that long-term training may induce regional increases in white matter volume (Reference Schmithorst and WilkeSchmithorst & Wilke, 2002; Reference Bengtsson, Nagy and SkareBengtsson et al, 2005). In the case of lying, it is conceivable that excessive lying repeatedly activates the prefrontal circuit underlying lying, resulting in permanent changes in brain morphology. This ‘Pinocchio's nose’ hypothesis of pathological lying could be compared with the competing predispositional hypothesis using a prospective longitudinal study assessing both white matter volume and degree of lying from childhood to adulthood.

The engagement of ventral and lateral prefrontal regions in lying may be anticipated from fMRI studies, several of which have associated these regions with executive functions crucial to successful deception, including decision-making, moral reasoning, rule maintenance/retrieval and response inhibition (Reference BungeBunge, 2004). Although some studies showed partial activation in the superior frontal cortex when lying involved a non-vocal motor response (Langleben et al, Reference Langleben, Schroeder and Maldjian2002, Reference Langleben, Loughead and Bilker2005), this region is more associated with functions less directly linked to deception, such as spatial information processing, attention reorientation and novelty detection (Reference Gomot, Bernard and DavisGomot et al, 2006). Conversely, gains in white matter volume in these prefrontal regions (in the absence of gray matter reduction) may lead to faster sharing of information within frontal–cortical circuits in pathological liars. Thus, increased white matter in these subregions of the prefrontal cortex in liars may predispose to maintaining a lifestyle of pathological lying and malingering. The use of advanced imaging techniques such as diffusion tensor imaging to assess neural connectivity (Reference Nakamura, McCarley and KubickiNakamura et al, 2005) may allow more thorough investigation of the subtle abnormalities responsible for pathological lying.